Anti-fibrotic drug discovery 9781788015783, 9781788015103, 178801510X

Anti-fibrotic Drug Discovery is ideal for postgraduate students and researchers with an interest in anti-fibrotic drug d

1,212 280 13MB

English Pages xvi, 347 pages: illustrations (color, black and white; 24 cm [362] Year 2020

Report DMCA / Copyright

DOWNLOAD FILE

Polecaj historie

Anti-fibrotic drug discovery
 9781788015783, 9781788015103, 178801510X

Table of contents :
TGFß Signalling in Fibrosis
Targeting Integrins in Fibroproliferative Disease
Discovery, Structural Refinement and Therapeutic Potential of Farnesoid X Receptor (FXR) Activators
Autotaxin Inhibitors in Fibrosis
Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes: Intervention at the Core of Fibrotic Pathology
Galectin-3 Involvement in Fibrotic Diseases
The Emerging Role of CXCR4 in IPF
BH3 Mimetic Drugs for Anti-Fibrotic Therapy
Intratumoral Fibrosis: Emerging Concepts and Therapeutic Opportunities
Targeting Fibroblasts in Cancer and Fibrosis

Citation preview

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

Anti-­fibrotic Drug Discovery

View Online

Drug Discovery Series

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

Editor-­in-­chief

David Thurston, King's College London, UK

Series editors:

David Fox, Vulpine Science and Learning, UK Ana Martinez, Centro de Investigaciones Biologicas-­CSIC, Spain David Rotella, Montclair State University, USA Hong Shen, Roche Innovation Center Shanghai, China

Editorial advisor:

Ian Storer, AstraZeneca, UK

Titles in the Series:

1: Metabolism, Pharmacokinetics and Toxicity of Functional Groups 2: Emerging Drugs and Targets for Alzheimer's Disease; Volume 1 3: Emerging Drugs and Targets for Alzheimer's Disease; Volume 2 4: Accounts in Drug Discovery 5: New Frontiers in Chemical Biology 6: Animal Models for Neurodegenerative Disease 7: Neurodegeneration 8: G Protein-­coupled Receptors 9: Pharmaceutical Process Development 10: Extracellular and Intracellular Signaling 11: New Synthetic Technologies in Medicinal Chemistry 12: New Horizons in Predictive Toxicology 13: Drug Design Strategies: Quantitative Approaches 14: Neglected Diseases and Drug Discovery 15: Biomedical Imaging 16: Pharmaceutical Salts and Cocrystals 17: Polyamine Drug Discovery 18: Proteinases as Drug Targets 19: Kinase Drug Discovery 20: Drug Design Strategies: Computational Techniques and Applications 21: Designing Multi-­target Drugs 22: Nanostructured Biomaterials for Overcoming Biological Barriers 23: Physico-­chemical and Computational Approaches to Drug Discovery 24: Biomarkers for Traumatic Brain Injury 25: Drug Discovery from Natural Products 26: Anti-­inflammatory Drug Discovery 27: New Therapeutic Strategies for Type 2 Diabetes: Small Molecules 28: Drug Discovery for Psychiatric Disorders 29: Organic Chemistry of Drug Degradation 30: Computational Approaches to Nuclear Receptors

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

View Online

31: Traditional Chinese Medicine 32: Successful Strategies for the Discovery of Antiviral Drugs 33: Comprehensive Biomarker Discovery and Validation for Clinical Application 34: Emerging Drugs and Targets for Parkinson's Disease 35: Pain Therapeutics; Current and Future Treatment Paradigms 36: Biotherapeutics: Recent Developments using Chemical and Molecular Biology 37: Inhibitors of Molecular Chaperones as Therapeutic Agents 38: Orphan Drugs and Rare Diseases 39: Ion Channel Drug Discovery 40: Macrocycles in Drug Discovery 41: Human-­based Systems for Translational Research 42: Venoms to Drugs: Venom as a Source for the Development of Human Therapeutics 43: Carbohydrates in Drug Design and Discovery 44: Drug Discovery for Schizophrenia 45: Cardiovascular and Metabolic Disease: Scientific Discoveries and New Therapies 46: Green Chemistry Strategies for Drug Discovery 47: Fragment-­based Drug Discovery 48: Epigenetics for Drug Discovery 49: New Horizons in Predictive Drug Metabolism and Pharmacokinetics 50: Privileged Scaffolds in Medicinal Chemistry: Design, Synthesis, Evaluation 51: Nanomedicines: Design, Delivery and Detection 52: Synthetic Methods in Drug Discovery: Volume 1 53: Synthetic Methods in Drug Discovery: Volume 2 54: Drug Transporters: Role and Importance in ADME and Drug Development 55: Drug Transporters: Recent Advances and Emerging Technologies 56: Allosterism in Drug Discovery 57: Anti-­aging Drugs: From Basic Research to Clinical Practice 58: Antibiotic Drug Discovery: New Targets and Molecular Entities 59: Peptide-­based Drug Discovery: Challenges and New Therapeutics 60: Drug Discovery for Leishmaniasis 61: Biophysical Techniques in Drug Discovery 62: Acute Brain Impairment Through Stroke: Drug Discovery and ­ Translational Research 63: Theranostics and Image Guided Drug Delivery 64: Pharmaceutical Formulation: The Science and Technology of Dosage Forms 65: Small-­molecule Transcription Factor Inhibitors in Oncology 66: Therapies for Retinal Degeneration: Targeting Common Processes 67: Kinase Drug Discovery: Modern Approaches 68: Advances in Nucleic Acid Therapeutics

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

View Online

69: MicroRNAs in Diseases and Disorders: Emerging Therapeutic Targets 70: Emerging Drugs and Targets for Multiple Sclerosis 71: Cytotoxic Payloads for Antibody–Drug Conjugates 72: Peptide Therapeutics: Strategy and Tactics for Chemistry, Manufacturing, and Controls 73: Anti-­fibrotic Drug Discovery

How to obtain future titles on publication:

A standing order plan is available for this series. A standing order will bring delivery of each new volume immediately on publication.

For further information please contact:

Book Sales Department, Royal Society of Chemistry, Thomas Graham House, Science Park, Milton Road, Cambridge, CB4 0WF, UK Telephone: +44 (0)1223 420066, Fax: +44 (0)1223 420247 Email: [email protected] Visit our website at www.rsc.org/books

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

Anti-­fibrotic Drug Discovery Edited by

Jehrod Brenneman

KSQ Therapeutics, USA Email: [email protected] and

Malliga R. Iyer

National Institutes of Health, USA Email: [email protected]

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP001

View Online

Drug Discovery Series No. 73 Print ISBN: 978-­1-­78801-­510-­3 PDF ISBN: 978-­1-­78801-­578-­3 EPUB ISBN: 978-­1-­83916-­051-­6 Print ISSN: 2041-­3203 Electronic ISSN: 2041-­3211 A catalogue record for this book is available from the British Library © The Royal Society of Chemistry 2020 All rights reserved Apart from fair dealing for the purposes of research for non-­commercial purposes or for ­ private study, criticism or review, as permitted under the Copyright, Designs and Patents Act 1988 and the Copyright and Related Rights Regulations 2003, this publication may ­ not be reproduced, stored or transmitted, in any form or by any means, without the prior ­ permission in writing of The Royal Society of Chemistry or the copyright owner, or in the case of reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency in the UK, or in accordance with the terms of the licences issued by the appropriate Reproduction Rights Organization outside the UK. Enquiries concerning ­ reproduction outside the terms stated here should be sent to The Royal Society of ­ Chemistry at the address printed on this page. Whilst this material has been produced with all due care, The Royal Society of ­ Chemistry cannot be held responsible or liable for its accuracy and completeness, nor ­ for any consequences arising from any errors or the use of the information contained in this publication. The publication of advertisements does not constitute any endorsement by The Royal Society of Chemistry or Authors of any products advertised. The views and opinions advanced by contributors do not necessarily reflect those of The Royal Society of Chemistry which shall not be liable for any resulting loss or damage arising as a result of reliance upon this material. The Royal Society of Chemistry is a charity, registered in England and Wales, Number 207890, and a company incorporated in England by Royal Charter (Registered No. RC000524), registered office: Burlington House, Piccadilly, London W1J 0BA, UK, Telephone: +44 (0) 20 7437 8656. For further information see our web site at www.rsc.org Printed in the United Kingdom by CPI Group (UK) Ltd, Croydon, CR0 4YY, UK

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP007

Preface Fibrosis is a disease that culminates from aberrant tissue remodeling processes in a variety of organs. Fibrosis itself is not a discrete pathological node for intervention. Instead, it is the downstream outcome of earlier detrimental stress, damage repair or inflammatory states. Thus, targeting fibrotic disease has historically been a reactive, rather than proactive process. Fibrotic disease remains an area of high unmet medical need. In reality, it will only become more of a challenge for doctors, clinicians and health care systems as more of the world adopts lifestyles that promote fibrotic disease progression. Notably, despite the immense body of research focused on developing viable anti-­fibrotic therapies, to date, there have been very few examples of success clinically. The vast majority of therapies targeting the fibrotic disease axes, have met with failure, often during late-­phase clinical evaluation. This may be, in part, due to the complexity of fibrotic disease progression biology, limitations with the current translation capacity of in vitro and in vivo disease models, or a lack of robust disease-­relevant biomarkers. In reality, it is likely to be due to a combination of all these factors and more. Recent progress in understanding the complex interplay of disease and tissue remodeling pathways via systems biology, as well as the implementation of more physiologically relevant tissue culture and 3-­D printed organ models, may help bridge the gap in translating pre-­clinical efficacy to clinical application. This book was conceived as a means of highlighting some of the new therapeutic modalities that are emerging for fibrotic disease treatment. By no means exhaustive, we have chosen to focus on several key targets and pathways that are currently relevant. As a disclaimer, we have purposefully excluded the vast body of work relating to cystic fibrosis (CF) research. The decision to do so was in part due to the large body of work in this field, and

  Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

vii

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP007

viii

Preface

the currently well represented clinical landscape in CF research. Additionally, in CF, tissue remodeling and fibrosis is largely due to inflammatory damage resulting from repeated bacterial infections that are not cleared due to misfolded or ineffective cystic fibrosis transmembrane region (CFTR) proteins. Thus, the majority of current therapies target the CFTR (or are anti-­bacterial) rather than specific tissue remodeling processes. Hence, we have not chosen to include this area of research here. In the same vein, other promising targets and therapies were not included because the stories of their discovery and progression are not ready for publication yet [for instance the Gilead/ Nimbus acetyl-­CoA carboxylase (ACC) program for non-alcoholic steatohepatitis (NASH), the Goldfinch canonical transient receptor potential 6 (TRPC5) inhibitors for chronic kidney disease (CKD), or the Boehringer-­ Ingelheim soluble guanylate cyclase (sGC) activators for diabetic nephropathy (DN)]. Additionally, some topics were omitted as a result of data that emerged during the compilation of this book, which, in turn, warranted a re-­evaluation of their therapeutic potential. As a complex chronic disorder, fibrotic diseases may need polypharmacy of polypharmacological interventions. We envision that subsequent editions of this book would be poised to capture these and the latest emerging concepts and stories in anti-­fibrotic drug discovery in due course. Currently, 998 clinical trials for “fibrosis” are listed on ClinicalTrials.gov. These span a large number of targets for multiple fibrotic indications and involve various study designs. If one looks more closely at the distribution of clinical trials for which a pharmaceutical or biological intervention is under evaluation, it is clear that considerable effort is underway to tackle fibrotic disease (Figure 1). These interventions include cell therapies, antibodies, human proteins, small molecules, natural products/traditional Chinese medicines, and repurposed drugs. As is evident from Figure 1, the majority of clinical activity can be found in treating liver fibrosis. It is however important to point out that this includes a number of anti-­viral therapies targeting hepatitis C. The next largest area of clinical activity is in the space of idiopathic pulmonary fibrosis (IPF). This is in large part due to the clinical successes of the only two approved anti-­fibrotic drugs (pirfenidone and nintedanib, discussed further in Chapter 1). This book seeks to be agnostic to target tissue and therapeutic modality, but our chapters have, in essence, naturally mirrored the distributions shown above. In future editions, we would hope to see an expansion of clinical trials and hence drug discovery programs with robust drug discovery in the cardiorenal space, which is currently lacking. Targeted therapies for systemic sclerosis, ocular fibrosis and rare fibrotic disorders like the Hermansky–Pudlak Syndrome are also currently underway. From a modality perspective, we have captured fibrosis research concepts related to small molecules, carbohydrates, targeted degraders, antibodies and nanotherapeutics. We have also sought to provide insights into the interplay between fibrosis and cancer and the opportunities to capitalize on the research synergies between the two in the future. Our hope is that this book will serve as useful reference

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP007

Preface

ix

Figure 1 Drug Intervention Fibrosis Clinical Trials by Condition. Source: https:// clinicaltrials.gov. Search: “Fibrosis”. Processing: (1) “Condition” manually annotated to group by organ/tissue (998 trials identified); (2) Manually filtered by Intervention to remove diagnostic, device, or NA entries. Accessed: 9-­2-­2019.

tool for anyone working in the field of anti-­fibrotic drug discovery, and will encourage and excite the community at large to continue their search for the next generation of therapies. We wish to thank all of the contributing authors for their hard work and dedication to fibrotic drug discovery and to the compilation of this book. Their tireless dedication and commitment to sharing their work and the work of others in their respective areas of expertise, made this book a reality. We also want to thank all of the reviewers that edited and contributed to the refinement of the chapter content. Their guidance and helpful commentary allowed the chapters to emerge stronger and more insightful as a result. We also wish to thank Dave Rotella of Montclair State University for encouraging the development of this book and Katie Morrey and Drew Gwilliams of the Royal Society of Chemistry for their constant support and guidance during the entire process. Jehrod Brenneman and Malliga Iyer

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011

Contents Chapter 1 T  GFβ Signaling  Anne-­Ulrike Trendelenburg

1.1 Introduction 1.1.1 Fibrosis  1.1.2 TGFβ Signaling  1.2 TGFβ Inhibition 1.2.1 Ligand  1.2.2 Receptors  1.2.3 TGFβRII Antibodies  1.2.4 Signaling  1.2.5 Effectors  1.2.6 Interacting Pathways  1.3 Conclusion  References 

1 1 1 3 6 7 13 13 13 18 21 25 25

Chapter 2 T  argeting the αv Integrins in Fibroproliferative Disease  C. B. Nanthakumar, R. J. D. Hatley and R. J. Slack

37



37 39 39 40 46

2.1 Introduction  2.2 Role of αv Integrins in Fibrosis 2.2.1 TGF-­β and Fibrosis  2.2.2 αv Integrins and Activation of TGFβ  2.3 Disease Implications 

  Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

xi

View Online

Contents

xii

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011



2.4 Assays for Identification of αv Integrin Small Molecule Inhibitors 2.4.1 In Vitro Systems  2.4.2 In Vivo Fibrosis Models  2.5 Drug Design Approaches 2.5.1 RGD αv Integrin Inhibitors – Historic and Current Clinical Landscape  2.5.2 Properties and Drug Design of Small Molecule αv Integrin Inhibitors  2.5.3 Selected Small Molecule αv Integrin Patent Literature 2014–2018  2.6 Future Potential and Perspectives  References 

Chapter 3 D  iscovery, Structural Refinement and Therapeutic Potential of Farnesoid X Receptor Activators  Christina Lamers and Daniel Merk

3.1 Introduction 3.1.1 Structure and Activation Mechanism of FXR  3.1.2 FXR in (Patho)physiology  3.1.3 FXR and Fibrosis  3.2 Targeting FXR 3.2.1 The FXR Ligand Binding Site – FXR Ligand Recognition  3.2.2 FXR Ligand Types and Scaffolds  3.2.3 Hit/Lead Discovery – Identifying Chemical Matter  3.3 FXR Ligand Optimization Towards Clinical Candidates – Refining Chemical Matter 3.3.1 Steroidal FXR Agonists  3.3.2 Non-­steroidal FXR Agonists  3.3.3 Other Non-­steroidal FXR Agonists  3.4 Conclusions and Future Perspective  Abbreviations  References 

48 48 51 55 55 57 60 64 65 76 76 77 78 80 81 81 83 84 87 87 91 97 101 103 104

Chapter 4 A  utotaxin Inhibitors in Fibrosis  N. Desroy and B. Heckmann

117



117 118 120 122 123 125 125

4.1 Introduction 4.1.1 Role of ATX/LPA Biology in Fibrosis  4.1.2 Structure of ATX  4.1.3 ATX Inhibition Assays  4.2 ATX Inhibitors in Fibrosis 4.2.1 Ribomic, RBM-­006  4.2.2 iOnctura, IOA-­289 

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011

Contents



xiii

4.2.3 Amira  4.2.4 PharmAkea, PAT-­409  4.2.5 Galapagos, GLPG1690  4.2.6 X-­Rx, X-­165  4.2.7 Bridge Biotherapeutics, BBT-­877  4.3 Conclusion  References 

Chapter 5 I nhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes: Intervention at the Core of Fibrotic Pathology  Alison Findlay, Craig Turner and Dieter Hamprecht

5.1 Introduction  5.2 The Lysyl Oxidase Family of Enzymes  5.3 Lysyl Oxidases Catalyse the Formation of Cross-­links  5.4 Other Roles of Lysyl Oxidases  5.5 Lysyl Oxidase Expression in Healthy and Disease Tissue  5.6 Inhibitors of Lysyl Oxidase (Like) Enzymes  5.7 Conclusion and Outlook  Acknowledgements  References 

Chapter 6 T  argeting the Ubiquitin Proteasome System in Pulmonary Fibrosis  Andrew J. Thorley, Simon Krautwald and ­ David J. Rowlands

6.1 Idiopathic Pulmonary Fibrosis  6.2 The Ubiquitination Pathway  6.3 Proteasome Inhibitors  6.4 Regulation of E3 Ligases  6.5 Unfolded Protein Response  6.6 Mitochondrial Dysfunction and Senescence  6.7 The Deubiquitination Pathway 6.7.1 UCHL5  6.7.2 USP11  6.7.3 CYLD  6.7.4 USP13  6.8 Therapeutically Targeting the Ubiquitin Proteasome System 6.8.1 E3 Ligases  6.8.2 Deubiquitinases  6.9 Conclusion  References 

127 128 131 133 136 138 139

145 145 146 148 150 150 151 159 160 160 165

165 166 168 169 169 171 172 173 173 173 174 174 175 178 179 179

View Online

Contents

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011

xiv

Chapter 7 G  alectin-­3 Involvement in Fibrotic Diseases  Xiaosong Jiang, Natalie J. Torok and Joseph J. Barchi Jr

185



185 187 187 189 189 190



7.1 Introduction  7.2 Gal-­3 in Organ Fibrosis 7.2.1 Liver  7.2.2 Kidney  7.2.3 Lung  7.2.4 Heart  7.3 Anti-­Gal-­3 Therapeutic Design and Discovery in Fibrotic Disease  7.4 Direct and Putative Therapeutic Targeting of Gal-­3 in Fibrosis 7.4.1 Liver  7.4.2 Kidney  7.4.3 Lung  7.4.4 Heart  7.5 Future Outlook  References 

191 195 195 196 196 197 198 199

Chapter 8 E  merging Role of CXCR4 in Fibrosis  Xilun Anthony Wang, Katherine Griffiths and Michael Foley

211



211 214 218 220 222 226

8.1 Introduction  8.2 Idiopathic Pulmonary Fibrosis  8.3 Kidney Fibrosis  8.4 Eye Fibrosis  8.5 Anti-­CXCR4 Therapies  References 

Chapter 9 B  H3 Mimetic Drugs for Anti-­fibrotic Therapy  David Lagares

235



235



9.1 Introduction  9.2 Myofibroblast Apoptosis During Tissue Repair and Fibrosis  9.3 Control of Apoptosis By the BCL-­2 Family of Proteins  9.4 Molecular Mechanisms Controlling Myofibroblast Survival in Tissue Fibrosis  9.5 Mitochondrial Apoptotic Priming is Increased in Myofibroblasts  9.6 BH3 Mimetic Drugs Induce Myofibroblast Apoptosis and Reverse Established Fibrosis 9.6.1 ABT-­737  9.6.2 ABT-­263 

236 237 240 243 244 247 247

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011

Contents



xv

9.6.3 A-­1331852  9.6.4 A-­1155463  9.6.5 WEHI-­539  9.6.6 ABT-­199  9.6.7 S63845  9.6.8 GX15-­070  9.6.9 Summary  9.7 BH3 Profiling: A Functional Biomarker to Predict Anti-­fibrotic Efficacy of BH3 Mimetics in Clinical Settings  References 

Chapter 10 I ntratumoral Fibrosis: Emerging Concepts and Therapeutic Opportunities  Viviana Cremasco and Jonathan Chang

10.1 Introduction  10.2 The Desmoplastic Reaction 10.2.1 The Provisional Matrix and the Induction of Tumor Fibrosis  10.2.2 Collagen Deposition and Crosslinking in the Tumor Microenvironment  10.3 Cancer-­associated Fibroblasts 10.3.1 Phenotypic Features of CAFs  10.3.2 Origin of CAFs  10.4 CAF Functions in the Tumor Microenvironment 10.4.1 Modulation of Cancer Cell Growth, Proliferation and Survival  10.4.2 Contribution of CAFs and ECM to Drug Resistance  10.4.3 Immunomodulatory Functions of CAFs  10.5 Targeting Fibrosis in Cancer: An Unfolding Clinical Concept 10.5.1 Use of Antifibrotic Drugs in Cancer Patients  10.5.2 Direct Targeting of CAFs  10.6 Concluding Remarks  References 

248 248 248 248 249 249 249 250 254 259 259 261 262 263 265 266 268 270 270 276 278 285 285 288 289 290

Chapter 11 T  argeting Fibroblasts in Fibrosis and Cancer  Ahmed M. R. H. Mostafa, Ruchi Bansal and Jai Prakash

307



307 309 309

11.1 Fibrosis in Organs and Cancer  11.2 Fibroblasts – Key Players in Fibrosis and Cancer  11.3 Fibroblasts – Origin and Heterogeneity 

View Online

Contents

xvi

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-FP011



11.4 Role of Fibroblasts in Organ Fibrosis and Cancer 11.4.1 Role of Fibroblasts in Organ Fibrosis  11.4.2 Role of Fibroblasts in Cancer  11.5 Strategies to Target Fibroblasts 11.5.1 Potential Targets in Fibroblasts  11.5.2 (Myo)-­fibroblast Targeting Systems  11.6 Concluding Remarks  References 

Subject Index 

312 312 313 314 315 320 326 326 340

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

Chapter 1

TGFβ Signaling Anne-­Ulrike Trendelenburg* Novartis Institutes for Biomedical Research, Musculoskeletal Disease Area, Cambridge, MA 02139, USA *E-­mail: anne-­[email protected]

1.1  Introduction 1.1.1  Fibrosis Fibrosis, a pathological process characterized by excessive accumulation of extracellular matrix (ECM), contributes to the pathology of a variety of chronic diseases. Fibrosis can manifest in almost any organ and tissue, for example, the lung, kidney, heart, liver, muscle and skin. It is believed that about 45% of deaths are caused by fibrotic diseases, indicating the high importance of anti-­fibrosis therapeutic approaches. Progress has been made in recent years in understanding the molecular pathways causing fibrosis and subsequently finding targets suitable for therapy. Currently two molecules are approved for anti-­fibrosis therapy, pirfenidone and nintedanib, and many others are in preclinical and clinical development.1–3 In general, molecular mechanisms causing fibrosis are very similar across tissues and organs. Under physiological conditions fibrosis is a protective response to injury, recapitulating development processes to regenerate functional tissues, and is not a cause of disease. It is a key element in the early phase of wound and injury healing (i.e. physiological fibrosis), but can persist in inflammatory microenvironments, or in the presence of

  Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

1

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

2

Chapter 1

pro-­fibrotic triggers leading to permanent organ and tissue dysfunction (i.e. pathological fibrosis). In pathological fibrosis, resident, functional cells (e.g. alveolar epithelial cells) are permanently replaced by myofibroblasts, also called contractile fibroblasts. Myofibroblasts are transformed from multiple cell types, in particular tissue-­resident mesenchymal stem cells (MSC), epithelial cells (EC), endothelial cells (EndC) and fibroblasts, to enable migration to the injury site, contractility and production of ECM as a framework in the early repair phase. However, in physiological repair, this fibrotic transformation is temporary and subsequently replaced by tissue-­specific regeneration. In a pro-­fibrotic environment, myofibroblasts lacking tissue-­specific functions remain and cause tissue and organ malfunction.4–8 In cancer, fibrosis is described as a double-­edged sword, being both pro-­ and anti-­tumorigenic. Normal tissue fibroblasts restrain tumor initiation, whereas cancer-­associated fibroblasts (CAF) are critical components of the tumor supporting microenvironment, such that “anti-­fibrotic” therapy is an important element in cancer immunotherapy (see also Chapter 10). Thus, it is not surprising that most of the principles discussed in the present chapter are clinically explored in both cancer and fibrosis. However, since safety requirements for oncological drugs are quite different, adverse events acceptable for cancer therapy are often not favorable for use in general medicine.9 Transforming growth factor beta (TGFβ) signaling has been identified and broadly confirmed as a master regulator of fibrosis and presents a major target for pharmacotherapy. This chapter will discuss TGFβ signaling. As this is a very broad topic, an abundance of literature around TGFβ signaling is available. The focus here will be on the role of TGFβ in fibrosis, including elaboration on the emerging genetic links to disease, current thinking around the different levels of intervention, as well as the notable achievements and challenges of drug therapy in this pleiotropic pathway. Regarding the last point, the goal of an ideal anti-­fibrotic therapy is to efficiently and safely discriminate between normal physiological and undesired pathological fibrosis pathways. This has remained a major challenge for some time. Many anti-­fibrotic therapy agents looked very promising in preclinical studies, but poor translation to clinical application and unfavorable risk–benefit profiles in patients has often resulted in termination of drug development outside of cancer indications. This review will focus on the role of TGFβ in the indications of idiopathic pulmonary fibrosis (IPF) and muscular dystrophies, both diseases with severe fibrosis phenotypes and poor overall prognosis. Notably, IPF is very often used as initial clinical entry point for anti-­fibrotic drugs. As fibrotic mechanisms are often similar across tissues and organs, the principles successful in treating fibrosis in IPF also have a good chance of translating to other fibrotic conditions. The review will attempt to focus on the most relevant data for anti-­fibrotic TGFβ therapy. Additional information and detailed references are also provided.10–13

View Online

TGFβ Signaling

3

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

1.1.2  TGFβ Signaling The TGFβ superfamily is a large group of more than 35 structurally related proteins with different cell regulatory functions, including the TGFβ1/2/3 isoforms, activins, inhibins, bone morphogenic proteins (BMPs), growth differentiation factors (GDFs) and various others. Nomenclature around TGFβ is sometimes confusing as it has evolved over time, and the term TGFβ is used for both the superfamily and three, but not all, of its members, TGFβ1/2/3. The family was named after its first discovered protein, now known as TGFβ1. TGFβ1 was initially identified as a sarcoma growth factor (SGF) that was clearly different from another SGF, the epidermal growth factor (EGF, also known as TGFα). SGFs are secreted from cancer cells and generally stimulate growth, even though TGFβ can both stimulate and inhibit growth. More importantly for fibrosis, SGFs transform cells by causing profound morphological (e.g. growing in colonies on soft agar) and functional alterations, and thus SGFs were renamed TGFs. Later, TGFβ1 was cloned and two additional isoforms identified, namely TGFβ2 and TGFβ3. In this chapter, we will focus on the three TGFβ isoforms, TGFβ1–3, as they are the major pro-­fibrotic factors, even though other members of the TGFβ superfamily (e.g. BMP9 and activin A) are also involved in fibrotic diseases.13–18 TGFβ1, TGFβ2 and TGFβ3 have quite different functions, mainly based on their tissue expression and activation. This is also reflected by significantly different phenotypes observed in TGFβ1, TGFβ2 and TGFβ3 knockouts (KOs).19 TGFβ′s are produced as precursors consisting of an active C-­dimer and a latency associated peptide (LAP) which form the small latent complex (SLC). The SLC is further bound to different latent TGFβ binding proteins (LTBPs) in the large latent complex (LLC) which anchors latent TGFβ in the ECM and serves as a store of inactive TGFβ. In general, less than 1% of TGFβ occurs in the free, active C-­dimer form, so that it has to be released from the latent complex to trigger TGFβ signaling (see Figure 1.1). This activation process is quite diverse and subject to disease modification. The active TGFβ C-­dimer binds to type II TGFβ receptors (TGFβRII) which phosphorylate type I activin-­like kinase (ALK) receptors to induce canonical small and mothers against decapentaplegic (Smad) signaling. In brief, receptor Smads (Smad2/3 or Smad1/5/8) are phosphorylated by ALKs, bound to co-­Smad (Smad4/5) and then translocated into the nucleus to induce gene transcription events. Though TGFβ mainly functions via ALK5 to induce Smad2/3, it can also use ALK1 and Smad1/5/8 for signaling. It regulates production of inhibitor Smads (Smad6/7) which serves as a negative feedback loop. In addition, non-­canonical TGFβ signaling has been widely described. For example, activation of TGFβ-­activated kinase 1 (TAK-­1) and various downstream signaling networks [including those involving p38, c-­jun N-­terminal kinase (JNK), nuclear factor kappa B (NFκB) and inhibitor of DNA binding 1 (ID-­1)] are highly relevant for fibrosis. The three TGFβ isoforms produce similar effects if applied exogenously, confirming that isoform specificity seems to be mainly based on tissue expression and activation processes (for more details see ref. 11–13, 20–22 and 57).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

4

Chapter 1

Figure 1.1  Scheme  of TGFβ pathway and potential interventions. In fibrosis, tissue-­resident ECs are transformed into MSCs, a process called epithelial–mesenchymal transition (EMT), and subsequently transdifferentiated into myofibroblasts upon stimulation with pro-­fibrotic factors, such as the major fibrotic cytokine TGFβ. The origin of myofibroblasts has been debated and more recently EMT was also described as set of multiple and dynamic transitional states rather than a single transition between EC and MSC. Such intermediate EMT states promote organ fibrosis by producing pro-­fibrotic environments and subsequently triggering myofibroblast transformation from tissue-­residual fibroblasts.23 Myofibroblast transformation causes increases in cell mobility and a change to a contractile phenotype to enable the initial phase of tissue repair. In pathological fibrosis, this transformation is permanent and leads to tissue and organ dysfunction. While myofibroblasts can be derived from various cell types, TGFβ is a common and by far the best characterized activator of myofibroblast generation. The most important evidence for the central role of TGFβs in fibrosis comes from transgenics, where overexpression of TGFβ1 induces and promotes tissue fibrosis. Moreover, various genetic diseases with increased TGFβ signaling such as cystic fibrosis (CF), Marfan syndrome and Duchenne’s Muscular Dystrophy (DMD) present severe fibrotic phenotypes which were shown to be further facilitated by genetic modifiers, such as TGFβ and LTBP4 polymorphisms. Interestingly, most studies in the literature describe dysregulation of TGFβ1, the only isoform with endocrine functions, and thus, detectable in body fluids. In contrast, TGFβ2 and TGFβ3 function primarily in an autocrine and paracrine manner, which means that they are usually not detectable in body fluids and

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

5

subsequently protein changes are less likely to be observed. However, in fibrosis autocrine and paracrine TGFβ action is predominant, and all three TGFβ isoforms may play a role.24–29 Given its major role in fibrosis, TGFβ is a very attractive target for anti-­ fibrotic therapies. However, TGFβ action is pleiotropic and important for development and many normal physiologic processes. Therefore, the major hurdle for anti-­TGFβ therapy is safety. TGFβ knockout (KO) mice show major pathologies and similarly severe adverse events have been observed with various approaches to TGFβ inhibition. This might be the main reason that no “direct” TGFβ inhibitor has reached the market for any indication, despite the numerous approaches pursued. More recently, extensive studies have helped to identify more specific pathway targets and approaches to ‘indirectly” interact with TGFβ signaling with promising therapeutic opportunities. A first good example is the development of pirfenidone, which indirectly reduces TGFβ signaling and has been approved for treatment of IPF. Another example is nintedanib, a poly-­kinase inhibitor interfering with TGFβ signaling, which also reached the market for IPF as well as for cancer indications. In general, most of the anti-­fibrotic principles are either rederived or are concomitantly explored in cancer indications (primarily immuno-­oncology) as EMT transformation and subsequent TGFβ signaling play a major role in tumorigenesis and metastasis.22,30–33 Fibrosis can occur in almost any tissue and organ (recently reviewed in ref. 34), and a list of fibrotic diseases can be found in Table 1.1. IPF is the most common and severe form, affecting about five million patients worldwide, and is characterized by a progressive and irreversible decline in lung function with an average life expectancy of four years after diagnosis. Even though the cause is unknown, age as well as environmental and lifestyle factors seem to play a pivotal role. Most anti-­fibrotic agents are initially tested in IPF, and the two compounds approved are for this indication. However, as the principles underlying fibrosis are very similar across various diseases, indication expansions into other fibrotic areas are pursued and have high potential to succeed. This is particularly true when intervening with TGFβ signaling, which is linked to almost every form of fibrosis (see Table 1.1). Other commonly affected organs are the liver, heart, muscle, eye, kidney, skin and even the bone marrow. The most impressive occurrence of fibrosis can be observed in muscle from end-­ stage DMD patients, where muscles are almost completely replaced by fibrotic tissue with a profound loss of muscle function.35 In DMD, permanent muscle damage and subsequent repair in an increasingly inflammatory environment leads to extensive fibrosis, which is further enhanced in patients with LTBP4 modifiers.28,36 LTBP4 polymorphism was also shown to be a modifier in other fibrotic diseases (e.g. in heart and lung) and needs to be carefully considered in the selection of mouse strains for pre-­ clinical animal models.37

View Online

Chapter 1

6

Table 1.1  Overview  of diseases with fibrosis.

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

a

Tissue/Organ

Disease

TGFβ signaling

Lung

Idiopathic pulmonary fibrosis (IPF) Pulmonary hypertension Emphysema Dystrophies (g): e.g. Duchenne’s muscular dystrophy (DMD), Sarcopenia Non-­alcoholic fatty liver diseases (NAFLD) Hepatitis Cirrhosis Arrhythmia Myocardial infarction Cardiac fibrosis Cardiomyopathy Valvulopathies Marfan (g) Hypertrophic scars Keloid Glaucoma Cataract Focal segmental glomerulosclerosis (FSGS) Chronic kidney disease (CKD) Diabetic nephropathy Irritable bowel disease (IBD) Intestinal fibrosis Crohn's disease Vascular fibrosis Arterial stiffness Peritoneal fibrosis in dialysis patients Myelofibrosis Cystic fibrosis (g, CF) Systemic sclerosis (SSC) Sarcoidosis Cancer fibrosis/tumor stroma Irradiation-­induced fibrosis Type 2 diabetes (T2D) Graft versus host disease (GvHD)

Yes

Skeletal muscle Liver Heart

Skin Eye Kidney

Intestine Vessels Peritoneum Bone marrow Multi-­tissue/organ

Yes Yes Yes

Yes Yes Yes

Yes Yes Yes Yes Yes

a

g = genetic diseases.

1.2  TGFβ Inhibition As the master regulator of fibrosis, TGFβ is by far the most attractive and broadly explored target for anti-­fibrotic therapy. Interventions on many different levels of TGFβ signaling have been explored, such as blocking directly the ligand, the receptors, canonical and non-­canonical signaling paths, its effectors as well as interacting pathways. A common challenge for all approaches is to find effective and safe compounds in this pleiotropic pathway. Both overexpression and knockout of TGFβ cause significant

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

7

pathology, such that full inhibition is unlikely to be safe and tolerated. This can be limiting for antibody approaches, which usually show high specificity and target engagement, such that partial inhibition is hard to achieve. In contrast, low molecular weight (LMW) compounds can be carefully dosed, but often lack specificity or selectivity against related targets. This holds particularly true for kinase inhibitors (e.g. ALK), and is one reason why those are mainly used in cancer therapy. Similarly, enzymes such as proteases [e.g. matrix metalloproteinase (MMP)] are large families with quite different, sometimes opposite functions of isoforms. Increased understanding of the pathway and lessons learned from earlier failures helped to identify more specific intervention nodes, as well as advanced generations of drugs with improved risk–benefit profiles. Interestingly, the two compounds on the market for IPF with good risk–benefit ratios and manageable adverse events are indirect TGFβ inhibitors without a well-­ defined mode of action.

1.2.1  Ligand This section will discuss approaches aiming to directly block TGFβ ligands, by either inhibiting their production using antisense oligonucleotides (ASOs) or neutralizing their action by antibodies, inhibitory proteins or receptor traps (for summary see Table 1.2).

1.2.1.1 Production The production of TGFβ isoforms is reduced using ASOs, a highly specific way to knockdown expression of a single TGFβ isoform. Both TGFβ1 and TGFβ2 have been targeted, and TGFβ2 ASOs progressed to phase 3 clinical trials for cancer indications.38,39 Trabedersen (AP12009, OT 101), a synthetic TGFβ2 ASO was in clinical trials for various cancer indications with initially encouraging results,40–42 and TGFβ1 ASOs have been successfully tested in preclinical fibrosis and cancer models (see ref. 38 and 41). However, a big hurdle for ASO therapy is the delivery of the agent to the target tissue. Local or targeted delivery is needed for sufficient efficacy in humans. For example, trabedersen was directly applied into the tumor, an approach quite feasible for isolated tumors, but questionable for most fibrotic diseases. Thus, it is not surprising that there were only a few ASO approaches, and none of them has reached clinical use for fibrotic indications. Ultimately, the development of sophisticated delivery systems may enable further exploration of knockdown approaches in human fibrosis in the future. One such promising approach has been the use of TGFβ1 small interfering RNA (siRNA) encapsulated in liposome-­based nanoparticles. This successfully reduced peritoneal fibrosis, which in some instances is responsible for the discontinuation of peritoneal dialysis, in a preclinical model.43

Specificity

Molecule

Production TGFβ antisense (ASOs)

TGFβ1

AP11014

TGFβ2

Trabedersen AP12009

pan

αvβ6

FG-­2575 RXP-­1001 S33A Sizzled UK383367 STX-­100 (BG00011)

THBS inhibitors

αvβ6 pan

GSK3008348 LSKL peptide



GARP inhibitors

pan

ABBV151



Neutralization TGFβ antibodies

pan

Fresolimumab, (GC1008) SAR439459 Metelimumab (CAT192) LY2382770



Terminated

Fibrosis, Cancer

√ √

Terminated

Cancer Fibrosis



Terminated

Fibrosis

Lerdelimumab (CAT152) XPA-­089 Distertide P144® peptide AVID 200 Recombinant decorin



Discontinued

Fibrosis

Activation BMP1/tolloid-­like proteinase inhibitors Integrin inhibitors

pan TGFβ1

TGFβ2/3 TGFβR receptor traps Decorin mimetic

TGFβ1/2 pan TGFβ1/3 pan

Clinical Status



Indication

Comments

Fibrosis

Local skin application, preclinical data also in systemic fibrosis Route of administration challenging for systemic fibrosis

Cancer

√ Discontinued

Fibrosis

Highly potent with different selectivity profiles. None pursued to clinical use.

Fibrosis, Cancer

αvβ6 antibody, αvβ3, αvβ5 and αvβ8 also linked to fibrosis. Inhaled αvβ6 LMW Controversial as agonist is tested in cancer indications. Tissue-­or disease-­specific (T-­cells)

Fibrosis Fibrosis Cancer

√ √

Cancer Fibrosis

√ √

Fibrosis, Cancer Cancer, Fibrosis

Dose-­limiting adverse events; risk–benefit. Only few data from abstracts. Dose-­limiting adverse events, risk–benefit. Dose-­limiting adverse events, risk–benefit. Local after glaucoma surgery, lack of efficacy in phase 3 TGFβRIII peptide topical application. Intravenous infusion in phase 1 Short half-­life prevents systemic application, explored locally for ocular diseases.

Chapter 1

Principle

8

Published on 17 February 2020 on https://pubs.rsc.org | d

Table 1.2  Overview  of therapeutic approaches targeting production, activation and neutralization of TGFβs.

View Online

TGFβ Signaling

9

1.2.1.2 Neutralization

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

This section will discuss approaches aiming to neutralize the action of TGFβ through binding to antibodies, inhibitory proteins or receptor traps. 1.2.1.2.1  Antibodies.  Neutralizing antibodies against TGFβs, which bind the active C-­dimers and subsequently prevent receptor activation, are a common approach and extensively tested both preclinically and clinically in fibrotic diseases as well as cancer indications. By far, the most information is available for the pan-­TGFβ antibody, GC1008 (fresolimumab), which equally blocks TGFβ1, TGFβ2 and TGFβ3. Fresolimumab, or more often the mouse surrogate 1D11, has been explored in various fibrosis and cancer preclinical models with generally good efficacy. However, not surprisingly, dose-­limiting adverse events were observed in clinical settings and consequently very limited clinical success has been reported.44–47 SAR439459, potentially a follow-­up pan-­TGFβ antibody, has entered clinical trials for oncology indications (NCT03192345), and some of the first data is emerging in abstracts,48,49 but it remains to be seen whether this therapy will provide a significant benefit. XPA-­068, is another antibody with a similar broad-­spectrum profile, that has been preclinically studied in cancer. The results of these studies indicated that TGFβ1/2 inhibition is sufficient for tumor immunosurveillance. So the more selective antibody XPA-­ 089 (neutralizing only TGFβ1 and TGFβ2), was advanced to clinical use42,50,51 solely for cancer. It will be very interesting to see the clinical safety profile of this TGFβ1/2 antibody. In general, more favorable safety profiles might be expected from antibodies with a more limited specificity, in particular those antibodies neutralizing only one TGFβ isoform. Indeed, TGFβ1-­selective antibodies CAT192 (metelimumab),52 LY2382770,53 and a dual TGFβ2/3-­selective antibody CAT152 (lerdelimumab)54,55 have been widely explored in fibrosis. Despite good preclinical efficacy, clinical success for all these antibodies was very limited. In particular, inhibition of TGFβ1, the only endocrine isoform with important roles in fibrosis and many other functions, seems to be linked to dose-­limiting (mainly immunological) adverse events. Thus, targeted delivery of TGFβ antibodies similar to the approach described for ASOs is being explored. For example, a bispecific antibody against TGFβ and an extracellular domain of fibronectin was shown to enrich in fibrotic tissue and reduce fibrosis in a preclinical kidney fibrosis model.56 In summary, safety is the major limit for the therapeutic use of TGFβ antibodies in human fibrotic indications, whereas use in cancer indications is more feasible. When administered systemically, fresolimumab,44,45,47 metelimumab or LY2382770 53 did not show clear therapeutic effects, and some of the trials terminated early due to non-­favorable risk–benefit outcomes. Lerdelimumab was locally applied to reduce scaring after glaucoma surgery, but failed in phase 3 after promising results in earlier clinical trials.54,55 It appears that use of the more specific TGFβ2-­ or TGFβ3-­mono-­selective antibodies with potentially more favorable safety profiles, in combination with

View Online

10

Chapter 1

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

emerging targeted tissue-­delivery technologies may be the most promising future directions for antibody targeting in this pathway. 1.2.1.2.2  Inhibitory Proteins and Decoy Receptors.  Inhibitory proteins, such as decorin, or decoy receptors, bind active TGFβ C-­dimers to prevent receptor activation in a similar way as antibodies (for review see ref. 13 and 57). Again, specificity and subsequently safety is a major challenge as previously discussed for TGFβ antibodies. As such, only a few approaches have been pursued in clinical settings for fibrosis indications. In the following section, decorin and two TGFβ receptor traps are discussed. Decorin is a structural component of the connective tissue and a close relative of biglycan. It forms complexes with TGFβs and subsequently blocks their action, but also binds and neutralizes other proteins, including connective tissue growth factor (CTGF) and thrombospondins (THBS). Recombinant decorin was studied in cancer indications, but due to its relatively short half-­life, the high doses needed, and challenging production, it was not further developed for any systemic application. However, it has been explored locally in fibrotic eye diseases.58–60 AVID200 is a computationally designed TGFβR-­based trap that binds TGFβ1 and TGFβ3, but not TGFβ2 to minimize adverse events.61 It is currently in phase 1 trials for systemic sclerosis (NCT03831438) and has been tested in various cancer indications (reviewed by ref. 57). P144® (distertide) is a synthetic TGFβ inhibitor 15-­mer peptide derived from the TGFβRIII (also known as betaglycan). It has been explored in various preclinical fibrosis and cancer models,62–65 but it is poorly soluble and hydrophobic, so that systemic application is difficult.66 However, it was tested as a topical cream for skin fibrosis in systemic sclerosis patients (NCT00574613). This clinical trial has completed, but no data has been published (Scheme 1.1).

Scheme 1.1  Distertide. 

View Online

TGFβ Signaling

11

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

1.2.1.3 Activation This section will discuss approaches designed to inhibit activation of the TGFβ ligands from latency by various enzymatic processes as well as integrin receptors. As a complete chapter in this book is dedicated to integrin signaling, only a short summary will be given. TGFβs are stored as latent complexes, and for fibrotic diseases, storage in the ECM and subsequent activation by enzymatic processes or integrin signaling plays a major role. Under disease conditions, expression of TGFβ genes can be directly regulated. However, in some instances, expression of the ligand activating proteins can be even more effectively regulated. Intervening on the level of ligand activation may provide some specificity concerning isoforms and also pathologic processes. 1.2.1.3.1  BMP-­1/Tolloid-­like Proteinase (Tolloids) Inhibition.  BMP-­1/ Tolloid-­like proteinases (tolloids, also known as procollagen C-­proteinase67), consist of BMP-­1, BMP-­1 histidine rich (BMP-­1/his), mammalian tolloid (mTLD), tolloid like 1 (TLL-­1) and TLL-­2 68 with differential enzymatic activities and distributions.69 They activate TGFβ via cleavage of LTPBs and subsequent cleavage of LAPs by other proteases.70,71 In addition to TGFβ, tolloids cleave a range of ECM precursors such as procollagen, chordin, pro-­ myostatin and the TGFβ co-­receptor betaglycan.68,72 Thus it is not surprising that they play a key role in fibrosis and are interesting targets for pharmacotherapy. Moreover, TGFβ is a potent inducer of tolloids, contributing to a positive feedback loop.71–73 α2-­Macroglobulin serves a natural tolloid inhibitor,73 and highly potent LMW tolloid inhibitors as well as a BMP1–3 antibody have been generated with different potency and selectivity profiles to inhibit tolloids (for reviews see ref. 74–77). They have been tested, for example, in preclinical models of liver fibrosis78 or as anti-­scarring agents, but have not reached clinical use. Most probably compound and substrate selectivity profiles are limiting factors for tolloids and are presumably the reason they were not pursued clinically.76 If this is the case, these limitations might be partly overcome in the future by improved selectivity for tolloid isoforms and related proteases. 1.2.1.3.2  Integrin Inhibition.  Inhibition of integrins is a promising strategy to block TGFβ activation, and a full chapter in this book is dedicated to integrin inhibition (see Chapter 2). Briefly, integrins are a large family of cell adhesion and signaling receptors. A subset of integrins (αvβ3, αvβ5, αvβ6, αvβ8), play a key role in activation of TGFβ1 and TGFβ3 by binding to LAPs and liberating active C-­dimer from the LLC.79–81 Integrin inhibition by functional antibodies or low molecular weight inhibitors82 has been broadly explored in fibrotic diseases. Most preclinical data are available for the αvβ6, antibody STX-­100 (BG00011)82 along with the inhaled LMW compound GSK3008348,83 which have both been explored in clinical trials for IPF. Overall, more than 150 clinical trials are ongoing

View Online

12

Chapter 1

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

using integrin inhibitors with different specificity in various indications, including fibrosis.81 This reflects the promise of targeting this pathway (Scheme 1.2). 1.2.1.3.3  Thrombospondin Inhibition.  Thrombospondins (THBS) are other proteins that bind to LAP and modulate TGFβ activation.84 Binding is dependent on a specific sequence which was used to generate the peptide inhibitor LSKL85 (for review see ref. 84 and 86). It has been tested in various fibrotic disease models with good tolerability and anti-­fibrotic activity,87–89 but so far has not passed preclinical evaluation despite potentially offering a more promising path to TGFβ inhibition.84 However, this concept is somewhat controversial as the THBS analogue ABT-­510 has been explored in various cancer patients to inhibit angiogenesis with good tolerability, but little benefit.90,91 Definitely more data is needed to decide on the value of THBS inhibition (Scheme 1.3). 1.2.1.3.4  Glycoprotein A Repetitions Predominant (GARP) Inhibition.  A more recently identified mechanism which activates TGFβ, on regulatory T cells for example, is via glycoprotein A repetitions predominant [GARP, leucine rich repeat containing 32 (LRRC32)].92,93 GARP is believed to be one of the few specific activation elements (reviewed by ref. 94 and 95), and plays a role in cancer, fibrosis and immune disorders.94,96 A GARP antibody, ABBV-­ 151 is in phase 1 clinical trials for cancer indications (NCT03821935),57,93 but

Scheme 1.2  GSK3008348. 

Scheme 1.3  ABT-­  510.

View Online

TGFβ Signaling

13

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

very limited data is available for ABBV151 in fibrotic diseases. However, as GARP is of increasing interest in TGFβ signaling, such data should be on the way along with safety data.

1.2.2  Receptors This section will discuss approaches aiming to inhibit TGFβ activity on the level of signaling receptors, including type 1 ALK4/5 and type 2 TGFβRII receptors (for summary see Table 1.3).

1.2.2.1 Activin Receptor Like Kinase (ALK) Inhibition Type 1 receptor inhibition, in particular ALK4/5-­mediated canonical TGFβ signaling, is one of the most extensively explored mechanisms with broad TGFβ inhibition. There is a large amount of preclinical evidence in many indications, and various companies have had compounds in development. The most preclinically studied ALK4/5/7 inhibitor in scientific literature is SB-­431542 (Inman et al. 2002, more than 800 publications) which is highly efficacious in many fibrosis models (e.g. ref. 97), but not as suitable for clinical use as the follow up compound SB-­525334.98 In general, the therapeutic attractiveness of ALK4/5/7 inhibitors was diminished due to the observation of severe adverse events, most prominently valvulopathy99 and the majority of clinical projects were stopped. However, intermittent application, based on pharmacokinetic/pharmacodynamic models to determine a therapeutic window, seemed to circumvent severe adverse events, and some compounds, such as galunisertib and vactosertib (TEW 7197), made it to clinical use for cancer indications. Patients are 14 days on and 14 days off galunisertib, in 28 day cycles100,101 and vactosertib (TEW 7197) is given 5 days per week with 2 days off (ref. 102, NCT02160106). Whether such dosing regimens are also suitable for fibrotic indications remains to be explored. Notably, additional target adverse events are frequently observed with ALK4/5/7 inhibitors. This is not necessarily surprising since selectivity over other kinases can be hard to achieve for this class (see ref. 103) (Scheme 1.4).

1.2.3  TGFβRII Antibodies To date, Type II receptor inhibition has rarely been explored. One notable example is the TGFβRII antibody (LY3022859), which has only been evaluated for cancer indications. However, no safe and tolerable dose was achieved in a phase 1 clinical trial.104

1.2.4  Signaling This section will discuss approaches aiming to inhibit TGFβ signaling downstream of receptor activation. Both inhibitors of canonical and the two non-­ canonical signaling pathways will be included (for summary see Table 1.3).

Published on 17 February 2020 on https://pubs.rsc.org | d

Table 1.3  Overview  of therapeutic approaches targeting TGFβ receptors, direct signaling, effectors and interacting pathways. Principle

Specificity

Molecule

Clinic

Receptors ALK 5 inhibitor

ALK 4/5/7

Galunisertib LY2157299

ALK 4/5/7

Vactosertib TEW-­7197

ALK 4/5/7 pan

SB431542, SB525334 LY3022859



Terminated Cancer

NOX inhibitor

Smad3 Smad3 NOX1/4/(5)

SIS3 Halofuginone GKT137831

√ √

Fibrosis, Cancer Terminated Fibrosis Fibrosis

TAK-­1 inhibitor

NOX4 pan n.a.

GLX7013114 VAS2870 Takinib

Fibrosis, Cancer Cancer, Fibrosis Fibrosis

pan JNK1>JNK2

Tanzisertib CC-­930 √ CC9001 √

Fibrosis Fibrosis, Cancer

n.a.

SK216

Fibrosis

n.a.

TM5275

Fibrosis

MMP12

FP-­025



Fibrosis

MMP2/9

S3304



Cancer

MMP9

Andecaliximab (GS-­5745)



Cancer, Fibrosis

TGFβRII inhibitor Direct signaling Smad2/3

JNK inhibitor Effectors PAI-­1 inhibitor

MMP inhibitor

Status

Indication

Comments



Cancer



Cancer

Intermittent dose regimen to avoid cardiac side effects, risk–benefit for fibrosis questionable. Intermittent dose regimen to avoid cardiac side effects, risk–benefit for fibrosis questionable On-­target cardiac side effects (valvulopathy) Antibody no safe dose was achieved

Fibrosis, Cancer

Only preclinical data available Explored for DMD Excellent safety and tolerability, but not sufficient efficacy First in vitro data published No clinical data found Liver toxicity of KO limit use of inhibitors. Unfavorable risk–benefit Improved safety compared with CC-­930 Pro-­and antifibrotic, broadly used as biomarker Pro-­and antifibrotic, broadly used as biomarker Needs more data regarding isoform involvement Explored in various clinical trials >10 years Antibody, failed in phase 2/3 ulcerative colitis

Published on 17 February 2020 on https://pubs.rsc.org | d

Multiple, not MMP1

XL784



Fibrosis

CTGF inhibitor

n.a.



Fibrosis

THBD mimetic

n.a. n.a. n.a.

Pamrevlumab FG3019 PF06473871 RXI-­109 ART123

√ √ √

Fibrosis Fibrosis Fibrosis

POSTN inhibitor

n.a.

Antibody

Interaction Pathways TGFβ inhibition Mode of action not well defined TGFβ inhibition Multikinase-­inhibitor (PDGF, EGF, FGF) TGFβ inhibition Angiotensin

ROCK2

Pirfenidone Esbriet® Nitedanib BIBF1120 OFEV® Tranilast Rizaben® Losartan, Valsartan etc. Lisinopril, Enalapril etc. Angiotensin (1–7) TXA127 AVE0991 KD025

pan

AMA0428

pan pan

Y27632 Fasudil

n.a.

Pravastatin, Simvastatin Metformin PF-­06409577 MK8722

Mode of action not well defined AT1 receptor inhibitor ACE inhibitor AT2/mas receptor activator

ROCK inhibitor

AMPK activator

n.a. Multiple, including β1 Multiple, including β2

Cancer, Fibrosis

MMP1 inhibition causes muscle toxicity Antibody with promising results in IPF phase 2 ASO for topical use Self-­delivering siRNA for topical use Recombinant protein in phase 3 with data expected soon Broadly used as biomarker, also IPF





Fibrosis





Fibrosis, Cancer





Fibrosis





Fibrosis

Marketed anti-­allergic, high doses needed for anti-­fibrosis Marketed for cardiac diseases





Fibrosis

Marketed for cardiac diseases



Fibrosis, Cancer

Explored in various other indications



Fibrosis, Cancer

ROCK2 selective to avoid cardiovascular effects Soft inhibitor, systemic application possible Weak inhibitor Weak inhibitor Marketed for vascular disease Shown to also inhibit ROCK

Fibrosis, Cancer √







√ √



Fibrosis Fibrosis, Cancer

Fibrosis, Cancer Fibrosis, Cancer Fibrosis, Cancer

Marketed for IPF Use recommended Marketed for IPF with manageable long-­term safety

Marketed for metabolic diseases Allosteric activator Induce cardiac hypertrophy

View Online

Chapter 1

16

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

1.2.4.1 Smad2/3 Inhibition Interacting directly with canonical Smad2/3 signaling is not trivial as Smad2/3 is a transcriptional activator, a function not easily addressable with therapeutics. Therefore, only a few compounds act on this level of the pathway. Halofuginone (HT-­100), a derivate of a natural alkaloid, is a repurposed drug, originally used as an anti-­protozoal agent in veterinary medicine. It also has anti-­fibrotic activity, and analysis of the mode of action indicated that it may partly work via inhibition of Smad3 phosphorylation.105 It was believed to have broad application (e.g. ref. 106 and 107) and was initially developed for fibrosis related to DMD, but clinical trials were terminated without posted results (NCT01847573, NCT01847573). Another molecule explored preclinically for fibrosis and cancer is the specific Smad3 inhibitor, SIS3.108–110 SIS3 inhibits Smad3 phosphorylation with specificity over Smad2, but was never used in clinical settings (Scheme 1.5).

1.2.4.2 NADPH Oxidase (NOX) Inhibition More druggable targets also believed to be part of canonical TGFβ signaling are NADPH oxidases (NOX) which have undergone preclinical and clinical exploration in fibrotic diseases. VAS2870 is a pan-­NOX inhibitor111 and primarily used preclinically. As pan-­NOX inhibition has a range of adverse events (reviewed by ref. 112), more isoform-­specific NOX inhibitors were developed for clinical studies. For example, NOX4 was shown to be the key player in fibrosis using knockout mice,113 and the potent and selective NOX1/4/5 inhibitor GKT137831 has progressed to clinical trials114 (reviewed

Scheme 1.4  (a)  SB-­431542, (b) SB-­525334, (c) Galunisertib (LY2157299), (d) Vactoserib (TEW-­7197).

Scheme 1.5  (a)  Halofuginone (HT-­100), (b) SIS3.

View Online

TGFβ Signaling

17

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

by ref. 115). Clinical trials are ongoing, and recently the first selective NOX4 inhibitor has been described, GLX7013114 (structure not disclosed).58 It will be exciting to follow this compound class (Scheme 1.6).

1.2.4.3 TGFβ Activated Kinase (TAK-­1) Inhibition An important non-­canonical, ALK-­independent TGFβ signaling pathway with a clear role in fibrosis is TAK-­1.3,116,117 Preclinical evidence comes from Inducible KOs that are protected from renal fibrosis.118 In addition, TAK-­1 seems to be an important linker between TGFβ and inflammatory cytokine signaling,21 opening the possibility to address fibrosis from two different angles at once. Thus, potent and selective TAK-­1 inhibitors have been generated (see Tan et al. 2017), and the most advanced compound takinib, is a starting point for further chemical optimization.119 However, TAK-­1 is a kinase and full-­body KOs show severe liver toxicity.120 Due to the risk for toxicity, TAK-­1 inhibitors need to be closely monitored regarding risk–benefit profiles. Therefore, it is not surprising that a TAK-­1 inhibitor has not reached clinical use to date (Scheme 1.7).

1.2.4.4 c-­jun N-­terminal Kinase (JNK) Inhibition Further downstream of non-­canonical TAK-­1 signaling is c-­jun N-­terminal kinase JNK,21 and JNK inhibition is being explored in fibrotic diseases. The pan-­JNK inhibitor CC930 121 was active in preclinical models of IPF122

Scheme 1.6  (a)  VAS2870, (b) GKT137831.

Scheme 1.7  Takinib. 

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

18

Chapter 1

Scheme 1.8  Tanzisertib  (CC-­930). and made it up to phase 2 for this indication, but was terminated due to a negative risk–benefit profile.123 A second generation compound CC-­9001 (structure not disclosed), more potent on JNK1 than JNK2, shows improved safety and promising initial clinical results.124,125 If highly JNK1-­selective compounds can be developed, this could be a promising anti-­fibrotic therapy (Scheme 1.8).

1.2.5  Effectors This section will discuss approaches aiming to inhibit downstream effectors of TGFβ signaling. These effectors are all secreted and propagate TGFβ signaling extracellularly in an autocrine, paracrine and endocrine fashion. Many of the effectors are also valuable circulating biomarkers, and therapeutics targeting effectors have the big advantage that they do not have to pass cellular barriers to reach their targets (for summary see Table 1.3).

1.2.5.1 Plasminogen Activator Inhibitor 1 (PAI-­1) Inhibition Plasminogen activator inhibitor 1 (PAI-­1, Serpin E1) is a serine protease inhibitor induced by TGFβ signaling with a wide variety of physiological functions, for example, in coagulation. PAI-­1 is also commonly used as a circulating biomarker. In fibrosis, it has both pro-­ and anti-­fibrotic properties so that the therapeutic aim is normalization of pathological levels, as both complete absence and overexpression induce fibrosis.126,127 PAI-­1 inhibitors, such as SK216 or TM5275, have been generated and seem to be safe and potent anti-­fibrotic agents in preclinical models.128–130 Thus far, clinical data are not available. It is worth of note that PAI-­1 deficient individuals have bleeding issues, so a careful risk–benefit analysis will be important (Scheme 1.9).

1.2.5.2 Thrombomodulin (THBD) Thrombomodulin (THBD), an endothelial cell glycoprotein and important anticoagulant, is decreased by TGFβ. Inversely, THBD reduces TGFβ expression by a negative feedback loop via high-­mobility group box 1 (HMGB1) and thrombin.131–133 Thus, the therapeutic approach for fibrosis, is to substitute

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

19

Scheme 1.9  (a)  SK216, (b) TM5275. with recombinant THBD, and a retrospective analysis of IPF patient records showed encouraging results.134 In IPF patients, recombinant THBD is used to treat coagulation issues after acute exacerbation, and in a subsequent clinical trial positive effects were confirmed.135 ART123, a recombinant THBD, has been evaluated in various clinical trials. More recently, a phase III study for acute exacerbation of IPF was completed (NCT02739165), and data should be available soon. However, the parenteral dosing of ART123 in chronic fibrotic diseases is not ideal. This remains a big hurdle compared with the acute, short-­term dosing after exacerbation, and maybe not be viable in chronic settings.

1.2.5.3 Periostin (POSTN) Inhibition Periostin (POSTN) is a secreted matricellular protein and its expression and subsequent secretion is stimulated by TGFβ. Secreted POSTN protein binds integrin receptors, e.g. αvβ3 and αvβ5, to support EMT and subsequently fibrosis136 (reviewed by ref. 137). Knockout or blockade of POSTN by antibodies was shown to efficiently protect various tissues from fibrosis (ref. 138–141, for review see ref. 142). However, in a myocardial infarction model POSTN knockout mice were more prone to ventricular rupture, even though surviving mice had less cardiac fibrosis, indicating that complete absence of POSTN can also have negative effects. Moreover, therapeutic inhibition is limited to neutralizing antibodies, and POSTN antibodies have not been used in clinical trials. On the other hand, POSTN has been broadly explored as a fibrosis biomarker, for example, in IPF.143,144 Pirfenidone treatment was found to reduce levels of POSTN in a preclinical fibrosis model.145

1.2.5.4 Connective Tissue Growth Factor (CTGF) Inhibition Connective tissue growth factor [CTGF, cellular communication network factor 2 (CCN2)] is another matricellular protein induced by TGFβ that mediates intercellular signaling with a prominent role in many biological processes, including fibrosis.146,147 CTGF has no specific receptors, but binds in similar fashion to that of POSTN to integrin receptors, e.g. αvβ3,148 and many

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

20

Chapter 1

other proteins, leading to TGFβ-­dependent induction of fibrosis. Strong evidence for the role of CTGF in fibrosis comes from the results of transgenic studies, indicating that overexpression of CTGF promotes and knockdown inhibits fibrosis (reviewed by ref. 149 and 150). Both neutralizing antibodies and siRNAs have been explored as therapeutic approaches with promising results in preclinical and clinical studies.151 For example, pamrevlumab (FG3019) showed good safety and tolerability along with promising results in phase 2 trials in IPF with reduced fibrosis progression.152,153 Pamrevlumab is currently in many clinical trials for fibrotic and cancer indications, and further results will be guiding. RXI-­109, is a self-­delivering CTGF siRNA, and PF06473871 is an ASO, both used locally, with initial positive results in dermal and retinal scaring.154,155

1.2.5.5 Metalloproteinase (MMP) Inhibition The final group of TGFβ effector molecules discussed in this chapter are matrix metalloproteinases (MMPs), which consist of more than 20 isoforms with different localization and sometimes opposite function. They are induced by TGFβ and serve as important modulators of tissue remodeling.156 Tissue inhibitors of metalloproteinase (TIMPs) are natural inhibitors of MMPs.157 As MMPs have protease activity, degrading TGFβ and other ECM proteins, small molecule enzymatic inhibitors were generated. However, due to their pleiotropic functions, a major challenge is to identify the key MMP isoforms involved in fibrosis,158 and then produce compounds with favorable specificity profiles (see ref. 159). MMP inhibitors have a long history as anti-­fibrotic or anti-­TGFβ agents, with at least three generations of molecules.159–161 However, so far, no major breakthrough in their clinical application has been reported. Regardless, due to strong target validation, efforts continue with strategies to overcome toxicity and other challenges.162 As our understanding of the MMP's continues to evolve, various isoforms seem to be key players in fibrosis (see ref. 163), including MMP9, MMP7, MMP2 and MMP12,156,158,164,165 (for reviews see ref. 163 and 166). Herein a selection of late-­ generation MMP inhibitors will be discussed. In asthma, the MMP12 inhibitor FP-­025 (structure not disclosed) is under evaluation based on MMP12 KO data showing improvement in lung fibrosis.167,168 Trials in asthma and COPD are ongoing (NCT03858686). The MMP2/9 inhibitor S3304 showed good safety and tolerability169 and was tested in cancer indications, but no data has been posted (e.g. NCT00078390). Andecaliximab (GS-­5745), a MMP9 antibody, was explored for various indications and insufficient treatment benefit lead to termination of a phase 2/3 trial in ulcerative colitis (2016, Gilead homepage). Additional ongoing trials were terminated or had no data regarding outcomes available. Based on findings that MMP1 inhibition is linked to muscle toxicity,170 the small molecule inhibitor XL784 with selectivity against MMP1 (but similar activity against other MMPs) was generated, sparing muscle toxicity.171 It was tested in cancer and fibrotic diseases more than 10 year

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

21

Scheme 1.10  (a)  S3304, (b) XL-­784. ago with disappointing clinical results and no further development due to adverse events (Scheme 1.10).172 In summary, results of extensive research on MMP inhibition indicated that broad inhibition is rather harmful and MMP isoform selectivity is hard to achieve. Thus, early excitement in the MMP inhibitor field has diminished to some extent. More recent efforts to advance specific inhibitors and new strategies were explored, but so far with limited clinical success or with trial outcome data that has not emerged.

1.2.6  Interacting Pathways This section will discuss approaches aiming to indirectly inhibit TGFβ signaling addressing interacting pathways. This approach, the most successful thus far, has produced two molecular entities marketed for fibrotic diseases, namely pirfenidone and nintedanib. Moreover, many of the interacting pathways have been successfully explored for other indications, with favorable safety profiles. This Indicates that they might be a good alternative to circumvent the safety challenges of directly inhibiting TGFβ signaling (for summary see Table 1.3).

1.2.6.1 Pirfenidone Pirfenidone (Esbriet®), an orally available pyridone analog, was the first drug approved worldwide for the treatment of IPF. Its mode of action is multimodal and not totally understood, but it is mainly considered to act via TGFβ inhibition. For example, pirfenidone was shown to inhibit transcription and translation of TGFβ in preclinical fibrosis models. Moreover, it also inhibits other pro-­fibrotic factors [e.g. platelet-­derived growth factor (PDGF)] inflammatory cytokines [e.g. tumor necrosis factor alpha (TNFα)] as well as the production of reactive oxygen species (ROS). Together, all these mechanisms most probably contribute to the anti-­fibrotic activity observed. Clinically, pirfenidone showed meaningful reduction in IPF disease progression with mild and manageable adverse events.173–178 In 2015, the clinical IPF

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

22

Chapter 1

Scheme 1.11  Pirfenidone. 

Scheme 1.12  Nintedanib.  guidelines assigned pirfenidone a conditional recommendation for its use in IPF179 and currently almost 100 clinical trials are ongoing, mainly for fibrotic conditions (Scheme 1.11).

1.2.6.2 Nintedanib Another compound approved for IPF treatment is the multi-­kinase inhibitor nintedanib (OFEV®) which is also approved for non-­small cell lung cancer as Vargatef®. Nintedanib targets platelet-­derived growth factor (PDGF), EGF, and fibroblast growth factor (FGF) receptors, all modulating TGFβ signaling.180–182 As with pirfenidone, multiple anti-­TGFβ actions have been reported (e.g. reduced TGFβ-­induced EMT and collagen production), but it is clear that various other mode of action components (e.g. anti-­angiogenesis) contribute to its anti-­fibrotic activity. Significant reduction of IPF disease progression was observed in clinical trials with manageable long-­term safety.181,183 In 2015, the clinical IPF guidelines also assigned nintedanib a conditional recommendation for its use in IPF179 and currently more than 100 clinical trials are ongoing in cancer and fibrotic conditions. Treatment selection between pirfenidone and nintedanib is mainly based on safety and tolerability and combination therapy has been suggested for the future (Scheme 1.12).181

1.2.6.3 Tranilast Another marketed compound interacting with TGFβ is tranilast. It was initially, and still is, used as an anti-­allergic compound in Asia. It was later shown to inhibit release of TGFβ from fibroblasts and subsequently EMT

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

23

Scheme 1.13  Tranilast.  progression.184,185 It was reported that its anti-­fibrotic efficacy appears to be mainly mediated by suppression of TGFβ expression, secretion and pathway activation. However, again other effects such as suppression of other pro-­ fibrotic and pro-­inflammatory agents may contribute. Relatively high doses are needed for the anti-­fibrotic activity, making it less attractive compared with the marketed principle for clinical development, despite low adverse events (reviewed by ref. 186). However, a few clinical trials are exploring its therapeutic potential in fibrotic diseases (Scheme 1.13).

1.2.6.4 Angiotensin Interaction of angiotensin II (ATII) and TGFβ signaling on multiple levels was discovered more than 20 years ago, and these interactions clearly contribute to fibrosis.187 For example, ATII can directly activate Smad signaling (see ref. 188) or promote TGFβ expression and activation, which leads to increased ECM synthesis.189,190 Subsequently, ATII inhibition has been extensively explored as an anti-­fibrotic therapy using either angiotensin II receptor type 1 (AT1) receptor antagonists (e.g. losartan, valsartan) or angiotensin converting enzyme (ACE) inhibitors (e.g. lisinopril, enalapril), that have been marketed for cardiovascular diseases with excellent safety and tolerability, and tremendous clinical experience (for review see ref. 191 and 192). Indeed, promising results have been obtained with various molecules in a variety of fibrotic diseases and there are still clinical trials ongoing. However, none of the molecules has been approved for fibrotic diseases. More recently it has been found that the renin–angiotensin system (RAS) also plays a role in fibrosis protection, through the ACE2–Ang(1–7)–AT2–Massey oncogene homolog (mas) receptor axis which negatively regulates TGFβ.192–196 Thus, various Ang(1–7) agonists and mimetics (e.g. AVE0991 and TXA127) are being explored in cancer and fibrotic indications with initial promising effects (Scheme 1.14).196–200

1.2.6.5 Rho-­associated Kinase (ROCK) Rho-­associated kinases (ROCK), consisting of two isoform (ROCK1 and 2), regulate cytoskeletal organization and cell migration, and have a therapeutic potential in a wide range of pathological conditions, including fibrosis.201 ROCK interacts on various levels with TGFβ signaling, such as activation, signaling potentiation and most importantly via a positive feedback loop.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

24

Chapter 1

Scheme 1.14  (a)  AVE0991, (b) TXA127.

Scheme 1.15  (a)  Fasudil, (b) Y-­27632, (c) KD025c. TGFβ has been shown to be an upstream regulator of ROCK kinase.202 ROCK inhibitors, such as Fasudil, were initially developed and approved in Asia for cardiovascular and cerebrovascular diseases, and later also used locally for glaucoma therapy. More than 170 ROCK inhibitors have been generated, but unwanted cardiovascular side effects due to dual ROCK1/2 activity lead to a narrow therapeutic window. This was addressed by developing so-­called “weak/soft” [e.g. fasudil, AMA0428 (structure not disclosed), Y27632] or ROCK2-­selective compounds (KD025 203) (for review see ref. 201 and 204). Various fibrosis trials are ongoing with the ROCK2-­selective inhibitor KD025. Moreover, some statins, 3-­hydroxy-­e-­methylglutaryl CoA (HMG-­COA) inhibitors (e.g. simvastatin) have also been shown to inhibit ROCK, and are being explored for fibrotic disease.205,206 A very significant observation with ROCK inhibitors was that they can not only prevent fibrosis, but also cause regression of already established fibrosis in IPF, as they might selectively target profibrotic cells (Scheme 1.15).202

1.2.6.6 AMP-­activated Kinase (AMPK) Activation AMP-­activated kinase (AMPK), is part of a nutrient-­sensing pathway with a key role in metabolism. The AMPK pathway is another player more recently described to interact with TGFβ signaling and contribute to fibrotic diseases. AMPK activation negatively regulates Smad2/3 signaling, and AMPK ablation

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

25

Scheme 1.16  (a)  PF-­06409577, (b) MK8722. leads to enhanced TGFβ–Smad signaling in vitro.207,208 In accordance, both pharmacologic and genetic activation of AMPK effectively prevents fibrosis in vivo.46,209–213 By far the most data is available for metformin, an approved anti-­diabetic drug and indirect AMPK activator, with a variety of clinical trials. Moreover, various direct activators (e.g. PF-­06409577 and MK8722) have been generated, mainly for metabolic diseases, and are now being preclinically explored for their therapeutic potential in fibrotic diseases (for review see ref. 214). However, despite good preclinical efficacy, cardiac side effects seem to prevent further development.215 To address adverse events, compounds with different subunit selectivities are currently under exploration,216 as the subunits show different distributions and functions (Scheme 1.16).214

1.3  Conclusion Major progress has been made to treat fibrotic diseases by interacting with TGFβ signaling. Most of the therapeutics are highly active in preclinical studies but have limited clinical success due to non-­favorable adverse events. However, further pathway analysis to find more specific inhibition nodes was key to improving the safety and selectivity of the next generation of therapies under development. In fact, two compounds have been approved for the treatment of IPF, namely pirfenidone and nintedanib, which slow progression of fibrosis with manageable adverse events. For both, expansion of clinical indications is being explored. Moreover, new compounds and targets are currently being studied that directly or indirectly target TGFβ signaling, and it will be very exciting to follow their preclinical and clinical development.

References 1. T. J. Franklin, Int. J. Biochem. Cell Biol., 1997, 29, 79–89. 2. S. L. Friedman, D. Sheppard, J. S. Duffield and S. Violette, Sci. Transl. Med., 2013, 5, 167sr161. 3. J. Li, C. Liang, Z. K. Zhang, X. Pan, S. Peng, W. S. Lee, A. Lu, Z. Lin, G. Zhang, W. N. Leung and B. T. Zhang, Cell Discovery, 2017, 3, 17023. 4. R. F. Diegelmann and M. C. Evans, Front. Biosci., 2004, 9, 283–289. 5. T. A. Wynn, J. Pathol., 2008, 214, 199–210.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

26

Chapter 1

6. F. Klingberg, B. Hinz and E. S. White, J. Pathol., 2013, 229, 298–309. 7. D. Sheppard, Ann. Am. Thorac. Soc., 2015, 12(Suppl. 1), S21–S23. 8. R. C. Stone, I. Pastar, N. Ojeh, V. Chen, S. Liu, K. I. Garzon and M. Tomic-­ Canic, Cell Tissue Res., 2016, 365, 495–506. 9. C. Chandler, T. Liu, R. Buckanovich and L. G. Coffman, Transl. Res., 2019, 55–67. 10. K. A. Harradine and R. J. Akhurst, Ann. Med., 2006, 38, 403–414. 11. J. Massagué and R. R. Gomis, FEBS Lett., 2006, 580, 2811–2820. 12. X. M. Meng, D. J. Nikolic-­Paterson and H. Y. Lan, Nat. Rev. Nephrol., 2016, 12, 325–338. 13. K. L. Walton, K. E. Johnson and C. A. Harrison, Front. Pharmacol., 2017, 8, 461. 14. J. E. de Larco and G. J. Todaro, Proc. Natl. Acad. Sci. U. S. A., 1978, 75, 4001–4005. 15. A. B. Roberts, L. C. Lamb, D. L. Newton, M. B. Sporn, J. E. De Larco and G. J. Todaro, Proc. Natl. Acad. Sci. U. S. A., 1980, 77, 3494–3498. 16. A. B. Roberts, M. B. Sporn, R. K. Assoian, J. M. Smith, N. S. Roche, L. M. Wakefield, U. I. Heine, L. A. Liotta, V. Falanga and J. H. Kehrl, Proc. Natl. Acad. Sci. U. S. A., 1986, 83, 4167–4171. 17. M. A. Anzano, A. B. Roberts, J. M. Smith, M. B. Sporn and J. E. De Larco, Proc. Natl. Acad. Sci. U. S. A., 1983, 80, 6264–6268. 18. R. Derynck, J. A. Jarrett, E. Y. Chen, D. H. Eaton, J. R. Bell, R. K. Assoian, A. B. Roberts, M. B. Sporn and D. V. Goeddel, Nature, 1985, 316, 701–705. 19. A. B. Kulkarni, T. Thyagarajan and J. J. Letterio, Curr. Mol. Med., 2002, 2, 303–327. 20. N. Khalil, Microbes Infect., 1999, 1, 1255–1263. 21. A. U. Trendelenburg, A. Meyer, C. Jacobi, J. N. Feige and D. J. Glass, Skeletal Muscle, 2012, 2, 3. 22. R. J. Akhurst, Cold Spring Harbor Perspect. Biol., 2017, 9, 10. 23. M. A. Nieto, R. Y. Huang, R. A. Jackson and J. P. Thiery, Cell, 2016, 166, 21–45. 24. D. Lauffenburger and C. Cozens, Biotechnol. Bioeng., 1989, 33, 1365–1378. 25. A. B. Roberts, Miner. Electrolyte Metab., 1998, 24, 111–119. 26. B. Vidal, A. L. Serrano, M. Tjwa, M. Suelves, E. Ardite, R. De Mori, B. Baeza-­Raja, M. Martínez de Lagrán, P. Lafuste, V. Ruiz-­Bonilla, M. Jardí, R. Gherardi, C. Christov, M. Dierssen, P. Carmeliet, J. L. Degen, M. Dewerchin and P. Muñoz-­Cánoves, Genes Dev., 2008, 22, 1747–1752. 27. K. Benke, B. Ágg, B. Szilveszter, F. Tarr, Z. B. Nagy, M. Pólos, L. Daróczi, B. Merkely and Z. Szabolcs, J. Cardiol., 2013, 20, 227–234. 28. K. A. Swaggart and E. M. McNally, Exp. Physiol., 2014, 99, 621–626. 29. J. Lu, Q. Liu, L. Wang, W. Tu, H. Chu, W. Ding, S. Jiang, Y. Ma, X. Shi, W. Pu, X. Zhou, L. Jin, J. Wang and W. Wu, Lab. Invest., 2017, 97, 1121. 30. T. Brabletz, R. Kalluri, M. A. Nieto and R. A. Weinberg, Nat. Rev. Cancer, 2018, 18, 128–134. 31. J. M. Carthy, J. Cell. Physiol., 2018, 233, 98–106. 32. P. Lachapelle, M. Li, J. Douglass and A. Stewart, Pharmacol. Ther., 2018, 187, 98–113.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

27

33. B. Ballester, J. Milara and J. Cortijo, Int. J. Mol. Sci., 2019, 20, 593. 34. L. Caja, F. Dituri, S. Mancarella, D. Caballero-­Diaz, A. Moustakas, G. Giannelli and I. Fabregat, Int. J. Mol. Sci., 2018, 19, 1294. 35. L. R. Smith and E. R. Barton, Matrix Biol., 2018, 68–69, 602–615. 36. Y. Kharraz, J. Guerra, P. Pessina, A. L. Serrano and P. Muñoz-­Cánoves, BioMed Res. Int., 2014, 2014, 965631. 37. A. Heydemann, E. Ceco, J. E. Lim, M. Hadhazy, P. Ryder, J. L. Moran, D. R. Beier, A. A. Palmer and E. M. McNally, J. Clin. Invest., 2009, 119, 3703–3712. 38. J. T. March, G. Golshirazi, V. Cernisova, H. Carr, Y. Leong, N. Lu-­Nguyen and L. J. Popplewell, Biomedicines, 2018, 6, 74. 39. N. S. Nagaraj and P. K. Datta, Expert Opin. Invest. Drugs, 2010, 19, 77–91. 40. P. Hau, P. Jachimczak and U. Bogdahn, Expert Rev. Anticancer Ther., 2009, 9, 1663–1674. 41. R. J. Akhurst and A. Hata, Nat. Rev. Drug Discovery, 2012, 11, 790–811. 42. A. de Gramont, S. Faivre and E. Raymond, OncoImmunology, 2017, 6, e1257453. 43. H. Yoshizawa, Y. Morishita, M. Watanabe, K. Ishibashi, S. Muto, E. Kusano and D. Nagata, Gene Ther., 2015, 22, 333–340. 44. H. Trachtman, F. C. Fervenza, D. S. Gipson, P. Heering, D. R. Jayne, H. Peters, S. Rota, G. Remuzzi, L. C. Rump, L. K. Sellin, J. P. Heaton, J. B. Streisand, M. L. Hard, S. R. Ledbetter and F. Vincenti, Kidney Int., 2011, 79, 1236–1243. 45. L. M. Rice, C. M. Padilla, S. R. McLaughlin, A. Mathes, J. Ziemek, S. Goummih, S. Nakerakanti, M. York, G. Farina, M. L. Whitfield, R. F. Spiera, R. B. Christmann, J. K. Gordon, J. Weinberg, R. W. Simms and R. Lafyatis, J. Clin. Invest., 2015, 125, 2795–2807. 46. Z. Liang, T. Li, S. Jiang, J. Xu, W. Di, Z. Yang, W. Hu and Y. Yang, OncoTarget, 2017, 8, 62780–62792. 47. F. Vincenti, F. C. Fervenza, K. N. Campbell, M. Diaz, L. Gesualdo, P. Nelson, M. Praga, J. Radhakrishnan, L. Sellin, A. Singh, D. Thornley-­ Brown, F. V. Veronese, B. Accomando, S. Engstrand, S. Ledbetter, J. Lin, J. Neylan, J. Tumlin and Focal Segmental Glomerulosclerosis Study Group, Kidney Int. Rep., 2017, 2, 800–810. 48. R. C. Gregory, R. Greco, H. Qu, N. Malkova, M. Levit, K. Perron, W. Racki, F. Sun, G. Shapiro, C. Winter, D. Wiederschain, T. T. Lin and J. Pollard, Cancer Res., 2018, 78, 2790. 49. J. Theilhaber, J. Cavallo, S. L. Madden, C. Manning, S. Cao, P. Mankoo, R. Pomponio, H. Qu, N. Malkova, G. Shapiro, C. Winter, D. Wiederschain, M. Sanicola-­Nadel, F. Sun, T. T. Lin, R. C. Gregory and J. Pollard, Cancer Res., 2018, 78, 5550. 50. M. Terabe, F. C. Robertson, K. Clark, E. De Ravin, A. Bloom, D. J. Venzon, S. Kato, A. Mirza and J. A. Berzofsky, OncoImmunology, 2017, 6, e1308616. 51. D. Bedinger, L. Lao, S. Khan, S. Lee, T. Takeuchi and A. M. Mirza, mAbs, 2016, 8, 389–404.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

28

Chapter 1

52. C. P. Denton, P. A. Merkel, D. E. Furst, D. Khanna, P. Emery, V. M. Hsu, N. Silliman, J. Streisand, J. Powell, A. Akesson, J. Coppock, F. Hoogen, A. Herrick, M. D. Mayes, D. Veale, J. Haas, S. Ledbetter, J. H. Korn, C. M. Black, J. R. Seibold, Cat-­192 Study Group and Scleroderma Clinical Trials Consortium, Arthritis Rheum., 2007, 56, 323–333. 53. J. Voelker, P. H. Berg, M. Sheetz, K. Duffin, T. Shen, B. Moser, T. Greene, S. S. Blumenthal, I. Rychlik, Y. Yagil, P. Zaoui and J. B. Lewis, J. Am. Soc. Nephrol., 2017, 28, 953–962. 54. P. Khaw, F. Grehn, G. Holló, B. Overton, R. Wilson, R. Vogel, Z. Smith and CAT-­152 0102 Trabeculectomy Study Group, Ophthalmology, 2007, 114, 1822–1830. 55. F. Grehn, G. Holló, P. Khaw, B. Overton, R. Wilson, R. Vogel, Z. Smith and CAT-­152 Trabeculectomy Study Group, Ophthalmology, 2007, 114, 1831–1838. 56. S. McGaraughty, R. A. Davis-­Taber, C. Z. Zhu, T. B. Cole, A. L. Nikkel, M. Chhaya, K. J. Doyle, L. M. Olson, G. M. Preston, C. M. Grinnell, K. M. Salte, A. M. Giamis, Y. Luo, V. Sun, A. D. Goodearl, M. Gopalakrishnan and S. E. Lacy, J. Am. Soc. Nephrol., 2017, 28, 3616–3626. 57. E. Batlle and J. Massagué, Immunity, 2019, 50, 924–940. 58. X. Wang, A. Elksnis, P. Wikström, E. Walum, N. Welsh and P. O. Carlsson, PLoS One, 2018, 13, e0204271. 59. T. A. Järvinen and S. Prince, BioMed Res. Int., 2015, 2015, 654765. 60. A. M. Abdullatif, T. A. Macky, M. M. Abdullatif, K. Nassar, S. Grisanti, H. A. Mortada and M. M. Soliman, Graefe's Arch. Clin. Exp. Ophthalmol., 2018, 256, 2473–2481. 61. M. O'Connor-­McCourt, A. Lenferink, J. Zwaagstra, T. Sulea, R. Weeratna, S. Maleki, J. Baardsnes, C. Collins, C. Cantin, Y. Durocher, R. Singh, R. Figueredo, L. Krishnan, J. Koropatnick and I. Tikhomirov, Eur. J. Cancer, 2016, 69, S105. 62. J. Zarranz-­Ventura, P. Fernández-­Robredo, S. Recalde, A. Salinas-­ Alamán, F. Borrás-­Cuesta, J. Dotor and A. García-­Layana, PLoS One, 2013, 8, e65434. 63. N. Hermida, B. López, A. González, J. Dotor, J. J. Lasarte, P. Sarobe, F. Borrás-­Cuesta and J. Díez, Cardiovasc. Res., 2009, 81, 601–609. 64. G. Gallo-­Oller, A. Vollmann-­Zwerenz, B. Meléndez, J. A. Rey, P. Hau, J. Dotor and J. S. Castresana, Cancer Lett., 2016, 381, 67–75. 65. S. S. Qiu, J. Dotor and B. Hontanilla, PLoS One, 2015, 10, e0144489. 66. S. Murillo-­Cuesta, L. Rodríguez-­de la Rosa, J. Contreras, A. M. Celaya, G. Camarero, T. Rivera and I. Varela-­Nieto, Front. Aging Neurosci., 2015, 7, 32. 67. E. Kessler, K. Takahara, L. Biniaminov, M. Brusel and D. S. Greenspan, Science, 1996, 271, 360–362. 68. E. D. Turtle and W.-­B. Ho, Expert Opin. Ther. Pat., 2004, 14, 1185–1197. 69. I. C. Scott, I. L. Blitz, W. N. Pappano, Y. Imamura, T. G. Clark, B. M. Steiglitz, C. L. Thomas, S. A. Maas, K. Takahara, K. W. Cho and D. S. Greenspan, Dev. Biol., 1999, 213, 283–300.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

29

70. D. R. Hopkins, S. Keles and D. S. Greenspan, Matrix Biol., 2007, 26, 508–523. 71. G. Ge and D. S. Greenspan, J. Cell Biol., 2006, 175, 111–120. 72. T. Tovar-­Vidales, A. M. Fitzgerald, A. F. Clark and R. J. Wordinger, Invest. Ophthalmol. Visual Sci., 2013, 54, 4741–4748. 73. Y. Zhang, G. Ge and D. S. Greenspan, J. Biol. Chem., 2006, 281, 39096–39104. 74. P. V. Fish, G. A. Allan, S. Bailey, J. Blagg, R. Butt, M. G. Collis, D. Greiling, K. James, J. Kendall, A. McElroy, D. McCleverty, C. Reed, R. Webster and G. A. Whitlock, J. Med. Chem., 2007, 50, 3442–3456. 75. S. Bailey, P. V. Fish, S. Billotte, J. Bordner, D. Greiling, K. James, A. McElroy, J. E. Mills, C. Reed and R. Webster, Bioorg. Med. Chem. Lett., 2008, 18, 6562–6567. 76. M. Talantikite, P. Lécorché, F. Beau, O. Damour, C. Becker-­Pauly, W. B. Ho, V. Dive, S. Vadon-­Le Goff and C. Moali, FEBS Open Bio, 2018, 8, 2011–2021. 77. L. S. Kallander, D. Washburn, M. A. Hilfiker, H. S. Eidam, B. G. Lawhorn, J. Prendergast, R. Fox, S. Dowdell, S. Manns, T. Hoang, S. Zhao, G. Ye, M. Hammond, D. A. Holt, T. Roethke, X. Hong, R. A. Reid, R. Gampe, H. Zhang, E. Diaz, A. R. Rendina, A. M. Quinn and B. Willette, ACS Med. Chem. Lett., 2018, 9, 736–740. 78. L. Grgurevic, I. Erjavec, I. Grgurevic, I. Dumic-­Cule, J. Brkljacic, D. Verbanac, M. Matijasic, H. C. Paljetak, R. Novak, M. Plecko, J. Bubic-­ Spoljar, D. Rogic, V. Kufner, M. Pauk, T. Bordukalo-­Niksic and S. Vukicevic, Growth Factors, 2017, 35, 201–215. 79. S. L. Nishimura, Am. J. Pathol., 2009, 175, 1362–1370. 80. J. J. Worthington, J. E. Klementowicz and M. A. Travis, Trends Biochem. Sci., 2011, 36, 47–54. 81. C. Margadant and A. Sonnenberg, EMBO Rep., 2010, 11, 97–105. 82. N. C. Henderson and D. Sheppard, Biochim. Biophys. Acta, 2013, 1832, 891–896. 83. C. H. Maden, D. Fairman, M. Chalker, M. J. Costa, W. A. Fahy, N. Garman, P. T. Lukey, T. Mant, S. Parry, J. K. Simpson, R. J. Slack, S. Kendrick and R. P. Marshall, Eur. J. Clin. Pharmacol., 2018, 74, 701–709. 84. J. E. Murphy-­Ullrich and M. J. Suto, Matrix Biol., 2018, 68–69, 28–43. 85. S. M. Ribeiro, M. Poczatek, S. Schultz-­Cherry, M. Villain and J. E. Murphy-­Ullrich, J. Biol. Chem., 1999, 274, 13586–13593. 86. M. T. Sweetwyne and J. E. Murphy-­Ullrich, Matrix Biol., 2012, 31, 178–186. 87. H. Kondou, S. Mushiake, Y. Etani, Y. Miyoshi, T. Michigami and K. Ozono, J. Hepatol., 2003, 39, 742–748. 88. X. S. Xie, F. Y. Li, H. C. Liu, Y. Deng, Z. Li and J. M. Fan, Arch. Pharmacal Res., 2010, 33, 275–284. 89. F. Liao, G. Li, W. Yuan, Y. Chen, Y. Zuo, K. Rashid, J. H. Zhang, H. Feng and F. Liu, Exp. Ther. Med., 2016, 12, 2537–2543.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

30

Chapter 1

90. S. N. Markovic, V. J. Suman, R. A. Rao, J. N. Ingle, J. S. Kaur, L. A. Erickson, H. C. Pitot, G. A. Croghan, R. R. McWilliams, J. Merchan, L. A. Kottschade, W. K. Nevala, C. B. Uhl, J. Allred and E. T. Creagan, Am. J. Clin. Oncol., 2007, 30, 303–309. 91. M. V. Recouvreux, M. A. Camilletti, D. B. Rifkin, D. Becu-­Villalobos and G. Díaz-­Torga, Endocrinology, 2012, 153, 3861–3871. 92. D. Q. Tran, J. Andersson, R. Wang, H. Ramsey, D. Unutmaz and E. M. Shevach, Proc. Natl. Acad. Sci. U. S. A., 2009, 106, 13445–13450. 93. J. Cuende, S. Liénart, O. Dedobbeleer, B. van der Woning, G. De Boeck, J. Stockis, C. Huygens, D. Colau, J. Somja, P. Delvenne, M. Hannon, F. Baron, L. Dumoutier, J. C. Renauld, H. De Haard, M. Saunders, P. G. Coulie and S. Lucas, Sci. Transl. Med., 2015, 7, 284ra256. 94. J. Stockis, O. Dedobbeleer and S. Lucas, Mol. BioSyst., 2017, 13, 1925–1935. 95. O. Dedobbeleer, J. Stockis, B. van der Woning, P. G. Coulie and S. Lucas, J. Immunol., 2017, 199, 391–396. 96. A. Metelli, M. Salem, C. H. Wallace, B. X. Wu, A. Li, X. Li and Z. Li, J. Hematol. Oncol., 2018, 11, 24. 97. R. Y. Koh, C. L. Lim, B. D. Uhal, M. Abdullah, S. Vidyadaran, C. C. Ho and H. F. Seow, Mol. Med. Rep., 2015, 11, 3808–3813. 98. E. T. Grygielko, W. M. Martin, C. Tweed, P. Thornton, J. Harling, D. P. Brooks and N. J. Laping, J. Pharmacol. Exp. Ther., 2005, 313, 943–951. 99. C. S. Elangbam, Toxicol. Pathol., 2010, 38, 837–848. 100. S. Herbertz, J. S. Sawyer, A. J. Stauber, I. Gueorguieva, K. E. Driscoll, S. T. Estrem, A. L. Cleverly, D. Desaiah, S. C. Guba, K. A. Benhadji, C. A. Slapak and M. M. Lahn, Drug Des., Dev. Ther., 2015, 9, 4479–4499. 101. R. B. Holmgaard, D. A. Schaer, Y. Li, S. P. Castaneda, M. Y. Murphy, X. Xu, I. Inigo, J. Dobkin, J. R. Manro, P. W. Iversen, D. Surguladze, G. E. Hall, R. D. Novosiadly, K. A. Benhadji, G. D. Plowman, M. Kalos and K. E. Driscoll, J. Immunother. Cancer, 2018, 6, 47. 102. V. L. Keedy, T. M. Bauer, J. M. Clarke, H. Hurwitz, I. Baek, I. Ha, C.-­Y. Ock, S. Y. Nam, M. Kim, N. Park, J. Y. Kim and S.-­J. Kim, J. Clin. Oncol., 2018, 36, 3031. 103. L. A. Smyth and I. Collins, J. Chem. Biol., 2009, 2, 131–151. 104. A. W. Tolcher, J. D. Berlin, J. Cosaert, J. Kauh, E. Chan, S. A. Piha-­Paul, A. Amaya, S. Tang, K. Driscoll, R. Kimbung, S. R. Kambhampati, I. Gueorguieva and D. S. Hong, Cancer Chemother. Pharmacol., 2017, 79, 673–680. 105. M. Pines and A. Nagler, Gen. Pharmacol., 1998, 30, 445–450. 106. A. Nagler, N. Firman, R. Feferman, S. Cotev, M. Pines and S. Shoshan, Am. J. Respir. Crit. Care Med., 1996, 154, 1082–1086. 107. Y. Luo, X. Xie, D. Luo, Y. Wang and Y. Gao, J. Leukocyte Biol., 2017, 102, 1333–1345. 108. M. Jinnin, H. Ihn and K. Tamaki, Mol. Pharmacol., 2006, 69, 597–607. 109. C. P. Wu, M. Murakami, S. H. Hsiao, T. C. Liu, N. Yeh, Y. Q. Li, T. H. Hung, Y. S. Wu and S. V. Ambudkar, Cancer Lett., 2018, 433, 259–272.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

31

110. J. Shou, J. Cao, S. Zhang, R. Sun, M. Zhao, K. Chen, S. B. Su, J. Yang and T. Yang, Biochem. Biophys. Res. Commun., 2018, 503, 757–762. 111. J. Yang, J. Li, Q. Wang, Y. Xing, Z. Tan and Q. Kang, Int. J. Mol. Med., 2018, 42, 123–130. 112. S. Altenhöfer, K. A. Radermacher, P. W. Kleikers, K. Wingler and H. H. Schmidt, Antioxid. Redox Signaling, 2015, 23, 406–427. 113. E. R. Jarman, V. S. Khambata, C. Cope, P. Jones, J. Roger, L. Y. Ye, N. Duggan, D. Head, A. Pearce, N. J. Press, B. Bellenie, B. Sohal and G. Jarai, Am. J. Respir. Cell Mol. Biol., 2014, 50, 158–169. 114. H. Murphy-­Marshman, K. Quensel, X. Shi-­Wen, R. Barnfield, J. Kelly, A. Peidl, R. J. Stratton and A. Leask, PLoS One, 2017, 12, e0186740. 115. G. Teixeira, C. Szyndralewiez, S. Molango, S. Carnesecchi, F. Heitz, P. Wiesel and J. M. Wood, Br. J. Pharmacol., 2017, 174, 1647–1669. 116. M. E. Choi, Y. Ding and S. I. Kim, Semin. Nephrol., 2012, 32, 244–252. 117. S. I. Kim and M. E. Choi, Kidney Res. Clin. Pract., 2012, 31, 94–105. 118. F. Y. Ma, G. H. Tesch, E. Ozols, M. Xie, M. D. Schneider and D. J. Nikolic-­ Paterson, Am. J. Physiol., 2011, 300, F1410–F1421. 119. J. Totzke, D. Gurbani, R. Raphemot, P. F. Hughes, K. Bodoor, D. A. Carlson, D. R. Loiselle, A. K. Bera, L. S. Eibschutz, M. M. Perkins, A. L. Eubanks, P. L. Campbell, D. A. Fox, K. D. Westover, T. A. J. Haystead and E. R. Derbyshire, Cell Chem. Biol., 2017, 24, 1029–1039.e1027. 120. S. Inokuchi, T. Aoyama, K. Miura, C. H. Osterreicher, Y. Kodama, K. Miyai, S. Akira, D. A. Brenner and E. Seki, Proc. Natl. Acad. Sci. U. S. A., 2010, 107, 844–849. 121. V. Plantevin Krenitsky, L. Nadolny, M. Delgado, L. Ayala, S. S. Clareen, R. Hilgraf, R. Albers, S. Hegde, N. D'Sidocky, J. Sapienza, J. Wright, M. McCarrick, S. Bahmanyar, P. Chamberlain, S. L. Delker, J. Muir, D. Giegel, L. Xu, M. Celeridad, J. Lachowitzer, B. Bennett, M. Moghaddam, O. Khatsenko, J. Katz, R. Fan, A. Bai, Y. Tang, M. A. Shirley, B. Benish, T. Bodine, K. Blease, H. Raymon, B. E. Cathers and Y. Satoh, Bioorg. Med. Chem. Lett., 2012, 22, 1433–1438. 122. J. L. van der Velden, Y. Ye, J. D. Nolin, S. M. Hoffman, D. G. Chapman, K. G. Lahue, S. Abdalla, P. Chen, Y. Liu, B. Bennett, N. Khalil, D. Sutherland, W. Smith, G. Horan, M. Assaf, Z. Horowitz, R. Chopra, R. M. Stevens, M. Palmisano, Y. M. Janssen-­Heininger and P. H. Schafer, Clin. Transl. Med., 2016, 5, 36. 123. J. Cicenas, E. Zalyte, A. Rimkus, D. Dapkus, R. Noreika and S. Urbonavicius, Cancers, 2017, 10, 1. 124. S. Greenberg, G. Horan, B. Bennett, K. Blease, Y. Ye, A. Azaryan, F. Ramirez-­Valle, R. Ceres and P. Schafer, Eur. Respir. J., 2017, 50, OA474. 125. K. Blease, Y. Ye, A. Azaryan, F. Ramirez-­Valle, R. Ceres, G. Horan, P. Schafer, J. L. V. D. Velden and Y. M. W. Janssen-­Heininger, CC-­90001, a Second Generation Jun N-­Terminal Kinase (JNK) Inhibitor for the Treatment of Idiopathic Pulmonary Fibrosis, in C38. Understanding Therapeutics in IPF, 2017, pp. A5409–A5409, DOI: 10.1164/ajrccm-­ conference.2017.195.1_MeetingAbstracts.A5409.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

32

Chapter 1

126. P. Flevaris and D. Vaughan, Semin. Thromb. Hemostasis, 2017, 43, 169–177. 127. A. K. Ghosh and D. E. Vaughan, J. Cell. Physiol., 2012, 227, 493–507. 128. W. T. Huang, P. K. Vayalil, T. Miyata, J. Hagood and R. M. Liu, Am. J. Respir. Cell Mol. Biol., 2012, 46, 87–95. 129. K. Omori, N. Hattori, T. Senoo, Y. Takayama, T. Masuda, T. Nakashima, H. Iwamoto, K. Fujitaka, H. Hamada and N. Kohno, PLoS One, 2016, 11, e0148969. 130. B. Y. Jeong, M. J. Uddin, J. H. Park, J. H. Lee, H. B. Lee, T. Miyata and H. Ha, PLoS One, 2016, 11, e0157012. 131. T. Ohji, H. Urano, A. Shirahata, M. Yamagishi, K. Higashi, S. Gotoh and Y. Karasaki, Thromb. Haemostasis, 1995, 73, 812–818. 132. Y. C. Kao, L. W. Wu, C. S. Shi, C. H. Chu, C. W. Huang, C. P. Kuo, H. M. Sheu, G. Y. Shi and H. L. Wu, Mol. Cell. Biol., 2010, 30, 4767–4785. 133. T. Kida, T. Seno, H. Nagahara, T. Inoue, A. Nakabayashi, Y. Kukida, K. Fujioka, W. Fujii, M. Wada, M. Kohno and Y. Kawahito, Am. J. Physiol., 2018, 314, L473–L483. 134. T. Isshiki, S. Sakamoto, A. Kinoshita, K. Sugino, A. Kurosaki and S. Homma, Respiration, 2015, 89, 201–207. 135. S. Hayakawa, Y. Matsuzawa, T. Irie, H. Rikitake, N. Okada and Y. Suzuki, Multidiscip. Respir. Med., 2016, 11, 38. 136. Q. Hu, S. Tong, X. Zhao, W. Ding, Y. Gou, K. Xu, C. Sun and G. Xia, Cell. Physiol. Biochem., 2015, 36, 799–809. 137. L. González-­González and J. Alonso, Front. Oncol., 2018, 8, 225. 138. A. Lorts, J. A. Schwanekamp, T. A. Baudino, E. M. McNally and J. D. Molkentin, Proc. Natl. Acad. Sci. U. S. A., 2012, 109, 10978–10983. 139. J. H. Hwang, S. H. Yang, Y. C. Kim, J. H. Kim, J. N. An, K. C. Moon, Y. K. Oh, J. Y. Park, D. K. Kim, Y. S. Kim, C. S. Lim and J. P. Lee, Am. J. Nephrol., 2017, 46, 501–517. 140. J. N. An, S. H. Yang, Y. C. Kim, J. H. Hwang, J. Y. Park, D. K. Kim, J. H. Kim, D. W. Kim, D. G. Hur, Y. K. Oh, C. S. Lim, Y. S. Kim and J. P. Lee, Am. J. Physiol., 2019, 316, F426–F437. 141. Y. Nakazawa, Y. Taniyama, F. Sanada, R. Morishita, S. Nakamori, K. Morimoto, K. T. Yeung and J. Yang, Sci. Rep., 2018, 8, 4013. 142. D. F. Mosher, M. W. Johansson, M. E. Gillis and D. S. Annis, Crit. Rev. Biochem. Mol. Biol., 2015, 50, 427–439. 143. P. K. Naik, P. D. Bozyk, J. K. Bentley, A. P. Popova, C. M. Birch, C. A. Wilke, C. D. Fry, E. S. White, T. H. Sisson, N. Tayob, B. Carnemolla, P. Orecchia, K. R. Flaherty, M. B. Hershenson, S. Murray, F. J. Martinez, B. B. Moore and C. Investigators, Am. J. Physiol., 2012, 303, L1046–L1056. 144. S. Ohta, M. Okamoto, K. Fujimoto, N. Sakamoto, K. Takahashi, H. Yamamoto, H. Kushima, H. Ishii, K. Akasaka, J. Ono, A. Kamei, Y. Azuma, H. Matsumoto, Y. Yamaguchi, M. Aihara, T. Johkoh, A. Kawaguchi, M. Ichiki, H. Sagara, J. I. Kadota, M. Hanaoka, S. I. Hayashi, S. Kohno, T. Hoshino, K. Izuhara and Consortium for Development of Diagnostics for Pulmonary Fibrosis Patients (CoDD-­PF), PLoS One, 2017, 12, e0174547.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

33

145. X. Song, W. Yu and F. Guo, Exp. Ther. Med., 2018, 16, 1800–1806. 146. T. Mori, S. Kawara, M. Shinozaki, N. Hayashi, T. Kakinuma, A. Igarashi, M. Takigawa, T. Nakanishi and K. Takehara, J. Cell. Physiol., 1999, 181, 153–159. 147. Y. Liu, H. Liu, C. Meyer, J. Li, S. Nadalin, A. Königsrainer, H. Weng, S. Dooley and P. ten Dijke, J. Biol. Chem., 2013, 288, 30708–30719. 148. A. M. Babic, C. C. Chen and L. F. Lau, Mol. Cell. Biol., 1999, 19, 2958–2966. 149. D. R. Brigstock, J. Cell Commun. Signal., 2010, 4, 1–4. 150. N. Toda, M. Mukoyama, M. Yanagita and H. Yokoi, Inflammation Regener., 2018, 38, 14. 151. S. Wang, B. Li, C. Li, W. Cui and L. Miao, J. Diabetes Res., 2015, 2015, 962383. 152. G. Raghu, M. B. Scholand, J. de Andrade, L. Lancaster, Y. Mageto, J. Goldin, K. K. Brown, K. R. Flaherty, M. Wencel, J. Wanger, T. Neff, F. Valone, J. Stauffer and S. Porter, Eur. Respir. J., 2016, 47, 1481–1491. 153. E. Gorina, L. Richeldi, G. Raghu, E. Fernandez Perez, U. Costabel, C. Albera, D. Lederer, K. Flaherty, N. Ettinger, P. Bercz, B. Singh, R. Perez, J. Goldin, E. Kouchakji and S. Porter, Eur. Respir. J., 2017, 50, OA3400. 154. L. Libertine, G. Cauwenbergh, K. Bulock, K. Holton, N. Paz and P. Pavco, J. Am. Acad. Dermatol., 2014, 70, AB196. 155. J. D. Gale, J. Jensen, G. Berman, W. Freimuth, G. Li, A. Pleil, M. Kutty, A. Rosenthal, C. B. Boswell, V. E. M. Noah and L. Young, Plast. Reconstr. Surg., 2018, 6, e1861. 156. H. L. Hsieh, H. H. Wang, W. B. Wu, P. J. Chu and C. M. Yang, J. Neuroinflammation, 2010, 7, 88. 157. M. J. Arthur, Am. J. Physiol., 2000, 279, G245–G249. 158. S. Robert, T. Gicquel, T. Victoni, S. Valença, E. Barreto, B. Bailly-­Maître, E. Boichot and V. Lagente, Biosci. Rep., 2016, 36, e00360. 159. T. Fischer, N. Senn and R. Riedl, Chem. – Eur. J., 2019, 7960–7980. 160. J. M. Cathcart and J. Cao, Front. Biosci., Landmark Ed., 2015, 20, 1164–1178. 161. L. Devy and D. T. Dransfield, Biochem. Res. Int., 2011, 2011, 191670. 162. F. Barbara, Curr. Pharm. Des., 2007, 13, 333–346. 163. V. J. Craig, L. Zhang, J. S. Hagood and C. A. Owen, Am. J. Respir. Cell Mol. Biol., 2015, 53, 585–600. 164. B. Ke, C. Fan, L. Yang and X. Fang, Front. Physiol., 2017, 8, 21. 165. T. Kobayashi, H. Kim, X. Liu, H. Sugiura, T. Kohyama, Q. Fang, F. Q. Wen, S. Abe, X. Wang, J. J. Atkinson, J. M. Shipley, R. M. Senior and S. I. Rennard, Am. J. Physiol., 2014, 306, L1006–L1015. 166. M. Roderfeld, Matrix Biol., 2018, 68–69, 452–462. 167. S. K. Madala, J. T. Pesce, T. R. Ramalingam, M. S. Wilson, S. Minnicozzi, A. W. Cheever, R. W. Thompson, M. M. Mentink-­Kane and T. A. Wynn, J. Immunol., 2010, 184, 3955–3963. 168. G. Matute-­Bello, M. M. Wurfel, J. S. Lee, D. R. Park, C. W. Frevert, D. K. Madtes, S. D. Shapiro and T. R. Martin, Am. J. Respir. Cell Mol. Biol., 2007, 37, 210–221.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

34

Chapter 1

169. A. A. Chiappori, S. G. Eckhardt, R. Bukowski, D. M. Sullivan, M. Ikeda, Y. Yano, T. Yamada-­Sawada, Y. Kambayashi, K. Tanaka, M. M. Javle, T. Mekhail, C. L. O'Bryant and P. J. Creaven, Clin. Cancer Res., 2007, 13, 2091–2099. 170. P. Krzeski, C. Buckland-­Wright, G. Bálint, G. A. Cline, K. Stoner, R. Lyon, J. Beary, W. S. Aronstein and T. D. Spector, Arthritis Res. Ther., 2007, 9, R109. 171. T. Ennis, J. Jin, S. Bartlett, B. Arif, K. Grapperhaus and J. A. Curci, J. Cardiovasc. Pharmacol. Ther., 2012, 17, 417–426. 172. S. B. Pushpakumar, S. Kundu, N. Metreveli, S. C. Tyagi and U. Sen, Physiol. Rep., 2013, 1, e00063. 173. R. Rafii, M. M. Juarez, T. E. Albertson and A. L. Chan, J. Thorac. Dis., 2013, 5, 48–73. 174. Y. Takeda, K. Tsujino, T. Kijima and A. Kumanogoh, Patient Prefer. Adherence, 2014, 8, 361–370. 175. G. Sgalla, E. Cocconcelli, R. Tonelli and L. Richeldi, Expert Rev. Respir. Med., 2016, 10, 393–405. 176. P. W. Noble, C. Albera, W. Z. Bradford, U. Costabel, R. M. du Bois, E. A. Fagan, R. S. Fishman, I. Glaspole, M. K. Glassberg, L. Lancaster, D. J. Lederer, J. A. Leff, S. D. Nathan, C. A. Pereira, J. J. Swigris, D. Valeyre and T. E. King, Eur. Respir. J., 2016, 47, 243–253. 177. T. Stahnke, B. S. Kowtharapu, O. Stachs, K. P. Schmitz, J. Wurm, A. Wree, R. F. Guthoff and M. Hovakimyan, PLoS One, 2017, 12, e0172592. 178. Y. Isaka, Int. J. Mol. Sci., 2018, 19, 2532. 179. S. Aryal and S. D. Nathan, Expert Opin. Emerging Drugs, 2018, 23, 159–172. 180. L. Wollin, E. Wex, A. Pautsch, G. Schnapp, K. E. Hostettler, S. Stowasser and M. Kolb, Eur. Respir. J., 2015, 45, 1434–1445. 181. C. Hayton and N. Chaudhuri, Drugs Aging, 2017, 34, 647–653. 182. A. Hajari Case and P. Johnson, BMJ Open Respir. Res., 2017, 4, e000192. 183. B. Crestani, J. T. Huggins, M. Kaye, U. Costabel, I. Glaspole, T. Ogura, J. W. Song, W. Stansen, M. Quaresma, S. Stowasser and M. Kreuter, Lancet Respir. Med., 2019, 7, 60–68. 184. H. Suzawa, S. Kikuchi, N. Arai and A. Koda, Jpn. J. Pharmacol., 1992, 60, 91–96. 185. R. Harigai, S. Sakai, H. Nobusue, C. Hirose, O. Sampetrean, N. Minami, Y. Hata, T. Kasama, T. Hirose, T. Takenouchi, K. Kosaki, K. Kishi, H. Saya and Y. Arima, Sci. Rep., 2018, 8, 6069. 186. S. Darakhshan and A. B. Pour, Pharmacol. Res., 2015, 91, 15–28. 187. I. M. C. Dixon, N. L. Reid and H. Ju, Heart Failure Rev., 1997, 2, 107–116. 188. J. Rodríguez-­Vita, E. Sánchez-­López, V. Esteban, M. Rupérez, J. Egido and M. Ruiz-­Ortega, Circulation, 2005, 111, 2509–2517. 189. S. Kagami, W. A. Border, D. E. Miller and N. A. Noble, J. Clin. Invest., 1994, 93, 2431–2437. 190. X. Gao, X. He, B. Luo, L. Peng, J. Lin and Z. Zuo, Eur. J. Pharmacol., 2009, 606, 115–120.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

TGFβ Signaling

35

191. S. Kim and H. Iwao, Pharmacol. Rev., 2000, 52, 11–34. 192. A. M. Murphy, A. L. Wong and M. Bezuhly, Fibrog. Tissue Repair, 2015, 8, 7. 193. Y. S. Li, S. Y. Ni, Y. Meng, X. L. Shi, X. W. Zhao, H. H. Luo and X. Li, PLoS One, 2013, 8, e76289. 194. M. J. Acuña, P. Pessina, H. Olguin, D. Cabrera, C. P. Vio, M. Bader, P. Muñoz-­Canoves, R. A. Santos, C. Cabello-­Verrugio and E. Brandan, Hum. Mol. Genet., 2014, 23, 1237–1249. 195. L. L. Lv and B. C. Liu, Front. Physiol., 2015, 6, 117. 196. R. A. S. Santos, W. O. Sampaio, A. C. Alzamora, D. Motta-­Santos, N. Alenina, M. Bader and M. J. Campagnole-­Santos, Physiol. Rev., 2018, 98, 505–553. 197. M. C. Chappell and E. M. Al Zayadneh, J. Cell Signalling, 2017, 2, 134–142. 198. G. Wiemer, L. W. Dobrucki, F. R. Louka, T. Malinski and H. Heitsch, Hypertension, 2002, 40, 847–852. 199. S. V. Pinheiro, A. C. Simões e Silva, W. O. Sampaio, R. D. de Paula, E. P. Mendes, E. D. Bontempo, J. B. Pesquero, T. Walther, N. Alenina, M. Bader, M. Bleich and R. A. Santos, Hypertension, 2004, 44, 490–496. 200. J. E. Rupert, L. G. Koniaris and T. A. Zimmers, Cancer Res., 2019, 79, 699–700. 201. Y. Feng, P. V. LoGrasso, O. Defert and R. Li, J. Med. Chem., 2016, 59, 2269–2300. 202. R. S. Knipe, A. M. Tager and J. K. Liao, Pharmacol. Rev., 2015, 67, 103–117. 203. T. E. Albertson, D. M. Baratz, S. Chaudhary, S. Mobin, T. O'Brien, M. B. Scholand, T. P. M. Whelan, M. Poyurovsky, O. Schueller, J. Ryan and K. F. Gibson, A Convolutional Neural Network for the Classification of InterstitialLung Disease Patterns, in C97. Diffuse Parenchymal Lung Diseases: Evaluation, Outcomes, and Trials, 2018, pp. A5927–A5927, DOI: 10.1164/ajrccm-­conference.2018.197.1_MeetingAbstracts.A5927. 204. J. C. Koch, L. Tatenhorst, A. E. Roser, K. A. Saal, L. Tönges and P. Lingor, Pharmacol. Ther., 2018, 189, 1–21. 205. T. Yang, M. Chen and T. Sun, Cell. Physiol. Biochem., 2013, 31, 863–874. 206. M. Li, Z. Li and X. Sun, Eur. J. Pharmacol., 2008, 591, 219–223. 207. H. Lin, N. Li, H. He, Y. Ying, S. Sunkara, L. Luo, N. Lv, D. Huang and Z. Luo, Mol. Pharmacol., 2015, 88, 1062–1071. 208. Y. Pan, L. Liu, S. Li, K. Wang, R. Ke, W. Shi, J. Wang, X. Yan, Q. Zhang, Q. Wang, L. Chai, X. Xie and M. Li, Sci. Rep., 2018, 8, 3624. 209. D. Garcia, K. Hellberg, A. Chaix, M. Wallace, S. Herzig, M. G. Badur, T. Lin, M. N. Shokhirev, A. F. M. Pinto, D. S. Ross, A. Saghatelian, S. Panda, L. E. Dow, C. M. Metallo and R. J. Shaw, Cell. Reprogram., 2019, 26, 192–208.e196. 210. R. M. Esquejo, C. T. Salatto, J. Delmore, B. Albuquerque, A. Reyes, Y. Shi, R. Moccia, E. Cokorinos, M. Peloquin, M. Monetti, J. Barricklow, E. Bollinger, B. K. Smith, E. A. Day, C. Nguyen, K. F. Geoghegan, J. M. Kreeger, A. Opsahl, J. Ward, A. S. Kalgutkar, D. Tess, L. Butler, N. Shirai, T. F. Osborne, G. R. Steinberg, M. J. Birnbaum, K. O. Cameron and R. A. Miller, EBioMedicine, 2018, 31, 122–132.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00001

36

Chapter 1

211. G. Juban, M. Saclier, H. Yacoub-­Youssef, A. Kernou, L. Arnold, C. Boisson, S. Ben Larbi, M. Magnan, S. Cuvellier, M. Théret, B. J. Petrof, I. Desguerre, J. Gondin, R. Mounier and B. Chazaud, Cell. Reprogram., 2018, 25, 2163–2176.e2166. 212. H. Qi, Y. Liu, S. Li, Y. Chen, L. Li, Y. Cao, E. Mingyao, P. Shi, C. Song, B. Li and H. Sun, Mol. Ther.-­-­Nucleic Acids, 2017, 8, 277–290. 213. N. Sato, N. Takasaka, M. Yoshida, K. Tsubouchi, S. Minagawa, J. Araya, N. Saito, Y. Fujita, Y. Kurita, K. Kobayashi, S. Ito, H. Hara, T. Kadota, H. Yanagisawa, M. Hashimoto, H. Utsumi, H. Wakui, J. Kojima, T. Numata, Y. Kaneko, M. Odaka, T. Morikawa, K. Nakayama, H. Kohrogi and K. Kuwano, Respir. Res., 2016, 17, 107. 214. J. Kim, G. Yang, Y. Kim and J. Ha, Exp. Mol. Med., 2016, 48, e224. 215. R. W. Myers, H. P. Guan, J. Ehrhart, A. Petrov, S. Prahalada, E. Tozzo, X. Yang, M. M. Kurtz, M. Trujillo, D. Gonzalez Trotter, D. Feng, S. Xu, G. Eiermann, M. A. Holahan, D. Rubins, S. Conarello, X. Niu, S. C. Souza, C. Miller, J. Liu, K. Lu, W. Feng, Y. Li, R. E. Painter, J. A. Milligan, H. He, F. Liu, A. Ogawa, D. Wisniewski, R. J. Rohm, L. Wang, M. Bunzel, Y. Qian, W. Zhu, H. Wang, B. Bennet, L. LaFranco Scheuch, G. E. Fernandez, C. Li, M. Klimas, G. Zhou, M. van Heek, T. Biftu, A. Weber, D. E. Kelley, N. Thornberry, M. D. Erion, D. M. Kemp and I. K. Sebhat, Science, 2017, 357, 507–511. 216. C. T. Salatto, R. A. Miller, K. O. Cameron, E. Cokorinos, A. Reyes, J. Ward, M. F. Calabrese, R. G. Kurumbail, F. Rajamohan, A. S. Kalgutkar, D. A. Tess, A. Shavnya, N. E. Genung, D. J. Edmonds, A. Jatkar, B. S. Maciejewski, M. Amaro, H. Gandhok, M. Monetti, K. Cialdea, E. Bollinger, J. M. Kreeger, T. M. Coskran, A. C. Opsahl, G. G. Boucher, M. J. Birnbaum, P. DaSilva-­Jardine and T. Rolph, J. Pharmacol. Exp. Ther., 2017, 361, 303–311.

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Chapter 2

Targeting the αv Integrins in Fibroproliferative Disease C. B. Nanthakumar, R. J. D. Hatley* and R. J. Slack Fibrosis Discovery Performance Unit, Respiratory Therapy Area, Medicines Research Centre, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, SG1 2NY, UK *E-­mail: [email protected]

2.1  Introduction Fibrosis is the formation of abnormal scar tissue following repeated tissue injury, leading to the disruption of extracellular matrix (ECM) homeostasis with loss of tissue architecture and function. In the developed world, fibrosis is a leading cause of morbidity and mortality whereby multiple organs can be individually affected, including the heart, kidney, liver, lungs and skin.1 In addition, fibrosis is often an underlying causal mechanism present in other diseases.2 Despite significant research efforts, there remains limited therapeutic options for patients suffering with chronic fibrotic disease.3–5 However, therapeutic tractability has been demonstrated for idiopathic pulmonary fibrosis (IPF), a debilitating chronic lung condition of unknown aetiology, with the approval of two oral therapies (pirfenidone and nintedanib)6 and recent clinical trial results demonstrating potential utility in interstitial lung disease (ILD) associated with systemic sclerosis (SSc).7 Over the last decade, the αv integrins have emerged as a target class with significant potential to intervene in multi-­organ fibrosis due to their role in the activation of the key pro-­fibrotic cytokine, transforming growth factor   Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

37

View Online

Chapter 2

38

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

8

(TGF)-­β. Pre-­clinical evidence indicates that TGF-­β has profound effects on a range of cells types including on the migration9 and apoptosis10 of epithelial cells, increased collagen synthesis and ECM production from fibroblasts, as well as inducing transformation into myofibroblasts.11,12 In addition, direct blockade of the TGF-­β receptor I [TGF-­βRI or activin receptor-­like kinase 5 (ALK5) receptor] or its signalling pathway in vivo demonstrated anti-­fibrotic effects.13–15 Clinically, the hypothesis of targeting and modulating TGF-­β in fibrotic disease is yet to be fully tested. Numerous therapeutic approaches have been taken to target TGF-­β in a range of fibrotic and non-­fibrotic disorders, including cancers.16 The approaches that have investigated this pathway include antibodies which bind and reduce available soluble TGF-­β; blocking activation (functional antagonism); inhibiting downstream signal transduction; or direct blockade of the TGF-­βRI or II receptors.16 The vast majority of interventions are accompanied by potential negative side effects associated with global TGF-­β blockade, as a result of its intrinsic pleiotropic nature as a regulator of immunosuppression, inflammatory responses, tumour suppression, cell growth, differentiation and apoptosis. Knockout mice deficient in TGF-­β demonstrate abnormalities in auto-­immune responses and an inability to effectively control inflammation.17–20 In addition, on-­target toxicology effects have been observed with ALK5 inhibitors, that directly inhibit TGF-­ βRI, including the formation of heart valve lesions.21 Therefore, to negate these risks, one potential strategy is to only block TGF-­β activity in the local microenvironment of the fibrotic lesion. This has led to renewed focus on the αv integrins to target disease-­specific, excessive and uncontrolled TGF-­β production. Although drug discovery efforts have been directed at members of this integrin sub-­family in the past, predominantly αvβ3 for cancer and osteoporosis,22 the αv integrins are currently undergoing a renaissance due to recent compelling target validation in fibrotic diseases. A growing number of pharmaceutical and biotechnology companies, as well as academic groups, have generated patents in the arginyl–glycinyl–aspartic acid (RGD)-­mimetic chemical space. Small molecules and antibodies have generally focussed on the αvβ1 and αvβ6 integrins as key targets in fibrosis.23–30 Previous attempts at drug design have been plagued by molecules with sub-­optimal pharmacokinetic and pharmacodynamic profiles, that have ultimately led to poor clinical efficacy.22 Historical drug discovery integrin programmes highlight the challenges in both chemical tractability and in the design of robust pre-­ clinical and clinical studies. More broadly, integrins have been identified to play major roles in numerous diseases, prior to the more recent findings in fibrosis, that have included autoimmune disorders, cancer, infections and thrombosis.31 However, as of early 2012, approximately 260 clinical candidates targeting integrins had entered clinical development, resulting in only five approved therapeutics on the market.32 The majority of these approved drugs have targeted the αIIbβ3 RGD integrin for thrombosis, which underlines an important point – only a very small proportion of the integrin family to date have demonstrable tractability as drug targets, the result of complex functional roles in both normal physiology and disease pathobiology.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

39

The aim of this chapter is to summarise the evidence for the αv integrins in fibrotic disease and review the status of the drug discovery field within this target class. This will include a review of the key methods currently used to prosecute these receptors as well as assay systems that may have future utility. In addition, a summary of the current patent literature is provided. As this field has also included investigation of selective, humanized, therapeutic antibodies, these will also be summarised in the course of the chapter.

2.2  Role of αv Integrins in Fibrosis 2.2.1  TGF-­β and Fibrosis Of the multitude of growth factors and cytokines implicated in the patho­ genesis of fibrotic diseases, TGF-β is the most notorious pro-­fibrotic mediator and modulation of its activities in disease settings is considered beneficial but requires a subtle intervention due to the multi-­functional nature of this cytokine. Physiologically, the mammalian forms; TGF-­β1–3 are anti-­ inflammatory, immunomodulatory, anti-­proliferative and promote wound closure by regulating fibroblast and myofibroblast ECM remodelling.16 Furthermore, TGF-­β can elicit biphasic and opposing effects dependent on concentration. Pathologically, TGF-­β1–3 promote ECM deposition,33 myofibroblast differentiation, cellular invasion and migration, with implications in both oncology and fibrotic settings. However, modulation of canonical TGF-­β signalling presents significant challenges associated with pro-­inflammatory changes and adverse effects and consequently a narrow therapeutic index when defining dose versus tolerability. In fibroproliferative diseases, the TGF-­ β1 isoform is most well-­characterised and will be referred to in the context of integrins described in this chapter. The activation of TGF-­β is complex and exquisitely controlled at multiple levels, such that activation in the local tissue microenvironment following injury is achievable and the latent form of TGF-­β is already present, tethered to the ECM, ready for release.34 Prior to this, the synthesis and secretion of TGF-­β requires proteolytic processing including cleavage by furin convertase, formation of the small latent complex (SLC) where mature TGF-­β is bound to the latency associated peptide (LAP) and further binding to the latent TGF-­β binding protein (LTBP) to form the large latent complex (LLC). Anchoring to ECM proteins such as fibronectin and fibrillin occurs via LTBP which may be cleaved by bone morphogenetic protein-­1 (BMP-­1). Release of active TGF-­ β from LAP can be mediated by thrombospondin,35 extreme pH changes,36 matrix metalloproteinases37,38 and by integrins via the RGD sequence present in LAP. Upon release, the active TGF-­β dimer binds the transmembrane TGF-­ βRII (a member of the type II serine/threonine receptor family) that in turn results in recruitment and heterodimerisation with TGF-­βRI [a member of the type I serine/threonine receptor family also known as activin receptor-­ like kinases (ALKs)]. This heterodimerisation initiates signalling by transphosphorylation of the TGF-­βRI by the TGF-­βRII that can be subsequently transmitted into the cell via either canonical [small and mothers against

View Online

Chapter 2

40

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

decapentaplegic related protein (Smad)-­dependent] or non-­canonical TGF-­β signalling pathways. The focus of this review will be integrin-­mediated activation of TGF-­β.

2.2.2  αv Integrins and Activation of TGFβ Integrins comprise a large family of adhesion molecules, each consisting of an α-­subunit and a β-­subunit with 24 heterodimers identified to date (Figure 2.1). Under normal physiological conditions, integrins are present on most cell types and can bind plasma proteins, such as C-­reactive proteins and fibrinogen, and recognize complement factors. However, integrins play a vital role in the formation of focal adhesion contacts connecting the cellular cytoskeleton to ECM proteins, such as collagen, laminin, vitronectin and fibronectin, influencing fundamental processes such as tissue growth, embryonic development, angiogenesis and immune cell adhesion. Force transmission is an important feature of integrin activity and can lead to the release of active growth factors as has been recently described for TGF-­β.39 A further sub-­classification of integrins is based on the ability to recognise endogenous ligands containing the tri-­amino-­acid motif Arg–Gly–Asp (RGD) and currently eight RGD integrins are known. In addition to endogenous ligands, the RGD sequence is displayed on viral capsids permitting binding and entry into cells to initiate the infectious cycle, although viruses can also

Figure 2.1  Classification  of the αv integrin sub-­family. A total of 24 integrin heterodimers have been identified, 8 bind RGD-­containing ligands and of these, 5 contain the αv subunit (β1, β3, β5, β6, β8). Reproduced from ref. 22 with permission from John Wiley and Sons, © 2018 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

41

employ non-­RGD integrin-­mediated host invasion. This tri-­peptide sequence has been targeted as a potential drug delivery mechanism for binding to cell surface receptors, followed by internalization and through the development of RGD peptide and non-­peptide mimetics, it may be possible to block integrin activity. For example, the RGD-­peptide A20FMDV2, derived from the foot-­ and-­mouth virus, pharmacologically shows high affinity for the αvβ6 integrin RGD site40 and this property maybe exploited for non-­invasive imaging to visualize αvβ6 in man.41 RGD integrins of the αv subtype form heterodimers with five β-­subunits to form a further sub-­category comprising αvβ1, αvβ3, αvβ5, αvβ6 and αvβ8. Currently, there are no clinically approved αv integrin inhibitors, but small molecule and monoclonal antibody approaches are under investigation (see Table 2.2). Interest in the αv integrins has been re-­ignited by a surge in clinical activity and the development of anti-­fibrotic therapies.42 All five αv integrins have been shown to activate the pro-­fibrotic mediator, TGF-­β (reviewed by Margadent and Sonnenberg),8 releasing this growth factor from its inactive state when bound to LAP and tethered to the ECM. Integrin activation is limited to the TGF-­β1 and -­β3 isoforms only, as the TGF-­β2–LAP complex lacks the RGD sequence.43 Latent TGF-­β activation by myofibroblast integrins (αvβ1, αvβ3, αvβ5 and αvβ8) requires a contractile cytoskeleton and as fibroblasts differentiate into myofibroblasts contractility increases, especially following stimulation with growth factors. These integrins may be compensatory in their ability to activate TGF-­β. In a similar fashion, αvβ6 on epithelial cells requires tractional force and cytoskeletal integrity to release TGF-­β from pro-­ TGF-­β.39 Furthermore, integrin-­mediated activation of TGF-­β may proceed via a protease-­dependent or non-­protease dependent pathway (see Figure 2.2). In the case of αvβ8, proteolytic activity is required and matrix metalloproteinase 14 (MMP-­14) is simultaneously recruited to the LAP RGD binding site.44 Protease-­independent TGF-­β activation by integrins requires close proximity coupled with tractional force resulting in the presentation of TGF-­ β to its cognate receptor.45 This can perpetuate a feedforward loop whereby TGF-­β upregulates integrin expression and a repertoire of ECM proteins leading to continual and self-­sustaining growth factor activation. Furthermore, the phenotype of integrin knockout mice closely resembles that of TGF-­β1 null mice18 for β6,46 αv47 and β8 48,49 and includes multi-­organ inflammation especially skin and lung inflammation. The individual RGD integrins capable of activating TGF-­β will be discussed in the context of TGF-­β1 activation.

2.2.2.1 αvβ1 The αvβ1 integrin has remained an elusive target, as achieving specificity for this transmembrane receptor has proven challenging, although recent reports suggest developments in this area with the identification of potentially selective small molecule inhibitors29 (Table 2.1). Moreover, the study of αvβ1 has been further hampered by the lack of selective tool antibodies to

View Online

Chapter 2

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

42

Figure 2.2  TGF-­  β activation by integrins. (A) Protease-­dependent activation by inte-

grin αvβ8 and MMP14. (B) Protease-­independent activation results from a conformational change of LAP–TGF-­β induced by cell traction forces. FXa, coagulation factor X; Gαq, G protein αq; LAP, latency-­associated protein; LPA, lysophosphatidic acid; LPAR2, lysophosphatidic acid receptor 2; LTBP, latent TGF-­β binding protein; MMP14, matrix metalloproteinase 14; PAR1, protease-­activated receptor 1; ROCK; Rho-­ associated kinase; TGF-­β, transforming growth factor-­β; TGF-­βR, transforming growth factor-­β receptor. Reproduced from ref. 8 with permission from John Wiley and Sons, © 2010 European Molecular Biology Organization.

Name; structure; CAS no.

Potencya and selectivity 73

Fibrosis model

(1) BG00011 (STX-­100, 3G9) Humanized monoclonal antibody CAS no. 1439902-­67-­6

Selective αvβ6 

●● Inhibition of lung, liver, kidney fibrosis in mouse models23–25

(2) c8

Selective αvβ1 IC50 0.089–0.63 nM

●● Inhibition of lung, liver, kidney fibrosis in mouse models29,30

Pan αv αvβ1 IC50 1.8 nM αvβ3 IC50 0.8 nM αvβ5 IC50 61 nM αvβ6 IC50 1.5 nM αvβ8 IC50 0.2 nM

●● Significantly reduced CCl4 liver fibrosis and pulmonary fibrosis

αvβ6 IC50 6 nM (1.6 µM)b αvβ3 IC50 9500 nM αvβ5 IC50 > 10 000 nM

●● EMD527040 attenuated bile ductular proliferation and

αvβ3 IC50 0.08 nM αvβ5 IC50 10 nM αIIbβ3 IC50 34.7 µM127,128

●● Suppressed TGF-­β-­induced fibrosis marker gene expression in

CAS no. 1689540-­62-­2 (3) CWHM-­12

CAS no. 1564286-­55-­0 (4) EMD527040

in mice76

●● Reverses fibrosis in the CDAHFD mouse model of NASH122 ●● Inhibition of pancreatic fibrosis in a mouse model with

CWHM-­12 125

●● Attenuates skeletal muscle and cardiac fibrosis in a mouse

model126

Targeting the αv Integrins in Fibroproliferative Disease

Published on 17 February 2020 on https://pubs.rsc.org | d

Table 2.1  Selected  αv-­RGD molecules assessed in pre-­clinical models of fibrosis disease.

peribiliary collagen deposition by 40–50% in a BDL liver fibrosis model27 ●● Inhibited liver fibrosis in a BDL mouse model26

CAS no. 851333-­14-­7 (5) MK-­0429 (L000845704)

a

treatment with MK-­0429 resulted in significant reduction in proteinuria, kidney fibrosis, and collagen accumulation124

 v integrin potency as referenced. For consistency, IC50 values have also been determined in cell adhesion assays as previously described.22 α cell attachment assay.

b

43

CAS no. 227963-­15-­7

kidney fibroblasts

●● In an obese ZSF1 rat model of diabetic nephropathy, chronic

Published on 17 February 2020 on https://pubs.rsc.org | d

Name (synonym); structure; CAS no. (1) BG00011 (STX-­100, 3G9) Humanized mAb

Potencya and selectivity 73

Selective αvβ6 

CAS no. 1629249-­33-­7 (7) GLPG-­0187

CAS no. 1320346-­97-­1 (8) PLN-­74809b

●● Phase II – safety, tolerability, pharmacokinetics, immunogenicity,

biomarkers in patients with IPF completed (NCT01371305). to safety concerns.

Selective αvβ6 143 αvβ6 pKD 10.8 αvβ1 pKD 8.6 αvβ3 pKD 7.7 αvβ5 pKD 7.7 αvβ8 pKD 8.6 αvβ1 pKD 7.0 α8β1 pKD 9.6

●● First time in human (FTIH) study in healthy volunteers and IPF patients

Pan αv135 αvβ1 IC50 1.3 nM αvβ3 IC50 3.7 nM αvβ5 IC50 2.0 nM αvβ6 IC50 1.4 nM αvβ8 IC50 1.2 nM α5β1 IC50 7.7 nM

●● Three registered clinical trials, two in healthy subjects (NCT01580644,

Dual αvβ1/αvβ6 145 αvβ1 IC50 3.4 nM αvβ6 IC50 5.7 nM

●● Phase IIa – Evaluation of PLN-­74809 on αvβ6 receptor occupancy using

(NCT02612051 and NCT03069989 -­PET study) completed but withdrawn for strategic reasons.144

NCT00928343) and one in solid tumours (NCT01313598).

●● Pharmacokinetic and pharmacodynamic effects reported but

continuous infusion failed to provide efficacy.

●● No clinical development since 2013.

PET imaging in participants with IPF (NCT04072315).

 v integrin potency unless otherwise referenced or stated are IC50 values determined in cell adhesion assays as previously described.22 α Proposed structure listed in Cortellis Competitor Intelligence report May 2019: Search term was the naphthyridine sub-­structure.

b

Chapter 2

a

Clinical trials for fibrosis or cancer

●● Phase II – efficacy and safety study (SPIRIT, NCT03573505) stopped due

CAS no. 1439902-­67-­6 (6) GSK3008348

44

Table 2.2  Selected  current clinical αv-­RGD targeted inhibitors.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

45

investigate tissue expression, functional inhibition and the inability to generate a β1 knockout mouse phenotype, as homozygous β1 null mice do not survive through to birth.50 Results of studies in A549 cells indicate that latent TGF-­β may be activated by αvβ1 and cellular adhesion is disrupted by monoclonal antibodies targeting the individual αv and β1 integrin subunits.51 The β1 integrin subunit is also implicated in mechanotransduction, detecting changes in ECM contraction to regulate fibroblast survival.52

2.2.2.2 αvβ3 The αvβ3 integrin is of interest in the oncology field as a pro-­angiogenic mediator but remains controversial as mice deficient in the β3 subunit demonstrate enhanced angiogenesis and tumour growth.53 In the context of TGF-­β activation, αvβ3 is associated with mesenchymal cells including cardiac fibroblasts,54 lung fibroblasts55 and skin fibroblasts.56 Additionally, as the vitronectin receptor, αvβ3 facilitates cell attachment.

2.2.2.3 αvβ5 The αvβ5 integrin is widely expressed on epithelial cells, fibroblasts, osteoclasts and monocytes, although αvβ5 knockout mice develop, grow and reproduce normally57 and are capable of healing cutaneous wounds normally. Evidence indicates that αvβ5 may be a critical regulator of pulmonary vascular permeability and blocking αvβ5 prevented lung vascular permeability in two models of acute lung injury (ALI); ischemia–reperfusion in rats and ventilation-­induced injury in mice.58 Inhibition of αvβ5 in vitro reduces the fibrogenic potential of fibroblasts.59 Whilst αvβ6 (discussed below) may regulate TGF-­β activation in the epithelial/fibroblast milieu, αvβ5-­mediated contraction is important for myofibroblast TGF-­β autocrine production.60

2.2.2.4 αvβ6 The αvβ6 integrin is expressed at very low levels in healthy tissue, with expression confined to epithelial cells. Integrin expression is upregulated during development, in tissue injury and on epithelial tumours.61–63 The αvβ6 integrin activates TGF-­β1 and -­β3 via specific binding to the RGD tripeptide sequence found within LAP and cellular cytoskeletal-­mediated traction. Other ligands for αvβ6 include fibronectin and tenascin.64,65 Upon injury, αvβ6 expression is specifically upregulated in the epithelium and binds LAP, resulting in the generation of free TGF-­β. Free TGF-­β binds to its cognate receptors expressed on fibroblasts, ultimately resulting in enhanced ECM secretion via Smad signalling and initiation of protein translation. β6-­null mice exhibit enhanced pulmonary inflammation with activated lymphocytes, although inflammatory lesions were confined to the lung, in contrast to TGF-­β-­deficient mice.

View Online

46

Chapter 2

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

2.2.2.5 αvβ8 Latent TGF-­β1 and -­β3 may be activated by αvβ8 but the mechanism is protease-­dependent with MMP-­14 recruited simultaneously with LAP/ RGD engagement that results in proteolytic cleavage and release of TGF-­ β.44 This mechanism indicates that αvβ8 is distinct from other αv integrins. αvβ8-­mediated activation of TGF-­β has been studied in immune cells, most recently in T-­cells66 but has also been implicated in tumour biology and fibroinflammatory airways disease.67 Like αvβ6, αvβ8 may also be found in airway epithelial cells. Embryos deficient in αvβ8 can die in utero due to impaired vasculogenesis and surviving embryos have cleft palate and brain abnormalities.48 Sub-­populations of dendritic cells (DC) express αvβ8 to drive TGF-­β activation as a consequence of DC lineage and the local tissue microenvironment to support TGF-­β-­mediated immunomodulation.68 Conditional deletion of αvβ8 in murine lung fibroblasts further supports an important role for αvβ8-­mediated TGF-­β release in DC trafficking.69 The αvβ8 integrin is also expressed in human hepatocytes at the tissue level and conditional deletion in murine hepatocytes led to accelerated liver regeneration after partial hepatectomy.70

2.3  Disease Implications The central nature of TGF-­β driving fibrotic changes across organs indicates that modulation of αv integrins to minimise TGF-­β activation could be a viable therapeutic strategy in a range of fibroproliferative disorders. Of the αv integrins, the most widely studied in the fibrosis field is αvβ6, given its restricted expression, upregulation following injury and the generation of pre-­clinical and clinical data using monoclonal antibodies targeting αvβ6. In lung biopsy tissue obtained from normal margins in cancer patients undergoing resection surgery, αvβ6 expression was undetectable but fibrosis samples from patients with SSc and IPF showed strong αvβ6 immunoreactivity, localising to type II and type I epithelial cells in fibrotic lesions24 and αvβ6 staining intensity was further increased for patients with a usual interstitial pneumonia (UIP) histopathological classification, positively correlating with poor prognosis in patients with interstitial lung disease.71 Expression of αvβ6 in epithelial cells is also increased in a number of chronic renal diseases associated with fibrotic changes, including glomerulonephritis, diabetes, IgA nephropathy and Alport syndrome.25 In end-­stage liver disease, αvβ6 protein is upregulated in bile duct epithelia and transitional hepatocytes whilst αvβ6 mRNA expression increased with disease progression in patients with hepatitis C.26 The majority of target validation data supporting αvβ6 in fibrotic diseases has been generated using in vivo models of experimental fibrosis. Whilst TGF-­β1-­deficient mice develop multi-­organ inflammation and epithelial cell hyperplasia and TGF-­β2 and-­β3 transgenic mice exhibit developmental defects,18–20 mice lacking αvβ6 due to a deletion mutation in the β6 subunit gene have enhanced skin and lung inflammation but fail to

View Online

Targeting the αv Integrins in Fibroproliferative Disease

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

46,72

47

develop fibrosis. Upon bleomycin instillation, lung morphology in αvβ6-­ deficient mice remained relatively unchanged with small patches of fibrosis and no increase in hydroxyproline content, in contrast to wild type mice.72 Protection from bleomycin-­induced fibrosis was not due to inhibition of inflammation, as αvβ6 null mice had increased numbers of neutrophils, lymphocytes and macrophages in bronchoalveolar lavage (BAL) compared with wild type mice receiving bleomycin. The αvβ6 null mice do not demonstrate abnormalities in other organs, indicating that αvβ6-­mediated TGF-­β1 activation may be a local response to injury specifically in the skin and lung and could be an evolutionary feature, as these organs are more prone to environmental insults. BG00011 (1) (Table 2.1) is a selective monoclonal antibody with αvβ6 specificity and blocks αvβ6-­mediated latent TGF-­β activation.73 Whilst αvβ6-­null mice are protected from bleomycin-­induced pulmonary fibrosis,72 BG00011 has demonstrated beneficial effects in multiple models of experimental fibrosis across organs, including bleomycin-­and radiation-­induced lung fibrosis74 and in experimental models of kidney fibrosis.25 Following advances in small molecule integrin chemistry, αvβ1 modulation has been examined in experimental models of pulmonary, hepatic and renal fibrosis highlighting a role for this integrin during the development of tissue fibrosis.29,30 Pre-­clinically, c8 (2) (Table 2.1), a small molecule inhibitor with reported selectivity for αvβ1 has shown protective effects in experimental models of fibrosis in the lung, liver and kidney. Despite αvβ1 inhibition via c8 (Table 2.1) blocking TGF-­β activation in vitro and collagen deposition in the unilateral ureteral obstruction (UUO) model of kidney fibrosis in vivo30 the assays used to assess integrin affinity, functionality and specificity can present significant challenges and limitations and are discussed in detail in the next section. PLN-­74809 (8) (Table 2.2) has recently completed phase I evaluation as a dual-­specificity, small molecule inhibitor of both αvβ6 and αvβ1 to target epithelial cells and fibroblasts respectively. Using precision-­cut lung slices (PCLS) from IPF patients undergoing transplant therapy, ex vivo PLN-­74809 treatment reduced collagen gene expression.75 PLN-­74809 is also of interest in progressive liver disease, such as primary sclerosing cholangitis. Alternatively, combinations of integrins may be optimal for targeting to overcome the potential for redundancy and pan-­αv inhibition using a humanized monoclonal antibody such as abituzumab, originally developed for prostate cancer was under investigation in phase II trials for SSc-­ILD (NCT02745145). Likewise, small-­molecule integrin inhibitors (CWHM-­12) (3) (Table 2.1) demonstrating pan-­αv affinity have been reported to significantly reduce fibrotic end-­points in murine models of liver and lung fibrosis.76 The extent of TGF-­β modulation afforded by pan-­αv integrin inhibition could be greater than that from targeting a single αv integrin, but this may affect many more cell types, raising the possibility of reduced tolerability and therapeutic index in man. In chronic kidney disease (CKD), evidence indicates a potential role for both αvβ3 and αvβ5 in experimentally-­induced models of renal fibrosis. Using

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

48

Chapter 2

a model of ischemia–reperfusion injury (IRI), rats treated with an αvβ5 blocking antibody had reduced levels of renal injury. Renal fibroblasts express αvβ1, αvβ3, αvβ5 and αvβ1 inhibition via c8 (Table 2.1) blocked TGF-­β activation in vitro and collagen deposition in the unilateral ureteral obstruction (UUO) model of kidney fibrosis in vivo. In patients with diabetic nephropathy (DN), circulating levels of active TGF-­β were shown to be significantly higher compared with diabetic patients with no renal impairment.77 A monoclonal antibody directed against αvβ3 has completed phase II evaluation in DN (NCT02251067) although the suggested mechanism was inhibition of IGF-­1 signalling rather than TGF-­β activation and it is yet to progress to further clinical development.78 Skin fibrosis may present as hypertrophic scarring, scarring associated with keloid lesions or skin changes associated with SSc connective tissue disease. In fibroblasts isolated from SSc, the levels of activated β3 are increased79 and cilengitide (Figure 2.4 – αvβ3 and αvβ5 inhibitor) therapeutically administered in a murine model of SSc blocked cutaneous and pulmonary fibrosis, as evaluated using histological end-­points.80 However, these effects were thought to be due to inhibition of integrin signalling pathways rather than a result of blockade of TGF-­β activation.79,80

2.4  A  ssays for Identification of αv Integrin Small Molecule Inhibitors 2.4.1  In Vitro Systems There have been several types of assay format used for identification of αv integrin small molecule inhibitors and to measure the key parameters of integrin affinity, selectivity and functional inhibition of TGF-­β activation. These have ranged from simple protein assay systems focussed on binding, through to more complex 2D cellular systems and ex vivo tissue studies. The determination of each of these parameters comes with challenges and it is important to understand the strengths and weaknesses of each experimental system being used. This allows any caveats associated with data generation to be understood, especially critical when data are a pivotal requirement for driving iterative medicinal chemistry structural–activity relationships (SAR) and prior to progressing to in vivo experimentation. In all assay systems, a number of factors should be considered. For example, with affinity/potency and selectivity estimates, the type and concentration of divalent metal cation should be explored to more closely resemble physiological conditions,81 as well as the effects of receptor number on the tight binding limit of an assay.82 This also affects functional assays, where it is important to use control compounds that are fully pharmacologically characterised to validate the αv integrins contributing to TGF-­β activation.83

View Online

Targeting the αv Integrins in Fibroproliferative Disease

49

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

2.4.1.1 Soluble αv Integrin Protein Binding Assays Soluble recombinant protein preparations for the αv integrins are commercially available and can be used in low-­cost and high-­throughput assay formats for the identification and characterisation of small molecule inhibitors. Historically, methods using soluble protein preparations have included fluorescence polarisation (FP) binding,84 competitive binding enzyme-­linked immunosorbent assay (ELISA)85 and radioligand binding,34 with the former lending itself well to high-­throughput and SAR screening. The concentration giving 50% of maximum inhibition (IC50; FP/ELISA) or inhibition constant (KI; radioligand binding) values generated via these techniques measure the ability of a compound to inhibit the binding of an RGD ligand to the integrin. Although having high-­throughput and being efficient in differentiating the rank order of IC50 values of compounds against a single integrin, one of the limitations of the ELISA and FP assay types is that a true affinity (KI) value cannot be calculated. In order to measure the KI of a ligand, the Cheng–Prusoff equation86 is required, that allows the binding affinity, and the amount, of the competing ligand to be taken into consideration. In ELISA and FP formats the parameters required for the Cheng– Prusoff correction can either not be determined or are crude estimates, meaning that relative affinities for the different integrins are difficult to establish. In addition, these assay types do not allow a full characterisation of the type of binding for compounds – whether they are competitive and reversible (or not) in behaviour, and the kinetics of the compound–integrin interaction cannot be ascertained. The lower throughput and higher cost radioligand binding assays offer application of the Cheng–Prusoff equation and therefore provide the most sensitive measure of affinity and accurate determination of selectivity across the αv integrins.34,35 In addition, this format has also been used to obtain early characterisation of compound kinetics within this target class.87 The improved sensitivity of this approach also negates the issue of a tight-­binding limit where the concentration of inhibitor required to cause inhibition is close to the concentration of the receptor or enzyme in the system.88 In other methods, for example FP, this can be a limitation when compounds approach higher affinities (usually in the sub-­nanomolar range) and additionally has the potential to affect integrin selectivity estimates. Unlike in the kinase field, there are no extensive commercial screening panels for profiling integrin selectivity available. To help build robust validation for targets, it is critical to compare not only across the αv integrins but beyond to the other RGDs and any other shared integrin subunits where selectivity maybe predicted to be an issue e.g. αvβ1 compared with the other 11 β1 subunit containing integrins (see Figure 2.1). Although applied to this field for large peptides,89 surface plasmon resonance (SPR) is a potential highly sensitive, high-­throughput and non-­radiometric method able to give early readouts on kinetics for small molecules, that is

View Online

Chapter 2

50

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

90

currently used in other receptor fields to great effect and could be more widely applied to the αv integrins. However, the sensitivity in the SPR signal for integrin interactions with small versus large molecules with this technique may be a limiting factor.

2.4.1.2 Cell Adhesion Assays The most routinely used assay system for determining an empirical measure of potency of small molecules for the integrins is cell adhesion. This has been one of the most frequently used method according to the literature.22 These assays measure the ability of a test compound to inhibit the binding of an integrin (either in a primary cell or recombinantly expressed in a cell line) to an endogenous peptide ligand coated in a microtitre plate, usually using a fluorescent or luminescent cell-­permeating dye. As is the case with the FP binding assay format, cell adhesion lends itself well to high-­throughput screening and ranking compounds against a single integrin. However, cell adhesion assays have limitations as the variable receptor number present between cell lines and batches will influence the detection limit and sensitivity of the system. This can be further exacerbated if the type and/or amount of the endogenous peptide ligand used in the system differs between integrin cell adhesion assays.34 These limitations make it difficult to compare selectivity across different integrins and more appropriate assays may be adopted.

2.4.1.3 Functional Cell Systems For determination of the functional consequences of the inhibition of TGF-­β-­ activation via blockade of the αv integrins, co-­culture systems have generally been employed using both primary human cells (normal and disease) and immortalised cell lines. These have used a biosensor method whereby detection of TGF-­β-­activation and release from the cell or integrin of interest e.g. epithelial cells for αvβ6/8,67,91 mesenchymal cells for αvβ1/3/5,29,54 are measured using a transformed mink lung cell expressing firefly luciferase under the control of a TGF-­β-­sensitive portion of the PAI-­1 promoter.92 However, it is also possible to use single cell systems to measure downstream signalling of the TGF-­β pathway via phosphorylated proteins such as the Smad2/3.93 More complex systems allowing the investigation of the interplay between epithelial cells and fibroblasts and the measurement of TGF-­β-­mediated ECM deposition in 2D94,95 and 3D models96 may also offer a more translational system to profile αv integrin inhibitors in the future. Engagement of the RGD binding site of the αv integrins has been shown to cause internalisation of these receptors, though this has primarily been studied with αvβ3 97,98 and αvβ6.40,99 Imaging and flow cytometry have predominantly been used to investigate this process in both normal and diseased primary cells and stable cell lines. Determining the effect of potential

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

51

therapeutic small molecules on the cell surface integrin expression via internalisation is important as this can influence the duration of pharmacodynamic effects.100 In addition, the potential signalling cascades initiated via RGD engagement, activation and subsequent internalisation should also be considered from a toxicology point of view.101

2.4.1.4 Human Tissue Systems The use of human tissue from healthy and diseased organs has been, to date, limited to determining the levels of αv integrins via immunohistochemistry.24–26 However, precision-­cut slices from both healthy and diseased lungs are beginning to be investigated for functional pharmacodynamic and fibrotic end points.102–105 The main difficulty remains the availability and consistent supply of disease tissue that can be received within short timelines post-­transplant. To overcome logistical issues, researchers are using surrogate systems via stimulation of healthy tissue with pro-­fibrotic mediators.106 Exploration of αv integrin inhibitors in human tissue systems has been minimal to date but it is likely that future studies will utilise these models to improve pre-­clinical to clinical translation.

2.4.2  In Vivo Fibrosis Models In the αv integrin field, as with the majority of drug discovery initiatives, the selection and rationale for the use of in vivo models is key. Truly translational disease in vivo models rarely exist, regardless of the target or disease area being investigated,107,108 and this is no different when targeting αv integrins and fibrosis. The lack of selective drug-­like tools for each αv integrin also makes interpretation of data difficult.29,35 Although the use of in vitro diseased human tissue systems will probably be a key platform for the development of future anti-­fibrotic therapies, validation and implementation are at an early stage coupled with the requirement to investigate whole-­body systems. One approach may be to use experimental models to determine pharmacokinetic and pharmacodynamic relationships or to identify new disease biomarkers to replace clinically unfeasible or proven untranslatable end-­points. With this strategy clear clinical hypotheses can be generated and tested to complete the validation of a target by demonstrating clinical efficacy. The in vivo models described below have been used in gene knockout or drug intervention studies to validate either the role of a particular αv integrin or demonstrate efficacy of a pre-­clinical molecule in the lung, liver and kidney.

2.4.2.1 Pulmonary Fibrosis Models The majority of anti-­fibrotic agents targeting IPF have been assessed in the bleomycin-­induced lung fibrosis model. Bleomycin induces DNA strand breaks and was originally identified as a chemotherapy agent,

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

52

Chapter 2

however, a reduction in lung function via generation of pulmonary fibrosis was observed as a potential side effect.109 As such, bleomycin has been used to develop pre-­clinical models of lung fibrosis in rodents, despite not being widely accepted to be a representative model of IPF due to the lack of observable characteristic histological features of the disease and fibrotic lesions resolving over time.110,111 The model's translation to clinical effects is questionable even though currently approved IPF treatments; pirfenidone and nintedanib have been evaluated with mixed findings112,113 there still remains a significant number of failed clinical studies with drugs that demonstrated efficacy in the model.63,114 Guidelines on the use of this model, generated via an American Thoracic Society workshop report, are useful to consult when planning studies and assessing limitations.115 Measuring levels of hydroxyproline as a marker of collagen synthesis has been the gold standard method for assessing compound efficacy in the bleomycin-­induced lung fibrosis model, however assays are time consuming with poor sensitivity. Therefore, confirming target engagement and disease relevant end-­points that can be readily measured in a clinic setting would be beneficial, for example phosphorylated Smad 2 or 3 (pSmad2/3) as a pharmacodynamic end-­point for TGF-­ β-­activating integrins. The bleomycin model is characterised by elevated TGF-­β14,15 levels, however the primary αv integrin involved in activation is unclear. From gene knockout studies in mice and pharmacological intervention with a selective monoclonal antibody (1) (Table 2.1), αvβ6 was first highlighted as the critical integrin contributing to disease pathogenesis.24 Conversely, blockade of the αvβ1 integrin with a small molecule inhibitor (2) (Table 2.1) in this model also demonstrated efficacy29 although the selectivity of the tool molecule against other non-­αv integrins has raised questions around the validity of this observation.83 Combined with a lack of protection from fibrosis when other αv integrins were genetically removed,116 bleomycin-­induced pulmonary fibrosis may be predominantly driven by αvβ6-­mediated TGF-­β release. An alternative to bleomycin-­induced experimental lung fibrosis is adenovirus-­mediated delivery of TGF-­β with potential for fibrotic lesions to persist over longer time courses.117 In this model, recombinant adenoviral vectors are used to specifically overexpress TGF-­β1 in rat lungs, inducing excessive collagen deposition from 14 days post-­viral administration. As with the bleomycin model, hydroxyproline is the routine measure of collagen combined with histological changes. Therapeutic intervention has been investigated in this model for direct TGF-­β blockade,13 however characterisation of the expression of the αv integrins and the role they may play once fibrosis is established is yet to be determined. As TGF-­β exerts transcriptional control of all the αv integrins,118 it could by proposed that one or more could start to exacerbate the active TGF-­β adenovirus response in the early phases

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

53

of the model. Therefore, it could be an interesting system to test the therapeutic effects of αv integrin inhibitors. Furthermore, some data using ex vivo lung tissue from this model confirmed a role for the αv integrins-­mediated TGF-­β activation during established fibrosis.119 Other models of respiratory disease that have been investigated in the context of αv integrin-­mediated TGF-­β activation include radiation-­induced lung fibrosis,74 interleukin-­1β adenovirus and allergen-­induced lung injury using ovalbumin.69 The latter have been used in a single study investigating the role of αvβ8 during pro-­inflammatory responses and subsequent airway remodelling associated with COPD and asthma following conditional deletion of β8 in fibroblasts.

2.4.2.2 Hepatic Fibrosis Models A significant number of models are focussed on reproducing components of liver disease, from steatosis through to cirrhosis. These include chemical-­ induced, diet-­based, genetically modified and surgery-­based models that all come with advantages and disadvantages.120 So far, the lack of any approved medicines for fibrotic liver disease poses difficulties for pre-­clinical and clinical linkage. The models used for target validation and therapeutic intervention for the αv integrins have focussed on carbon tetrachloride (CCl4) chemical-­ induced and the surgery-­based bile-­duct ligation (BDL) models. CCl4 is the most common hepatotoxin used to generate fibrosis and cirrhosis in rodents. CCl4 induces free radical generation and cytokine production with activation of hepatic stellate cells (HSCs), myofibroblast differentiation and ECM deposition. In conditional knockout and therapeutic intervention studies with compounds (2), (3) and (4) (Table 2.1), the role of αv integrins, primarily αvβ1, in liver fibrosis has been evaluated.29,76 In contrast, the BDL model uses a surgical double ligation of the bile duct to increase biliary pressure, inducing inflammation and cytokine secretion that ultimately generates periportal biliary fibrosis via increases in fibrogenic mediators like TGF-­β1, alpha smooth muscle actin (α-­SMA) and tissue inhibitor of metalloproteinases-­1 (TIMP-­1). This model has been used to investigate the role of αvβ6 in gene knockout and inhibitor studies with a pan-­αv small molecule27 (4) (Table 2.1) and the αvβ6 selective antibody23 (1) (Table 2.1). Interestingly, the use of cilengitide (Figure 2.4) in the BDL model was shown to aggravate fibrosis.121 This combined with the inhibition observed with a pan-­αv small molecule in the same model from the same group23 (4) (Table 2.1), indicates an interplay between αv integrins, in addition to a sensitive balance in the selectivity profile required to provide a beneficial effect. The role of αvβ6 has also been investigated in liver models of primary sclerosing cholangitis (PSC). PSC is characterised by intra-­and extra-­hepatic bile

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

54

Chapter 2

duct inflammation and fibrosis that progresses to cirrhosis. Mice deficient in canalicular phospholipid flippase (Mdr2−/−) develop biliary fibrosis and demonstrate some features of PSC. These mice were protected from liver disease by either genetic deletion of β6 or treatment with an αvβ6 selective antibody28 (1) (Table 2.1). In the same study, 5-­diethoxycarbonyl-­1,4-­dihydr ocollidine-­fed β6-­deficient mice were protected against the advanced biliary fibrosis associated with this diet. As with pre-­clinical lung models, there are conflicting data in the liver regarding which αv integrin is most critical in disease. However, these models act as systems to test efficacy in vivo and no single system in isolation has yet been shown to predict outcomes in human disease. The potentially more disease-­relevant, genetic and diet-­based models for non-­alcoholic fatty liver disease (NAFLD) are expensive and have longer time courses that are required to induce a more pertinent fibrotic disease phenotype, making them less amenable to drug discovery. It is likely that as a result of the complexity in these models data showing whether an individual αv integrin, or a combination, should be targeted has yet to be generated. Pan-­αv blockade using (3) (Table 2.1) reportedly reversed fibrosis in the choline-­deficient, amino‐acid defined, high‐fat diet (CDAHFD) mouse model of non-­alcoholic steatohepatitis (NASH)122 and therefore this could be an appropriate model to test specific αv integrin hypotheses and potential clinical drug candidates.

2.4.2.3 Renal Fibrosis Models The kidney has attracted less attention compared with lung and liver for targeting αv integrins in fibrosis. The pre-­clinical model most frequently used to test the role of the αv integrins in chronic kidney disease is the UUO model. Single studies have also been conducted with the collagen type IV alpha 3 chain-­deficient (Col4A3−/−) mouse model of Alport syndrome. In the human form of this disease, patients develop glomerulonephritis leading to end-­stage renal disease (ESRD). Diabetic nephropathy (DN) has been modelled using the Zucker fatty/spontaneously hypertensive heart failure F1 (ZSF1) obese rat. Obstruction of the ureter in the UUO model results in proliferation of renal interstitial fibroblasts, by transformation into myofibroblasts and fibrosis due to excessive collagen deposition in the renal interstitium. As with the lung bleomycin model, both αvβ1 and αvβ6 have been suggested to drive the fibrotic response in the UUO model, demonstrated either by pharmacological intervention30 (2) (Table 2.2) or genetic deletion.123 In the Alport mouse kidney model, the human syndrome is recapitulated by knocking out the Col4A3 gene, which results in abnormal assembly of collagen IV networks and atypical basement membranes. When Col4A3-­ deficient mice were crossed with the β6 knockout or treated with an αvβ6 selective antibody (1) (Table 2.1), a reduction in interstitial collagen matrix deposition was observed.25

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

55

Whilst no specific αv integrin has been shown to drive fibrosis in the obese ZSF1 rat model of DN, the αvβ3/5 inhibitor124 (5) (Table 2.1) was effective at reducing collagen accumulation, indicating that further investigation with selective tools would be of interest.

2.5  Drug Design Approaches 2.5.1  R  GD αv Integrin Inhibitors – Historic and Current Clinical Landscape Only a relatively small number of integrin inhibitors, from any family, have yielded marketed medicines – representative examples are the small molecule, tirofiban (Figure 2.3), for thrombosis (αIIbβ3 antagonist – RGD family) and the monoclonal antibody, natalizumab, for the treatment of multiple sclerosis and Crohn's disease (α4β1/β7 integrin antagonist – leucocyte family).32 Within the RGD αv sub-family itself, several inhibitors have been assessed in clinical trials, but none have reached the market. Historically, the furthest examined examples of small molecules have been αvβ3 inhibitors (Figure 2.4).

Figure 2.3  Tirofiban. 

Figure 2.4  Clinical  αvβ3/αvβ5 dual-­active inhibitors.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

56

Chapter 2

These agents showed great promise in the treatment of osteoporosis, rheumatoid arthritis and cancer indications, but all fell short at various clinical phases either due to lack of efficacy or drug related toxicity.22 For example, non-­peptidic inhibitor SB-­273005 (Figure 2.4) entered a phase I clinical trial for osteoporosis but this was soon halted after the discovery of unique vascular toxicity in the aorta of mice.129 The most well-­known example, and nearest to delivering a marketed drug (Phase III) is the macrocyclic peptide, cilengitide130 (Figure 2.4), which was assessed in more than 30 clinical trials for various cancers. While it proved to be safe, it was not sufficiently efficacious in patients, despite promising results in preclinical tumour models.131,132 Similarly, dosing of MK-­0429 (5) (Table 2.1 and Figure 2.4) to treat osteoporosis in clinical settings did not come to fruition, despite encouraging results for increasing the bone mineral density in women with postmenopausal osteoporosis and being generally well tolerated.133 MK-­0429 has been modified by introduction of two fluorine atoms (Figure 2.4) for topical delivery in retinal diseases and is under clinical development by SciFluor Life Sciences (SF-­0166, NCT02914613 and NCT02914639).134 Several clinical αv integrin inhibitors have been investigated for oncology indications and more recently, fibrotic diseases. Amongst others, the small molecule from Galapagos, GLPG0187 135 (7) (Table 2.2) and the antibody abituzumab,136,137 under development by SFJ Pharmaceuticals, both having multi-­αv-­integrin activity, have been assessed for targeting solid tumours and metastatic colorectal cancer respectively. It is conceivable that these drugs could also be examined for fibrotic diseases – abituzumab, for example, was briefly evaluated in SSc-­ILD patients prior to termination due to lack of enrolment (NCT02745145), although development of GLPG0187 in oncology appears to have been halted due to lack of efficacy.135 Treatment of fibrotic diseases by first intent has focussed on inhibition of αvβ6. The furthest progressed αvβ6 inhibitor in clinical trials until recently was the selective antibody BG00011 (1) (Table 2.2), under development by Biogen for the treatment of IPF. This antibody (1) appears to act as an allosteric, non-­RGD inhibitor of αvβ6 79 and a Phase II clinical trial to establish efficacy and safety in participants with IPF (SPIRIT clinical trial, NCT03573505) was recently stopped due to undisclosed safety concerns. The preceding trial (NCT01371305) had begun to establish the dose and therapeutic index (TI).138,139 Preclinically, different concentrations were evaluated in the murine bleomycin model, demonstrating that attenuation of pulmonary fibrosis is achievable without causing heightened inflammatory responses with partial inhibition of TGF-­β.24 At this time it appears the clinical trials with BG00011 will not evaluate if targeting the αvβ6 mechanism in patients is beneficial and it is not clear if the safety concerns raised were due to on-­target effects. The potent and selective αvβ6 small molecule inhibitor, GSK3008348 (6) (Table 2.2) from GlaxoSmithKline has also been assessed in early clinical trials (NCT02612051 and NCT03069989) as a low-­dose inhibitor that has been delivered to healthy participants via nebulisation (1–3000 µg) and shown

View Online

Targeting the αv Integrins in Fibroproliferative Disease

57

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

140

to be well tolerated. The level of target engagement in fibrotic tissue was investigated in a positron emission tomography (PET) study (NCT03069989) with the specific αvβ6 radiolabelled peptide [18F]-­FBA-­A20FMDV2.40 As a prelude, confidence that small molecules can reach the required areas in lungs characterised by scarring and loss of pulmonary compliance was established following a successful study using radiolabelled salbutamol.141 If target engagement is successfully achieved for (6), this may pave the way for other similar modalities. Additionally, (6) may offer a safer TI compared with oral medications if systemic exposure is low. The most advanced clinical small molecule oral integrin inhibitor for fibrosis diseases, proceeding to phase II evaluation, is the dual αvβ6/αvβ1 inhibitor, PLN-­74809 (8) (Pliant Therapeutics)142 (see Table 2.2).

2.5.2  P  roperties and Drug Design of Small Molecule αv Integrin Inhibitors A plethora of reported small molecule αv integrin inhibitors (RGD-­mimetics) continue to be designed and developed by pharmaceutical companies, biotechs and academic groups, as evidenced by increased numbers of publications and patents. Yet, most molecules remain or have remained at the pre-­clinical stage, despite good biological rationale for integrin targets to treat numerous diseases. This could be due to target validation gaps but also indicates the overall complexity of developing integrin molecules of the RGD chemotype.22 The design of αv-­integrin inhibitors is well trodden territory, achieved by mimicking the RGD tripeptide sequence itself, contained in peptidic structures and small molecule drugs alike. The basic arginine (-­R-­) forms a strong interaction with the conserved Asp218 residue in the αv subunit, the glycine (-­G-­) residue provides linkage through to the β subunit and the aspartic acid (-­D -­) amino acid contains a carboxylic acid that binds a metal ion (Mg2+, Ca2+ or Mn2+) in the metal-­ion-­dependent-­adhesion-­site (MIDAS). It is also normally the requirement that the RGD-­mimetic spans a minimum distance across the α-­ and β-­subunits (typically 10–18 Å) to potently block binding of endogenous ligands. The binding features and some of the key interactions to explain selectivity can be observed for the in silico docking of RGD small molecule (6) in αvβ6 and αvβ3 crystal structures (Figure 2.5).87 With most αv binders having the RGD sequence (or a mimetic thereof) in common, it is interesting to observe that the structural diversity of ligands is still very wide and can encompass varied physicochemical drug space, providing much needed flexibility for the design of drug candidates. As with all small molecule drug discovery projects, the physicochemical properties and in silico descriptors [such as log of partition of a chemical compound between the lipid and aqueous phases (LogD), molecular weight (MW), polar surface area (PSA), protein binding, solubility, number of hydrogen bond acceptors (HBA), number of hydrogen bond donors (HBD) underpin drug

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

58

Chapter 2

Figure 2.5  Comparison  of binding site surfaces between an αvβ6 crystal structure 4UM9 (blue) and an αvβ3 crystal structure 1L5G (grey). The αvβ6 site provides a pocket into which bulky meta-­substituted aryl substituents can bind (solid blue surface). In comparison, the αvβ3 Tyr166 side chain and the salt-­bridge between Asp179 and Arg214 side chains result in a more enclosed pocket which is less favorable for these groups (grey mesh and residue labeling). Reproduced from ref. 87 with permission from American Chemical Society, Copyright 2018.

design. For αv integrin molecules in particular, one of the challenges is managing the properties of the typical zwitterionic pharmacophore for oral dosing, although high solubility and low promiscuity are usually forthcoming. A second key challenge is how to introduce high selectivity for one αv integrin, given the close sequence homology of the αv binding sites, along with desirable physicochemical properties. For example, the selective αvβ1 inhibitor (2) has high potency (nM) and selectivity (more than 100-­fold over other αv integrins) but suffers from a poor pharmacokinetic profile.83 In addition, identification of non-­peptidic selective αvβ5 or αvβ8 inhibitor small molecules has for the most part proved to be elusive, due to the close homology of αvβ3/αvβ5 binding sites, and similarly with αvβ8/αvβ6.22 However, good progress in addressing selectivity has been made recently with cyclic peptide inhibitors of both αvβ6 146,147 and αvβ8.148 Evidence that some of these hurdles have been addressed comes from the recent development of a dual αvβ1/αvβ6 orally bioavailable inhibitor (8) (Table 2.2), with a human pharmacokinetic profile that supports once-­daily dosing.149 Seminal work by Springer and colleagues has not only shown a crystal structure of αvβ6 bound to the RGD motif within the prodomains of TGF-­ β1 and TGF-­β3 150 but also that integrins can exist in at least three different

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

59

conformations (bent-­closed, extended-­closed, extended-­open). Across different assay formats (see Section 2.4) the presence of ligands and metal ions (Ca2+, Mg2+, Mn2+) can determine which conformation predominates,151,152 and together, can drive integrins to exist in the high-­affinity state, corresponding to the extended-­open conformation. In the absence of informative crystal structures for in silico docking studies, construction of homology models can be used as a surrogate for the design of new chemotypes. This is relevant to αvβ1 integrin for example, where no crystal structure exists. Indeed, the potent and selective molecule (2) was expertly designed by stitching together a typical αv subunit binding motif (guanidine) – derived from historic αvβ3 molecules, with a β1-­subunit binder (proline sulfonamide) – obtained from α2β1 molecules.29 Smaller peptides containing the RGD sequence are generally weaker inhibitors of αv integrins, especially αvβ6 and αvβ8.153 It is often the case that additional ligand–protein interactions are required to improve potency and selectivity over the RGD tripeptide itself, which could be through incorporation of additional amino acid residues or slightly larger drug-­like lipophilic groups which bring advantageous surface contacts. For example, the larger 20 amino acid peptide (A20FMDV2) derived from the foot and mouth disease virus (FMDV) is a potent and selective αvβ6 inhibitor.40 Strong ligand binding to Asp218 within the αv subunit can be achieved when the strongly basic guanidine [negative log of the acid dissociation constant (pKa) approximately 14]154 motif is retained, as observed for the αvβ1 molecule (2) and the cyclic peptide, cilengitide (Figure 2.4). This interaction replicates the strong salt bridge observed in peptides and endogenous ligands.155,156 Since the guanidine group is charged, even at neutral pH, it contributes to the low permeability of ligands containing this group. The low permeability can often be improved upon replacing the charged Arg mimetics with less basic groups such as aminopyridines and 1,2,3,4-­tetrahydro-­1 ,8-­naphthyridine derivatives (pKa typically 6–8)157 without detriment to the potency. The glycine residue (within an RGD ligand) typically spans the interface of the αv and β-­subunits of the integrin and is sometimes referred to as the linker region in drug mimetics. Changes in the linker structure can have a profound effect on αv potency and selectivity and the physicochemical properties. The widest structural differences are found in this region, where αv integrin inhibitors are surprisingly tolerant of functionality – accommodating peptide bonds, aliphatic heterocycles, linear chains and aromatic groups with neutral to basic properties. The drug designer can use this flexibility to advantage in tailoring or balancing other properties as determined by the zwitterionic nature of molecules, allowing good oral bioavailability to be achieved. The third key binding motif of the RGD recognition sequence is the carboxylic acid group (Asp residue), located in the MIDAS region. With very few exceptions, the acid group is required to achieve high potency and is critical for strong binding to the metal ion (Mn2+ or Mg2+) and with amide backbone

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

60

Chapter 2

Figure 2.6  RUC-­  4. residues.156 Due to the high network of interactions in the MIDAS region, the carboxylic acid is not very tolerant of even small structural changes, including isosteres. Changes made to the ligand in the β-­region, distant to the acid, can be used to help dial in the required physicochemical properties, typically achieved by modifying the substituents on an adjacent aryl group158 which points to the specificity determining loop (SDL) (Figure 2.5). It is worth noting that while the acid group helps to confer advantages in solubility and selectivity over other target classes, it may also contribute to reduced permeability, increased in vivo clearance rates, or even hepatotoxicity due to glucuronidation pathways.159,160 There have also been approaches to identify non-­RGD mimetics – these typically lack either the Arg or the Asp binder and are of interest because of their differentiated property profiles, avoiding the zwitterionic pharmacophore. However, without the full complement of RGD binding interactions it may be a challenge to maintain high potency and several unwanted pan-­ assay interference compounds not suitable for progression have unwittingly been identified in this space.161 There has been considerable interest in compounds RUC-­2 and RUC-­4 (Figure 2.6) which lack the carboxylic acid binder and have been designed as effective antagonists of the related RGD integrin, αIIbβ3. These molecules offer an alternative binding mode, where a primary amine in place of the carboxylic acid displaces, rather than binds, the metal ion located in the MIDAS region.162,163

2.5.3  S  elected Small Molecule αv Integrin Patent Literature 2014–2018 RGD αv inhibitor molecules have been the subject matter of a relatively small but steady stream of patents over a number of years. However, a recent upsurge in filings, mainly targeting fibrotic indications, has taken hold (Table 2.3). These patents describe drug-­like small molecules for inhaled or topical administration e.g. WO2014/154725, while others describe molecules with good oral properties e.g. WO2017/117538. From a chemical structure perspective, it is interesting to observe that the preferred αv inhibitor molecules normally contain the 1,2,3,4-­tetrahydro-­1,8-­naphthyridine as the Arg mimetic and that the Asp mimetic is usually a standard carboxylic acid

Published on 17 February 2020 on https://pubs.rsc.org | d

Applicant

Patent no.

Indications

Exemplar molecule

Integrin target

GlaxoSmithKline

WO2014/154725

IPF

αvβ6

GlaxoSmithKline

WO2016/046226

Fibrosis; IPF

αvβ6

Scifluor Life Sciences

WO2016/134223

Fibrosis; Ophthalmological diseases

αvβ3/αvβ5

Saint Louis University

WO2017/117538

Fibrosis

αv integrins

Rockefeller University and Icahn School of Medicine

WO2018/009501

Large range of diseases including fibrosis

αvβ3

Pliant Therapeutics

WO2018/049068

Fibrosis; liver fibrosis; renal fibrosis; pulmonary fibrosis

αvβ1

61

(continued)

Targeting the αv Integrins in Fibroproliferative Disease

Table 2.3  Selected  αv integrin patent literature with exemplar small molecules.

Published on 17 February 2020 on https://pubs.rsc.org | d

62

Table 2.3  (continued) Pliant Therapeutics

WO2018/119087

Tissue specific fibrosis e.g. IPF

αvβ6

Lazuli/Morphic Therapeutic

WO2018/160522

Various fibrotic diseases

αvβ6

Saint Louis University and WO2018/132268 Indalo Therapeutics

Scleroderma; liver fibrosis; renal fibrosis; pulmonary fibrosis

αv integrins

Bristol-­Myers Squibb

WO2018/089355

Multiple diseases, including pathological fibrosis

αvβ6

Bristol-­Myers Squibb

WO2018/089353

Multiple diseases, including pathological fibrosis

αvβ6

Bristol-­Myers Squibb

WO2018/089357

Multiple diseases, including pathological fibrosis

αv integrins

Chapter 2

Published on 17 February 2020 on https://pubs.rsc.org | d

WO2018/089360

Multiple diseases, including pathological fibrosis

αv integrins

Bristol-­Myers Squibb

WO2018/089358

Multiple diseases, including pathological fibrosis

αvβ6

Bristol-­Myers Squibb

WO2019/094319

Multiple diseases, including pathological fibrosis

αvβ6

Pliant Therapeutics

WO2019/173653

Fibrosis

αvβ1, αvβ6

Targeting the αv Integrins in Fibroproliferative Disease

Bristol-­Myers Squibb

63

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

64

Chapter 2

group. A snapshot of exemplar structures from each of the patents is listed (See Table 2.3) and clearly shows the structural diversity contained in the linker region as previously described. In addition to presenting freedom for patenting purposes, this allows the required properties of the ligand to be installed, whether that be pharmacokinetic, potency, selectivity or to overcome other potential liabilities such as human ether-­a-­go-­go related gene (hERG) activity or solubility. Notably, many of the molecules are reported to be potent at several αv integrins or the wider profile is not reported, which may indicate the difficulty of designing αv inhibitors with all the desired properties in a single molecule. However, it shouldn't be ruled out that multiple integrin activity could be beneficial for treating certain diseases. With the continued growth in this field it is expected that additional patents will be published in the near future.

2.6  Future Potential and Perspectives The past decade has seen an exponential increase in global research interests focussed on αv integrins as therapeutic drug targets, particularly in the fibrosis field. It is evident that, with renewed investment, significant advances have led to a substantial number of patent publications and registration of clinical studies focussing on this integrin class by companies including Bristol-­Myers Squibb, GlaxoSmithKline, Indalo Therapeutics, Merck Research Laboratories, Morphic Therapeutics and Pliant Therapeutics. The race is on to be the first to demonstrate clinical efficacy in a fibrotic indication using integrin inhibitors for therapeutic benefit. The development of drug candidates against this sub-­family of integrins dates back to the 1990s, and despite several early failures in the oncology field targeting αvβ3, it now appears a corner has been turned, raising prospects for success in this target class. Nevertheless, challenges remain, including which αv integrin, or combination, should be targeted for drug development. A further challenge is how to combine the preferred selectivity profile with the physicochemical properties and pharmacokinetic profile enabling sufficient target engagement. This must be accomplished while balancing the potential adverse events associated with inhibiting the TGF-­β pathway, a cytokine that will be required for homeostatic control and normal physiology. When a sub-­family of receptors, such as the αv integrins can carry out the same biological process, in this case the activation of TGF-­β via very similar mechanisms, there is always a concern with redundancy. This is further exacerbated in the case of the αv integrins where TGF-­β controls integrin gene expression and it is not possible to completely exclude the possibility that compensatory mechanisms through alternative integrins may arise following inhibition of a specific TGF-­β-­activating αv integrin. As with most modern drug discovery initiatives, the generation of translational disease systems and biomarkers that can be linked to the clinical setting will be pivotal for successful drug development in the αv integrin field.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

65

Some of the αv integrins themselves could offer prognostic value, for example αvβ6 in IPF,71 whereby imaging of this integrin in patients is being pursued41 to track disease progression. Circulating ECM neoepitope biomarkers are also emerging as potential biomarkers for tracking disease severity over time103,164 in a range of fibrotic diseases.71,165,166 In addition, both approaches could be used as potential enrichment strategies to identify patients that either possess high levels of target expression or have rapidly progressive forms of disease. The absence of readily available specific small molecule and antibody tools for all five αv integrins has been a significant obstacle in pre-­clinical target validation. In some cases, this can lead to the wrong conclusion being drawn. The concentrations of inhibitors used in vitro should be based on accurate selectivity profiling and robust pharmacokinetic assessment to translate findings to a site of action concentration in vivo. In vivo models should be viewed as tools to test early clinical hypotheses, pharmacokinetic and pharmacodynamic relationships or to identify and measure effects on potential translational biomarkers and not be viewed as absolute validation of a target or drug effect in disease. In addition, where ambiguity exists over the contribution of multiple αv integrins in a model, selective inhibitors should be investigated not only individually but also in combination within the same experiment over a number of studies to determine potential additive effects, and in longer studies to endeavour to measure the potential for redundancy. In addition, and although not covered directly as part of this review, there is potential for pro-­fibrotic effects from other integrins not only within the RGD family (α5β1,167 α8β1 168) but also beyond (α3β1,169 α4β1 170), though investigation into these are in their infancy and also likely require the generation of more selective tool inhibitors. If an αv integrin inhibitor can be shown to be safe and efficacious for a fibrotic indication, repositioning in other diseases will probably occur. This could include non-­fibrotic disorders and perhaps a return to testing the αv integrin biological hypothesis in cancer with superior molecules to those available in the past. Regardless, any breakthrough would be greatly welcomed by patients, clinicians and scientific researchers looking to improve the lives of those living with fibrotic diseases of the lung, liver and kidney, where there is still a high unmet medical need.

References 1. T. A. Wynn, J. Clin. Invest., 2007, 117, 524–529. 2. J. Rosenbloom, S. V. Castro and S. A. Jimenez, Ann. Intern. Med., 2010, 152, 159–166. 3. B. M. Klinkhammer, R. Goldschmeding, J. Floege and P. Boor, Adv. Chronic Kidney Dis., 2017, 24, 117–129. 4. B. L. McVicker and R. G. Bennett, Front. Pharmacol., 2017, 8, 318. 5. D. Schuppan, M. Ashfaq-­Khan, A. T. Yang and Y. O. Kim, Matrix Biol., 2018, 68–69, 435–451.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

66

Chapter 2

6. G. Raghu and M. Selman, Am. J. Respir. Crit. Care Med., 2015, 191, 252–254. 7. O. Distler, K. B. Highland, M. Gahlemann, A. Azuma, A. Fischer, M. D. Mayes, G. Raghu, W. Sauter, M. Girard, M. Alves, E. Clerisme-­Beaty, S. Stowasser, K. Tetzlaff, M. Kuwana and T. M. Maher for the SENSCIS Trial Investigators, N. Engl. J. Med., 2019, 380, 2518–2528. 8. C. Margadant and A. Sonnenberg, EMBO Rep., 2010, 11, 97–105. 9. H. Yu, M. Königshoff, A. Jayachandran, D. Handley, W. Seeger, N. Kaminski and O. Eickelberg, FASEB J., 2008, 22, 1778–1789. 10. N. Hagimoto, K. Kuwano, I. Inoshima, M. Yoshimi, N. Nakamura, M. Fujita, T. Maeyama and N. Hara, J. Immunol., 2002, 168, 6470–6478. 11. R. Raghow, A. E. Postlethwaite, J. Keski-­Oja, H. L. Moses and A. H. Kang, J. Clin. Invest., 1987, 4, 1285–1288. 12. R. C. Chambers, P. Leoni, N. Kaminski, G. J. Laurent and R. A. Heller, Am. J. Pathol., 2003, 162, 533–546. 13. P. Bonniaud, P. J. Margetts, M. Kolb, J. A. Schroeder, A. M. Kapoun, D. Damm, A. Murphy, S. Chakravarty, S. Dugar, L. Higgins, A. A. Protter and J. Gauldie, Am. J. Respir. Crit. Care Med., 2005, 171, 889–898. 14. H. Higashiyama, D. Yoshimoto, T. Kaise, S. Matsubara, M. Fujiwara, H. Kikkawa, S. Asano and M. Kinoshita, Exp. Mol. Pathol., 2007, 83, 39–46. 15. J. Zhao, W. Shi, Y. L. Wang, H. Chen, P. Bringas Jr, M. B. Datto, J. P. Frederick, X. F. Wang and D. Warburton, Am. J. Physiol.: Lung Cell. Mol. Physiol., 2002, 282, L585–L593. 16. R. J. Akhurst and A. Hata, Nat. Rev. Drug Discovery, 2012, 11, 790–811. 17. F. A. Millan, F. Denhez, P. Kondaiah and R. J. Akhurst, Development, 1991, 111, 131–143. 18. M. M. Shull, I. Ormsby, A. B. Kier, S. Pawlowski, R. J. Diebold, M. Yin, R. Allen, C. Sidman, G. Proetzel and D. Calvin, Nature, 1992, 359, 693–699. 19. V. Kaartinen, J. W. Voncken, C. Shuler, D. Warburton, D. Bu, N. Heisterkamp and J. Groffen, Nat. Genet., 1995, 11, 415–421. 20. L. P. Sanford, I. Ormsby, A. C. Gittenberger-­de Groot, H. Sariola, R. Friedman, G. P. Boivin, E. L. Cardell and T. Doetschman, Development, 1997, 124, 2659–2670. 21. M. J. Anderton, H. R. Mellor, A. Bell, C. Sadler, M. Pass, S. Powell, S. J. Steele, R. R. Roberts and A. Heier, Toxicol. Pathol., 2011, 39, 916–924. 22. R. J. D. Hatley, S. J. F. Macdonald, R. J. Slack, J. Le, S. B. Ludbrook and P. T. Lukey, Angew. Chem., Int. Ed. Engl., 2018, 57, 3298–3321. 23. B. Wang, B. M. Dolinski, N. Kikuchi, D. R. Leone, M. G. Peters, P. H. Weinreb, S. M. Violette and D. M. Bissell, Hepatology, 2007, 46, 1404–1412. 24. G. S. Horan, S. Wood, V. Ona, D. J. Li, M. E. Lukashev, P. H. Weinreb, K. J. Simon, K. Hahm, N. E. Allaire, N. J. Rinaldi, J. Goyal, C. A. Feghali-­ Bostwick, E. L. Matteson, C. O'Hara, R. Lafyatis, G. S. Davis, X. Huang, D. Sheppard and S. M. Violette, Am. J. Respir. Crit. Care Med., 2008, 177, 56–65.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

67

25. K. Hahm, M. E. Lukashe, Y. Luo, W. J. Yang, B. M. Dolinski, P. H. Weinreb, K. J. Simon, L. Chun Wang, D. R. Leone, R. R. Lobb, D. J. McCrann, N. E. Allaire, G. S. Horan, A. Fogo, R. Kalluri, C. F. Shield 3rd, D. Sheppard, H. A. Gardner and S. M. Violette, Am. J. Pathol., 2007, 170, 110–125. 26. Y. Popov, E. Patsenker, F. Stickel, J. Zaks, K. R. Bhaskar, G. Niedobitek, A. Kolb, H. Friess and D. Schuppan, J. Hepatol., 2008, 48, 453–464. 27. E. Patsenker, Y. Popov, F. Stickel, A. Jonczyk, S. L. Goodman and D. Schuppan, Gastroenterology, 2008, 135, 660–670. 28. Z. W. Peng, N. Ikenaga, S. B. Liu, D. Y. Sverdlov, K. A. Vaid, R. Dixit, P. H. Weinreb, S. Violette, D. Sheppard, D. Schuppan and Y. Popov, Hepatology, 2016, 63, 217–232. 29. N. I. Reed, H. Jo, C. Chen, K. Tsujino, T. D. Arnold, W. F. DeGrado and D. Sheppard, Sci. Transl. Med., 2015, 7, 288ra79. 30. Y. Chang, W. L. Lau, H. Jo, K. Tsujino, L. Gewin, N. I. Reed, A. Atakilit, A. C. F. Nunes, W. F. DeGrado and D. Sheppard, J. Am. Soc. Nephrol., 2017, 28, 1998–2005. 31. D. Cox, M. Brennan and N. Moran, Nat. Rev. Drug Discovery, 2010, 9, 804–820. 32. S. L. Goodman and M. Picard, Trends Pharmacol. Sci., 2012, 33, 405–412. 33. R. K. Coker, G. J. Laurent, S. Shahzeidi, P. A. Lympany, R. M. du Bois, P. K. Jeffery and R. J. McAnulty, Am. J. Pathol., 1997, 150, 981–991. 34. P. Ten Dijke and H. M. Arthur, Nat. Rev. Mol. Cell Biol., 2007, 8, 857–869. 35. S. Schultz-­Cherry, S. Ribeiro, L. Gentry and J. E. Murphy-­Ullrich, J. Biol. Chem., 1994, 269, 26775–26782. 36. R. M. Lyons, J. Keski-­Oja and H. L. Moses, J. Cell Biol., 1988, 106, 1659–1665. 37. M. Wang, D. Zhao, G. Spinetti, J. Zhang, L. Q. Jiang, G. Pintus, R. Monticone and E. G. Lakatta, Arterioscler., Thromb., Vasc. Biol., 2006, 26, 1503–1509. 38. Q. Yu and I. Stamenkovic, Genes Dev., 2000, 14, 163–176. 39. X. Dong, B. Zhao, R. E. Iacob, J. Zhu, A. C. Koksal, C. Lu, J. R. Engen and T. A. Springer, Nature, 2017, 542, 55–59. 40. R. J. Slack, M. Hafeji, R. Rogers, S. B. Ludbrook, J. F. Marshall, D. J. Flint, S. Pyne and J. C. Denyer, Pharmacology, 2016, 97, 114–125. 41. N. Keat, J. Kenny, K. Chen, M. Onega, N. Garman, R. J. Slack, C. A. Parker, R. T. Lumbers, W. Hallett, A. Saleem, J. Passchier and P. T. Lukey, J. Nucl. Med. Technol., 2018, 46, 136–143. 42. C. B. Nanthakumar, R. J. Hatley, S. Lemma, J. Gauldie, R. P. Marshall and S. J. Macdonald, Nat. Rev. Drug Discovery, 2015, 14, 693–720. 43. D. Sheppard, Eur. Respir. Rev., 2008, 17, 157–162. 44. D. Mu, S. Cambier, L. Fjellbirkeland, J. L. Baron, J. S. Munger, H. Kawakatsu, D. Sheppard, V. C. Broaddus and S. L. Nishimura, J. Cell Biol., 2002, 157, 493–507. 45. P. J. Wipff and B. Hinz, Eur. J. Cell Biol., 2008, 87, 601–615.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

68

Chapter 2

46. X. W. Huang, J. F. Wu, D. Cass, D. J. Erle, D. Corry, S. G. Young, R. V. Farese and D. Sheppard, J. Cell Biol., 1996, 133, 921–928. 47. B. L. Bader, H. Rayburn, D. Crowley and R. O. Hynes, Cell, 1998, 95, 507–519. 48. J. Zhu, K. Motejlek, D. Wang, K. Zang, A. Schmidt and L. F. Reichardt, Development, 2002, 129, 2891–2903. 49. P. Aluwihare, Z. Mu, Z. Zhao, D. Yu, P. H. Weinreb, G. S. Horan, S. M. Violette and J. S. Munger, J. Cell Sci., 2009, 122, 227–232. 50. L. E. Stephens, A. E. Sutherland, I. V. Klimanskaya, A. Andrieux, J. Meneses, R. A. Pederson and C. H. Damsky, Genes Dev., 1995, 9, 1883–1895. 51. J. S. Munger, J. G. Harpel, F. G. Giancotti and D. B. Rifkin, Mol. Biol. Cell, 1998, 9, 2627–2638. 52. H. Xia, R. S. Nho, J. Kahm, J. Kleidon and C. A. Henke, J. Biol. Chem., 2004, 279, 33024–33034. 53. L. E. Reynolds, L. Wyder, J. C. Lively, D. Taverna, S. D. Robinson, X. Huang, D. Sheppard, R. O. Hynes and K. M. Hodivala-­Dilke, Nat. Med., 2002, 8, 27–34. 54. V. Sarrazy, A. Koehler, M. L. Chow, E. Zimina, C. X. Li, H. Kato, C. A. Caldarone and B. Hinz, Cardiovasc. Res., 2014, 102, 407–417. 55. D. V. Pechkovsky, A. K. Scaffidi, T. L. Hackett, J. Ballard, F. Shaheen, P. J. Thompson, V. J. Thannickal and D. A. Knight, J. Biol. Chem., 2008, 283, 12898–12908. 56. Y. Asano, H. Ihn, K. Yamane, M. Jinnin, Y. Mimura and K. Tamaki, J. Immunol., 2005, 175, 7708–7718. 57. X. Huang, M. Griffiths, J. Wu, R. V. Farese Jr and D. Sheppard, Mol. Cell. Biol., 2000, 20, 755–759. 58. G. Su, M. Hodnett, N. Wu, A. Atakilit, C. Kosinski, M. Godzich, X. Z. Huang, J. K. Kim, J. A. Frank, M. A. Matthay, D. Sheppard and J. F. Pittet, Am. J. Respir. Cell Mol. Biol., 2007, 36, 377–386. 59. Y. Asano, H. Ihn, K. Yamane, M. Jinnin and K. Tamak, Am. J. Pathol., 2006, 168, 499–510. 60. P. J. Wipff, D. B. Rifkin, J. J. Meister and B. J. Hinz, J. Cell Biol., 2007, 179, 1311–1323. 61. J. M. Breuss, J. Gallo, H. M. DeLisser, I. V. Klimamskaya, H. G. Folkesson, J. F. Pittet, S. L. Nishimura, K. Aldape, D. V. Landers, W. Carpenter, N. Gille, D. Sheppard, M. A. Matthay, S. M. Albelda, R. H. Kramer and R. Pytela, J. Cell Sci., 1995, 108, 2241–2251. 62. N. Ahmed, C. Riley, G. E. Rice, M. A. Quinn and M. S. Baker, J. Histochem. Cytochem., 2002, 50, 1371–1380. 63. G. J. Thomas, M. L. Nyström and J. F. Marshall, J. Oral Pathol. Med., 2006, 35, 1–10. 64. M. Busk, R. Pytela and D. Sheppard, J. Biol. Chem., 1992, 267, 5790–5796. 65. D. Katoh, K. Nagaharu, N. Shimojo, N. Hanamura, M. Yamashita, Y. Kozuka, K. Imanaka-­Yoshida and T. Yoshida, Oncogenesis, 2013, 2, e65.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

69

66. J. J. Worthington, A. Kelly, C. Smedley, D. Bauché, S. Campbell, J. C. Marie and M. A. Travis, Immunity, 2015, 42, 903–915. 67. S. Minagawa, J. Lou, R. I. Seed, A. Cormier, S. Wu, Y. Cheng, L. Murray, P. Tsui, J. Connor, R. Herbst, C. Govaerts, T. Barker, S. Cambier, H. Yanagisawa, A. Goodsell, M. Hashimoto, O. J. Brand, R. Cheng, R. Ma, K. J. McKnelly, W. Wen, A. Hill, D. Jablons, P. Wolters, H. Kitamura, J. Araya, A. J. Barczak, D. J. Erle, L. F. Reichardt, J. D. Marks, J. L. Baron and S. L. Nishimura, Sci. Transl. Med., 2014, 6, 241ra79. 68. M. Boucard-­Jourdin, D. Kugler, M. L. Endale Ahanda, S. This, J. De Calisto, A. Zhang, J. R. Mora, L. M. Stuart, J. Savill, A. Lacy-­Hulbert and H. Paidassi, J. Immunol., 2016, 197, 1968–1978. 69. H. Kitamura, S. Cambier, S. Somanath, T. Barker, S. Minagawa, J. Markovics, A. Goodsell, J. Publicover, L. Reichardt, D. Jablons, P. Wolters, A. Hill, J. D. Marks, J. Lou, J. F. Pittet, J. Gauldie, J. L. Baron and S. L. Nishimura, J. Clin. Invest., 2011, 121, 2863–2875. 70. S. N. Greenhalgh, K. P. Matchett, R. S. Taylor, K. Huang, J. T. Li, K. Saeteurn, M. C. Donnelly, E. E. M. Simpson, J. L. Pollack, A. Atakilit, K. J. Simpson, J. J. Maher, J. P. Iredale, D. Sheppard and N. C. Henderson, Am. J. Pathol., 2019, 189, 258–271. 71. G. Saini, J. Porte, P. H. Weinreb, S. M. Violette, W. A. Wallace, T. M. McKeever and G. Jenkins, Eur. Respir. J., 2015, 46, 486–494. 72. J. S. Munger, X. Huang, H. Kawakatsu, M. J. D. Griffiths, S. L. Dalton, J. Wu, J. Pittet, N. Kaminski, C. Garat, M. A. Matthay, D. B. Rifkin and D. Sheppard, Cell, 1999, 96, 319–328. 73. P. H. Weinreb, K. J. Simon, P. Rayhorn, W. J. Yang, D. R. Leone, B. M. Dolinski, B. R. Pearse, Y. Yokota, H. Kawakatsu, A. Atakilit, D. Sheppard and S. M. Violette, J. Biol. Chem., 2004, 279, 17875–17887. 74. K. Puthawala, N. Hadjiangelis, S. C. Jacoby, E. Bayongan, Z. Zhao, Z. Yang, M. L. Devitt, G. S. Horan, P. H. Weinreb, M. E. Lukashev, S. M. Violette, K. S. Grant, C. Colarossi, S. C. Formenti and J. S. Munger, Am. J. Respir. Crit. Care Med., 2008, 177, 82–90. 75. M. Decaris, J. Schaub, C. Chen, J. Cha, G. Lee, M. Rexhepaj, V. Rao, P. Kotak, L. Hooi, J. Wu, S. Martin, T. Chen, M. Munoz, T. Hom, K. Leftheris, D. Morgans, S. Turner and P. Andre, Am. J. Respir. Crit. Care Med., 2019, 199, A5875. 76. N. C. Henderson, T. D. Arnold, Y. Katamura, M. M. Giacomini, J. D. Rodriguez, J. H. McCarty, A. Pellicoro, E. Raschperger, C. Betsholtz, P. G. Ruminski, D. W. Griggs, M. J. Prinsen, J. J. Maher, J. P. Iredale, A. Lacy-­Hulbert, R. H. Adams and D. Sheppard, Nat. Med., 2013, 19, 1617–1624. 77. B. Hellmich, M. Schellner, H. Schatz and A. Pfeiffer, Metabolism, 2000, 49, 353–359. 78. M. D. Breyer and K. Susztak, Nat. Rev. Drug Discovery, 2016, 15, 568–588. 79. E. E. Gerber, E. M. Gallo, S. C. Fontana, E. C. Davis, F. M. Wigley, D. L. Huso and H. C. Dietz, Nature, 2013, 503, 126–130.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

70

Chapter 2

80. G. L. Bagnato, N. Irrera, G. Pizzino, D. Santoro, W. N. Roberts, G. Bagnato, G. Pallio, M. Vaccaro, F. Squadrito, A. Saitta, D. Altavilla and A. Bitto, Clin. Sci., 2018, 132, 231–242. 81. E. R. Hall and R. J. Slack, Biomed. Pharmacother., 2019, 110, 362–370. 82. J. E. Rowedder, S. B. Ludbrook and R. J. Slack, SLAS Discovery, 2017, 22, 962–973. 83. A. L. Wilkinson, J. W. Barrett and R. J. Slack, Eur. J. Pharmacol., 2019, 842, 239–247. 84. W. Wang, Q. Wu, M. Pasuelo, J. S. McMurray and C. Li, Bioconjugate Chem., 2005, 16, 729–734. 85. S. H. Hausner, D. DiCara, J. Marik, J. F. Marshall and J. L. Sutcliffe, Cancer Res., 2007, 67, 7833–7840. 86. Y. Cheng and W. H. Prusoff, Biochem. Pharmacol., 1973, 22, 3099–3108. 87. P. A. Procopiou, N. A. Anderson, J. Barrett, T. N. Barrett, M. H. J. Crawford, B. J. Fallon, A. P. Hancock, J. Le, S. Lemma, R. P. Marshall, J. Morrell, J. M. Pritchard, J. E. Rowedder, P. Saklatvala, R. J. Slack, S. L. Sollis, C. J. Suckling, L. R. Thorp, G. Vitulli and S. J. F. Macdonald, J. Med. Chem., 2018, 61, 8417–8443. 88. J. W. Williams and J. F. Morrison, Methods Enzymol., 1979, 63, 437–467. 89. S. Roesch, T. Lindner, M. Sauter, A. Loktev, P. Flechsig, M. Muller, W. Mier, R. Warta, G. Dyckhoff, C. Herold-­Mende, U. Haberkorn and A. Altmann, J. Nucl. Med., 2018, 59, 1679–1685. 90. F. Schiele, P. Ayaz and A. Fernández-­Montalván, Anal. Biochem., 2015, 468, 42–49. 91. M. Y. Xu, J. Porte, A. J. Knox, P. H. Weinreb, T. M. Maher, S. M. Violette, R. J. McAnulty, D. Sheppard and G. Jenkins, Am. J. Pathol., 2009, 174, 1264–1279. 92. M. Abe, J. G. Harpel, C. N. Metz, I. Nunes, D. J. Loskutoff and D. B. Rifkin, Anal. Biochem., 1994, 216, 276–284. 93. M. M. Giacomini, M. A. Travis, M. Kudo and D. Sheppard, Exp. Cell Res., 2012, 318, 716–722. 94. O. S. Qureshi, H. Bon, B. Twomey, G. Holdsworth, K. Ford, M. Bergin, L. Huang, M. Muzylak, L. J. Healy, V. Hurdowar and T. S. Johnson, Biol. Open., 2017, 6, 1423–1433. 95. H. Bon, P. Hales, S. Lumb, G. Holdsworth, T. Johnson, O. Qureshi and B. M. Twomey, Nephron, 2019, 142, 328–350. 96. L. A. van Grunsven, Adv. Drug Delivery Rev., 2017, 121, 133–146. 97. S. Castel, R. Pagan, F. Mitjans, J. Piulats, S. Goodman, A. Jonczyk, F. Huber, S. Vilaró and M. Reina, Lab. Invest., 2001, 81, 1615–1626. 98. K. Temming, R. M. Schiffelers, G. Molema and R. J. Kok, Drug Resist. Updates, 2005, 8, 381–402. 99. A. Saha, D. Ellison, G. J. Thomas, S. Vallath, S. J. Mather, I. R. Hart and J. F. Marshall, J. Pathol., 2010, 222, 52–63. 100. E. Gower, A. L. Wilkinson, V. Morrison, C. B. Nanthakumar and R. J. Slack, QJM, 2016, 109(S59), P109.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

71

101. G. J. Thomas, I. R. Hart, P. M. Speight and J. F. Marshall, Br. J. Cancer, 2002, 87, 859–867. 102. P. Olinga and D. Schuppan, J. Hepatol., 2013, 58, 1252–1253. 103. P. F. Mercer, H. V. Woodcock, J. D. Eley, M. Platé, M. G. Sulikowski, P. F. Durrenberger, L. Franklin, C. B. Nanthakumar, Y. Man, F. Genovese, R. J. McAnulty, S. Yang, T. M. Maher, A. G. Nicholson, A. D. Blanchard, R. P. Marshall, P. T. Lukey and R. C. Chambers, Thorax, 2016, 71, 701–711. 104. E. G. D. Stribos, T. Luangmonkong, A. M. Leliveld, I. J. de Jong, W. J. van Son, J. L. Hillebrands, M. A. Seelen, H. van Goor, P. Olinga and H. A. M. Mutsaers, Transl. Res., 2016, 170, 8–16e1. 105. H. L. Paish, L. H. Reed, H. Brown, M. C. Bryan, O. Govaere, J. Leslie, B. S. Barksby, M. Garcia Macia, A. Watson, X. Xu, M. Y. W. Zaki, L. Greaves, J. Whitehall, J. French, S. A. White, D. M. Manas, S. M. Robinson, G. Spoletini, C. Griffiths, D. A. Mann, L. A. Borthwick, M. J. Drinnan, J. Mann and F. Oakley, Hepatology, 2019, 70, 1377–1391. 106. M. Lehmann, L. Buhl, H. N. Alsafadi, S. Klee, S. Hermann, K. Mutze, C. Ota, M. Lindner, J. Behr, A. Hilgendorff, D. E. Wagner and M. Königshoff, Respir. Res., 2018, 19, 175. 107. T. Denayer, T. Stöhr and M. Van Roy, New Horiz. Transl. Med., 2014, 2, 5–11. 108. I. W. Y. Mak, N. Evaniew and M. Ghert, Am. J. Transl. Res., 2014, 6, 114–118. 109. N. R. Grande, M. N. D. Peão, C. M. de Sá and A. P. Águas, Scanning Microsc., 1998, 12, 487–494. 110. A. Moeller, K. Ask, D. Warburton, J. Gauldie and M. Kolb, Int. J. Biochem. Cell Biol., 2008, 40, 362–382. 111. C. J. Scotton and R. C. Chambers, Am. J. Physiol.: Lung Cell. Mol. Physiol., 2010, 299, L439–L441. 112. H. Oku, T. Shimizu, T. Kawabata, M. Nagira, I. Hikita, A. Ueyama, S. Matsushima, M. Torii and A. Arimura, Eur. J. Pharmacol., 2008, 590, 400–408. 113. L. Wollin, I. Maillet, V. Quesniaux, A. Holweg and B. Ryffel, J. Pharmacol. Exp. Ther., 2014, 349, 209–220. 114. L. Fregonese and I. Eichler, BMC Med., 2015, 13, 239. 115. R. G. Jenkins, B. B. Moore, R. C. Chambers, O. Eickelberg, M. Königshoff, M. Kolb, G. J. Laurent, C. B. Nanthakumar, M. A. Olman, A. Pardo, M. Selman, D. Sheppard, P. J. Sime, A. M. Tager, A. L. Tatler, V. J. Thannickal, E. S. White and ATS Assembly on Respiratory Cell and Molecular Biology, Am. J. Respir. Cell Mol. Biol., 2017, 56, 667–679. 116. K. Atabai, S. Jame, N. Azhar, A. Kuo, M. Lam, W. McKleroy, G. Dehart, S. Rahman, D. D. Xia, A. C. Melton, P. Wolters, C. L. Emson, S. M. Turner, Z. Werb and D. Sheppard, J. Clin. Invest., 2009, 119, 3713–3722. 117. P. J. Sime, Z. Xing, F. L. Graham, K. G. Csaky and J. Gauldie, J. Clin. Invest., 1997, 100, 768–776. 118. F. A. Mamuya and M. K. Duncan, J. Cell. Mol. Med., 2012, 16, 445–455.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

72

Chapter 2

119. A. R. Froese, C. Shimbori, P. S. Bellaye, M. Inman, S. Obex, S. Fatima, G. Jenkins, J. Gauldie, K. Ask and M. Kolb, Am. J. Respir. Crit. Care Med., 2016, 194, 84–96. 120. S. C. Yanguas, B. Cogliati, J. Willebrords, M. Maes, I. Colle, B. van den Bossche, C. P. M. S. de Oliveira, W. Andraus, V. A. F. Alves, I. Leclercq and M. Vinken, Arch. Toxicol., 2016, 90, 1025–1048. 121. E. Patsenker, Y. Popov, F. Stickel, V. Schneider, M. Ledermann, H. Sägesser, G. Niedobitek, S. L. Goodman and D. Schuppan, Hepatology, 2009, 50, 1501–1511. 122. B. Ulmasov, H. Noritake, P. Carmichael, K. Oshima, D. W. Griggs and B. A. Neuschwander-­Tetri, Hepatol. Commun., 2019, 3, 246–261. 123. L. J. Ma, H. Yang, A. Gaspert, G. Carlesso, M. M. Barty, J. M. Davidson, D. Sheppard and A. B. Fogo, Am. J. Pathol., 2003, 163, 1261–1273. 124. X. Zhou, J. Zhang, R. Haimbach, W. Zhu, R. Mayer-­Ezell, M. Garcia-­ Calvo, E. Smith, O. Price, Y. Kan, E. Zycband, Y. Zhu, M. Hoek, J. M. Cox, L. Ma, D. E. Kelley and S. Pinto, Pharmacol. Res. Perspect., 2017, 5, e00354. 125. B. Ulmasov, B. A. Neuschwander-­Tetri, J. Lai, V. Monastyrskiy, T. Bhat, M. P. Yates, J. Oliva, M. J. Prinsen, P. G. Ruminski and D. W. Griggs, Cell. Mol. Gastroenterol. Hepatol., 2016, 2, 499–518. 126. I. R. Murray, et al., Nat. Commun., 2017, 8, 1118. 127. M. Pickarski, A. Gleason, B. Bednar and L. T. Duong, Oncol. Rep., 2015, 33, 2737–2745. 128. J. H. Hutchinson, W. Halczenko, K. M. Brashear, M. J. Breslin, P. J. Coleman, L. T. Duong, C. Fernandez-­Metzler, M. A. Gentile, J. E. Fisher, G. D. Hartman, J. R. Huff, D. B. Kimmel, C. Leu, R. S. Meissner, K. Merkle, R. Nagy, B. Pennypacker, J. J. Perkins, T. Prueksaritanont, G. A. Rodan, S. L. Varga, G. A. Wesolowski, A. E. Zartman, S. B. Rodan and M. E. Duggan, J. Med. Chem., 2003, 46, 4790–4798. 129. D. A. D. Wilk, M. S. Scicchitano and D. Morel, Toxicol. In Vitro, 2013, 27, 272–281. 130. C. Mas-­Moruno, F. Rechenmacher and H. Kessler, Anticancer Agents Med. Chem., 2010, 10, 753–768. 131. M. A. Buerkle, S. A. Pahernik, A. Sutter, A. Jonczyk, K. Messmer and M. Dellian, Br. J. Cancer, 2002, 86, 788–795. 132. J. M. Albert, C. Cao, L. Geng, L. Leavitt, D. E. Hallahan and B. Lu, Int. J. Radiat. Oncol., Biol., Phys., 2006, 65, 1536–1543. 133. M. G. Murphy, K. Cerchio, S. A. Stoch, K. Gottesdiener, M. Wu and R. Recker, J. Clin. Endocrinol. Metab., 2005, 90, 2022–2028. 134. B. C. Askew, T. Furuya and D. S. Edwards, J. Pharmacol. Exp. Ther., 2018, 366, 244–250. 135. G. A. Cirkel, B. M. Kerklaan, F. Vanhoutte, A. Van der Aa, G. Lorenzon, F. Namour, P. Pujuguet, S. Darquenne, F. Y. F. de Vos, T. J. Snijders, E. E. Voest, J. H. M. Schellens and M. P. Lolkema, Invest. New Drugs, 2016, 34, 184–192.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

73

136. E. Élez, I. Kocáková, T. Höhler, U. M. Martens, C. Bokemeyer, E. Van Cutsem, B. Melichar, M. Smakal, T. Csőszi, E. Topuzov, R. Orlova, S. Tjulandin, F. Rivera, J. Straub, R. Bruns, S. Quaratino and J. Tabernero, Ann. Oncol., 2015, 26, 132–140. 137. M. Hussain, S. Le Moulec, C. Gimmi, R. Bruns, J. Straub and K. Miller, Clin. Cancer Res., 2016, 22, 3192–3200. 138. M. Arefayene, M. Mouded, C. Stebbins, G. Zhao, G. Song, R. Christmann, S. Violette and D. Gallagher, Eur. Respir. J., 2018, 52(Suppl. 62), PA596. 139. G. Raghu, M. Mouded, D. A. Culver, M. J. Hamblin, J. A. Golden, S. Veeraraghavan, R. I. Enelow, L. H. Lancaster, H. J. Goldberg, A. E. Frost, L. C. Ginns, B. J. Maroni, D. Sheppard, N. Kaminski, I. O. Rosas, M. Arjomandi, A. Prasse, C. Stebbins, G. Zhao, G. Song, M. Arefayene, R. Christmann de Souza, S. M. Violette, D. C. Gallagher and K. F. Gibson, Am. J. Respir. Crit. Care Med., 2018, 197, A7785. 140. C. H. Maden, D. Fairman, M. Chalker, M. J. Costa, W. A. Fahy, N. Garman, P. T. Lukey, T. Mant, S. Parry, J. K. Simpson, R. J. Slack, S. Kendrick and R. P. Marshall, Eur. J. Clin. Pharmacol., 2018, 74, 701–709. 141. O. S. Usmani, M. F. Biddiscombe, S. Yang, S. Meah, E. Oballa, J. K. Simpson, W. A. Fahy, R. P. Marshall, P. T. Lukey and T. M. Maher, Respir. Res., 2018, 19, 25. 142. https://w w w.prnewswire.com/news-­r eleases/pliant-­t herapeutics-­ initiates-­phase-­1-­clinical-­study-­of-­pln-­74809-­300772187.html. 143. E. R. Hall, L. I. Bibby and R. J. Slack, Biochem. Pharmacol., 2016, 117, 88–96. 144. https://www.biospace.com/article/gsk-­cuts-­six-­respiratory-­assets-­as-­it-­ continues-­to-­focus-­on-­oncology-­treatments/. 145. M. Decaris, J. Schaub, C. Chen, J. Cha, G. Lee, M. Rexhepaj, V. Rao, P. Kotak, L. Hooi, J. Wu, S. Martin, T. Chen, M. Munoz, T. Hom, K. Leftheris, D. Morgans, S. Turner and P. Andre, Am. J. Respir. Crit. Care Med., 2019, 199, A5875. 146. O. V. Maltsev, U. K. Marelli, T. G. Kapp, F. S. Di Leva, S. Di Maro, M. Nieberler, U. Reuning, M. Schwaiger, E. Novellino, L. Marinelli and H. Kessler, Angew. Chem., Int. Ed. Engl., 2016, 55, 1535–1539. 147. F. S. Di Leva, S. Tomassi, S. Di Maro, F. Reichart, J. Notni, A. Dangi, U. K. Marelli, D. Brancaccio, F. Merlino, H. J. Wester, E. Novellino, H. Kessler and L. Marinelli, Angew. Chem., Int. Ed. Engl., 2018, 57, 14645–14649. 148. F. Reichart, O. V. Maltsev, T. G. Kapp, A. F. B. Räder, M. Weinmüller, U. K. Marelli, J. Notni, A. Wurzer, R. Beck, H. J. Wester, K. Steiger, S. Di Maro, F. S. Di Leva, L. Marinelli, M. Nieberler, U. Reuning, M. Schwaiger and H. J. Kessler, J. Med. Chem., 2019, 62, 2024–2037. 149. https://w w w.prnewswire.com/news-­r eleases/pliant-­t herapeutics-­ reports-p ­ o s i t i v e - ­r e s ul t s - ­o f - ­p h a s e - ­1 - ­c l in i c a l - ­s t u d y - ­s u p p o r t a d v a n c e m e n t - ­o f - ­p l n - ­7 4 8 0 9 - ­f o r - ­i d i o p a t h i c - ­p u l m o n a r y -­ fibrosis-­300827597.html.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

74

Chapter 2

150. X. Dong, N. E. Hudson, C. Lu and T. A. Springer, Nat. Struct. Mol. Biol., 2014, 21, 1091–1096. 151. J. Takagi, B. M. Petre, T. Walz and T. A. Springer, Cell, 2002, 110, 599–611. 152. T. A. Springer and M. L. Dustin, Curr. Opin. Cell Biol., 2012, 24, 107–115. 153. T. G. Kapp, F. Rechenmacher, S. Neubauer, O. V. Maltsev, E. A. Cavalcanti-­ Adam, R. Zarka, U. Reuning, J. Notni, H. J. Wester, C. Mas-­Moruno, J. Spatz, B. Geiger and H. Kessler, Sci. Rep., 2017, 7, 39805. 154. C. A. Fitch, G. Platzer, M. Okon, E. B. Garcia-­Moreno and L. P. McIntosh, Protein Sci., 2015, 24, 752–761. 155. M. Nagae, S. Re, E. Mihara, T. Nogi, Y. Sugita and J. Takagi, J. Cell Biol., 2012, 197, 131–140. 156. J. P. Xiong, T. Stehle, R. Zhang, A. Joachimiak, M. Frech, S. L. Goodman and M. A. Arnaout, Science, 2002, 296, 151–155. 157. M. E. Duggan, L. T. Duong, J. E. Fisher, T. G. Hamill, W. F. Hoffman, J. R. Huff, N. C. Ihle, C. T. Leu, R. M. Nagy, J. J. Perkins, S. B. Rodan, G. Wesolowski, D. B. Whitman, A. E. Zartman, G. A. Rodan and G. D. Hartman, J. Med. Chem., 2000, 43, 3736–3745. 158. J. Adams, E. C. Anderson, E. Blackham, Y. RyanChiu, T. Clarke, N. Eccles, L. A. Gill, J. J. Haye, H. T. Haywood, C. R. Hoenig, H. L. Russell, C. Smedley, W. J. Tipping, T. Tongue, C. C. Wood, J. Yeung, J. E. Rowedder, M. J. Fray, T. McInally and S. J. F. Macdonald, ACS Med. Chem. Lett., 2014, 5, 1207–1212. 159. D. Cui, R. Subramanian, M. Shou, X. Yu, M. A. Wallace, M. P. Braun, B. H. Arison, J. A. Yergey and T. Prueksaritanont, Drug Metab. Dispos., 2004, 32, 848–861. 160. M. J. Bailey and R. G. Dickinson, Chem.-­Biol. Interact., 2003, 145, 117–137. 161. L. M. Miller, J. M. Pritchard, S. J. F. Macdonald, C. Jamieson and A. J. B. Watson, J. Med. Chem., 2017, 60, 3241–3251. 162. J. Zhu, W. S. Choi, J. G. McCoy, A. Negri, J. Zhu, S. Naini, J. Li, M. Shen, W. Huang, D. Bougie, M. Rasmussen, R. Aster, C. J. Thomas, M. Filizola, T. A. Springer and B. S. Coller, Sci. Transl. Med., 2012, 4, 125ra32. 163. J. Li, S. Vootukuri, Y. Shang, A. Negri, J. Jiang, M. Nedelman, T. G. Diacovo, M. Filizola, C. J. Thomas and B. S. Coller, Arterioscler., Thromb., Vasc. Biol., 2014, 34, 2321–2329. 164. C. B. Nanthakumar, J. D. Eley, Y. Man, N. S. Gudmann, R. C. Chambers, A. Blanchard, W. Fahy and T. M. Maher, Am. J. Respir. Crit. Care Med., 2019, 199, A7301. 165. D. G. K. Rasmussen, A. Fenton, M. Jesky, C. Ferro, P. Boor, M. Tepel, M. A. Karsdal, F. Genovese and P. Cockwell, Sci. Rep., 2017, 7, 17328. 166. M. A. Karsdal, S. T. Hjuler, Y. Luo, D. G. K. Rasmussen, M. J. Nielsen, S. Holm Nielsen, D. J. Leeming, Z. Goodman, R. H. Arch, K. Patel and D. Schuppan, Am. J. Physiol.: Gastrointest. Liver Physiol., 2019, 316, G25–G31.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00037

Targeting the αv Integrins in Fibroproliferative Disease

75

167. T. Van Bergen, G. Zahn, P. Caldirola, M. Fsadni, N. Caram-­Lelham, E. Vandewalle, L. Moons and I. Stalmans, Invest. Ophthalmol. Visual Sci., 2016, 57, 6428–6439. 168. G. Volkert, A. Jahn, C. Dinkel, F. Fahlbusch, C. Zürn, K. F. Hilgers, W. Rascher, A. Hartner and I. Marek, Cell Commun. Adhes., 2014, 21, 89–98. 169. K. K. Kim, Y. Wei, C. Szekeres, M. C. Kugler, P. J. Wolters, M. L. Hill, J. A. Frank, A. N. Brumwell, S. E. Wheeler, J. A. Kreidberg and H. A. Chapman, J. Clin. Invest., 2009, 119, 213–224. 170. Q. Wang, Y. Wang, D. M. Hyde, P. J. Gotwals, R. R. Lobb, S. T. Ryan and G. N. Giri, Biochem. Pharmacol., 2000, 60, 1949–1958.

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Chapter 3

Discovery, Structural Refinement and Therapeutic Potential of Farnesoid X Receptor Activators Christina Lamersa and Daniel Merk*b,c a

University Basel, Molecular Pharmacy, Klingelberstr. 50, CH-­4056 Basel, Switzerland; bGoethe University Frankfurt, Institute of Pharmaceutical Chemistry, Max-­von-­Laue-­Str. 9, D-­60438 Frankfurt, Germany; cSwiss Federal Institute of Technology (ETH) Zurich, Institute of Pharmaceutical Sciences, Vladimir-­Prelog-­Weg 4, CH-­8093 Zurich, Switzerland *E-­mail: [email protected]­frankfurt.de

3.1  Introduction The farnesoid X receptor (FXR, NR1H4)1–4 is a bile acid activated transcription factor and a key regulator of metabolism.5–8 The nuclear receptor displays high expression in liver, intestine and kidney but is also found in several other organs and tissues. Physiologically, FXR acts as cellular bile acid sensor and is activated by the bile acids chenodeoxycholic acid (CDCA, 1.1), cholic acid and deoxycholic acid.9 With a concentration giving half of the maximal response (EC50) value of 8.66 µM in a fluorescence resonance energy transfer (FRET)-­based assay, CDCA (1.1)6 is the most potent endogenous FXR activator known to date. Cholic acid and deoxycholic acid are weak FXR agonists.9–11   Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

76

View Online

Discovery, Structural Refinement and Therapeutic Potential

77

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

3.1.1  Structure and Activation Mechanism of FXR FXR has the typical architecture of nuclear receptors and is composed of several domains that fulfil different functions.8,12 FXR's N-­terminal end comprises the ligand-­independent activation function 1 (AF-­1) containing motifs for post-­translational modifications such as phosphorylation13,14 and addition of small ubiquitin-­like modifier (SUMOylation).15 While some reports ascribe this region importance in FXR activity, its role in FXR targeting drug discovery remains to be defined. The AF-­1 region is followed by the DNA binding domain (DBD) that mediates the interaction of FXR with the promoter regions of its target genes. The DBD contains two conserved zinc-­finger motifs and recognizes specific DNA sequences termed FXR response elements (RE). Via a flexible hinge region, the DBD is connected to the ligand binding domain (LBD) comprising 11 α-­helices arranged in three layers sometimes described as a “sandwich-­fold”. The C-­terminal end of FXR is unordered in absence of a ligand and constitutes the ligand-­dependent activation function 2 (AF-­2). Agonist binding to the FXR LBD induces conformational changes that form a binding surface at the LBD where the AF-­2 is stabilized as an α-­helix, also considered as helix 12 of the LBD.16,17 FXR can act as monomer and as homodimer but most of its activity is mediated by heterodimers with a retinoid X receptor (RXR) as heterodimer partner. These FXR–RXR heterodimers are permissive, meaning that gene transcription can be induced by agonists of either partner receptor and activation of both partners may induce synergistic efficacy. Dimerization between FXR and RXR is mainly mediated via helix 11 of both receptors with minor contributions from neighboring residues from helices 7 and 9 as well as the loops connecting helices 8 with 9 and 9 with 10.18 In the inactive state, i.e. in the absence of an agonistic ligand, FXR, respectively the FXR–RXR heterodimer, is bound to co-­repressor proteins19 such as nuclear co-­repressor (NCoR)20 and dosage-­sensitive sex reversal, adrenal hypoplasia critical region, on chromosome X, gene 1 (DAX1)21 that prevent the transcription of FXR-­regulated genes. Upon agonist binding, conformational changes leading to stabilization of AF-­2 at the core of the LBD also promote the release of co-­repressor proteins. The active FXR–LBD conformation with stabilized AF-­2 offers a mostly lipophilic binding surface formed by residues of helices 3, 4, 5 and 12 for co-­activator proteins.18,19,22 Direct interaction of FXR has, for example, been shown for the co-­activators steroid receptor co-­ activator 1 (SRC-­1),23 vitamin D receptor interacting protein (DRIP),24 peroxisome proliferator-­activated receptor gamma coactivator 1-­alpha (PGC-­1α),25 co-­activator-­associated arginine methyltransferase 1 (CARM1),26 protein arginine methyltransferase 1 (PRMT1),27 and p300 acetylase.28 Binding of the co-­activators is partly mediated by a so-­called charge clamp between Lys303 (helix 3 of the FXR–LBD) and Glu467 (helix 12/AF-­2 of FXR) holding a dipolar α-­helix of the co-­activator protein. Upon co-­activator binding, the full gene transcription machinery can be recruited and FXR-­regulated gene expression is induced.19

View Online

78

Chapter 3

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

3.1.2  FXR in (Patho)physiology FXR's key physiological role is the regulation of bile acid homeostasis. Therein, high (intracellular) levels of potentially toxic bile acids activate the nuclear receptor which in turn via two independent pathways [small heterodimer partner (SHP) and fibroblast growth factor 19 (FGF19)–fibroblast growth factor receptor 4 (FGFR4)] blocks the de novo synthesis of bile acids from cholesterol by repression of cholesterol 7α-­hydroxylase (CYP7A1). In addition, FXR activation promotes transport of bile acids from the liver to the bile by inducing various bile acid transport proteins. With these activities, FXR acts as important liver protector.29 Besides its key regulatory role in bile acid homeostasis,7,9,29,30 FXR is also involved in lipid and glucose metabolism. The majority of the metabolic effects caused by FXR activation are mediated via induction of the two key FXR-­regulated genes SHP and FGF19. SHP31,32 is an uncommon nuclear receptor that lacks a DBD and seems to exhibit its effects by direct interaction with other (ligand-­activated) transcription factors. Amongst many other effects, SHP suppresses CYP7A1 and sterol regulatory element binding protein 1c (SREBP1c) expression. SREBP1c in turn is an important regulator of lipid and glucose metabolism.33–35 FGF19 36–38 (the murine homolog is FGF15) is mainly induced by FXR in the intestine from where it enters circulation. FGF19 as an important endocrine signaling molecule of the gut–liver axis of FXR activity subsequently activates FGFR4 in liver and white adipose tissue. FGFR4 activation in the liver also causes repression of CYP7A1. Some reports have also ascribed a direct anti-­inflammatory activity by modulating nuclear factor κB (NF-­κB) to FXR in a so-­called tethering trans­ repression.39–41 FXR is capable of inhibiting the transcription of NF-­κB responsive genes by preventing the recruitment of p65 to the DNA. Thereby, FXR activation with obeticholic acid (OCA)41 or specific FXR modulation with mometasone furoate40 led to anti-­inflammatory effects with reduced expression of inflammatory genes. Recent data indicates40 that FXR-­ mediated alterations in CYP expression and in arachidonic acid metabolism are involved in these anti-­inflammatory effects. In a rodent model of inflammatory bowel disease, FXR activation reduced inflammation and preserved the intestinal barrier function.42 Further studies on the role of FXR in IBD found reduced ileal FXR activity in a subpopulation of IBD patients but no association with FXR polymorphisms.43 Moreover, reduced FXR and FGF15/19 signaling in IBD has been linked to alterations in bile acid homeostasis in intestinal cells.44 So far, clinical trials of FXR agonists have mainly focused on therapeutic efficacy in primary biliary cholangitis (PBC) as well as non-­alcoholic steatohepatitis (NASH) and results from clinical trials which allow an estimation of FXR's value as a drug target have almost exclusively been published for OCA. Several other FXR agonists have been studied in clinical trials (Table 3.1) but little has been reported about their performance so far.

View Online

Discovery, Structural Refinement and Therapeutic Potential

79

Table 3.1  FXR  ligands in clinical development.

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Name

Structure

Disease/ Progress

Obeticholic acid (OCA)

Approved for PBC Phase III for NASH Phase II for primary sclerosing cholangitis

INT-­767

Phase I

EDP-­305

Unknown (steroidal)

Phase I

Tropifexor (LNJ-­452)

Phase II for PBC Phase II for NASH

Px-­104

Phase II

GS-­9674

Phase II for PBC Phase II for NASH Phase II for primary sclerosing cholangitis

Three clinical trials45–47 have confirmed the therapeutic efficacy of OCA in PBC. Initially, the experimental drug was studied in double-­blind, randomized, placebo-­controlled trials alone or as add-­on therapy to ursodeoxycholic acid (UDCA) in PBC patients with inadequate response to UDCA. OCA was

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

80

Chapter 3

superior to placebo and improved liver health, as measured by plasma levels of the liver enzymes alkaline phosphatase (ALP), alanine aminotransferase (ALT) and γ-­glutamyl transferase (GGT) as well as bilirubin levels. The studies revealed no differences in non-­invasive markers of fibrosis. Safety of the study drug in the trials was acceptable, with dose-­dependent pruritus as common adverse effect. In 2016, OCA was approved by the Food and Drug Administration (FDA) as combination therapy with UDCA for PBC patients with inadequate response to UDCA or as monotherapy for patients unable to tolerate UDCA. Clinical development of OCA for the metabolic liver diseases non-­ alcoholic fatty liver (NAFL) and non-­alcoholic steatohepatitis (NASH) is also very advanced already. The first promising effects of the experimental drug in metabolic diseases were observed in a double-­blind, placebo-­controlled, proof-­of-­concept study48 in type 2 diabetes patients with NAFL. OCA improved insulin sensitivity, reduced levels of ALT and GGT and caused weight-­loss. Lower levels of circulating bile acids and induction of FGF19 indicated that OCA activated FXR. No safety issues occurred but increased low-­density lipoprotein cholesterol (LDL-­c) levels already indicated adverse effects on cholesterol balance. OCA was then studied in patients with histologically proven, non-­cirrhotic NASH.49 The bile acid derivative showed beneficial effects on various biochemical markers of liver health and significantly improved the NAFL activity score (NAS) in liver biopsies compared with placebo, which was mainly due to reduced steatosis and less hepatocyte damage. There was also a slight improvement in hepatic fibrosis and inflammation and patients receiving the study drug showed a slight reduction in body weight. OCA was again associated with moderate to severe pruritus and additionally caused unfavorable effects on cholesterol homeostasis. Although safety and long-­ term efficacy remain to be assessed,49 the therapeutic efficacy of OCA in clinical trials for liver diseases has validated FXR as a very valuable drug target for metabolic diseases.

3.1.3  FXR and Fibrosis With its liver-­protective and anti-­inflammatory activity, FXR holds particular potential as a molecular target to prevent or treat hepatic fibrosis. Accordingly, several studies have evaluated the application of FXR activators in experimental liver fibrosis animal models. Early reports have established an important role of the FXR–SHP axis in hepatic stellate cells.50 In chronic liver disease, activated hepatic stellate cells secrete extracellular matrix proteins as well as tissue inhibitors of metalloproteinases (TIMPs) and, thus, strongly contribute to liver fibrosis as major source of extracellular matrix in liver. In several hepatic fibrosis models such as porcine serum induced hepatic fibrosis,50 bile duct ligation induced hepatic fibrosis,50 thioacetamide induced hepatic fibrosis39 and melanocortin 4 receptor knockout,51 FXR activation with OCA effectively protected against liver fibrosis development, validating FXR as an anti-­fibrotic therapeutic

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

81

target. The encouraging data for hepatic fibrosis also led to several in vivo studies evaluating the receptor's potential role in other fibrotic diseases: FXR activators revealed promising anti-­fibrotic effects in models of renal fibrosis52,53 and diabetic nephropathy,54,55 and even in bleomycin-­induced pulmonary fibrosis.56

3.2  Targeting FXR FXR targeted drug discovery started with identification of the receptor and bile acids as its endogenous ligands. Several synthetic, non-­steroidal FXR agonist scaffolds such as the isoxazole series (GW4064),57 fexaramine22 and analogues, azepino[4,5-­b]indoles (WAY362450)58 and benzimidazoles59,60 were soon developed and potent pharmacological tools became available for in vitro and in vivo studies. In parallel, OCA was soon discovered as a significantly optimized steroidal FXR agonist. After this early hype, the number of new FXR ligand chemotypes discovered dropped significantly and FXR-­ targeted medicinal chemistry focused mainly on refining the available chemical matter.

3.2.1  The FXR Ligand Binding Site – FXR Ligand Recognition In the recent past, structural information for the FXR LBD has markedly increased and several dozen FXR LBD X-­ray structures in complex with diverse steroidal and non-­steroidal ligands are available. The FXR LBD is very flexible and can accommodate various ligand chemotypes. At more than 700 Å3, its ligand binding site is quite large. It is defined by helices 2, 3, 5, 6, 7, 11 and 12 and is mostly lipophilic, with few polar residues involved in ligand binding. Binding of the endogenous FXR agonist CDCA (Figure 3.1, PDB-­ID: 4QE6) is mediated by hydrogen bonds of its 3-­hydroxy group to tyrosine 361 and histidine 447 as well as the 7-­hydroxy group to

Figure 3.1  X-­  ray structures of the FXR LBD in complex with CDCA (left, PDB-­ID:

4QE6) and OCA (right, PDB-­ID: 1OT7): The complex of FXR bound to CDCA (1.1) illustrates the L-­shaped geometry of the FXR ligand binding site. Moreover, it reveals two unoccupied regions (arrows) that offer optimization potential. The 6α-­ethyl side chain of OCA protrudes to a lipophilic subpocket that is not addressed by CDCA.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

82

Chapter 3

serine 332 and tyrosine 369. In addition, a key interaction of CDCA and many other potent FXR agonists is a neutralizing contact with arginine 331 located at one end of the binding site, which illustrates the importance of acidic moieties in FXR ligands and their fatty acid mimetic61 structure. The endogenous bile acid agonists of FXR amongst steroids have a unique L-­shaped geometry that results from their A/B-­ring cis juncture.11 Their different geometries strongly contribute to the selectivity of different steroids for their receptors. The specific bile acid shape is reflected by the FXR ligand binding site and constitutes another essential feature of ligand recognition by FXR. Most agonistic FXR ligands, therefore, share an L-­shaped geometry while FXR antagonism can be achieved by altering this crucial geometry.6,11,62,63 The trifunctionalized isoxazole moiety of GW4064 turned out to be a very favorable residue for FXR activation. This so-­called “hammerhead”-­structure with a 2,6-­dichlorophenyl (or 2-­trifluoromethoxyphenyl) moiety and an isopropyl group as 3-­ and 5-­substituents of the isoxazole is widely conserved over almost all descendants of the highly potent FXR agonist GW4064. X-­ray structures of GW4064 (Figure 3.2) and derivatives in complex with the FXR LBD revealed that the isoxazole directly interacts with AF-­2 by an edge to face stacking with tryptophan 469.64 This direct contact with AF-­2 is a unique characteristic of the hammerhead structure and may explain the enormous activation efficacy of isoxazole-­based FXR agonists. The 2,6-­dichlorophenyl moiety by its ortho-­substituents is forced out of the plane of the isoxazole and favorably occupies a sub-­pocket formed by phenylalanine 284, leucine 287, tryptophan 454 and phenylalanine 461. It also significantly contributes to stabilization of the bound state of AF-­2/helix 12.

Figure 3.2  Binding  mode of the widely conserved “hammerhead”-­structure of GW4064 derived FXR agonists in the FXR LBD (PDB-­ID: 3DCU).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

83

Some reports also describe results indicative of allosteric binding sites enabling FXR modulation. Allosteric binding has been proposed for the gene-­selective FXR modulator guggulsterone, which, according to the results of molecular modeling studies, binds to the canonical FXR ligand binding site and another pocket in the loop region between helices 1 and 2.65 In addition, the kinase inhibitor imatinib was characterized as a positive allosteric modulator of FXR and optimized to a highly potent allosteric activator that synergistically promotes FXR activation by orthosteric agonists. Though direct interaction with FXR was experimentally confirmed, the binding site of imatinib and derivatives on FXR remains elusive.13

3.2.2  FXR Ligand Types and Scaffolds In contrast to other nuclear receptors, such as the retinoic acid related receptors (RORs) and nuclear receptor related 1 protein (Nurr1), FXR has no appreciable intrinsic activity. FXR ligands can therefore have two basic types of activity, agonism and antagonism. FXR agonists bind to the orthosteric FXR ligand binding site that is also addressed by the endogenous agonist CDCA and induce a conformational change allowing the AF-­2 helix to bind to the core of the LBD. The LBD then releases bound co-­repressors and recruits co-­activators to induce gene transcription. FXR antagonists competitively prevent agonists from binding to the orthosteric binding site and activating the receptor. According to current knowledge, FXR antagonists bind to the same orthosteric binding site as agonists but without inducing a conformation that is competent to recruit co-­activators. Since the unliganded state of FXR appears to have no intrinsic activity, inverse agonism, i.e. full stabilization of the receptor's inactive state, plays no role on FXR. Between agonists and antagonist, partial agonists66–69 exist that bind FXR with high affinity but cause only modest receptor activation. In light of the adverse effects of full FXR agonists,49 partial agonism may hold considerable therapeutic potential. Mechanistically, partial agonists appear to transform the FXR LBD into a conformational state which is capable of alternatingly binding co-­ activators and co-­repressors159 and, therefore, must also be considered as partial antagonists. Allosteric FXR modulation with small molecules seems also possible18 and allosteric activators13 as well as antagonists65 have been described. Further research is required to characterize the molecular basis, pharmacological effects and therapeutic potential of allosteric FXR ligands, however. Although FXR has seen tremendous drug discovery efforts since its identification1 and deorphanization2–4 in the 1990s, the chemical diversity of potent FXR ligands is still limited to a few chemotypes.70 Analysis of FXR ligands annotated in the ChEMBL70,71 database revealed that approximately two thirds of known FXR ligands are derived from only six basic chemotypes (Figure 3.3) with a strong dominance of analogues and descendants of GW4064.

View Online

Chapter 3

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

84

Figure 3.3  The  most prominent FXR activator chemotypes annotated in ChEMBL.70,71 The majority of known FXR modulators are derived from the first chemical tool for FXR, GW4064. Overall, the diversity of potent FXR activators reported in the literature is rather limited in light of the strong interest in the nuclear receptor by academic and industrial drug discovery. The remaining part (grey) of the FXR activators constitutes diverse synthetic scaffolds and natural products with weak activity.

3.2.3  Hit/Lead Discovery – Identifying Chemical Matter 3.2.3.1 In Vitro Screening Assays As for all early drug discovery programs, FXR ligand discovery requires robust in vitro test systems. Two general types of assays for screening and routine testing of FXR ligands are available, namely cellular reporter gene assays and cell-­free co-­activator recruitment assays. Both approaches have characteristic advantages and drawbacks.72 Reporter gene assays utilize the ability of nuclear receptors to interact with DNA and regulate gene expression. For this purpose, a suitable response element specific for the nuclear receptor in question is placed in the promoter region of a reporter gene (usually a luciferase) on a recombinant plasmid construct. After transfection of this construct into cultured cells, either intrinsically expressing the nuclear receptor or co-­transfected with nuclear receptor coding DNA, the nuclear receptor will bind to its response element and subsequently govern reporter gene transcription. Agonist binding will induce expression of the reporter gene, which can be observed afterwards by a biochemical readout such as bioluminescence. Robust reporter gene assays

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

85

include a second constitutively expressed gene that can be monitored for normalization of transfection efficacy and to recognize non-­specific effects such as compound toxicity. Two types of reporter gene assays for FXR ligand characterization are widely used. The more artificial systems employ a hybrid receptor composed of the (human) FXR LBD and the DNA binding domain of the yeast receptor galactose induced transcription factor 4 (Gal4).13,70 Accordingly, the reporter construct for this system contains a reporter gene under the control of a Gal4 response element. This system provides the advantage that the chimeric receptor does not require a heterodimer partner and that its activation can only be mediated via the human FXR LBD. More physiological FXR reporter gene assay settings employ the full human FXR–RXR heterodimer to govern reporter gene transcription. The reporter construct then contains a human FXR response element for example from the promoter region of the FXR regulated gene bile salt export protein (BSEP).73,74 The nuclear receptors FXR and RXR can either be intrinsically present in the cell type used for the assay or artificially overexpressed by co-­transfection of constitutive expression constructs, which usually gives better results in terms of robustness and signal-­to-­noise ratios. Reporter gene assays employing the FXR–RXR heterodimer are as close as possible to the physiological settings of nuclear receptor activity in cells and, therefore, give the most predictive results for FXR ligand characterization. However, these test systems are also susceptible to assay artifacts arising from heterodimer activation via RXR or via the ligand-­independent AF-­1 due to cellular effects. Despite being cost-­and time-­intensive, reporter gene assays constitute the most favorable technique for FXR ligand discovery and routine characterization due to several advantages. With their cellular background, reporter gene assays not only provide data on the activity of a test compound but also capture the compounds' cell penetration ability, which is a very important aspect for nuclear receptor ligands that are expected to address a cellular or nuclear target. Compounds identified and optimized in a cell-­free environment might fail to have activity in cells and organisms even if they display high affinities to the nuclear receptor when they cannot access the cellular compartment of action. In addition, reporter gene assays allow a realistic estimation of nuclear receptor activation efficacy of test compounds and, as a third advantage, give hints of compound toxicity. Cell-­free co-­activator recruitment assays also rely on the natural mechanism of nuclear receptor activation and mimic the recruitment of a nuclear receptor co-­activator peptide to the recombinant LBD of the nuclear receptor in question. In order to enable observation of this recruitment, both the co-­activator peptide and the nuclear receptor LBD must be labeled. Time-­ resolved fluorescence resonance energy transfer (TR-­FRET) and the amplified luminescent proximity homogeneous assay (alpha-­screen) technology are widely used methods for co-­activator recruitment assays and both rely on detecting spatial proximity of nuclear receptor LBD and labeled co-­activator peptide.72 Labeled FXR LBD and labeled co-­activator peptide in absence of an

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

86

Chapter 3

agonist are separate in solution and give no or weak FRET and alpha-­screen signals. Upon addition of an agonist, conformational changes in the FXR LBD enable binding of the co-­activator to the LBD leading to close proximity of both labels which induces the FRET or alpha-­screen signal. The efficacy of a ligand in recruiting the co-­activator peptide to the LBD can be used to estimate nuclear receptor activation efficacy. However, the use of shortened co-­activator peptides may not fully reflect the interaction of the LBD with the entire co-­activator and the existence of various different co-­activators that might be differentially recruited by different LBD–ligand complexes75,76 complicate translation of the readout from cell-­free systems to the activity of a ligand in cells or even organisms. Thus, co-­activator recruitment assays are robust and specific but more artificial than reporter gene assays and lack their cellular background that holds valuable additional information as discussed above.

3.2.3.2 Screening Approaches to Discover FXR Ligands The first potent FXR agonist GW4064 (2.1) was identified from a combinatorial library (10 000 compounds) of stilbene carboxylic acids that was screened in a cell-­free FRET-­based SRC-­1 recruitment assay.57 The other early potent FXR agonist frameworks originated from high throughput screening campaigns. WAY-­362450 (3.1)58 and fexaramine (4.4)22 were each developed from high-­throughput cell-­based reporter gene assay screening hits, whereas benzimidazole-­based FXR ligands59 were discovered using cell-­free high-­ throughput scintillation-­proximity assay screening. The availability of X-­ray structures of the FXR LBD in complex with the structurally diverse first ligands later enabled structure-­based virtual screening on FXR.77–80 Several FXR agonists and antagonists were discovered by these approaches as potential lead compounds for further optimization. Recently, workflows involving automated docking, similarity searching and ranking of predicted binding pose energies have even discovered novel natural product FXR ligands.81,82 With increasing availability of FXR ligands and their activity data also, ligand based virtual screening70,83 approaches and integrated ligand–structure-­based methods84 gained relevance and contributed several novel FXR modulator chemotypes. Recently, FXR was topic of the Drug Design Data Resource (D3R) Grand Challenge 2 85 based on a dataset of 36 X-­ray structures of the FXR LBD in complex with diverse ligands and activity data for 102 FXR ligands. This enormous data set served for the competitive evaluation of computational methods to predict binding poses and ligand affinities for FXR. Although the FXR ligand binding site is rather flexible and highly lipophilic, most pose prediction strategies yielded reasonable binding modes with a median root-­mean-­square deviation (RMSD) of less than 2.0 Å. Better results were obtained when co-­crystal structures of similar ligands were available as starting points, whereas novel ligand frameworks were less accurately placed, highlighting the challenge of identifying new FXR modulator scaffolds by

View Online

Discovery, Structural Refinement and Therapeutic Potential

87

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

70

computational approaches. Overall, no docking algorithm was superior to predict FXR ligand binding poses and rather the use of available structural information as well as the reasonable combination of computational techniques seemed to affect the prediction accuracy.85 FXR ligand affinity predictions in the D3R Challenge were less encouraging since simple correlation of affinity with lipophilicity (clogP) ranked among the best performing methods.85 Thus, structure-­based computational techniques for FXR ligand optimization require further improvement to fully support medicinal chemistry. The computational approaches to FXR ligand binding pose and affinity prediction were published along with the overall challenge report.85

3.3  F  XR Ligand Optimization Towards Clinical Candidates – Refining Chemical Matter As is obvious from Figure 3.3, a few chemotypes account for the majority of FXR activators with the GW4064-­derived isoxazole scaffold as most prominent class of FXR ligands. This is, in part, due to the enormous industrial and academic efforts spent in analyzing the structure–activity relationship (SAR) of the successful FXR activator classes in depth. As a result, broad knowledge is available on what molecular determinants drive potency of these FXR ligand types and what structural changes made to improve physicochemical and pharmacokinetic properties are tolerated. In the following, the SAR of the four most deeply studied FXR activator classes is discussed.

3.3.1  Steroidal FXR Agonists The semi-­synthetic bile acid analogue OCA (1.2; Figure 3.4) derived from the natural FXR agonist CDCA (1.1) is still the most successful FXR ligand in clinical trials to date. Its discovery originated from a small screening86 of bile acids as well as methylated and fluorinated bile acid analogues87,88 in

Figure 3.4  Structural  optimization of the endogenous FXR agonist CDCA (1.1) to

the potent drug obeticholic acid (OCA, 1.2). Introduction of a single ethyl side chain at the 6α-­position yielded an improvement in potency by a factor of 100.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

88

Chapter 3

a cell-­free assay monitoring recruitment of an SRC-­1 fragment to the FXR LBD. Thereby, 6α-­methyl-­CDCA (1.3) was identified as a considerably more potent FXR activator than CDCA (1.1) leading to further exploration of the 6α-­ position of the CDCA scaffold. Amongst three derivatives (6α-­ethyl, -­propyl and -­benzyl) analyzed, the 6α-­ethyl analogue 1.2 exhibited most potency as FXR agonist while larger substituents in the 6α-­position were not tolerated (Figure 3.4). By introduction of only an ethyl substituent, 1.2 gained by a factor of 100 in potency over the endogenous FXR agonist 1.1 and simultaneously possessed higher activation efficacy. X-­ray analysis of OCA bound to rat FXR-­LBD (Figure 3.1 right panel, PDB-­ID: 1OT7) illustrated the molecular basis of the enormous gain in potency achieved by introduction of the ethyl side chain. The ethyl moiety occupies a lipophilic sub-­pocket defined by isoleucine 349, isoleucine 359, methionine 362 and phenylalanine 363 that is not addressed by CDCA. Further structure–activity evaluation of the CDCA core89 failed to discover a superior moiety in the 6α-­position compared with the ethyl residue in OCA (1.2). Only the 6α-­allyl and the 6α-­propargyl derivatives retained submicromolar activity on FXR while especially polar substituents, such as hydroxyl and hydroxyethyl, were not tolerated in this region. Removal of the 3-­hydroxy group of CDCA (3-­deoxy-­CDCA, EC50 = 1.3 µM) led to a slight improvement in potency over CDCA (1.1) while it is essential for activation of Takeda-­G-­protein 5 (TGR5),90 indicating that the 3-­position of the CDCA scaffold may provide a potential selectivity handle. When it was combined with the 6-­α-­ethyl side chain of 1.2, 3-­OH removal inverted the activity on TGR5 but simultaneously caused a marked loss in potency on FXR (3-­deoxy-­OCA, BAR704, EC50(FXR) = 0.95 µM, concentration giving 50% of maximum inhibition (IC50(TGR5) = 11 µM)).91,92 Isomerization of the 3-­hydroxy group in 1.2 was accompanied by significantly reduced activity on FXR, as well (BAR710, EC50(FXR) = 1.3 µM).90,91 In contrast to the 3-­OH, the presence and orientation of the 7-­hydroxyl moiety of the CDCA scaffold turned out to be crucial for activity on FXR90 while hydroxylation at the C16α/β-­positions was not favored.11,93 A variety of SAR studies has focused on the side chain of the steroidal bile acid scaffold. Some side chain modifications, such as rigidization with a cyclopropyl moiety, were tolerated and the carboxylic acid could be replaced by a sulfonic acid or an ethyl carbamate without major effects on potency. Surprisingly, even a free amine was tolerated instead of the carboxylic acid. These observations prompted the introduction of larger cinnamyl carbamate residue into the side chains of CDCA and OCA.94 In case of the CDCA scaffold, this bulky side chain modification was accompanied by a strong increase in potency (EC50 = 0.90 µM, 55% efficacy relative to CDCA) but combination with the 6α-­ethyl residue of OCA failed to achieve further improvement (EC50 = 0.15 µM, 290% efficacy relative to CDCA) compared with OCA. Molecular modeling studies indicate that both bulky cinnamyl carbamates protrude to a “back door” pocket close to the canonical FXR ligand binding site.11,94 The sulfonic acid analogue INT-­767 (Table 3.1) of OCA (EC50 = 0.1

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

89

µM) turned out to be even slightly more potent on FXR (EC50 = 0.03 µM) but also possesses high activity on TGR5 (EC50 = 0.6 µM).95 This dual FXR–TGR5 agonist was studied in various animal models of metabolic diseases and, for example, showed efficacy in NASH,96–98 age-­related kidney disease99 and nephropathy.100 The compound is currently being evaluated in early stage clinical trials. Introduction of a methyl group in the α-­position of the carboxylic acid (C23) was not tolerated by FXR but generated rather selective TGR5 ligands favoring the methyl group modification in S-­configuration.101 Moreover, shortening of the carboxylic acid side chain in 1.2 by one methylene bridge caused a marked loss in FXR agonistic potency.102 The chain shortened bile alcohol NorECDCOH retained intermediate activity on FXR with an EC50 value of 2 µM. Further SAR studies on CDCA and OCA focused on replacement of the carboxylic acid in 1.2 with a variety of bioisosteric groups (amides, ureas, sulfonamides, carbamates) to prevent formation of taurine and glycine conjugates in vivo. Several bioisoster analogues of 1.2 such as the respective 1H-­tetrazole [EC50(FXR) = 0.06 µM, 153% efficacy relative to CDCA, 30-­fold selectivity over TGR5] retained high potency and efficacy on FXR but achieved no robust selectivity over TGR5.91 OCA (1.2) was the first FXR ligand that was suitable for clinical development and a prime example of successful drug development from an endogenous ligand. 1.2 entered clinical development for the severe liver diseases primary biliary cholangitis (PBC) and non-­alcoholic steatohepatitis (NASH). Therein, the bile acid derivative 1.2 has shown great therapeutic efficacy and validated FXR as drug target (see Section 3.1.2). However, clinical development of FXR activators has also revealed significant disturbances in cholesterol homeostasis and severe pruritus as considerable adverse effects. Cholesterol accumulation under OCA treatment may be ascribed to FXR activation and, thus, constitute a mechanism-­based side effect of FXR agonists because FXR activation leads to repression of CYP7A1. As this enzyme catalyzes the key reaction of cholesterol metabolism to bile acids and as this metabolic pathway contributes up to half the elimination of cholesterol, potential deleterious effects of strong FXR activation on cholesterol balance are obvious. In contrast, the pruritus observed after OCA administration appears not to be related to FXR activation but might result from an off–target activity of the steroidal FXR agonist. In addition to its high FXR agonistic potency (EC50 = 0.1 µM), OCA (1.2) also activates the membrane bile acid receptor TGR5 (EC50 = 15 µM). This G-­protein coupled receptor shares the bile acids as endogenous ligands with FXR and amongst many other activities can activate the ion channel transient receptor potential ankyrin 1 (TRPA1) to induce itching.103 This side activity may explain pruritus under OCA therapy and renders selectivity over TGR5 as a crucial attribute for FXR ligands. Moreover, bile acids were found to possess more favorable pharmacokinetic properties and lower cytotoxicity with increasing number of hydroxyl groups104,105 which supported further derivatization of OCA (1.2).

View Online

Chapter 3

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

90

With the help of new structural insights from the X-­ray structure of the human FXR LBD in complex with CDCA (PDB-­ID: 4QE6, Figure 3.1 left panel), OCA (1.2), therefore, was further optimized towards improved selectivity. The CDCA bound FXR LBD revealed a small unoccupied polar region in proximity to C11 and C12 of the steroid scaffold which appeared capable of accommodating a small additional substituent. Synthesis and in vitro characterization of the four isomers of OCA comprising an additional hydroxyl group in 11α, 11β, 12α or 12β positions revealed that only the 11β-­hydroxy derivative 1.4 (TC-­100)106 conserved similar nanomolar potency on FXR compared to OCA (1.2). However, 1.4 was significantly less active on TGR5 and, thus, superior to OCA in terms of selectivity (Figure 3.5). An additional hydroxyl group at the 12α-­position (cholic acid), in contrast, is preferred by TGR5. The FXR-­optimized bile acid derivative 1.4 also turned out to be selective over a series of related nuclear receptors, possessed improved aqueous solubility and lower lipophilicity compared with OCA (1.2) and was non-­toxic in vitro. Moreover, 1.4 had even higher efficacy in inducing FXR regulated gene expression in hepatocytes and in mouse intestine. The successful development of the CDCA-­derived FXR agonist OCA and its success in clinical trials were crucial for the rise of FXR as a drug target and boosted FXR-­targeting drug discovery efforts. Despite some drawbacks in pharmacokinetic properties (enterohepatic circulation, short hepatic residence, drug–drug interaction potential), the steroidal FXR agonists OCA is leading the NASH pipeline with good efficacy.49 EDP-­305 (Enanta), another steroidal FXR agonist, is succeeding in the earlier stages of clinical development. The compound differs from bile acid derivatives, such as OCA, in its lack of a carboxylic acid and has been granted fast-­track status by the FDA for development in treatment of NASH with liver fibrosis. Figure 3.6 gives an overview of the published structure–activity relationship of FXR agonists derived from CDCA. It illustrates that beyond the two key improvements of introduction of a 6α-­ethyl side chain and an 11β-­ hydroxy group, no significant optimization has been achieved, so far. In

Figure 3.5  Introduction  of an 11β-­hydroxyl group in OCA retained potency on FXR and strongly improved selectivity over TGR5.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

91

Figure 3.6  Structure–activity  relationship of bile acid derivatives as FXR agonists. addition, owing to the demanding synthesis and derivatization of the steroidal scaffold, several regions of bile acid derived FXR agonists remain to be explored.

3.3.2  Non-­steroidal FXR Agonists 3.3.2.1 Isoxazole-­Based FXR Agonists The first non-­steroidal FXR agonists were disclosed by Maloney and coworkers at GSK in the year 2000.57,107 The isoxazole-­bearing scaffold was identified out of 9900 stilbene carboxylic acids in a high-­throughput screen (HTS) using a FRET SRC-­1 recruitment assay (Figure 3.7, 2.0). Breaking down the identified hit compound into three molecular fragments, a focused three-­component library was synthesized on resin to systematically study their structure–activity relationship. Little preference was observed in variations of compound parts A and B. In contrast to that, the SAR was proven to be quite steep at moiety C and para-­substituted aryl groups were not tolerated while ortho substitution was favored. The isoxazole ring was identified as key structural element, with a minimum requirement of a small alkyl at the 5-­position, a 2,6-­dihalogenaryl at the 3-­position and a linker towards moiety B at the 4-­position of the isoxazole. The most active compound from this series (GW4064, 2.1) possessed nanomolar potency (EC50 15 nM) determined in a FRET assay with 140% FXR activation efficacy compared with 50 µM CDCA. First pharmacokinetic assessment in rats showed an oral bioavailability of 10%, a half-­life of 3.5 h and triglyceride (TG) lowering effects as pharmacodynamic activity of FXR agonism.57 GW4064 was not suitable for clinical development due to its low bioavailability and the unfavorable characteristics of the stilbene moiety such as potential toxicity and photo-­instability. Still, GW4064 became the most important tool compound to study FXR pharmacodynamics and is widely used as a FXR agonistic reference compound.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

92

Chapter 3

Figure 3.7  Isoxazole  identified as first non-­steroidal FXR agonistic scaffold. Screening hit with systematically optimized compound regions A, B and C.

Since the discovery of GW4064 (2.1), an enormous amount of data has been generated on the SAR of isoxazole-­based FXR agonists, which was mostly published in patent literature but has recently been reviewed.108 As the high FXR activation efficacy of the 3,5-­disubstituted isoxazole has hardly been reached by any other scaffold, hundreds of GW4064 derivatives were synthesized by several pharmaceutical companies. When analyzing this vast amount of structure–activity data, it becomes obvious that GW4064 has set a benchmark in potency early on. Most attempts at producing improved compounds resulted in less active analogues and only few equipotent compounds were discovered. The isoxazole head with its aryl-­/alkyl-­substitution pattern turned out to be essential for potency and was conserved in all compounds, while the tether connecting the isoxazole (“hammer-­”)head with the carboxylic acid requires a certain rigidity, length and lipophilicity as structural features. In this part, however, more structural solutions are tolerated. In the following paragraphs, the various approaches to improve the isoxazole scaffold will be discussed in a mostly chronological order to underline the influence of inspiration from previous patents and publications. The chronological development of GW4064 descendants is depicted in Figure 3.8. The first follow-­up SAR studies of GSK focused on replacing the stilbene moiety to circumvent the drawbacks discussed above. GSK claimed the replacement of the stilbene by oxymethylene, methylmethylene or sulfone-­ and carboxamide spacers in a patent application109 without improved activities (Figure 3.8, 2.2). Furthermore, the introduction of a methylene spacer at position 3 of the isoxazole towards the aryl-­moiety was described. Replacement of the 2,6-­dichloro moiety by 2-­OCF3, moving the carboxylic acid from the 3-­to the 4-­position as well as replacement of benzoic acid by non-­acidic moieties or heteroaromatic residues were identified as tolerated structural features, which nevertheless had reduced potencies compared with GW4064 with negative logs of the EC50s (pEC50s) of less than 7.110 In parallel, GSK and other companies have proposed additional replacements for the stilbene moiety, such as bicyclic aromatic systems, which led to equipotent derivatives. Similar to compounds claimed by Lion Bioscience AG (Figure 3.8, 2.3 111), GSK investigated naphthoic acid derivatives as stilbene replacements.109 In 2008 a description of the small naphtoic acid

View Online

93

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

Figure 3.8  Evolution  of isoxazole-­based FXR agonists. Depicted are the structures, activity and origin of the most active compounds. FRET, Fluorescence resonance energy transfer-­based coactivator recruitment assay; TT, transactivation assay.

SAR was published64 which focused on the position of the carboxylic acid and identified 6-­substituted 1-­naphthoic acid as most active compound (GSK8062, Figure 3.8, 2.4, 87 nM, 134%, FRET) obtaining similar potency like GW4064 (2.1, 59 nM, 100%, FRET). Changing the position of the carboxylic acid was detrimental for activity, which dropped to micromolar potency and

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

94

Chapter 3

partial agonists were obtained. X-­ray data from a FXR LBD complex bound to GSK8062 confirmed the compound's GW4064-­like conformation and favorable interaction of the naphthoic acid with Arg331. However, GSK8062 (Figure 3.8, 2.4) showed rapid clearance in rats, limited solubility at neutral pH as well as difficulties in obtaining a solid salt form. Thus, the compound was not suitable for clinical development either.64 Also, Eli Lilly engaged on an extensive SAR campaign based on GW4064 in 2007 which resulted in three patents.112–114 The study focused on replacing the stilbene moiety by bicyclic (hetero-­)aromatic systems directly linked to the central phenyl ring using benzofuran, 1H-­indole, 1H-­indazole, benzothiopehene (Figure 3.8, 2.5, 2.6), as well as shortened five-­membered heteroaryl residues. Little information has been reported about individual compound potencies but only a range of 365 to 3000 nM in an SRC1 recruitment assay, indicating lower potency than GW4064. In addition to optimizing the stilbene moiety, Eli Lilly addressed the 5-­substituent of the isoxazole identifying a cyclopropyl group (Figure 3.8, 2.6) as more active than the original isopropyl residue.113 Additionally, a 2-­trifluoromethoxy group as replacement for the 2,6-­dichlorosubstituents was introduced as well as carboxylic acid bioisosters such as N-­alkylsulfonylacetamide. In further patent applications112,114 methylaminobenzyl is used as stilbene replacement, as previously introduced by GSK.110 Furthermore, possible replacements of the isoxazole by other small heteroaromatic cyclic molecules such as pyrazoles and triazoles (Figure 3.8, 2.7) were studied which retained activity of the isoxazole derivatives. Also, in these patents, little information is given about potencies except for single examples (Figure 3.8, 2.7), which makes it difficult to draw conclusions. Phenex Pharmaceuticals were the first to investigate the central phenyl moiety of GW4064-­derived FXR agonists using pyridine and pyrazole derivatives.115–117 Its replacement by a pyridine was tolerated and displayed similar activity (Figure 3.8, 2.8), but solubility as well as pharmacokinetic parameters were improved. By optimizing the position of the carboxylic acid to meta and using the cyclopropyl substituent on the isoxazole (more than twofold improvement over isopropyl), Phenex generated a single digit nanomolar FXR agonist (Figure 3.8, 2.9).118,119 By combining knowledge from previous compound series,64 GSK then generated FXR agonists based on naphthoic acids and aza-­analogues attached at the para position to the central phenyl ring. The position of the carboxylic acid was varied to identify the most preferred conformation. In the most active compound of the series GSK2324 (Figure 3.8, 2.10, 120 nM, 105% FRET; 50 nM, 102% TT), the stilbene moiety is replaced with a quinoline comprising a carboxylic acid in plane with the aromatic system. GSK2324 has similar potency to GW4064, but improved aqueous solubility (60×), lower clearance in rat and an easily obtained solid potassium-­salt form. The crystal structure of GSK2324 revealed additional space for lipophilic alkoxy-­substituents at the quinoline system, but their introduction despite moderately promoting potency disrupted the favorable aqueous solubility.120,121 Furthermore, using

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

95

5.6-­bicyclic (hetero-­)aromatic systems to replace the stilbene region similar to the compounds claimed by Eli Lilly in 2007 ,113 GSK improved the potency to a double-­digit nanomolar range.122 Benzothiophene 2.11 (Figure 3.8, 20 nM 107%, FRET) and indole 2.12 (Figure 3.8, 21 nM, 115%, FRET) turned out to be the most potent examples of this FXR agonist series. The study again underlined the importance of the position of the carboxylic acid since the most active compounds had similar conformations to GW4064 with the carboxylic acid in plane with the aromatic system. In 2009, GSK reported a series of GW4064 analogues focusing on the substitution pattern on the 3-­arylisoxazole moiety after having identified further space around this residue in the crystal structure of GW4064.123 To extend the structure towards the free space, tethers of 1, 2 and 3 carbon atoms were introduced but caused a reduction in activity. Potency was regained with a two-­atom tether comprising a sulfoxide moiety which achieved similar activity to GW4064 (Figure 3.8, 2.13, 28 nM, 110%, FRET). Moreover, activity data obtained for the unsubstituted 3-­phenylisoxazole analogue confirmed that the 2,6-­substitution pattern fixing the aromatic ring in a favorable conformation is required for potency.123 In parallel SAR attempts, still focusing on replacement of the stilbene moiety, GSK also applied bicyclic (hetero-­)aromatic systems to replace the central aromatic ring of GW4064.124,125 Two series of compounds were reported where the central aromatic ring was linked either to the distal or proximal stilbene carbon atoms, forming a bicyclic aromatic system (indoles, benzothiophen, benzothiazole). This resulted in highly constrained compounds when the entire stilbene was incorporated in the ring system (Figure 3.8, 2.14), or more flexible derivatives comprising one more rotatable bond (Figure 3.8, 2.15). The conformationally more constrained compounds were preferred over more flexible analogues by a factor of 2–20. The most active compound of the constrained series (Figure 3.8, 2.14, 55 nM, 90%, FRET; 32 nM, 87%, TT)124 was equipotent to GW4064. This study additionally revealed that an aromatic system in the stilbene–linker region is favored for activity, as partly saturated bicyclic systems had strongly reduced activity (approximately 700 nM, TT). Furthermore, compared with the earlier published compounds122 heteroaromatic systems were not well tolerated as the central moiety, however, which is most probably due to the penalty for desolvation of the heteroatoms, since the bicyclic system will be placed in a narrow and highly lipophilic part of the FXR ligand binding pocket. An exception was sulfur as contained in compound 2.14 (Figure 3.8). Alternatively, placing the heteroatoms close to the carboxylic acid (as in previous compounds 2.5, 2.6, 2.11, 2.12) where they can potentially contribute to H-­bonds formation towards the R331 appears to be better tolerated. Moreover, it was suggested that the carboxylic acid is close to the solvent front and that the desolvation cost for heteroatoms is lower when they are close to the carboxylate function.120 A key evolutionary step in the optimization of isoxazole based FXR agonists was initiated by Eli Lilly in 2009. They succeeded in replacing the

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

96

Chapter 3

central aromatic residue by saturated six-­or seven-­membered (hetero-­)cyclic systems in combination with bicyclic heteroaromatic groups as terminal carboxylate bearing moieties (Figure 3.8, 2.16 126). At the isoxazole system, the cyclopropyl substituent was conserved. Activities were determined in an SRC1 recruitment assay but again, only a potency range (38–5200 nM) was reported, rendering the compounds up to a factor 10 more potent. LY2562175 (Figure 3.8, 2.16) originated as a clinical candidate. It acted as a FXR agonist in a cell-­free co-­activator recruitment assay (121 nM, 93%) but only had partial agonistic potency in the transactivation assay (193 nM, 41%) compared with GW4064. In an LDL-­c knock out mouse model, LY2562175 robustly lowered TG and cholesterol levels, while increasing high-­density lipoprotein cholesterol (HDL-­c). The compound continued to a clinical phase I single ascending dose study which supported once-­daily dosing127 but no further clinical development has been reported to date. Phenex Pharmaceuticals introduced saturated cyclic systems to replace the stilbene moiety, as well, linking the terminal and the central aromatic ring. Several cyclopropyl-­ (Figure 3.8, 2.17 128) and cyclobutyl-­derivatives were studied to retain the general constraint of the molecule. Introduction of a hydroxyl-­group at the cyclic linker element (Figure 3.8, 2.18) increased the overall polarity of the molecule and improved in vitro and in vivo properties. Moreover, several bioisosteric replacements for the carboxylic acid such as tetrazole or sulfonamides were characterized but all failed to conserve high potency.129 The racemic compound PX-­102 (Figure 3.8, 2.17), as well its eutomer (PX-­104) were the first synthetic agonists from Phenex which entered clinical trials (NCT01998659, NCT01999101) but their clinical development was stopped due to their amphiphilic structure, which led to accumulation in liver and increased ALT levels. In 2014 Gilead acquired Phenex's FXR program and took the more hydrophilic compound GS9674 (Figure 3.8, 2.18) into clinical development where it is still under investigation in phase II (NCT01998672, NCT02854605, NCT02808312). Positive results of this phase II trial in primary sclerosing cholangitis (PSC) patients have been reported recently and the FDA has granted orphan drug status.130 In 2012 Novartis claimed GW4064 derivatives that combined favorable structural features of previously published attempts from several competitors. Fusing 5-­cyclopropylisoxazole, nortropoline as constrained linker and a bicyclic heteroaromatic ring system bearing the carboxylic acid generated the first FXR agonists of this scaffold with sub-­nanomolar potency (Figure 3.8, 2.20, 2.21).131–133 The bridged nortropoline scaffold increased activity by a factor of 30 over the respective piperidine. With minor variations on the 3-­arylisoxazole substituents (trifluormethoxy vs. cyclopropyl) and on the benzothiazole carboxylate (4-­fluoro-­substituent) tropifexor (Figure 3.8, 2.22, LJN452)134 retained sub-­nanomolar potency (0.2 nM, 92%, HTFR; 0.26 nM, 89%, TT) and improved pharmacokinetics, solubility and metabolic stability. LJN452 is currently undergoing phase II clinical trials (NCT02855164, NCT02713243, NCT02516605).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

97

In 2016 Gilead slightly modified the successful structures of PX-­102 and LJN452 using their own previous knowledge. The resulting compounds (Figure 3.8, 2.19) comprise cyclic amine linkers as stilbene replacement and are active in the single-­digit nanomolar range in a transactivation assay.135,136 The positive results of OCA in clinical trials ultimately validated FXR as target for liver diseases. This has further encouraged the development of FXR agonists based on the isoxazole scaffold and accelerated structural optimization, which recently resulted in GW4064 analogues with a tricyclic (Figure 3.8, 2.23)137 or tertiary amine based stilbene replacement (Figure 3.8, 2.24)138 and piperidine based compounds similar to nortropolin LJN452 (Figure 3.8, 2.25, 2.26, 2.27). Bioisosteric replacements of the carboxylic acid such as sulfonylurea and sulfonamides (Figure 3.8, 2.26, 2.27)139,140 came into focus, as well. However, recent patents141–145 reported no activity data or only ranges, which impedes interpretation of the effects of these structural variations on activity.

3.3.3  Other Non-­steroidal FXR Agonists In addition to the dominant isoxazole scaffold, other non-­steroidal FXR ligands have been developed that can be classified into five distinct compound series (see Figure 3.3). One of the first published scaffolds are the azepino-­indole derivatives, with WAY362,450 (XL335, FXR-­450, Turofexorate isopropyl, Figure 3.9, 3.1) being the most prominent representative.146 It was discovered in a HTS effort of the Exelixis library which yielded 3.0 (Figure 3.9, EC50 600 nM, 100% in a transient transfection assay in CV-­1 cells, compared with 100 µM CDCA) as an initial hit. The first SAR studies focused on different esters, where the butyl ester showed a two-­fold reduction in potency, while isopropyl or n-­propyl ester retained activity compared with the original ethyl ester. In parallel, monomethyl substitution at position 1 of the azepino[4,5-­b]indole was found to promote potency by a factor 10 (57 nM, 160%), and dimethyl substitution generated an additional twofold improvement. Investigations on the benzamide residue revealed no difference when 4-­fluorine was replaced by chlorine or a methoxy group, but a twofold improvement was achieved with a 3,4-­difluoro substitution. Combining all above described improvements generated FXR-­450 (Figure 3.9, 3.1)58 with an EC50 of 4 nM (149%). It was selective over a broad panel of other nuclear receptors [Liver X receptor (LXR), peroxisome proliferator-­activated receptor (PPAR), retinoid X receptor (RXR), retinoic acid receptor (RAR), vitamin D receptor (VDR), steroid and xenobiotic receptor (SXR), estrogen receptor (ER), glucocorticoid receptor (GR), androgen receptor (AR), mineralocorticoid receptor (MR) and progesterone receptor (PR); no activity at 10 µM] and provided an oral bioavailability of 37.6% in rats. Furthermore, in low-­density lipoprotein receptor-­deficient (LDLR−/−) rats the compound reduced cholesterol and triglyceride levels, underlining its therapeutic potential. However, the compound's high lipophilicity (clogP 5.30) and poor solubility prevented further clinical development.147

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

98

Chapter 3

Figure 3.9  Evolution  of azepine-­based FXR agonists. Depicted are the structures

and activity of the most active compounds. FRET, Fluorescence resonance energy transfer-­based coactivator recruitment assay; TT, transactivation assay.

In an attempt to reduce lipophilicity, Mehlmann et al.148 replaced the azepinoindole with an azepinopyrrole. Though the compounds gained a twofold improvement in activity (Figure 3.9, 3.2, 6.3 nM, 121% in stable co-­ transfected HEK-­293 cells compared with GW4064; FXR-­450 16 nM, 130%) and a lower cLogP (5.30 vs. 3.89), their aqueous solubility at pH 7.4 was not increased. The authors suspected high planarity and stable crystal packing of the compounds as being the reason. To circumvent this, close structural analogues comprising a saturated azepine ring were evaluated, leading to a marked improvement in solubility, but a tenfold loss in activity. In a second attempt to increase solubility, solubilizing groups were introduced at the benzamide.149 Based on the X-­ray structure of 3.1 in complex with the FXR LBD (3FLI), a tether was designed to reach the solvent front of the FXR LBD. Various linker types (alkyl and alkoxy), lengths and attachment points, as well as several basic solubilizing groups (morpholine, pyrrolidine, piperazine and dimethylamine) were studied for this purpose. A clear preference for the para-­orientation of the linker over the meta, and for a longer linker (n = 3 with a 2.5-­fold improvement compared with n = 2) was observed. Compared with other basic moieties, morpholine was favored with a twofold to fourfold higher activity (Figure 3.9, 3.3, 101 nM, 156%). Furthermore, introduction

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

99

of an 8-­fluoro substituent at the indole-­ring increased metabolic stability. The compounds (n = 2 and 3) were soluble as hydrochloride salts (6 mg ml−1 in 0.5% methylcellulose–2% Tween-­80 in water) and demonstrated lowering effects on serum LDL-­c and TG levels in primates (Figure 3.9, 3.4). A more recent patent application150 claimed the insertion of heteroatoms in the azepino-­indole moiety, while conserving the rest of the scaffold (Figure 3.9, 3.5). The compounds retained activity in the FRET-­based assay, but lost a factor 20 in potency in a cellular assay.150,151 Furthermore, reduced ring systems were investigated in that regard,152 which additionally comprised substituents at the pyrazole moiety (Figure 3.9, 3.6). Combining this scaffold with a tethered morpholine (Figure 3.9, 3.7) was claimed, as well,153 but again only ranges of activity were published with the highest potency being less than 200 nM in a cell-­based assay. Another HTS campaign on a natural product-­like library (10 000 compounds) using a transactivation assay discovered benzopyrans (Figure 3.10, 4.0) as FXR agonists (5–10 µM).154 A follow up focused library of 200 benzopyran-­based compounds was synthesized on solid phase and characterized but still resulted in compounds with activities of 5–10 µM. 4.0 was among the most active compounds and was chosen as the starting point for a systematic optimization approach by dividing the scaffold into three distinct regions (Figure 3.10, region I, II and III). Since most FXR agonists bear a carboxylic acid moiety, the authors included a carboxylic acid in region I. The SAR showed the importance of the length and rigidity of the tether between the aromatic core and the functionality, as well as the type of carbonyl functionality, with methyl ester and methyl ether being the most potent. The SAR was astonishingly steep with ethyl and iso-­propyl ester as well as cyano and amide functionalities being inactive. Also, the meta position of the substituent at the aromatic core in region I turned out to be essential, with para substitution leading to inactive compounds. Due to its easy synthetic accessibility compound 4.1 was used to further investigate region II and III. In region II small aliphatic and aromatic amides, as well as bulky cycloalkyls were tolerated. When a benzene was used in region II, substitutions at the aromatic moiety reduced activity. Replacement of the amide by a thioamide, amine or sulfone was not tolerated. 4.2 (Figure 3.10, 358 nM) comprising a cyclohexyl moiety in region II turned out to be the most potent derivative of this early series. Further studies in region III (benzopyran) revealed a limited SAR, with most substitutions at the benzopyran decreasing activity. Therefore, the ring system in region III was exchanged to phenyl, naphthyl, biphenyl, cinnamate and stilbenes. Small aromatic moieties had detrimental effects on activity and naphthyl was less active than benzopyran (680 nM), but larger conjugated system such as biphenyl (Figure 3.10, 4.3, 36 nM) and stilbene (Figure 3.10, 4.4, 69 nM) improved activity. Three distinct series of this compound class [Figure 3.10, 4-­tert-­butylcinnamate (4.5, 127 nM), stilbene (4.3, 36 nM) and the biphenyl (4.4, 69 nM)] were further studied. In the 4-­tert-­butyl-­cinnamate series, para-­cinnamate was preferred, while ortho-­ and meta-­cinnamates

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

100

Chapter 3

Figure 3.10  Evolution  of Fexaramine derivatives. Depicted are the structures and

activity of the most active compounds. FRET, Fluorescence resonance energy transfer-­based coactivator recruitment assay; TT, transactivation assay.

were less active by more than a factor 10. Combining knowledge obtained from the first rounds of optimization in region I and II, the SAR of the cinnamates is still consistent: methyl-­ester is the most potent moiety in region I and cyclohexyl in region II. Interestingly, saturation of the cinnamate in region I leads to a mild decrease in potency (twofold), which indicates, that the rigidity rather than an electrophile characteristic of this moiety is responsible for activity. By further investigating region III, the size of the ester moiety was shown to be important, with ethyl-­, methyl-­and no ester losing more than tenfold activity. Methyl-­and ethyl-­allylic ether were tolerated and led to a slight reduction of activity. Saturation of the cinnamate in this position caused a slight decrease in activity, as well. Substitutions at the aromatic ring in region III are not tolerated in this compound class, making the starting compound 4.5 still the most potent one (EC50 of 127 nM).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

101

For the SAR of biaryl and stilbene-­containing libraries a split-­and-­pool solid-­phase strategy fixing region I with methyl ester cinnamate was used to obtain a 93-­membered library. As shown before, the cyclohexyl moiety for region II was preferred. At region III several substituents were tested at the terminal aromatic ring and no substituent improved the potency for the stilbene compounds, but in case of para substituents led to a loss of at least tenfold. Also using pyridine or thiazole aromatic rings diminished activity. As expected, due to the smaller size of the biaryl compounds, substituents in para mostly increased potency with dimethylamino (Me2N)-­ and methyl-­ being the most potent ones (Figure 3.10, 4.6, Fexaramine). The compounds obtained show intestinal-­restricted FXR activity, improving the metabolic profile in an animal model of high-­fat diet (HFD)-­induced obesity without showing systemic exposure, thereby, reducing the risk of side effects. In a recent patent155 the SAR was intensified on deuterated fexaramine derivatives, replacing the cyclohexyl by a bridged ring system, as well as investigating several substituents at the phenyl-­ring in region I (Figure 3.10, 4.8). Furthermore, the biphenyl in region III was replaced by bicyclic aromatic moieties (Figure 3.10, 4.9), which were proven to be potent in the GW4064 scaffold. Also inspired by the isoxazole SAR, saturated rings were introduced (Figure 3.10, 4.10)156 and the cinnamate moiety in region I was replaced by isoquinoline-­derivatives (Figure 3.10, 4.11).157 The compounds were tested in a cell-­based transactivation assay and their activites were claimed to be in the range of less than 1 µM up to more than 10 µM, making these attempts presumably less active than previous fexaramine derivatives.

3.4  Conclusions and Future Perspective The nuclear bile acid sensor FXR has seen a steep rise in interest as an (experimental) drug target in the past few years and has been ascribed enormous therapeutic potential in liver disorders as well as in metabolic diseases. Recent clinical data obtained with the steroidal first-­in-­class FXR agonist OCA confirmed that FXR activation can treat primary biliary cholangitis and non-­alcoholic steatohepatitis. In addition, the steroid caused beneficial effects on diabetes and obesity in some populations. Therapeutic efficacy of FXR activation with OCA in NASH patients also involved anti-­ fibrotic activity and, since fibrosis is considered a key factor of NASH progression towards liver cirrhosis or hepatocellular carcinoma, this effect of FXR activation strongly contributes to NASH therapy. Moreover, several preclinical studies have demonstrated that anti-­fibrotic effects of FXR activation also occur in kidney where fibrosis can have similar detrimental consequences as in liver. Thus, preclinical and clinical data indicate that FXR agonists might have a future in various other indications beyond the severe liver diseases PBC and NASH for which OCA has received approval or is close to being approved. First clinical experience with the steroidal FXR agonist OCA has also uncovered three major problems, which might limit the application of FXR

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

102

Chapter 3

activators. Whether this is a general problem of FXR activators, or more related to the chemical scaffold, remains to be elucidated. Recently, OCA has been flagged with a black box warning after several deaths were reported due to hepatotoxicity, which mostly were induced by wrong dosing regimens. The second issue, which already led to treatment discontinuations during clinical trials is OCA-­induced pruritus. Recent evidence indicates that pruritus might be induced by TGR5 agonism and, therefore, more selective FXR activators may overcome this adverse activity. Notably, pruritus can already occur as a symptom in liver diseases. Third, despite these promising preclinical and clinical results, FXR has pleiotropic activities and targeting FXR holds potential for adverse effects that might hinder full exploration of its therapeutic potential with strong activators. Physiologically, FXR regulates bile acid homeostasis including the metabolic formation of bile acids from cholesterol. This is mainly mediated via the FXR-­dependent repression of CYP7A1 which is the rate-­limiting enzyme of bile acid formation from cholesterol in human. FXR activation upregulates expression of SHP and FGF19 which via independent pathways cause repression of CYP7A1. Thus, strong FXR activation can block metabolic cholesterol elimination and may cause severe disturbances in cholesterol homeostasis. To avoid this potential adverse effect, partial agonists66,67,73 and selective bile acid receptor modulators (SBARMs)158 hold promise for safer therapeutic targeting of FXR. Partial agonists activate the receptor, but to a smaller extent than full agonists. In the case of FXR this seems to be achieved by stabilizing the receptor conformation, which shifts the binding equilibrium of corepressor and coactivator binding to a balanced state. Gene-­selective ligands would activate the nuclear receptor as well, but only lead to transcription of a specific subset of genes. Concerted development of such compounds would, of course, imply that specific side effects can be assigned to the transcription of certain target genes and may be avoided by sparing these genes in FXR modulation. Furthermore, extensive characterization of gene–expression profiles would then be required as a routine test system throughout FXR ligand discovery since classical in vitro assays cannot provide this enormous amount of data, yet. However, although FXR has been intensively studied as drug target, the molecular basis of partial or even selective FXR activation remains widely elusive. Rational design of small molecule FXR modulators that specifically address subsets of genes or recruit distinct coactivators is, therefore, hindered. Moreover, although promising in terms of improved safety, partial or selective FXR activation may come at the cost of reduced therapeutic activity, and since multifactorial disorders, such as NASH and other fibrotic diseases, require strong efficacy of treatment, multi-­target compounds that modulate FXR and another synergistic target are coming into focus, as well.74 So far, FXR-­targeted drug discovery has yielded several classes of highly potent and highly efficacious FXR activators that have validated the nuclear receptor as a valuable drug target for the treatment of metabolic, fibrotic and inflammatory diseases. Therein, non-­steroidal FXR

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

103

agonists might have several advantages over steroidal, bile-­acid like compounds in terms of reduced hepatotoxicity and increased selectivity over the bile acid-­sensing GPCR TGR5. The use of potent and selective FXR activators as pharmacological tools enables evaluation of FXR's potential in further pathophysiological conditions and study of its role in physiology. However, preclinical and clinical development of these strong FXR agonists has simultaneously revealed the need for more specific modulation of the nuclear receptor and supported the change in paradigm from strong activation efficacy towards application-­ tailored modulation. The broad SAR knowledge obtained in the discovery of potent steroidal and non-­steroidal FXR agonists and the availability of more than 60 X-­ray structures of the FXR LBD in complex with various ligands provide a solid basis for future development of novel, innovative FXR modulators to enable full exploration of the receptors' therapeutic potential. The interest in FXR activators is historically high since OCA was approved for PBC. A huge increase in scientific literature, patents, preclinical trials and clinical candidates can be observed. Several more FXR-­targeting compounds are expected to enter clinical trials and hopefully reach the market, not only for PBC treatment. Positive results reported for other liver diseases, like NASH, which is an increasing global health burden, but also preclinical data for various indications have further validated FXR as a valuable drug target. While it can be speculated that metabolic and hepatic diseases will be the main therapeutic area for FXR ligands in the near future, further indications may arise, such as fibrotic and inflammatory diseases. First preclinical observations in these fields are very promising.

Abbreviations AF-­1 (ligand independent) activation function 1 AF-­2 (ligand dependent) activation function 2 ALP alkaline phosphatase alpha-screen amplified luminescent proximity homogeneous assay screen ALT alanine aminotransferase CARM1 co-­activator-­associated arginine methyltransferase 1 CDCA chenodeoxycholic acid CYP7A1 cholesterol 7α-­hydroxylase DBD DNA binding domain DRIP vitamin D receptor interacting protein FGF19 fibroblast growth factor 19 FGFR4 fibroblast growth factor receptor 4 FXR farnesoid X receptor GGT γ-­glutamyl transferase HDL-­c high-­density lipoprotein cholesterol IBD inflammatory bowel disease

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

104

Chapter 3

LBD ligand binding domain LDL-­c low-­density lipoprotein cholesterol NAFL non-­alcoholic fatty liver NAS NAFL activity score NASH non-­alcoholic steatohepatitis NF-­κB nuclear factor κB Nurr1 nuclear receptor related 1 protein OCA obeticholic acid PBC primary biliary cholangitis PGC-­1α peroxisome proliferator-­activated receptor gamma coactivator 1-­alpha PPAR peroxisome proliferator-­activated receptor PSC Primary Sclerosing Cholangitis RE response element RXR retinoid X receptor ROR retinoic acid related receptor SAR structure–activity relationship SHP small heterodimer partner SRC-­1 steroid receptor co-­activator 1 PRMT1 protein arginine methyltransferase 1 TG triglyceride TGR5 Takeda G-­protein receptor 5 TIMPs tissue inhibitors of metalloproteinases TR-­FRET time-­resolved fluorescence resonance energy transfer TRPA1 transient receptor potential ankyrin 1 TT transactivation assay.

References 1. B. M. Forman, E. Goode, J. Chen, A. E. Oro, D. J. Bradley, T. Perlmann, D. J. Noonan, L. T. Burka, T. McMorris and W. W. Lamph, et al., Identification of a Nuclear Receptor That Is Activated by Farnesol Metabolites, Cell, 1995, 81(5), 687–693. 2. D. J. Parks, S. G. Blanchard, R. K. Bledsoe, G. Chandra, T. G. Consler, S. A. Kliewer, J. B. Stimmel, T. M. Willson, A. M. Zavacki and D. D. Moore, et al., Bile Acids: Natural Ligands for an Orphan Nuclear Receptor, Science, 1999, 284(5418), 1365–1368. 3. M. Makishima, A. Y. Okamoto, J. J. Repa, H. Tu, R. M. Learned, A. Luk, M. V. Hull, K. D. Lustig, D. J. Mangelsdorf and B. Shan, Identi­fication of a Nuclear Receptor for Bile Acids, Science, 1999, 284(5418), 1362–1365. 4. H. Wang, J. Chen, K. Hollister, L. C. Sowers and B. M. Forman, Endogenous Bile Acids Are Ligands for the Nuclear Receptor FXR/BAR, Mol. Cell, 1999, 3(5), 543–553. 5. F. Kuipers, V. W. Bloks and A. K. Groen, Beyond Intestinal Soap-­ Bile Acids in Metabolic Control, Nat. Rev. Endocrinol., 2014, 10(8), 488–498.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

105

6. D. Merk, D. Steinhilber and M. Schubert-­Zsilavecz, Medicinal Chemistry of Farnesoid X Receptor Ligands: From Agonists and Antagonists to Modulators, Future Med. Chem., 2012, 4(8), 1015–1036. 7. S. Fiorucci, A. Mencarelli, E. Distrutti and A. Zampella, Farnesoid X Receptor: From Medicinal Chemistry to Clinical Applications, Future Med. Chem., 2012, 4(7), 877–891. 8. D. D. Moore, S. Kato, W. Xie, D. J. Mangelsdorf, D. R. Schmidt, R. Xiao and S. A. Kliewer, International Union of Pharmacology. LXII. The NR1H and NR1I Receptors: Constitutive Androstane Receptor, Pregnene X Receptor, Farnesoid X Receptor Alpha, Farnesoid X Receptor Beta, Liver X Receptor Alpha, Liver X Receptor Beta, and Vitamin D Receptor, Pharmacol. Rev., 2006, 58(4), 742–759. 9. V. Sepe, E. Distrutti, V. Limongelli, S. Fiorucci and A. Zampella, Steroidal Scaffolds as FXR and GPBAR1 Ligands: From Chemistry to Therapeutical Application, Future Med. Chem., 2015, 7(9), 1109–1135. 10. T. Fujino, M. Une, T. Imanaka, K. Inoue and T. Nishimaki-­Mogami, Structure–Activity Relationship of Bile Acids and Bile Acid Analogs in Regard to FXR Activation, J. Lipid Res., 2004, 45(1), 132–138. 11. A. Gioiello, B. Cerra, S. Mostarda, C. Guercini, R. Pellicciari and A. Macchiarulo, Bile Acid Derivatives as Ligands of the Farnesoid X Receptor: Molecular Determinants for Bile Acid Binding and Receptor Modulation, Curr. Top. Med. Chem., 2014, 14(19), 2159–2174. 12. A. Aranda and A. Pascual, Nuclear Hormone Receptors and Gene Expression, Physiol. Rev., 2001, 81(3), 1269–1304. 13. M. Gabler, J. Kramer, J. Schmidt, J. Pollinger, J. Weber, A. Kaiser, F. Löhr, E. Proschak, M. Schubert-­Zsilavecz and D. Merk, Allosteric Modulation of the Farnesoid X Receptor by a Small Molecule, Sci. Rep., 2018, 8(1), 6846. 14. F. Lien, A. Berthier, E. Bouchaert, C. Gheeraert, J. Alexandre, G. Porez, J. Prawitt, H. Dehondt, M. Ploton and S. Colin, et al., Metformin Interferes with Bile Acid Homeostasis through AMPK-­FXR Crosstalk, J. Clin. Invest., 2014, 124(3), 1037–1051. 15. N. Balasubramaniyan, Y. Luo, A. Q. Sun and F. J. Suchy, SUMOylation of the Farnesoid X Receptor (FXR) Regulates the Expression of FXR Target Genes, J. Biol. Chem., 2013, 288(19), 13850–13862. 16. L. Mi, S. Devarakonda, J. Harp, Q. Han, R. Pellicciari, T. Willson, S. Khorasanizadeh and F. Rastinejad, Structural Basis for Bile Acid Binding and Activation of the Nuclear Receptor FXR, Mol. Cell, 2003, 11, 1093–1100. 17. G. Costantino, A. Entrena-­Guadix, A. Macchiarulo, A. Gioiello and R. Pellicciari, Molecular Dynamics Simulation of the Ligand Binding Domain of Farnesoid X Receptor. Insights into Helix-­12 Stability and Coactivator Peptide Stabilization in Response to Agonist Binding, J. Med. Chem., 2005, 48(9), 3251–3259. 18. N. Wang, Q. Zou, J. Xu, J. Zhang and J. Liu, Ligand Binding and Heterodimerization with Retinoid X Receptor α (RXRα) Induce Farnesoid X Receptor (FXR) Conformational Changes Affecting Coactivator Binding, J. Biol. Chem., 2018, 293(47), 18180–18191.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

106

Chapter 3

19. K. B. Horwitz, T. A. Jackson, D. L. Bain, J. K. Richer, G. S. Takimoto and L. Tung, Nuclear Receptor Coactivators and Corepressors, Mol. Endocrinol., 1996, 10(10), 1167–1177. 20. F. S. Di Leva, C. Festa, C. D'Amore, S. De Marino, B. Renga, M. V. D'Auria, E. Novellino, V. Limongelli, A. Zampella and S. Fiorucci, Binding Mechanism of the Farnesoid X Receptor Marine Antagonist Suvanine Reveals a Strategy To Forestall Drug Modulation on Nuclear Receptors. Design, Synthesis, and Biological Evaluation of Novel Ligands, J. Med. Chem., 2013, 56(11), 4701–4717. 21. J. Li, Y. Lu, R. Liu, X. Xiong, Z. Zhang, X. Zhang, G. Ning and X. Li, DAX1 Suppresses FXR Transactivity as a Novel Co-­Repressor, Biochem. Biophys. Res. Commun., 2011, 412(4), 660–666. 22. M. Downes, M. A. Verdecia, A. J. Roecker, R. Hughes, J. B. Hogenesch, H. R. Kast-­Woelbern, M. E. Bowman, J.-­L. Ferrer, A. M. Anisfeld and P. A. Edwards, A Chemical, Genetic, and Structural Analysis of the Nuclear Bile Acid Receptor FXR, Mol. Cell, 2003, 11(4), 1079–1092. 23. T. Fujino, Y. Sato, M. Une, T. Kanayasu-­Toyoda, T. Yamaguchi, K. Shudo, K. Inoue and T. Nishimaki-­Mogami, In Vitro Farnesoid X Receptor Ligand Sensor Assay Using Surface Plasmon Resonance and Based on Ligand-­Induced Coactivator Association, J. Steroid Biochem. Mol. Biol., 2003, 87(4–5), 247–252. 24. S. Fiorucci, A. Mencarelli, E. Distrutti, G. Palladino and S. Cipriani, Targetting Farnesoid-­X-­Receptor: From Medicinal Chemistry to Disease Treatment, Curr. Med. Chem., 2010, 17(2), 139–159. 25. E. Kanaya, T. Shiraki and H. Jingami, The Nuclear Bile Acid Receptor FXR Is Activated by PGC-­1alpha in a Ligand-­Dependent Manner, Biochem. J., 2004, 382(Pt 3), 913–921. 26. M. Ananthanarayanan, S. Li, N. Balasubramaniyan, F. J. Suchy and M. J. Walsh, Ligand-­Dependent Activation of the Farnesoid X-­Receptor Directs Arginine Methylation of Histone H3 by CARM1, J. Biol. Chem., 2004, 279(52), 54348–54357. 27. G. Rizzo, B. Renga, E. Antonelli, D. Passeri, R. Pellicciari and S. Fiorucci, The Methyl Transferase PRMT1 Functions as Co-­Activator of Farnesoid X Receptor (FXR)/9-­Cis Retinoid X Receptor and Regulates Transcription of FXR Responsive Genes, Mol. Pharmacol., 2005, 68(2), 551–558. 28. S. Fang, S. Tsang, R. Jones, B. Ponugoti, H. Yoon, S.-­Y. Wu, C.-­M. Chiang, T. M. Willson and J. K. Kemper, The P300 Acetylase Is Critical for Ligand-­Activated Farnesoid X Receptor (FXR) Induction of SHP, J. Biol. Chem., 2008, 283(50), 35086–35095. 29. R. Pellicciari, G. Costantino and S. Fiorucci, Farnesoid X Receptor: From Structure to Potential Clinical Applications, J. Med. Chem., 2005, 48(17), 5383–5403. 30. J. Y. Chiang, Recent Advances in Understanding Bile Acid Homeostasis, F1000Research, 2017, 6, 2029.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

107

31. Y. S. Lee, D. Chanda, J. Sim, Y. Y. Park and H. S. Choi, Structure and Function of the Atypical Orphan Nuclear Receptor Small Heterodimer Partner, Int. Rev. Cytol., 2007, 261, 117–158. 32. B. Barranco-­Fragoso, P. Almeda-­Valdes, N. Aguilar-­Olivos and N. Méndez-­Sánchez, The Role of Small Heterodimer Partner in Hepatic Lipid Homeostasis, Ann. Hepatol., 2015, 14(2), 286–287. 33. H. Shimano and R. Sato, SREBP-­Regulated Lipid Metabolism: Convergent Physiology — Divergent Pathophysiology, Nat. Rev. Endocrinol., 2017, 13(12), 710–730. 34. R. Dentin, J. Girard and C. Postic, Carbohydrate Responsive Element Binding Protein (ChREBP) and Sterol Regulatory Element Binding Protein-­1c (SREBP-­1c): Two Key Regulators of Glucose Metabolism and Lipid Synthesis in Liver, Biochimie, 2005, 87(1), 81–86. 35. D. Eberlé, B. Hegarty, P. Bossard, P. Ferré and F. Foufelle, SREBP Transcription Factors: Master Regulators of Lipid Homeostasis, Biochimie, 2004, 86(11), 839–848. 36. M. Piglionica, M. Cariello and A. Moschetta, The Gut–liver Axis in Hepatocarcinoma: A Focus on the Nuclear Receptor FXR and the Enterokine FGF19, Curr. Opin. Pharmacol., 2018, 43, 93–98. 37. C. Degirolamo, C. Sabbà and A. Moschetta, Therapeutic Potential of the Endocrine Fibroblast Growth Factors FGF19, FGF21 and FGF23, Nat. Rev. Drug Discovery, 2016, 15(1), 51–69. 38. N. Bozadjieva, K. M. Heppner and R. J. Seeley, Targeting FXR and FGF19 to Treat Metabolic Diseases—Lessons Learned From Bariatric Surgery, Diabetes, 2018, 67(9), 1720–1728. 39. L. Verbeke, I. Mannaerts, R. Schierwagen, O. Govaere, S. Klein, I. Vander Elst, P. Windmolders, R. Farre, M. Wenes and M. Mazzone, et al., FXR Agonist Obeticholic Acid Reduces Hepatic Inflammation and Fibrosis in a Rat Model of Toxic Cirrhosis, Sci. Rep., 2016, 6(1), 33453. 40. I. T. G. W. Bijsmans, C. Guercini, J. M. Ramos Pittol, W. Omta, A. Milona, D. Lelieveld, D. A. Egan, R. Pellicciari, A. Gioiello and S. W. C. van Mil, The Glucocorticoid Mometasone Furoate Is a Novel FXR Ligand That Decreases Inflammatory but Not Metabolic Gene Expression, Sci. Rep., 2015, 5(1), 14086. 41. Z. Gai, M. Visentin, T. Gui, L. Zhao, W. E. Thasler, S. Häusler, I. Hartling, A. Cremonesi, C. Hiller and G. A. Kullak-­Ublick, Effects of Farnesoid X Receptor Activation on Arachidonic Acid Metabolism, NF-­KB Signaling, and Hepatic Inflammation, Mol. Pharmacol., 2018, 94(2), 802–811. 42. R. M. Gadaleta, K. J. van Erpecum, B. Oldenburg, E. C. L. Willemsen, W. Renooij, S. Murzilli, L. W. J. Klomp, P. D. Siersema, M. E. I. Schipper and S. Danese, et al., Farnesoid X Receptor Activation Inhibits Inflammation and Preserves the Intestinal Barrier in Inflammatory Bowel Disease, Gut, 2011, 60(4), 463–472.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

108

Chapter 3

43. R. M. Nijmeijer, R. M. Gadaleta, S. W. C. van Mil, A. A. van Bodegraven, J. B. A. Crusius, G. Dijkstra, D. W. Hommes, D. J. de Jong, P. C. F. Stokkers and H. W. Verspaget, et al., Farnesoid X Receptor (FXR) Activation and FXR Genetic Variation in Inflammatory Bowel Disease, PLoS One, 2011, 6(8), 4–9. 44. X. Zhou, L. Cao, C. Jiang, Y. Xie, X. Cheng, K. W. Krausz, Y. Qi, L. Sun, Y. M. Shah and F. J. Gonzalez, et al., PPARα-­UGT Axis Activation Represses Intestinal FXR-­FGF15 Feedback Signalling and Exacerbates Experimental Colitis, Nat. Commun., 2014, 5(1), 4573. 45. G. M. Hirschfield, A. Mason, V. Luketic, K. Lindor, S. C. Gordon, M. Mayo, K. V. Kowdley, C. Vincent, H. C. Bodhenheimer and A. Parés, et al., Efficacy of Obeticholic Acid in Patients With Primary Biliary Cirrhosis and Inadequate Response to Ursodeoxycholic Acid, Gastroenterology, 2015, 148(4), 751–761.e8. 46. F. Nevens, P. Andreone, G. Mazzella, S. I. Strasser, C. Bowlus, P. Invernizzi, J. P. H. Drenth, P. J. Pockros, J. Regula and U. Beuers, et al., A Placebo-­Controlled Trial of Obeticholic Acid in Primary Biliary Cholangitis, N. Engl. J. Med., 2016, 375(7), 631–643. 47. K. V. Kowdley, V. Luketic, R. Chapman, G. M. Hirschfield, R. Poupon, C. Schramm, C. Vincent, C. Rust, A. Parés and A. Mason, et al., A Randomized Trial of Obeticholic Acid Monotherapy in Patients with Primary Biliary Cholangitis, Hepatology, 2018, 67(5), 1890–1902. 48. S. Mudaliar, R. R. Henry, A. J. Sanyal, L. Morrow, H. U. Marschall, M. Kipnes, L. Adorini, C. I. Sciacca, P. Clopton and E. Castelloe, et al., Efficacy and Safety of the Farnesoid X Receptor Agonist Obeticholic Acid in Patients with Type 2 Diabetes and Nonalcoholic Fatty Liver Disease, Gastroenterology, 2013, 145(3), 574–582.e1. 49. B. A. Neuschwander-­Tetri, R. Loomba, A. J. Sanyal, J. E. Lavine, M. L. Van Natta, M. F. Abdelmalek, N. Chalasani, S. Dasarathy, A. M. Diehl and B. Hameed, et al., Farnesoid X Nuclear Receptor Ligand Obeticholic Acid for Non-­Cirrhotic, Non-­Alcoholic Steatohepatitis (FLINT): A Multicentre, Randomised, Placebo-­Controlled Trial, Lancet, 2014, 385(9972), 956–965. 50. S. Fiorucci, E. Antonelli, G. Rizzo, B. Renga, A. Mencarelli, L. Riccardi, S. Orlandi, R. Pellicciari and A. Morelli, The Nuclear Receptor SHP Mediates Inhibition of Hepatic Stellate Cells by FXR and Protects against Liver Fibrosis, Gastroenterology, 2004, 127(5), 1497–1512. 51. T. Goto, M. Itoh, T. Suganami, S. Kanai, I. Shirakawa, T. Sakai, M. Asakawa, T. Yoneyama, T. Kai and Y. Ogawa, Obeticholic Acid Protects against Hepatocyte Death and Liver Fibrosis in a Murine Model of Nonalcoholic Steatohepatitis, Sci. Rep., 2018, 8(1), 8157. 52. K. Zhao, J. He, Y. Zhang, Z. Xu, H. Xiong, R. Gong, S. Li, S. Chen and F. He, Activation of FXR Protects against Renal Fibrosis via Suppressing Smad3 Expression, Sci. Rep., 2016, 6(1), 37234.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

109

53. Z. Hu, L. Ren, C. Wang, B. Liu and G. Song, Effect of Chenodeoxycholic Acid on Fibrosis, Inflammation and Oxidative Stress in Kidney in High-­ Fructose-­Fed Wistar Rats, Kidney Blood Pressure Res., 2012, 36(2), 85–97. 54. Z. Gai, L. Chu, Z. Xu, X. Song, D. Sun and G. A. Kullak-­Ublick, Farnesoid X Receptor Activation Protects the Kidney from Ischemia-­Reperfusion Damage, Sci. Rep., 2017, 7(1), 9815. 55. T. Jiang, X. X. Wang, P. Scherzer, P. Wilson, J. Tallman, H. Takahashi, J. Li, M. Iwahashi, E. Sutherland and L. Arend, et al., Farnesoid X Receptor Modulates Renal Lipid Metabolism, Fibrosis, and Diabetic Nephropathy, Diabetes, 2007, 56(10), 2485–2493. 56. P. Comeglio, S. Filippi, E. Sarchielli, A. Morelli, I. Cellai, F. Corcetto, C. Corno, E. Maneschi, A. Pini and L. Adorini, et al., Anti-­Fibrotic Effects of Chronic Treatment with the Selective FXR Agonist Obeticholic Acid in the Bleomycin-­Induced Rat Model of Pulmonary Fibrosis, J. Steroid Biochem. Mol. Biol., 2017, 168, 26–37. 57. P. R. Maloney, D. J. Parks, C. D. Haffner, A. M. Fivush, G. Chandra, K. D. Plunket, K. L. Creech, L. B. Moore, J. G. Wilson and M. C. Lewis, et al., Identification of a Chemical Tool for the Orphan Nuclear Receptor FXR, J. Med. Chem., 2000, 43(16), 2971–2974. 58. B. Flatt, R. Martin, T. L. Wang, P. Mahaney, B. Murphy, X. H. Gu, P. Foster, J. Li, P. Pircher and M. Petrowski, et al., Discovery of XL335 (WAY-­ 362450), a Highly Potent, Selective, and Orally Active Agonist of the Farnesoid X Receptor (FXR), J. Med. Chem., 2009, 52(4), 904–907. 59. H. G. F. Richter, G. M. Benson, D. Blum, E. Chaput, S. Feng, C. Gardes, U. Grether, P. Hartman, B. Kuhn and R. E. Martin, et al., Discovery of Novel and Orally Active FXR Agonists for the Potential Treatment of Dyslipidemia & Diabetes, Bioorg. Med. Chem. Lett., 2011, 21(1), 191–194. 60. H. G. F. Richter, G. M. Benson, K. H. Bleicher, D. Blum, E. Chaput, N. Clemann, S. Feng, C. Gardes, U. Grether and P. Hartman, et al., Optimization of a Novel Class of Benzimidazole-­Based Farnesoid X Receptor (FXR) Agonists to Improve Physicochemical and ADME Properties, Bioorg. Med. Chem. Lett., 2011, 21(4), 1134–1140. 61. E. Proschak, P. Heitel, L. Kalinowsky and D. Merk, Opportunities and Challenges for Fatty Acid Mimetics in Drug Discovery, J. Med. Chem., 2017, 60(13), 5235–5266. 62. C. Lamers, M. Schubert-­Zsilavecz and D. Merk, Medicinal Chemistry and Pharmacological Effects of Farnesoid X Receptor (FXR) Antagonists, Curr. Top. Med. Chem., 2014, 14(19), 2188–2205. 63. T. Nishimaki-­Mogami, Y. Kawahara, N. Tamehiro, T. Yoshida, K. Inoue, Y. Ohno, T. Nagao and M. Une, 5α-­Bile Alcohols Function as Farnesoid X Receptor Antagonists, Biochem. Biophys. Res. Commun., 2006, 339(1), 386–391. 64. A. Akwabi-­Ameyaw, J. Y. Bass, R. D. Caldwell, J. A. Caravella, L. Chen, K. L. Creech, D. N. Deaton, S. A. Jones, I. Kaldor and Y. Liu, et al.,

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

110



















Chapter 3

Conformationally Constrained Farnesoid X Receptor (FXR) Agonists: Naphthoic Acid-­Based Analogs of GW 4064, Bioorg. Med. Chem. Lett., 2008, 18(15), 4339–4343. 65. U. Meyer, G. Costantino, A. Macchiarulo and R. Pellicciari, Is Antagonism of E/Z-­Guggulsterone at the Farnesoid X Receptor Mediated by a Noncanonical Binding Site? A Molecular Modeling Study, J. Med. Chem., 2005, 48(22), 6948–6955. 66. D. Merk, M. Gabler, R. C. Gomez, D. Flesch, T. Hanke, A. Kaiser, C. Lamers, O. Werz, G. Schneider and M. Schubert-­Zsilavecz, Anthranilic Acid Derivatives as Novel Ligands for Farnesoid X Receptor (FXR), Bioorg. Med. Chem., 2014, 22(8), 2447–2460. 67. D. Merk, C. Lamers, K. Ahmad, R. Carrasco Gomez, G. Schneider, D. Steinhilber, M. Schubert-­zsilavecz, R. C. Gomez, G. Schneider and D. Steinhilber, et al., Extending the Structure–Activity Relationship of Anthranilic Acid Derivatives as Farnesoid X Receptor Modulators: Development of a Highly Potent Partial Farnesoid X Receptor Agonist, J. Med. Chem., 2014, 57(19), 8035–8055. 68. S. Schierle, J. Schmidt, A. Kaiser and D. Merk, Selective Optimization of Pranlukast to Farnesoid X Receptor Modulators, ChemMedChem, 2018, 2530–2545. 69. D. Flesch, M. Gabler, A. Lill, R. C. Gomez, R. Steri, G. Schneider, H. Stark, M. Schubert-­Zsilavecz and D. Merk, Fragmentation of GW4064 Led to a Highly Potent Partial Farnesoid X Receptor Agonist with Improved Drug-­like Properties, Bioorg. Med. Chem., 2015, 23(13), 3490–3498. 70. D. Merk, F. Grisoni, K. Schaller, L. Friedrich and G. Schneider, Discovery of Novel Molecular Frameworks of Farnesoid X Receptor Modulators by Ensemble Machine Learning, ChemistryOpen, 2018, 7–14. 71. A. P. Bento, A. Gaulton, A. Hersey, L. J. Bellis, J. Chambers, M. Davies, F. A. Krüger, Y. Light, L. Mak and S. McGlinchey, et al., The {ChEMBL} Bioactivity Database: An Update, Nucleic Acids Res., 2014, 42(Database issue), D1083–D1090. 72. D. Merk, D. Steinhilber and M. Schubert-­Zsilavecz, Characterizing Ligands for Farnesoid X Receptor-­Available in Vitro Test Systems for Farnesoid X Receptor Modulator Development, Expert Opin. Drug Discovery, 2014, 9(1), 27–37. 73. D. Flesch, S.-­Y. Cheung, J. Schmidt, M. Gabler, P. Heitel, J. S. Kramer, A. Kaiser, M. Hartmann, M. Lindner and K. Lüddens-­Dämgen, et al., Non-­ Acidic Farnesoid X Receptor Modulators, J. Med. Chem., 2017, 60(16), 7199–7205. 74. J. Schmidt, M. Rotter, T. Weiser, S. Wittmann, L. Weizel, A. Kaiser, J. Heering, T. Goebel, C. Angioni and M. Wurglics, et al., A Dual Modulator of Farnesoid X Receptor and Soluble Epoxide Hydrolase to Counter Nonalcoholic Steatohepatitis, J. Med. Chem., 2017, 60(18), 7703–7724. 75. P. Heitel, L. Gellrich, J. Heering, T. Goebel, A. Kahnt, E. Proschak, M. Schubert-­Zsilavecz and D. Merk, Urate Transporter Inhibitor Lesinurad Is a Selective Peroxisome Proliferator-­Activated Receptor Gamma Modulator (SPPARγM) in Vitro, Sci. Rep., 2018, 8(1), 13554.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

111

76. L. Gellrich and D. Merk, Therapeutic Potential of Peroxisome Proliferator-­Activated Receptor Modulation in Non-­Alcoholic Fatty Liver Disease and Non-­Alcoholic Steatohepatitis, Nucl. Recept. Res., 2017, 4, 101310. 77. L. Wang, P. Si, Y. Sheng, Y. Chen, P. Wan, X. Shen, Y. Tang, L. Chen and W. Li, Discovery of New Non-­Steroidal Farnesoid X Receptor Modulators Through 3D Shape Similarity Search and Structure-­Based Virtual Screening, Chem. Biol. Drug Des., 2015, 85(4), 481–487. 78. J. Fu, P. Si, M. Zheng, L. Chen, X. Shen, Y. Tang and W. Li, Discovery of New Non-­Steroidal FXR Ligands via a Virtual Screening Workflow Based on Phase Shape and Induced Fit Docking, Bioorg. Med. Chem. Lett., 2012, 22(22), 6848–6853. 79. G. Deng, W. Li, J. Shen, H. Jiang, K. Chen and H. Liu, Pyrazolidine-­3, 5-­Dione Derivatives as Potent Non-­Steroidal Agonists of Farnesoid X Receptor: Virtual Screening, Synthesis, and Biological Evaluation, Bioorg. Med. Chem. Lett., 2008, 18(20), 5497–5502. 80. M. Marinozzi, A. Carotti, E. Sansone, A. Macchiarulo, E. Rosatelli, R. Sardella, B. Natalini, G. Rizzo, L. Adorini and D. Passeri, et al., Pyrazole[3,4-­e][1,4]Thiazepin-­7-­One Derivatives as a Novel Class of Farnesoid X Receptor (FXR) Agonists, Bioorg. Med. Chem., 2012, 20(11), 3429–3445. 81. X. Gao, T. Fu, C. Wang, C. Ning, Y. Kong, Z. Liu, H. Sun, X. Ma, K. Liu and Q. Meng, Computational Discovery and Experimental Verification of Farnesoid X Receptor Agonist Auraptene to Protect against Cholestatic Liver Injury, Biochem. Pharmacol., 2017, 146, 127–138. 82. Y. Diao, J. Jiang, S. Zhang, S. Li, L. Shan, J. Huang, W. Zhang and H. Li, Discovery of Natural Products as Novel and Potent FXR Antagonists by Virtual Screening, Front. Chem., 2018, 6, 140. 83. R. Steri, J. Achenbach, D. Steinhilber, M. Schubert-­Zsilavecz and E. Proschak, Investigation of Imatinib and Other Approved Drugs as Starting Points for Antidiabetic Drug Discovery with FXR Modulating Activity, Biochem. Pharmacol., 2012, 83(12), 1674–1681. 84. J. Achenbach, M. Gabler, R. Steri, M. Schubert-­Zsilavecz and E. Proschak, Identification of Novel Farnesoid X Receptor Modulators Using a Combined Ligand-­ and Structure-­Based Virtual Screening, MedChemComm, 2013, 4(6), 920. 85. Z. Gaieb, S. Liu, S. Gathiaka, M. Chiu, H. Yang, C. Shao, V. A. Feher, W. P. Walters, B. Kuhn and M. G. Rudolph, et al., D3R Grand Challenge 2: Blind Prediction of Protein–ligand Poses, Affinity Rankings, and Relative Binding Free Energies, J. Comput.-­Aided Mol. Des., 2018, 32(1), 1–20. 86. R. Pellicciari, S. Fiorucci, E. Camaioni, C. Clerici, G. Costantino, P. R. Maloney, A. Morelli, D. J. Parks and T. M. Willson, 6α-­Ethyl-­Chenodeoxycholic Acid (6-­ECDCA), a Potent and Selective FXR Agonist Endowed with Anticholestatic Activity, J. Med. Chem., 2002, 45(17), 3569–3572. 87. A. Roda, R. Pellicciari, C. Cerrè, C. Polimeni, B. Sadeghpour, M. Marinozzi, G. C. Forti and E. Sapigni, New 6-­Substituted Bile Acids:

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

112



















Chapter 3

Physico-­Chemical and Biological Properties of 6 Alpha-­Methyl Ursodeoxycholic Acid and 6 Alpha-­Methyl-­7-­Epicholic Acid, J. Lipid Res., 1994, 35(12), 2268–2279. 88. R. Aldini, A. Roda, M. Montagnani, C. Cerre, R. Pellicciari and E. Roda, Relationship between Structure and Intestinal Absorption of Bile Acids with a Steroid or Side-­Chain Modification, Steroids, 1996, 61(10), 590–597. 89. R. Pellicciari, G. Costantino, E. Camaioni, B. M. Sadeghpour, A. Entrena, T. M. Willson, S. Fiorucci, C. Clerici and A. Gioiello, Bile Acid Derivatives as Ligands of the Farnesoid X Receptor. Synthesis, Evaluation, and Structure–Activity Relationship of a Series of Body and Side Chain Modified Analogues of Chenodeoxycholic Acid, J. Med. Chem., 2004, 47(18), 4559–4569. 90. V. Sepe, C. Festa, B. Renga, A. Carino, S. Cipriani, C. Finamore, D. Masullo, F. del Gaudio, M. C. Monti and S. Fiorucci, et al., Insights on FXR Selective Modulation. Speculation on Bile Acid Chemical Space in the Discovery of Potent and Selective Agonists, Sci. Rep., 2016, 6(1), 19008. 91. V. Sepe, E. Distrutti, S. Fiorucci and A. Zampella, Farnesoid X Receptor Modulators 2014-­Present: A Patent Review, Expert Opin. Ther. Pat., 2018, 28(5), 351–364. 92. A. Zampella and S. Fiorucci, WO Pat., WO2015181275A1, 2015. 93. R. Pellicciari, A. Gioiello, P. Sabbatini, F. Venturoni, R. Nuti, C. Colliva, G. Rizzo, L. Adorini, M. Pruzanski and A. Roda, et al., Avicholic Acid: A Lead Compound from Birds on the Route to Potent TGR5 Modulators, ACS Med. Chem. Lett., 2012, 3(4), 273–277. 94. A. Gioiello, A. Macchiarulo, A. Carotti, P. Filipponi, G. Costantino, G. Rizzo, L. Adorini and R. Pellicciari, Extending SAR of Bile Acids as FXR Ligands: Discovery of 23-­N-­(Carbocinnamyloxy)-­3α,7α-­Dihydroxy-­6α -­Ethyl-­24-­nor-­5β-­Cholan-­23-­Amine, Bioorg. Med. Chem., 2011, 19(8), 2650–2658. 95. G. Rizzo, D. Passeri, F. De Franco, G. Ciaccioli, L. Donadio, G. Rizzo, S. Orlandi, B. Sadeghpour, X. X. Wang and T. Jiang, et al., Functional Characterization of the Semisynthetic Bile Acid Derivative INT-­767, a Dual Farnesoid X Receptor and TGR5 Agonist, Mol. Pharmacol., 2010, 78(4), 617–630. 96. P. Comeglio, I. Cellai, T. Mello, S. Filippi, E. Maneschi, F. Corcetto, C. Corno, E. Sarchielli, A. Morelli and E. Rapizzi, et al., INT-­767 Prevents NASH and Promotes Visceral Fat Brown Adipogenesis and Mitochondrial Function, J. Endocrinol., 2018, 238(2), 107–127. 97. J. D. Roth, M. Feigh, S. S. Veidal, L. K. Fensholdt, K. T. Rigbolt, H. H. Hansen, L. C. Chen, M. Petitjean, W. Friley and N. Vrang, et al., INT-­767 Improves Histopathological Features in a Diet-­Induced Ob/Ob Mouse Model of Biopsy-­Confirmed Non-­Alcoholic Steatohepatitis, World J. Gastroenterol., 2018, 24(2), 195–210. 98. Y.-­B. Hu, X.-­Y. Liu and W. Zhan, Farnesoid X Receptor Agonist INT-­767 Attenuates Liver Steatosis and Inflammation in Rat Model of Nonalcoholic Steatohepatitis, Drug Des., Dev. Ther., 2018, 12, 2213–2221.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

113

99. X. X. Wang, Y. Luo, D. Wang, L. Adorini, M. Pruzanski, E. Dobrinskikh and M. Levi, A Dual Agonist of Farnesoid X Receptor (FXR) and the G Protein–coupled Receptor TGR5, INT-­767, Reverses Age-­Related Kidney Disease in Mice, J. Biol. Chem., 2017, 292(29), 12018–12024. 100. X. X. Wang, D. Wang, Y. Luo, K. Myakala, E. Dobrinskikh, A. Z. Rosenberg, J. Levi, J. B. Kopp, A. Field and A. Hill, et al., FXR/TGR5 Dual Agonist Prevents Progression of Nephropathy in Diabetes and Obesity, J. Am. Soc. Nephrol., 2018, 29(1), 118–137. 101. R. Pellicciari, H. Sato, A. Gioiello, G. Costantino, A. Macchiarulo, B. M. Sadeghpour, G. Giorgi, K. Schoonjans and J. Auwerx, Nongenomic Actions of Bile Acids. Synth & Characterization of 23-­ & 6,23-­Alkyl-­Sub Bile Acid Deriv as Selective Modulators for GPCR TGR5, J. Med. Chem., 2007, 50(18), 4265–4268. 102. C. Festa, B. Renga, C. D'Amore, V. Sepe, C. Finamore, S. De Marino, A. Carino, S. Cipriani, M. C. Monti and A. Zampella, et al., Exploitation of Cholane Scaffold for the Discovery of Potent and Selective Farnesoid X Receptor (FXR) and G-­Protein Coupled Bile Acid Receptor 1 (GP-­BAR1) Ligands, J. Med. Chem., 2014, 57(20), 8477–8495. 103. T. Lieu, G. Jayaweera, P. Zhao, D. P. Poole, D. Jensen, M. Grace, P. McIntyre, R. Bron, Y. M. Wilson and M. Krappitz, et al., The Bile Acid Receptor TGR5 Activates the TRPA1 Channel to Induce Itch in Mice, Gastroenterology, 2014, 147(6), 1417–1428. 104. A. Roda, R. Pellicciari, A. Gioiello, F. Neri, C. Camborata, D. Passeri, F. De Franco, S. Spinozzi, C. Colliva and L. Adorini, et al., Semisynthetic Bile Acid FXR and TGR5 Agonists: Physicochemical Properties, Pharmacokinetics, and Metabolism in the Rat, J. Pharmacol. Exp. Ther., 2014, 350(1), 56–68. 105. A. F. Hofmann and L. R. Hagey, Key Discoveries in Bile Acid Chemistry and Biology and Their Clinical Applications: History of the Last Eight Decades, J. Lipid Res., 2014, 55(8), 1553–1595. 106. R. Pellicciari, D. Passeri, F. De Franco, S. Mostarda, P. Filipponi, C. Colliva, R. M. Gadaleta, P. Franco, A. Carotti and A. Macchiarulo, et al., Discovery of 3α,7α,11β-­Trihydroxy-­6α-­Ethyl-­5β-­Cholan-­24-­Oic Acid (TC-­100), a Novel Bile Acid as Potent and Highly Selective FXR Agonist for Enterohepatic Disorders, J. Med. Chem., 2016, 59(19), 9201–9214. 107. S. G. Blanchard, A. Kliewer, J. Lehmann, D. J. Parks, J. B. Stimmel and T. M. Willson, WO Pat., WO2000037077A1, 2000. 108. C. Gege, O. Kinzel, C. Steeneck, A. Schulz and C. Kremoser, Knocking on FXR's Door:The “Hammerhead”-­Structure Series of FXRs Agonists– Amphiphilic Isoxazoles with Potent In Vitro and In Vivo Activities, Curr. Top. Med. Chem., 2015, 14(19), 2143–2158. 109. D. N. Deaton, R. B. McFadyen, F. Navas III, R. Caldwell and P. K. Spearing, WO Pat., WO2007076260A2, 2007. 110. S. D. Boggs, J. L. Collins, S. M. Hyatt and P. R. Maloney, WO Pat., WO2004/048349, 2004.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

114

Chapter 3

111. U. Bauer, Z. Cheruvallath, U. Deuschle, E. Dneprovskaia, T. Gahman, K. Giegrich, R. Hanecak, N. Hebert, J. Kiely, I. Kober, M. Kogl, H. Kranz, C. Kremoser, M. Lee, K. Otte, C. Sage and M. Sud, WO Pat., WO2003015771A1, 2003. 112. M. G. Bell, R. A. Doti, M. S. Dowling, M. J. Genin, P. A. Lander, T. Ma, N. B. Mantlo, J. M. Ochoada, L. S. Stelzer, R. E. Stites and A. M. Warshawsky, WO Pat., WO2007140174A2, 2007. 113. M. G. Bell, M. J. Genin, P. A. Lander, L. S. Stelzer, R. A. Doti, F. J. Agejas-­ Chicharro, M. Bueno, B. Ana, P. R. Manninen, J. M. Ochoada, Q. Shen, A. M. Warshawsky, T. Ma and R. E. Stites, WO Pat., WO2007092751A2, 2007. 114. M. G. Bell, R. A. Doti, M. J. Genin, P. A. Lander, T. Ma, P. R. Manninen, J. M. Ochoada, F. Qu, L. S. Stelzer, R. E. Stites and A. M. Warshawsky, WO Pat., WO2007140183A1, 2007. 115. U. Abel, T. Schlüter, A. Schulz, E. Hambruch, C. Steeneck, M. Hornberger, T. Hoffmann, S. Perović-­Ottstadt, O. Kinzel and M. Burnet, et al., Synthesis and Pharmacological Validation of a Novel Series of Non-­Steroidal FXR Agonists, Bioorg. Med. Chem. Lett., 2010, 20(16), 4911–4917. 116. C. Kremoser, U. Deuschle, U. Abel and A. Schulz, WO Pat., WO2008025539A1, 2008. 117. C. Kremoser, U. Deuschle, U. Abel and A. Schulz, WO Pat., WO2008025540A1, 2008. 118. U. Abel and C. Kremoser, WO Pat., WO2009149795A2, 2009. 119. U. Deuschle, C. Kremoser, WO Pat., WO2013037482A1, 2013. 120. J. Y. Bass, J. A. Caravella, L. Chen, K. L. Creech, D. N. Deaton, K. P. Madauss, H. B. Marr, R. B. McFadyen, A. B. Miller and W. Y. Mills, et al., Conformationally Constrained Farnesoid X Receptor (FXR) Agonists: Heteroaryl Replacements of the Naphthalene, Bioorg. Med. Chem. Lett., 2011, 21(4), 1206–1213. 121. J. Y. Bass III, D. N. Deaton, J. Caravella, R. B. McFayden, F. Navas III and P. K. Spearing, WO Pat., WO2008051942A2, 2008. 122. A. Akwabi-­Ameyaw, J. A. Caravella, L. Chen, K. L. Creech, D. N. Deaton, K. P. Madauss, H. B. Marr, A. B. Miller, F. Navas and D. J. Parks, et al., Conformationally Constrained Farnesoid X Receptor (FXR) Agonists: Alternative Replacements of the Stilbene, Bioorg. Med. Chem. Lett., 2011, 21(20), 6154–6160. 123. J. Y. Bass, R. D. Caldwell, J. A. Caravella, L. Chen, K. L. Creech, D. N. Deaton, K. P. Madauss, H. B. Marr, R. B. McFadyen and A. B. Miller, et al., Substituted Isoxazole Analogs of Farnesoid X Receptor (FXR) Agonist GW4064, Bioorg. Med. Chem. Lett., 2009, 19(11), 2969–2973. 124. A. Akwabi-­Ameyaw, J. Y. Bass, R. D. Caldwell, J. A. Caravella, L. Chen, K. L. Creech, D. N. Deaton, K. P. Madauss, H. B. Marr and R. B. McFadyen, et al., FXR Agonist Activity of Conformationally Constrained Analogs of GW 4064, Bioorg. Med. Chem. Lett., 2009, 19(16), 4733–4739. 125. A. A. Akwabi-­Ameyaw, D. N. Deaton, R. B. McFadyen and F. Navas III, WO Pat., WO2009005998A1, 2009.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

Discovery, Structural Refinement and Therapeutic Potential

115

126. M. J. Genin, F. J. Agejas-­Chicharro, A. B. Bueno Melendo, P. R. Manninen and A. M. Warshawsky, WO Pat., WO2009012125A1, 2009. 127. M. J. Genin, A. B. Bueno, J. Agejas Francisco, P. R. Manninen, W. P. Bocchinfuso, C. Montrose-­Rafizadeh, E. A. Cannady, T. M. Jones, J. R. Stille and E. Raddad, et al., Discovery of 6-­(4-­{[5-­Cyclopropyl-­3-­(2,6-­Dich lorophenyl)Isoxazol-­4-­Yl]Methoxy}piperidin-­1-­Yl)-­1-­Methyl-­1H-­Indole-­ 3-­Carboxylic Acid: A Novel FXR Agonist for the Treatment of Dyslipidemia, J. Med. Chem., 2015, 58(24), 9768–9772. 128. C. Kremoser, U. Abel, C. Steeneck and O. Kinzel, WO Pat., WO2011020615A1, 2011. 129. O. Kinzel, C. Steeneck, T. Schlüter, A. Schulz, C. Gege, U. Hahn, E. Hambruch, M. Hornberger, A. Spalwisz and K. Frick, et al., Novel Substituted Isoxazole FXR Agonists with Cyclopropyl, Hydroxycyclobutyl and Hydroxyazetidinyl Linkers: Understanding and Improving Key Determinants of Pharmacological Properties, Bioorg. Med. Chem. Lett., 2016, 26(15), 3746–3753. 130. https://w w w.gilead.com/ne ws-­a nd-­p ress/press-­r oom/press-­ releases/2018/11/gilead-­announces-­positive-­phase-­2-­results-­for-­gs9674-­ in-­primary-­sclerosing-­cholangitis-­psc-­at-­the-­liver-­meeting-­2018. 131. D. C. Tully, P. V. Rucker, P. B. Alper, D. Mutnick and D. Chianelli, WO Pat., WO2012/087519, 2012. 132. D. C. Tully, A. Vidal, D. Mutnick and P. B. Alper, WO Pat., WO2012/087520, 2012. 133. D. C. Tully and D. Chianelli, WO Pat., WO2012/087521, 2012. 134. D. C. Tully, P. V. Rucker, D. Chianelli, J. Williams, A. Vidal, P. B. Alper, D. Mutnick, B. Bursulaya, J. Schmeits and X. Wu, et al., Discovery of Tropifexor (LJN452), a Highly Potent Non-­Bile Acid FXR Agonist for the Treatment of Cholestatic Liver Diseases and Nonalcoholic Steatohepatitis (NASH), J. Med. Chem., 2017, 60(24), 9960–9973. 135. O. Kinzel, K. Kremoser, P. A. Blomgren, K. S. Currie, J. E. Kropf, A. Schmitt, W. J. Watkins, J. Xu and C. Gege, WO Pat., WO201696116, 2016. 136. O. Kinzel, K. Kremoser, A. Schmitt and C. Gege, WO Pat., WO201696115, 2016. 137. X. Wang, X. Yang, S. Pan, R. Guo, J. Wu, Y. Zhang and C. Cheng, WO Pat., WO2016127924, 2016. 138. G. Wang and L. Beigelman, WO Pat., WO2017147047, 2017. 139. Y. S. Or, R. Shen, X. Xing, B. Granger, B. Wang, J. Ma, J. He, Y. He, J. Long and G. Wang, WO Pat., WO2017189651, 2017. 140. Y. S. Or, B. Granger, R. Shen, X. Xing, B. Wang, J. Ma, J. He, J. Long, Y. He and G. Wang, WO Pat., WO2017189652, 2017. 141. Y. S. Or, J. Ma, B. Wang, Y. He, X. Xing, R. Shen, B. Granger, J. He, J. Long and G. Wang, WO Pat., WO2017201150, 2017. 142. Y. S. Or, H. Yong, R. Shen, X. Xing, B. Granger, B. Wang, J. Ma, J. He, J. Long and G. Wang, WO Pat., WO2017201152, 2017. 143. 贺海鹰, 余军, 陈曙辉, WO Pat., WO2018214959, 2018.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00076

116

Chapter 3

144. 刘钢, 于华, 杨定菊, 何婷, 康熙伟, 蔡家强, 刘金明, 吴勇勇, 曾宏, 宋宏梅, 苏东海, 周信, 谭玉婷, 王利春, 王晶翼, WO Pat., WO2018133730, 2018. 145. J.-­H. Kang, H.-­S. Lee, Y.-­S. Lee, J.-­A. Jeong, S.-­W. Kwon, J.-­G. Kim, K.-­S. Kim, D.-­K. Song, S.-­Y. Park, K.-­J. Kim, J.-­H. Choi and H.-­M. Hwang, WO Pat., WO2018190643, 2018. 146. R. Martin, T.-­L. Wang, B. T. Flatt, X.-­H. Gu and R. Griffith, WO Pat., WO03099821, 2003. 147. B. Busch, B. T. Flatt, X.-­H. Gu, R. Martin, R. Mohan, T.-­L. Wang and J. H. Wu, WO Pat., WO2005056554, 2005. 148. J. F. Mehlmann, M. L. Crawley, J. T. Lundquist IV, R. J. Unwalla, D. C. Harnish, M. J. Evans, C. Y. Kim, J. E. Wrobel and P. E. Mahaney, Pyrrole[2,3-­d]Azepino Compounds as Agonists of the Farnesoid X Receptor (FXR), Bioorg. Med. Chem. Lett., 2009, 19(18), 5289–5292. 149. J. T. Lundquist IV, D. C. Harnish, C. Y. Kim, J. F. Mehlmann, R. J. Unwalla, K. M. Phipps, M. L. Crawley, T. Commons, D. M. Green and W. Xu, et al., Improvement of Physiochemical Properties of the Tetrahydroaze­ pinoindole Series of Farnesoid X Receptor (FXR) Agonists: Beneficial Modulation of Lipids in Primates, J. Med. Chem., 2010, 53(4), 1774–1787. 150. R. Mohan and B. A. Pratt, WO Pat., WO2016151403, 2016. 151. G. Wang and L. Beigelman, WO Pat., WO2017143134, 2017. 152. B. A. Pratt and R. Mohan, WO Pat., WO2016081918, 2016. 153. B. A. Pratt and R. Mohan, WO Pat., WO2017205633, 2017. 154. K. C. Nicolaou, R. M. Evans, A. J. Roecker, R. Hughes, M. Downes and J. A. Pfefferkorn, Discovery and Optimization of Non-­Steroidal FXR Agonists from Natural Product-­like Libraries, Org. Biomol. Chem., 2003, 1(6), 908–920. 155. R. M. Evans, M. Downes, A. Atkins, S. Fang, J. M. Suh, T. J. BAiga, R. T. Yu and J. F. W. Keana, WO Pat., WO2015138969, 2015. 156. N. D. Smith, S. P. Govek and K. L. Douglas, WO Pat., WO2017049176, 2017. 157. N. D. Smith and S. P. Govek, WO Pat., WO2017049177, 2017. 158. V. Massafra, R. Pellicciari, A. Gioiello and S. W. C. van Mil, Progress and Challenges of Selective Farnesoid X Receptor Modulation, Pharmacol. Ther., 2018, 191, 162–177. 159. D. Merk, S. Sreeramulu, D. Kudlinzki, K. Saxena, V. Linhard, S. L. Gande, F. Hiller, C. Lamers, E. Nilsson, A. Aagaard, L. Wissler, N. Dekker, K. Bamberg, M. Schubert-Zsilavecz and H. Schwalbe, Nat. Commun., 2019, 10, 2915.

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Chapter 4

Autotaxin Inhibitors in Fibrosis N. Desroy* and B. Heckmann Galapagos SASU, 102 Avenue Gaston Roussel, 93230 Romainville, France *E-­mail: [email protected]

4.1  Introduction Autotaxin (ATX) is a 125 kDa circulating glycoprotein which was originally identified as an autocrine motility factor isolated from A2058 melanoma cells in 1992.1 ATX belongs to the family of ectonucleotide pyrophospha­ tase/phosphodiesterase (ENPP) proteins which consists of seven enzymes that hydrolyse pyrophosphate or phosphodiester bonds in (di)nucleotides and phospholipids. In 2002 ATX, or ENPP2, was recognized as plasma lyso­ phospholipase D (LysoPLD), an enzyme which catalyses the production of lysophosphatidic acid (LPA) through hydrolysis of lysophosphatidyl choline (LPC) in blood.2 Although five alternative splicing isoforms of ATX have been identified as ATXα, ATXβ, ATXγ, ATXδ and ATXε, they all have been shown to be catalyti­ cally active and a clear understanding of the role of each specific isoform is still lacking.3 ATX isoforms show different expression across tissues, ATXβ is mainly expressed in peripheral tissues and is identical to plasma LysoPLD. ATX is the major enzyme responsible for the production of lysophosphatidic acids (LPAs) through hydrolysis of lysophosphatidyl choline in blood (Figure 4.1).4 LPAs consist of a glycerophosphate backbone esterified with a fatty acid containing a saturated or unsaturated carbon chain of varying length. Other ways to produce LPA exist, such as hydrolysis of phosphatidic

  Drug Discovery Series No. 73 Anti-­fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

117

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

118

Figure 4.1  (A)  Production of LPA by ATX or sPLA and action of LPA on its receptors. (B) Examples of abundant LPA species in blood.

acids (PA) by secreted phospholipases (sPLA), however, there is experimental evidence that ATX is the major source of LPA production in blood. Mice het­ erozygous for an ATX deletion have approximately 50% of the circulating LPA levels of wild-­t ype animals.5 Administration of ATX inhibitors to rodents also resulted in more than 90% depletion of LPA in blood. LPAs are bioactive phospholipids that elicit a variety of cellular responses, including cytokine secretion, cell proliferation, cell migration, differentia­ tion and survival, through their interaction with at least six G-­protein-­coupled receptors (GPCRs) known as LPA receptors LPA1–6.6 Deregulation of ATX–LPA signalling has been implicated in a variety of diseases such as fibrosis, can­ cer, vascular development and inflammatory disorders among others.7

4.1.1  Role of ATX/LPA Biology in Fibrosis Several observations on patients and in animal models linked ATX–LPA biol­ ogy to the pathophysiology of fibrosis and idiopathic pulmonary fibrosis (IPF) in particular.8 Higher amounts of LPA in bronchoalveolar lavage fluids

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

119

(BALF) and of ATX in lung tissue were observed in samples from IPF and fibrotic non-­specific interstitial pneumonia (fNSIP) patients compared with those with other interstitial diseases and especially control samples.9 Mice challenged with bleomycin (BLM) displayed increased levels of ATX, LPC and LPA in BALF, and ATX protein levels were also increased in lung homogenates after lung injury.10,11 Mice lacking ATX expression specifically in bronchial epithelial cells and macrophages were shown to be less sensitive to exper­ imental models of lung fibrosis.9 Ubiquitous deletion of either LPA recep­ tor 1 or 2 (Lpar1 or Lpar2) in mice also markedly protected animals in the BLM-­induced fibrosis model.10,12 LPA1 was identified as the predominant LPA receptor in lung fibroblasts of IPF patients, responsible for increased fibroblast cell migration and vascular leakage. Among the reported antag­ onists of LPA1, BMS-­986020 was evaluated in a phase 2 clinical trial study (NCT01766817) in patients with IPF for 26 weeks at dose of 600 mg once or twice daily.13 Whilst markers of fibrosis or inflammation were improved after treatment with BMS-­986020, presumed hepatobiliary toxicity occurred in some patients. This adverse event was linked to drug-­specific off–target activity rather than LPA1 antagonism. The effects of LPA on lung remodelling were described through effects on both LPA1 and LPA2.14 LPA signalling via LPA1 was shown to promote epithelial cell apoptosis but also to contribute to fibroblast accumulation and resistance to apoptosis.10,15 LPA2 was shown to play a key role in the αvβ6 integrin-­mediated transforming growth factor beta (TGF-­β) activation of epithelial cells under fibrotic conditions.16 The inhibi­ tion of ATX-­mediated production of LPA would address effects driven by both LPA1 and LPA2, indicating an additional benefit compared with the use of LPA1 or LPA2 antagonists alone. The ATX–LPA biology was also linked to fibrotic disease affecting other organs. Based on the correlation between serum ATX levels and liver fibro­ sis stage, ATX serum level was proposed as a non-­invasive biomarker for liver fibrosis in hepatitis C virus and hepatitis B virus infected patients.17–19 Serum ATX level also correlated with parameters of liver fibrosis in patients with hepatocellular carcinoma and in cirrhosis patients.20,21 Serum ATX and plasma LPA levels were increased and correlated with disease severity in a rat carbon tetrachloride (CCl4) preclinical model of liver fibrosis.22 Skin fibrosis is also affected by ATX–LPA signalling. Increased expression of ATX and LPA1 were observed in blister skin when compared with normal skin.23 Elevated serum level of arachidonoyl (20 : 4)-­LPA were measured in systemic sclerosis patients compared with controls.24 Genetic deletion of LPA1 and pharmaco­ logical antagonism of LPA1 and LPA3 protected mice from dermal fibrosis induced by bleomycin.25,26 SAR100842, a LPA1 antagonist was evaluated in a phase 2a study (NCT01651143) in patients with diffuse cutaneous systemic sclerosis (dcSSc) at the dose of 300 mg twice a day for eight weeks to look at safety, tolerability and preliminary signs of efficacy in patients.27 The mole­ cule was well tolerated and showed target engagement based on the reduc­ tion of LPA related genes. Regarding disease evolution, a greater decrease of the Rodnan skin score (mRSS) was seen in the compound-­treated group

View Online

120

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

compared with the group that received placebo, although it didn't reach sta­ tistical significance, the rather short duration of treatment might have lim­ ited the extent of the effect.

4.1.2  Structure of ATX The first experimental structures of rodent orthologs of ATX were reported in 2011, revealing important structural features that explain the uncommon biochemical properties of this enzyme within the ENPP family as well as the binding mode of different LPA ligands and inhibitors.28,29 On the basis of sequence and structural homology, ATX presents two somatomedin B (SMB)-­ like domains close to the N-­terminus, which are followed by the catalytic ENPP domain and an inactive nuclease-­like domain (Figure 4.2). The catalytic domain is organized in a T-­shaped tripartite binding site: a catalytic pocket that exhibits a nucleophilic threonine residue (Thr210 in the human ortholog) and two adjacent zinc ions, a hydrophobic pocket that accommodates the hydrophobic tail of a variety of lysophospholipids and a so-­called tunnel. The hydrophobic pocket able to accommodate the acyl chains of lysophospholipids is unique to ATX among ENPP family members. Co-­crystal structures indicated that the pocket can accommodate different acyl chain lengths and saturation, provided bends are introduced for longer acyl chain lengths (Figure 4.3). The tunnel presents both hydrophobic and hydrophilic residues on its inner walls; unexpectedly co-­crystal structures revealed the presence of lipophilic molecules, such as LPA acyl chain or ara­ chidonic acid, in the tunnel in addition to LPA species or ligands bound in the hydrophobic and catalytic pockets. This observation and the location of SMB-­like domains near the tunnel have indicated a possible role of ATX for transport and delivery of LPA to its cognate receptors involving recognition of SMB-­like domains by integrins present at the cell surface.30

Figure 4.2  Co-­  crystal structure of mouse ATX with 14 : 0 LPA (PDB 3NKN).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

121

Figure 4.3  Overlay  of 14 : 0 LPA and 22 : 6 LPA co crystallized in ATX (PDB 3NKN and 3NKR respectively).

In contrast with this hypothesis results of a recent kinetics study indicated that LPA bound in the tunnel could increase the catalytic efficiency of ATX and that the tunnel might serve as an entrance for LPA to enhance ATX activ­ ity.31 The two hypotheses converge in considering tunnel occupancy as an important feature for ATX activity. Co-­crystal structures of ATX with diverse inhibitors were described and revealed a variety of binding modes, which have been classified into four types illustrated in Figure 4.4.36 Type I inhibitors, such as PF-­8380, com­ pete with LPA and LPC to bind in the catalytic site and hydrophobic pocket, but don't prevent binding of LPA in the tunnel, which stabilizes LPC bind­ ing and increases the rate of hydrolysis. Type II inhibitors, such as PAT-­494, occupy the hydrophobic pocket by largely exploiting its intrinsic plasticity and inducing a conformational rearrangement of the side-­chain of several residues.32 Type II inhibitors also extend into the shallow groove between the catalytic site and the tunnel but do not fully occupy any of them, which could allow binding of an additional ligand in the tunnel (arachidonic acid molecule for PAT-­494 in Figure 4.4). Type III inhibitors, such as PAT-­347, bind in the tunnel, leaving the hydrophobic pocket and catalytic site accessible for an LPA (or LPC) molecule. LPA can also displace Type III inhibitors from the tunnel and increase catalytic efficiency of ATX. Type IV inhibitors, such as GLPG1690, occupy both the hydrophobic pocket and the tunnel and there­ fore prevent binding of LPA (or LPC) in these two sites. Whether the tunnel serves as an entrance for LPA, or contributes to LPA transport and delivery to its receptors, or both, needs to be further doc­ umented but occupancy of the tunnel by ATX inhibitors is expected to

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

122

Figure 4.4  Schematic  representation and examples of the four types of binding

modes of ATX inhibitors, including co-­crystal structures of ATX with PF-­8380 in green (PDB 5l0k), PAT-­494 in purple (PDB 4zga), PAT-­347 in blue (PDB 4zg7) and GLPG1690 in orange (PDB 5mhp). Zinc ions are depicted in magenta. The grey dotted lines represent secondary ligands modelled next to the inhibitor as shown with grey carbons on the illus­ trations; some structures lack secondary ligand models but exhibit a positive electron density in the same region. Adapted from ref. 36 with permission from American Chemical Society, Copyright 2017.

influence their mode of action. A recent study described how binding modes of ATX inhibitors could affect the kinetics of hydrolysis of LPC by ATX in the presence of LPA.31 As a consequence the diverse binding modes of ATX inhib­ itors might ultimately result in different therapeutic effects.

4.1.3  ATX Inhibition Assays Synthetic substrates allowing the detection of fluorescence upon hydrolysis by ATX have frequently been used to identify ATX inhibitors owing to their suitability for high-­throughput screening (HTS) purposes. Glycerol deriv­ ative FS-­3 is an analogue of LPA containing a fluorophore and a quencher group, light emission occurs when the fluorophore is released by phosphate hydrolysis (Figure 4.5).33 BNPP [bis(4-­nitrophenyl)phosphate] is a common reagent used to assay phosphatase activity leading to the release of a chro­ mophore upon hydrolysis. Several examples describing discrepancies between measured activity with synthetic substrates and the natural substrate LPC have been reported.32,34–37

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

123

Figure 4.5  Synthetic  substrates used to monitor ATX activity.

Figure 4.6  Detection  of LPC hydrolysis by ATX. Hydrolysis of LPC leads to the formation of choline and LPA, both of which can be detected using a series of biochemical transformation leading to luminescence or liquid chromatography tandem mass spectrometry (LC-­MS/ MS) analytical methods respectively (Figure 4.6). In this assay, choline oxi­ dase converts choline into betaine and hydrogen peroxide, which horserad­ ish peroxidase, in turn, uses to oxidize the mixture of 4-­aminoantipyrine and sodium 3-­(N-­ethyl-­3-­methylanilino)-­2-­hydroxypropanesulfonate (TOOS) into a quinoneimine dye. Assay kits including Amplex Red reagent can also be used to detect the formation of hydrogen peroxide. In addition to its physio­ logical relevance, this latter assay also allows monitoring of the production of LPA in plasma. Since both ATX and LPC are naturally present in blood, the demonstration of target engagement with ATX inhibitors is generally shown by measuring the inhibition of production of LPA in plasma incubated ex vivo or by monitoring the reduction of LPA levels in vivo.

4.2  ATX Inhibitors in Fibrosis Several reviews on ATX inhibitors and their structural evolution over time have been published.38 The following section will focus on ATX inhibitors evaluated for fibrosis or related indications. The activity of ATX inhibitors shown in Figure 4.7 in murine models of fibrosis has been described in the literature. There are other ATX inhibitors for which activity in murine models

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

124

Figure 4.7  Structures  of ATX inhibitors with activity in murine models of fibrosis described in the literature.

of fibrosis has only been mentioned in patent applications or at conferences that will also be discussed in the following section. The first report of evaluation of an ATX inhibitor in a fibrosis model is on the activity of GWJ-­A-­23 (Ki = 18 nM, FS-­3 substrate)39 in the mouse model of lung fibrosis induced by intratracheal instillation of bleomycin in 2012.9 The compound was administered intraperitoneally on alternate days at a dose of 10 mg kg−1 and led to significant decrease of collagen, cell infiltration, TGF-­β and LPA levels in BALF. ATX activity measured using Amplex Red PLD activity kit and total LPA content were also decreased in BALF in the compound-­treated group compared with those that received placebo. GWJ-­A-­23 is a commercially available tool compound displaying a lipid-­like structure with a fatty acid tail and a polar phosphonic acid head. GK442 (IC50 = 60 nM, 16 : 0 LPC substrate) is a recent example of lipid-­like ATX inhibitor with a hydroxamic acid head tested in the mouse model of lung fibrosis induced by orotracheal administration of bleomycin.40 Intra­ peritoneal administration of GK442 at a daily dose of 30 mg kg−1 for 15

View Online

Autotaxin Inhibitors in Fibrosis

125

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

days gave significant decreases in collagen, total protein and ATX activity in BALF as well as improvement of lung architecture. No further development of GK442 has been reported yet.

4.2.1  Ribomic, RBM-­006 Since ATX is a secreted enzyme, it can be targeted by non-­small molecule inhibitors. RB014 (IC50 = 2.0 nM, 14 : 0 LPC substrate) belongs to a family of anti-­ATX RNA aptamers.41 RB011, a precursor of RB014 was co-­crystallized with ATX and shown to bind to the catalytic domain of ATX and induces a structural rearrangement of the ATX protein. RB014 was tested in the mouse model of lung fibrosis induced by intranasal administration of bleomy­ cin. Intranasal administration of the aptamer (20 µg) three times per week led to significant reduction in collagen, total protein and ATX activity in BALF. RB014 also significantly reduced the amount of 18 : 2 LPA in BALF of bleomycin-­treated mice. The current pipeline of Ribomic indicates that an anti-­ATX aptamer RBM-­006 is at the pre-­clinical stage for fibrosis as an indication.42

4.2.2  iOnctura, IOA-­289 PF-­8380 (IC50 = 1.7 nM, 17 : 0 LPC substrate) was the first ATX inhibitor demonstrating in vivo activity after oral administration in 2010; the com­ pound provided strong LPA reduction in plasma and at the air pouch site of inflammation.43 PF-­8380 was evaluated in a mouse model of CCl4-­ induced liver fibrosis.44 The compound dosed intraperitoneally at 30 mg kg−1 twice daily (two to four weeks post CCl4 administration) attenuated fibrosis and significantly decreased collagen deposition and LPA level in liver. The compound was later tested at oral doses of 60 and 120 mg kg−1 twice daily in the mouse model of lung fibrosis induced by intratracheal instillation of bleomycin.45 Treatment with PF-­8380 improved lung archi­ tecture (quantified using the modified Ashcroft score) and gave signifi­ cant decreases in total protein content and collagen in BALF. ATX activity as well as 16 : 0 LPA amount were also significantly reduced in BALF in the PF-­8380-­treated group compared with the vehicle group. Whereas properties of PF-­8380 were initially disclosed by Pfizer's scientists, the compound is part of a patent by Merck KGaA,46 and PF-­8380 inspired the design of ATX inhibitors by other companies.47 Efforts that led to the iden­ tification of PF-­8380 (also called MSC2108323) and MSC2285264 (IC50 = 60 nM, egg LPC substrate48) were disclosed at a conference in 2012 (Fig­ ure 4.8).49 PF-­8380 was mentioned to suffer from chemical instability and lead compound MSC2285264 failed to show antitumor activity in vivo. As exemplified in Figure 4.8, several scaffold or linker modifications were investigated, including chiral sulfoxide analogues such as compound 10a for which seven gram synthesis of an advanced chiral sulfoxide intermedi­ ate was described.50 As shown in Figure 4.9, several other chemical series

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

126

Figure 4.8  ATX  inhibitors by Merck KGaA, IC50 determined using egg LPC as substrate.

Figure 4.9  Markush  formula and examples of ATX inhibitors by Merck KGaA, IC50 determined using egg LPC as substrate.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

127

were also identified by Merck KGaA for which no development has been reported so far.51 In 2017 Merck KGaA founded iOnctura, a spin-­out com­ pany currently developing an ATX inhibitor IOA-­289 for solid tumours and IPF. IOA-­289 is expected to enter clinical trials in early 2020.52 No struc­ ture or activity data are available for IOA-­289.

4.2.3  Amira Amira was the first company to report the identification of a preclinical can­ didate ATX inhibitor in 2010; the structure of the molecule has not been dis­ closed.53 In 2011 Amira was acquired by BMS and no further development of the ATX preclinical candidate has been reported. The chemical series identified by Amira is based on a polysubstituted indole scaffold, most com­ pounds contain a thioaryl or thioheteroaryl substituent bearing a carbox­ ylic acid (Figure 4.10).54 Only the in vitro range of activity was reported using ATX produced endogenously by a human melanoma cell line (MDA-­MB-­435S) and 14 : 0 LPC as substrate. Interestingly compound 4-­4 (Figure 4.10) is also known as PAT-­048.

Figure 4.10  Markush  formula and examples of ATX inhibitors by Amira, IC50 deter­ mined using 14 : 0 LPC as substrate.

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

128

The latter compound was evaluated in the bleomycin-­induced skin fibrosis mouse model in preventive and delayed treatment settings at an oral daily dose of 20 mg kg−1.55 Both regimens led to significant attenuation of the der­ mal thickness and hydroxyproline increases associated with the disease. Compound 4-­4/PAT-­048 was also tested at an oral daily dose of 20 mg kg−1 in the bleomycin-­induced pulmonary fibrosis mouse model, where it failed to show efficacy on the bleomycin-­induced increase of total protein and hydroxyproline contents in BALF.11 Importantly, the compound inhibited ATX activity systemically and in BALF based on ex vivo LysoPLD assay with addition of 14 : 0 LPC substrate, but it had no effect on any LPA species in BALF, which is in contrast with other ATX inhibitors reported to be active in the bleomycin-­induced pulmonary fibrosis mouse model.

4.2.4  PharmAkea, PAT-­409 PharmAkea was founded in 2012 by former Amira employees. PharmAkea also explored an indole-­based series of ATX inhibitors and reported in 2017 the identification of PAT-­409, a phase 1 ready ATX inhibitor (undisclosed structure) which went through 28-­day good laboratory practice (GLP) toxicol­ ogy studies and was shown to reduce fibrosis in rodent models of NASH.56,57 PharmAkea made several reports on the binding mode and pharmaco­ logical activity of their ATX inhibitors. Interestingly several subseries were designed around the indole scaffold and compounds from these subseries display unique mechanisms of inhibition of ATX-­mediated hydrolysis of LPC linked to their binding mode determined by co-­crystallization with human ATX (Figure 4.11).32 Depending on the substituents on the indole nitrogen, C2 and C3 posi­ tions, compounds show competitive inhibition of LysoPLD activity of ATX (PAT-­078, IC50 = 472 nM, 14 : 0 LPC substrate), non-­competitive (PAT-­347, IC50 = 2 nM, 14 : 0 LPC substrate) or a mixed-­mode of inhibition (PAT-­494, IC50 =

Figure 4.11  Structure  and mode of inhibition of LPC hydrolysis of PAT-­078, PAT-­ 347, PAT-­494 and PAT-­352.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

129

20 nM, 14 : 0 LPC substrate; and PAT-­352, IC50 = 26 nM, 14 : 0 LPC substrate). No in vivo pharmacological activity has been described for PAT-­078, PAT-­347 and PAT-­494. PAT-­352 was prepared at the 42-­gram scale and the compound was able to decrease baseline glucose and total blood glucose area under the curve (AUC) at the oral dose of 30 mg kg−1 twice a day in a glucose tolerance model in mice fed with a high-­fat diet.58 PAT-­505 (IC50 = 2.0 nM, 14 : 0 LPC substrate) is a close analogue of PAT-­048 (or compound 4-­4 from Amira, IC50 = 1.1 nM, 14 : 0 LPC substrate) containing a cyclopropyl substituent in position 2 of the indole ring (Figure 4.12).59,60 Such modification was not included in Amira's patents where the increase of size of the substituent in position 2 with an ethyl or trifluoromethyl group appeared detrimental to activity as described for N-­benzyl indole deriva­ tives.54 PAT-­505 in which an N-­ethyl pyrazolyl group is linked to the indole nitrogen is a non-­competitive inhibitor of ATX for which activity in multiple pharmacological models has been reported. PAT-­505 was evaluated in the Stelic Animal Model (STAM™) mouse model and the choline-­deficient, amino acid-­defined high-­fat diet model (CDAA–HFD) of non-­alcoholic steatohepatitis (NASH).60 PAT-­505 was tested at oral doses of 10 and 30 mg kg−1 twice daily in the STAM™ NASH model and at oral daily doses of 3, 10 and 30 mg kg−1 in the mouse CDAA–HFD NASH model. Overall ATX inhibition by PAT-­505 showed direct antifibrotic effects in the liver, with little to no effect on hepatic inflammation, hepatocellular ballooning, and steatosis. In contrast with the antifibrotic effect of PAT-­505 in mouse liver models of fibrosis, ATX inhibitor Example 31 (24) (IC50 = 27 nM, 18 : 1 LPC, Figure 4.13) from Ono Pharmaceutical displayed no efficacy in two models of advanced liver fibrosis in rat.61,62 The compound was administered orally at 15 mg kg−1 twice daily in the choline-­deficient l-­amino acid-­defined (CDAA) diet and the CCl4-­induced hepatic fibrosis rat models. Despite more than 95% reduction

Figure 4.12  Structure  of PAT-­505 and PAT-­048 and compounds E and B from patent applications by PharmAkea.

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

130

Figure 4.13  Structure  of ATX inhibitor by Ono Pharmaceuticals tested in a NASH model.

in plasma LPA levels in both studies, treatment resulted in absence of effect on biomarkers of liver function, inflammation or fibrosis and did not lead to any histological improvements in diseased animals. Although the lack of activity of Example 31 (24) could call into question the value of ATX inhibi­ tion as a target for the treatment of advanced stages of NASH-­related liver fibrosis, differences such as experimental set-­up, species or binding mode to ATX might account for the discrepancies between activities of ATX inhibitors in different studies. Other pharmacological activity data for PAT-­505 in dermal, kidney and peritoneal fibrosis models were described in a patent application by Phar­ mAkea.63 PAT-­505 showed a significant reduction in skin fibrosis and hydroxy­ proline content in the mouse model of bleomycin-­induced skin fibrosis. The compound also led to a reduction of hydroxyproline content in the ligated kidneys and peritoneum of mice when tested in the mouse unilateral uret­ eral obstruction (UUO) kidney fibrosis model and mouse peritoneal fibrosis model respectively. Compounds E and B shown in Figure 4.12 are two additional notable com­ pounds from PharmAkea. Compound E is an analogue of the non-­competitive inhibitor PAT-­347 for which synthesis of racemate and both enantiomers were described, with one enantiomer prepared at the four gram scale (exam­ ple 114, compound 2–58).64 Compound E was able to decrease baseline glu­ cose at the oral dose of 30 mg kg−1 daily in a glucose tolerance model in mice fed with a high-­fat diet.58 Compound B is an analogue of PAT-­505 and PAT-­ 048 bearing a chlorine atom in position 2 of the indole ring, such modifica­ tion was also not included in Amira's patent applications.65 Two methods of preparation of sodium salt of compound B have been described yielding 23.5 grams and 31.8 grams respectively.63 According to the description com­ pound B was tested in liver and skin fibrosis rodent models. Compound B significantly reduced liver fibrosis when dosed at 10 mg kg−1 in the CDAA– HFD mouse model of liver fibrosis. In this animal model, treatment of mice with 1 mg kg−1, 3 mg kg−1 or 10 mg kg−1 of compound B resulted in about 49%, 67%, and 75% inhibition of trough plasma ATX activity, respectively (as

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

131

measured by choline production). Interestingly, PAT-­409 was also described as reducing liver fibrosis at an oral daily dose of 10 mg kg−1 in the CDAA–HFD mouse model of liver fibrosis and to show 49%, 67%, and 75% inhibition of trough plasma ATX activity at doses of 1 mg kg−1, 3 mg kg−1 and 10 mg kg−1, respectively.57

4.2.5  Galapagos, GLPG1690 Galapagos reported the start of a phase 3 clinical trial with GLPG1690 in IPF patients at the end of 2018 (ISABELA, NCT03733444, NCT03711162).66 GLPG1690 is the most advanced ATX inhibitor in clinical trials and the first ATX inhibitor to have completed a phase 2 clinical trial (FLORA, NCT02738801).67 Patients with IPF received 600 mg oral GLPG1690 or placebo for 12 weeks. Overall, GLPG1690 was well tolerated by patients over 12 weeks, showing a similar safety profile to placebo. Reductions in 18 : 2 LPA concentrations in plasma in the GLPG1690 group were measured (maximum of 89.4% from baseline) and confirmed target engagement in patients. GLPG1690 showed encouraging results on disease-­associated read-­outs, as mean change from baseline in forced vital capacity decreased over the 12 weeks treatment period in the placebo group [−70 ml, 95% confidence interval (CI) −208 to 68] but remained similar to or greater than baseline values in the GLPG1690 treatment group (+25 ml, 95% CI −75 to 124) with the last observation carried forward method for analysis. In addition, to further assessing the potential of GLPG1690 as a novel treatment for IPF, Galapagos started a Phase 2a trial in patients with systemic sclerosis in early 2019 (NOVESA, NCT03798366).68 Medicinal chemistry efforts that led to the discovery of GLPG1690 are sum­ marized in Figure 4.14.36,69,70 High-­throughput screening using an artificial FS-­3 substrate-­based assay led to the identification of a 2,3,6-­trisubstituted imidazo[1,2-­a]pyridine series with most potent compounds displaying potency at around 30 nM. The poor meta­ bolic stability of the series was improved by incorporating a N-­phenylthiazole substituent and an amide group in positions 3 and 6 of the scaffold respec­ tively as in compound 1 (Figure 4.14). The latter compound displayed only weak inhibition of LPA production in rat plasma which was attributed to the insufficient biochemical potency in the FS-­3 assay. However further analogues with IC50 below 10 nM using FS-­3 substrate were also weakly active in the plasma assay. The high shift of potency and absence of correlation between activity in the FS-­3 and plasma assays indicated that the FS-­3 assay was not a good predictor of plasma activity for this chemical series (Figure 4.15). In contrast assaying ATX inhibition using 16 : 0 LPC as substrate displayed a good correlation with plasma activity and was used for further optimization. As seen in compound 22 (Figure 4.14), introduction of a heterocyclic sub­ stituent bearing a basic group and extended with a H-­bond-­accepting group at position 6 of the imidazo[1,2-­a]pyridine scaffold strongly increased potency. An additional boost of potency was obtained by adding a nitrile group on the thiazole ring.

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

132

Figure 4.14  Summary  of medicinal chemistry efforts that led to the identification of GLPG1690, 16 : 0 LPC was used as substrate and plasma assay was performed in rat plasma.

Figure 4.15  (A)  Plot of FS-­3 assay IC50 versus rat plasma assay IC50. (B) Plot of LPC assay IC50 versus rat plasma assay IC50.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

133

The lead molecule 40 (Figure 4.14) displayed high potency in a rat plasma assay, however, it showed limited oral exposure and unsatisfactory clearance in rodents. In addition, the compound inhibited the human ether-­a-­go-­go related gene (hERG) channel with an IC50 of 2.9 µM in a hERG automated patch-­clamp assay and showed CYP3A4 time-­dependent inhibition (TDI) in a human liver microsomes assay; these properties were not appropriate to initiate clinical development of this compound. Replacing the piperidine substituent in position 6 of the imidazo[1,2-­a] pyridine scaffold with a less basic piperazine attenuated hERG inhibition and introduction of a methyl substituent at position 8 of the scaffold removed CYP3A4 time-­dependent inhibition, the latter modification also resulted in a slight loss of potency. The combination of these structural modifications also improved pharmacokinetic properties versus the lead compound and resulted in GLPG1690. GLPG1690 was evaluated in the mouse model of bleomycin-­induced pulmonary fibrosis at oral doses of 10 and 30 mg kg−1 twice daily in a pro­ phylactic setting where bleomycin administration and start of compound treatment took place on the same day. Treatment with GLPG1690 at both doses resulted in a significant decrease in the Ashcroft score, along with a significant reduction of the collagen content reported for the 30 mg kg−1 dose group. GLPG1690 treatment also decreased the levels of 16 : 0, 18 : 1, 18 : 2 and 20 : 4 LPA in BALF compared with the diseased vehicle-­treated group, which demonstrated the ability of the compound to inhibit ATX-­mediated LPA increase in BALF. The compound was also tested in a therapeutic setting of the bleomycin-­induced pulmonary fibrosis mouse model in which treatment started seven days post bleomycin administration. GLPG1690 dosed orally at 30 mg kg−1 twice daily led to a significant decrease of the Ashcroft score and of the collagen content.71

4.2.6  X-­Rx, X-­165 Early 2019 X-­Rx announced acceptance by the US Food and Drug Adminis­ tration (FDA) of the Investigational New Drug Application (IND) for X-­165, an ATX inhibitor being developed for the treatment of IPF.72 X-­165 is a small molecule inhibitor of ATX, the chemical series was identified by HTS using DNA encoded library technology. The structure of X-­165 has not been disclosed. Patent applications filed by X-­Rx encompass spirocyclic and piperidine-­based series of ATX inhibitors (Figure 4.16).73,74 An additional patent application75 was filed in collabora­ tion with Gilead76 claiming compositions of an ATX inhibitor from the spi­ rocyclic series in combination with additional therapeutic agents such as anti-­fibrotics, anti-­inflammatory agents, anti-­cancer agents and cardiovascu­ lar agents. Only the range of activity in the LysoPLD assay using 16 : 0 LPC as a sub­ strate are described for compounds in both patent applications. Most of

View Online

Chapter 4

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

134

Figure 4.16  Markush  formula from patent applications WO2015154023 (A) and WO2015175171 (B).

Figure 4.17  Example  compounds from patent application WO2015154023. IC50 values are based on inhibition of 16 : 0 LPC cleavage by ATX.

the potent compounds described for the spirocyclic series contain the 2-­fluoro-­5-­trifluoromethylbenzamide substitution pattern and (R)-­valine moiety as shown, for example, in compounds 52 and 100 depicted in Figure 4.17. Example 52 belongs to the potent compounds for which the synthesis is entirely described and the second to last step is performed to yield 5 grams of intermediate. Several analogues of example 52 containing the same 5-­substituted indazole moiety with modification of the benzamide substi­ tution pattern and replacement of valine group by other alpha-­substituted glycine residues were prepared. Regarding structure–activity relationships N-­methylation of benzamide (example 236) or removal of phenyl substitu­ ents (example 233) are detrimental to potency. Stereochemistry of the valine moiety appears to be important for activity as the (S)-­enantiomer (example 69)

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

135

is significantly less active than the (R)-­enantiomer (example 52). Loss of activity is also observed when the isopropyl substituent is replaced by a smaller methyl group (example 72), in contrast a bulkier group, such as cyclopentyl, is tolerated (example 57, not shown). Structural modifica­ tion of the indazole part is tolerated and multiple potent analogues are described such as example compounds 51, 100 and 149. Interestingly the 6-­substituted indazole isomer (example 53) is less active, indicating that the position of the H-­bond donating group is important for activity of example 52, although it might not be required as the N-­methylated inda­ zole analogue (example 12) also seems to be potent. Finally, the potency of example 149 indicates that one of the carbonyls of the hydantoin moiety is not required for activity. Most potent compounds from the piperidine-­based series74 contain a methylsulfone group such as in examples 4 and 36 shown in Figure 4.18. Despite structural similarities with spirocyclic series, there seem to be some differences in structure–activity relationship, as the methylsulfonylphenyl derivative in the spirocyclic series (example 9) appears less potent than the pyridine-­based series analogue (example 27). As mentioned previously, the structure of X-­165 was not disclosed but properties such as activity and bioavailability of X-­165 were reported at a con­ ference (Table 4.1).77 X-­165 inhibited ATX in biochemical and human whole blood assays with IC50 values of 5.4 and 41 nM respectively and displayed bio­ availability in mouse, rat and dog of 81%, 66% and 20% respectively. X-­165 was able to reduce cell infiltration in a mouse model of bleomycin-­induced fibrosis in a similar way to dexamethasone, no dose or other read-­outs were reported.

Figure 4.18  Example  compounds from patent application WO2015175171 (except example 9). IC50 values are based on inhibition of 16 : 0 LPC hydrolysis by ATX.

View Online

Chapter 4

136

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Table 4.1  Properties  reported for X-­165. %F, oral bioavailability. ATX biochemical assay IC50 ATX human whole blood assay IC50 %F (mice, rat, dog)

5.4 nM 41 nM 81, 66, 20

Figure 4.19  Markush  formula from patent application WO2018212534 (A) and substructure (B).

4.2.7  Bridge Biotherapeutics, BBT-­877 At the end of 2018 Bridge Biotherapeutics announced that the US FDA had cleared the IND application of BBT-­877 and recruitment for the first in human study (NCT03830125) on the drug candidate started early 2019.78 Interim data indicating that the compound was well tolerated in a single ascending dose were disclosed in May 2019.79 In addition to IPF, investigation of other indications such as NASH and certain types of cancers are mentioned for BBT-­877.80 BBT-­877 was discovered by LegoChem Biosciences and licensed to Bridge Biotherapeutics. In July 2019 Bridge Biotherapeutics and Boeh­ ringer Ingelheim announced their collaboration to develop BBT-­877 with an initial focus on IPF.81 The structure of BBT-­877 has not been disclosed yet but activity in a mouse model of bleomycin induced fibrosis was reported.82 At doses of 10 and 30 mg kg−1 twice daily, the compound was significantly active on several read-­ outs of a BLM-­induced fibrosis model [Matsuse's modified Ashcroft score, lung weight and collagen type I alpha 1 chain (COL1A1) staining]. LegoChem Biosciences filed a patent application describing a series of para-­disubstituted 6-­membered heteroaryl scaffold (Figure 4.19).83 Many compounds are derived from substructure (B) shown in Figure 4.19 with vari­ ation of the substituent at position 3 of the pyrazole ring. Reported activity data include FS-­3 assay for most compounds and ex vivo LysoPLD assay measuring 18 : 1 LPA formation in mouse and/or human serum for several compounds. Activity with BNPP substrate is also described for 12 compounds. Activity in the low nanomolar range on all assays is depicted only for compounds 96 and 116 (Figure 4.20). Interestingly compound 56 illustrates the fact that substitution in position 3 of the pyrazole is not man­ datory to achieve high potency in ex vivo assay.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

137

Figure 4.20  Structure  and activity data for example compounds from patent appli­

cation WO2018212534. Ex vivo assay data are in mouse serum moni­ toring formation of 18 : 1 LPA; n.d.: not described.

Table 4.2  Ex  vivo inhibition of LPA production in mouse serum. Data in parenthe­ ses indicate inhibition in human serum for BBT-­877. IC50 (nM) Compound

16 : 0 LPA

18 : 0 LPA

18 : 1 LPA

18 : 2 LPA

20 : 4 LPA

Example 15 (compound 96) Example 34 (compound 115) Example 35 (compound 116) BBT-­877

3.26

14.9

3.65

3.39

2.77

31.7

323

125

107

78.2

2.72

30.0

7.10

5.30

4.46

3.33 (6.19) 16.9 (8.35) 8.28 (7.66)

5.31 (6.89) 5.36 (8.76)

Inhibition of the production of different LPA species in mice serum are reported for compounds 96, 115 and 116 and have also been described for BBT-­877 in mice and human serum (Table 4.2).82 Compounds are able to inhibit production of 16 : 0, 18 : 0, 18 : 1, 18 : 2 and 20 : 4 LPA but tend to be less potent to inhibit production of 18 : 0 LPA versus other LPA species. Notably BBT-­877 shows similar potencies in mouse and human serum. Bioavailabil­ ity reported for BBT-­877 in mouse, rat, dog and monkey ranged between 16 and 63% (Table 4.3).

View Online

Chapter 4

138

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Table 4.3  Bioavailability  of BBT-­877. Species

%F (10 mg kg−1, orally)

%F (30 mg kg−1, orally)

Mouse Rat Dog Monkey

35 56 36 49

53 39 16 63

Table 4.4  ATX  inhibitors in development. Molecule, company

Status

GLPG1690, Galapagos

Phase 3 in IPF (NCT03733444, NCT03711162), phase 2 in systemic sclerosis (NCT03798366) Phase 1 (NCT03830125) Phase 1 to be started, IND accepted by FDA Preclinical, phase 1 planned for 2020 Preclinical Preclinical, phase 1 ready

BBT-­877, Bridge Biotherapeutics X-­165, X-­Rx IOA-­289, iOnctura RBM-­006, Ribomic PAT-­409, PharmAkea

4.3  Conclusion The ATX–LPA axis has been described as playing a role in pathophysiological processes involved in multiple disease areas, however, all the compounds that have entered clinical trials to date interfere with fibrosis-­related events. Unsurprisingly many big pharma and biotech companies have been involved in the search for ATX inhibitors and LPA receptor modulators. LPA1 recep­ tor antagonists from BMS (BMS-­986020) and Sanofi (SAR100842) were the first to enter clinical trials and showed encouraging results in phase 2 on IPF and systemic sclerosis patients respectively. BMS-­986020 progression was stopped due to presumed hepatobiliary toxicity arising from drug-­specific off–target activity rather than LPA1 antagonism, and the SAR100842 program was ended for undisclosed reasons.84 Regarding ATX inhibitors, GLPG1690 from Galapagos was the first to enter clinical trials and is currently being investigated in phase 3 trials for IPF and in phase 2 trials for systemic sclerosis as indications (Table 4.4). Another ATX inhibitor BBT-­877 from Bridge Biotherapeutics recently started phase 1 clinical trials, and IND status for X-­165 from X-­Rx was recently accepted by FDA. Other companies, such as iOnctura, PharmAkea and Ribomic, report ATX inhibitors at preclinical stages in their pipelines. Fibrosis and related diseases are currently intended as the primary indication for ATX inhibitors, however, in the future ATX inhibitors will probably be explored in clinics in other disease areas, such as cancer, as mentioned on several companies' websites. The understanding of the mode of action of ATX has progressed over the years. Results of structural and kinetics investigations on ATX activity

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

139

indicated that the composition of the surrounding lipid environment could influence the production of LPA species and that the tunnel could serve to deliver LPA to its cognate receptors after binding of ATX to cells. ATX inhib­ itors with different binding modes were described, and whereas they were optimized for their ability to inhibit LPA production, characterization of the effects of their binding modes on other ATX activities needs to be further documented.

References 1. M. L. Stracke, H. C. Krutzsch, E. J. Unsworth, A. Arestad, V. Cioce, E. Schiffmann and L. A. Liotta, J. Biol. Chem., 1992, 267, 2524. 2. A. Tokumura, E. Majima, Y. Kariya, K. Tominaga, K. Kogure, K. Yasuda and K. Fukuzawa, J. Biol. Chem., 2002, 277, 39436. 3. Y. Tokuhara, M. Kurano, S. Shimamoto, K. Igarashi, T. Nojiri, T. Kobayashi, A. Masuda, H. Ikeda, T. Nagamatsu, T. Fujii, J. Aoki and Y. Yatomi, PLoS One, 2015, 10, e0130074. 4. (a) K. Nakanaga, K. Hama and J. Aoki, J. Biochem., 2010, 148, 13; (b) A. Perrakis and W. H. Moolenaar, J. Lipid Res., 2014, 55, 1010. 5. (a) L. A. van Meeteren, P. Ruurs, C. Stortelers, P. Bouwman, M. A. van Rooijen, J. P. Pradère, T. R. Pettit, M. J. O. Wakelam, J. S. Saulnier-­Blache, C. L. Mummery, W. H. Moolenar and J. Jonkers, Mol. Cell. Biol., 2006, 26, 5015; (b) M. Tanaka, S. Okudaira, Y. Kishi, R. Ohkawa, S. Isei, M. Ota, S. Noji, Y. Yatomi, J. Aoki and H. Arai, J. Biol. Chem., 2006, 281, 25822. 6. (a) K. Bandoh, J. Aoki, A. Taira, M. Tsujimoto, H. Arai and K. Inoue, FEBS Lett., 2000, 478, 159; (b) M. E. Lin, D. R. Herr and J. Chun, Prostaglandins Other Lipid Mediators, 2010, 91, 130; (c) S. Okudaira, H. Yukiura and J. Aoki, Biochimie, 2010, 92, 698. 7. (a) Y. C. Yung, N. C. Stoddard and J. Chun, J. Lipid Res., 2014, 55, 1192; (b) N. C. Stoddard and J. Chun, Biomol. Ther., 2015, 23, 1. 8. (a) D. C. Budd and Y. Qian, Future Med. Chem., 2013, 5, 1935; (b) I. Ninou, C. Magkrioti and V. Aidinis, Front. Med., 2018, 5, 180; (c) X. Chu, X. Wei, S. Lu and P. He, Int. J. Clin. Exp. Med., 2015, 8, 17117. 9. N. Oikonomou, M. A. Mouratis, A. Tzouvelekis, E. Kaffe, C. Valavanis, G. Vilaras, A. Karameris, G. D. Prestwich, D. Bouros and V. Aidinis, Am. J. Respir. Cell Mol. Biol., 2012, 47, 566. 10. A. M. Tager, P. LaCamera, B. S. Shea, G. S. Campanella, M. Selman, Z. Zhao, V. Polosukhin, J. Wain, B. A. Karimi-­Shah, N. D. Kim, W. K. Hart, A. Pardo, T. S. Blackwell, Y. Xu, J. Chun and A. D. Luster, Nat. Med., 2008, 14, 45. 11. K. E. Black, C. K. Probst, B. A. Fontaine, D. Lagares, N. Ahluwalia, R. S. Knipe, A. M. Tager, E. Berdyshev, I. Bronova, G. Bain, L. Goulet, F. V. Castelino, B. S. Shea and V. Natarajan, FASEB J., 2016, 30, 2435. 12. L. S. Huang, P. Fu, P. Patel, A. Harijith, T. Sun, Y. Zhao, J. G. Garcia, J. Chun and V. Natarajan, Am. J. Respir. Cell Mol. Biol., 2013, 49, 912.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

140

Chapter 4

13. S. M. Palmer, L. Snyder, J. L. Todd, B. Soule, R. Christian, K. Anstrom, Y. Luo, R. Gagnon and G. Rosen, Chest, 2018, 154, 1061. 14. Y. Zhao and V. Natarajan, Biochim. Biophys. Acta, 2013, 1831, 86. 15. M. Funke, Z. Zhao, Y. Xu, J. Chun and A. M. Tager, Am. J. Respir. Cell Mol. Biol., 2012, 46, 355. 16. M. Y. Xu, J. Porte, A. J. Knox, P. H. Weinreb, T. M. Maher, S. M. Violette, R. J. McAnulty, D. Sheppard and G. Jenkins, Am. J. Pathol., 2009, 174, 1264. 17. S. Joshita, Y. Ichikawa, T. Umemura, Y. Usami, A. Sugiura, S. Shibata, T. Yamazaki, N. Fujimori, M. Komatsu, A. Matsumoto, K. Igarashi, M. Ota and E. Tanaka, Hepatol. Res., 2018, 48, 275. 18. H. Nakagawa, H. Ikeda, K. Nakamura, R. Ohkawa, R. Masuzaki, R. Tateishi, H. Yoshida, N. Watanabe, K. Tejima, Y. Kume, T. Iwai, A. Suzuki, T. Tomiya, Y. Inoue, T. Nishikawa, N. Ohtomo, Y. Tanoue, M. Omata, K. Igarashi, J. Aoki, K. Koike and Y. Yatomi, Clin. Chim. Acta, 2011, 412, 1201. 19. T. Yamazaki, S. Joshita, T. Umemura, Y. Usami, A. Sugiura, N. Fujimori, S. Shibata, Y. Ichikawa, M. Komatsu, A. Matsumoto, K. Igarashi and E. Tanaka, Sci. Rep., 2017, 7, 46705. 20. M. Kondo, T. Ishizawa, K. Enooku, Y. Tokuhara, R. Ohkawa, B. Uranbileg, H. Nakagawa, R. Tateishi, H. Yoshida, N. Kokudo, K. Koike, Y. Yatomi and H. Ikeda, Clin. Chim. Acta, 2014, 433, 128. 21. T. Pleli, D. Martin, B. Kronenberger, F. Brunner, V. Köberle, G. Grammatikos, H. Farnik, Y. Martinez, F. Finkelmeier, S. Labocha, N. Ferreiros, S. Zeuzem, A. Piiper and O. Waidmann, PLoS One, 2014, 9, e103532. 22. N. Watanabe, H. Ikeda, K. Nakamura, R. Ohkawa, Y. Kume, T. Tomiya, K. Tejima, T. Nishikawa, M. Arai, M. Yanase, J. Aoki, H. Arai, M. Omata, K. Fujiwara and Y. Yatomi, Life Sci., 2007, 81, 1009. 23. J. Mazereeuw-­Hautier, S. Gres, M. Fanguin, C. Cariven, J. Fauvel, B. Perret, H. Chap, J. P. Salles and J. S. Saulnier-­Blache, J. Invest. Dermatol., 2005, 125, 421. 24. A. Tokumura, L. D. Carbone, Y. Yoshioka, J. Morishige, M. Kikuchi, A. Postlethwaite and M. A. Watsky, Int. J. Med. Sci., 2009, 6, 168. 25. F. V. Castelino, J. Seiders, G. Bain, S. F. Brooks, C. D. King, J. S. Swaney, D. S. Lorrain, J. Chun, A. D. Luster and A. M. Tager, Arthritis Rheumatol., 2011, 63, 1405. 26. T. Ohashi and T. Yamamoto, Exp. Dermatol., 2015, 24, 698. 27. Y. Allanore, O. Distler, A. Jagerschmidt, S. Illiano, L. Ledein, E. Boitier, I. Agueusop, C. P. Denton and D. Khanna, Arthritis Rheumatol., 2018, 70, 1634. 28. J. Hausmann, S. Kamtekar, E. Christodoulou, J. E. Day, T. Wu, Z. Fulkerson, H. M. Albers, L. A. van Meeteren, A. J. Houben, L. van Zeijl, S. Jansen, M. Andries, T. Hall, L. E. Pegg, T. E. Benson, M. Kasiem, K. Harlos, C. W. Kooi, S. S. Smyth, H. Ovaa, M. Bollen, A. J. Morris, W. H. Moolenaar and A. Perrakis, Nat. Struct. Mol. Biol., 2011, 18, 198. 29. H. Nishimasu, S. Okudaira, K. Hama, E. Mihara, N. Dohmae, A. Inoue, R. Ishitani, J. Takagi, J. Aoki and O. Nureki, Nat. Struct. Mol. Biol., 2011, 18, 205.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

141

30. (a) W. H. Moolenaar and A. Perrakis, Nat. Rev. Mol. Cell Biol., 2011, 12, 647; (b) A. J. Houben, X. M. van Wijk, L. A. van Meeteren, L. van Zeijl, E. M. van de Westerlo, J. Hausmann, A. Fish, A. Perrakis, T. H. van Kuppe­ velt and W. H. Moolenaar, J. Biol. Chem., 2013, 288, 510; (c) Z. Fulkerson, T. Wu, M. Sunkara, C. V. Kooi, A. J. Morris and S. S. Smyth, J. Biol. Chem., 2011, 286, 34654; (d) H. Nishimasu, R. Ishitani, J. Aoki and O. Nureki, Trends Pharmacol. Sci., 2012, 33, 138. 31. F. Salgado-­Polo, A. Fish, M. T. Matsoukas, T. Heidebrecht, W. J. Keune and A. Perrakis, J. Biol. Chem., 2018, 293, 14312. 32. A. J. Stein, G. Bain, P. Prodanovich, A. M. Santini, J. Darlington, N. M. P. Stelzer, R. S. Sidhu, J. Schaub, L. Goulet, D. Lonergan, I. Calderon, J. F. Evans and J. H. Hutchinson, Mol. Pharmacol., 2015, 88, 982. 33. C. G. Ferguson, C. S. Bigman, R. D. Richardson, L. A. van Meeteren, W. H. Moolenaar and G. D. Prestwich, Org. Lett., 2006, 8, 2023. 34. L. M. Miller, W. J. Keune, D. Castagna, L. C. Young, E. L. Duffy, F. Potjewyd, F. Salgado-­Polo, P. Engel García, D. Semaan, J. M. Pritchard, A. Perrakis, S. J. Macdonald, C. Jamieson and A. J. Watson, J. Med. Chem., 2017, 60, 722. 35. W. J. Keune, J. Hausmann, R. Bolier, D. Tolenaars, A. Kremer, T. Heidebrecht, R. P. Joosten, M. Sunkara, A. J. Morris, E. Matas-­Rico, W. H. Moolenaar, R. P. Oude Elferink and A. Perrakis, Nat. Commun., 2016, 7, 11248. 36. A. Joncour, N. Desroy, C. Housseman, X. Bock, N. Bienvenu, L. Cherel, V. Labeguere, C. Peixoto, D. Annoot, L. Lepissier, J. Heiermann, W. J. Hengeveld, G. Pilzak, A. Monjardet, E. Wakselman, V. Roncoroni, S. Le Tallec, R. Galien, C. David, N. Vandervoort, T. Christophe, K. Conrath, M. Jans, A. Wohlkonig, S. Soror, J. Steyaert, R. Touitou, D. Fleury, L. Vercheval, P. Mollat, N. Triballeau, E. van der Aar, R. Brys and B. Heckmann, J. Med. Chem., 2017, 60, 7371. 37. T. Bretschneider, A. H. Luippold, H. Romig, D. Bischoff, K. Klinder, P. Nicklin and W. Rist, SLAS Discovery, 2017, 22, 425. 38. (a) H. M. H. G. Albers and H. Ovaa, Chem. Rev., 2012, 112, 2593; (b) E. Barbayianni, V. Magrioti, P. Moutevelis-­Minakakis and G. Kokotos, Expert Opin. Ther. Pat., 2013, 23, 1123; (c) D. Castagna, D. C. Budd, S. J. Macdonald, C. Jamieson and A. J. Watson, J. Med. Chem., 2016, 59, 5604; (d) A. N. Matralis, A. Afantitis and V. Aidinis, Med. Res. Rev., 2019, 39, 976. 39. G. Jiang, D. Madan and G. D. Prestwich, Bioorg. Med. Chem. Lett., 2011, 21, 5098. 40. A. Nikolaou, I. Ninou, M. G. Kokotou, E. Kaffe, A. Afantitis, V. Aidinis and G. Kokotos, J. Med. Chem., 2018, 61, 3697. 41. K. Kato, H. Ikeda, S. Miyakawa, S. Futakawa, Y. Nonaka, M. Fujiwara, S. Okudaira, K. Kano, J. Aoki, J. Morita, R. Ishitani, H. Nishimasu, Y. Nakamura and O. Nureki, Nat. Struct. Mol. Biol., 2016, 23, 395. 42. Ribomic pipeline, https://www.ribomic.com/eng/pipeline.php (accessed on 21 April 2019).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

142

Chapter 4

43. J. Gierse, A. Thorarensen, K. Beltey, E. Bradshaw-­Pierce, L. Cortes-­ Burgos, T. Hall, A. Johnston, M. Murphy, O. Nemirovskiy, S. Ogawa, L. Pegg, M. Pelc, M. Prinsen, M. Schnute, J. Wendling, S. Wene, R. Weinberg, A. Wittwer, B. Zweifel and J. A. Masferrer, J. Pharmacol. Exp. Ther., 2010, 334, 310. 44. E. Kaffe, A. Katsifa, N. Xylourgidis, I. Ninou, M. Zannikou, V. Harokopos, P. Foka, A. Dimitriadis, K. Evangelou, A. N. Moulas, U. Georgopoulou, V. G. Gorgoulis, G. N. Dalekos and V. Aidinis, Hepatology, 2017, 65, 1369. 45. I. Ninou, E. Kaffe, S. Müller, D. C. Budd, C. S. Stevenson, C. Ullmer and V. Aidinis, Pulm. Pharmacol. Ther., 2018, 52, 32. 46. K. Schiemann, M. Schultz, A. Blaukat and I. Kober, Int. Pat. Appl., WO2009046841, 2009. 47. (a) S. B. Jones, L. A. Pfeifer, T. J. Bleisch, T. J. Beauchamp, J. D. Durbin, V. J. Klimkowski, N. E. Hughes, C. J. Rito, Y. Dao, J. M. Gruber, H. Bui, M. G. Chambers, S. Chandrasekhar, C. Lin, D. J. McCann, D. R. Mudra, J. L. Oskins, C. A. Swearingen, K. Thirunavukkarasu and B. H. Norman, ACS Med. Chem. Lett., 2016, 7, 857; (b) C. A. Kuttruff, M. Ferrara, T. Bretschneider, S. Hoerer, S. Handschuh, B. Nosse, H. Romig, P. Nicklin and G. J. Roth, ACS Med. Chem. Lett., 2017, 8, 1252; (c) C. G. Thomson, D. Le Grand, M. Dowling, C. E. Brocklehurst, C. Chinn, L. Elphick, M. Fallere, M. Freeman, V. Furminger, C. Gasser, A. Hamadi, E. Hardaker, V. Head, J. C. Hill, D. I. Janus, D. Pearce, A.-­S. Poulaud, E. Stanley and L. Sviridenko, Bioorg. Med. Chem. Lett., 2018, 28, 2279. 48. Egg LPC substrate: mixture of LPC species, mainly 16 : 0 LPC and 18 : 0 LPC, Avanti Polar Lipids product reference 830071. 49. K. Schiemann, presented in part at the 22nd International Symposium on Medicinal Chemistry, Berlin, Germany, 2–6 September 2012. 50. (a) K. Schiemann, M. Schultz and W. Staehle, Int. Pat. Appl., WO2011044978, 2011; (b) W. Staehle, K. Schiemann and M. Schultz, Int. Pat. Appl., WO2010112116, 2010; (c) M. Schultz, K. Schiemann and W. Staehle, Int. Pat. Appl., WO2010112124, 2010; (d) K. Schiemann, M. Schultz, A. Blaukat, I. Kober and W. Staehle, Int. Pat. Appl., WO2009046842, 2009; (e) K. Schiemann, M. Schultz and W. Staehle, Int. Pat. Appl., WO2010115491, 2010. 51. (a) W. Staehle, I. Kober, K. Schiemann, M. Schultz and D. Wienke, Int. Pat. Appl., WO2010060532, 2010; (b) W. Staehle, M. Schultz and K. Schiemann, Int. Pat. Appl., WO2011116867, 2011; (c) K. Schiemann, M. Schultz, W. Staehle, I. Kober, D. Wienke and M. Krier, Int. Pat. Appl., WO2010063352, 2010; (d) M. Schultz, K. Schiemann and W. Staehle, Int. Pat. Appl., WO2011006569, 2011. 52. iOnctura pipeline, https://www.ionctura.com/pipeline/ (accessed on 21 April 2019). 53. PR Newswire, www.prnewswire.com/news-­releases/amira-­pharmaceuticals-­ announces-­the-­nomination-­of-­an-­orally-­available-­pre-­clinical-­candidate-­ in-­a-­new-­lpa-­related-­program-­an-­autotaxin-­inhibitor-­111923634.html (accessed on 11 February 2019).

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

Autotaxin Inhibitors in Fibrosis

143

54. (a) J. R. Roppe, T. A. Parr, N. S. Stock, D. Volkots and J. H. Hutchinson, Int. Pat. Appl., WO2012024620, 2012; (b) J. R. Roppe, T. A. Parr and J. H. Hutchinson, Int. Pat. Appl., WO2012166415, 2012. 55. F. V. Castelino, V. A. Pace, K. E. Black, L. George, C. K. Probst, A. M. Tager, G. Bain, L. Goulet and R. Lafyatis, Arthritis Rheumatol., 2016, 68, 2964. 56. PharmAkea Partnering, http://www.pharmakea.com/index.php?option= com_content&view=article&id=43&Itemid=233 (accessed on 21 April 2019). 57. D. A. MacKenna, K. E. Shannon, K. T. Nguyen, G. L. Ma, L. Goulet, D. Lonergan, J. H. Hutchinson, J. F. Evans and G. Bain, presented in part at The Liver Meeting 2017, Washington DC, United States of America, 20–24 October 2017. 58. J. F. Evans, Int. Pat. Appl., WO2016028686, 2016. 59. J. H. Hutchinson and D. Lonergan, Int. Pat. Appl., WO2015077503, 2015. 60. G. Bain, K. E. Shannon, F. Huang, J. Darlington, L. Goulet, P. Prodanovich, G. L. Ma, A. M. Santini, A. J. Stein, D. Lonergan, C. D. King, I. Calderon, A. Lai, J. H. Hutchinson and J. F. Evans, J. Pharmacol. Exp. Ther., 2017, 360, 1. 61. A. Ohata, S. Nakatani, T. Sugiyama and T. Morimoto, Int. Pat. Appl., WO2012005227, 2012. 62. M. Baader, T. Bretschneider, A. Broermann, J. F. Rippmann, B. Stierstorfer, C. A. Kuttruff and M. Mark, Br. J. Pharmacol., 2018, 175, 693. 63. G. Bain, J. F. Evans, J. H. Hutchinson and D. Lonergan, Int. Pat. Appl., WO2016191427, 2016. 64. J. H. Hutchinson, D. Lonergan, F. Huang, M. Rowbottom and I. Calderon, Int. Pat. Appl., WO2015048301, 2015. 65. The compound is also exemplified as Compound C, Example 3 in ref. 58. 66. Galapagos Press Release, 6 January 2019, https://www.glpg.com/ press-­releases (accessed on 6 January 2019). 67. T. M. Maher, E. M. van der Aar, O. Van de Steen, L. Allamassey, J. Desrivot, S. Dupont, L. Fagard, P. Ford, A. Fieuw and W. Wuyts, Lancet Respir. Med., 2018, 6, 627. 68. Galapagos Press Release, 17 December 2018, https://www.glpg.com/ press-­releases (accessed on 17 December 2018). 69. N. Desroy, A. Joncour, X. Bock, C. Housseman, C. Peixoto, N. Bienvenu, V. Labeguere, L. Cherel, D. Annoot, T. Christophe, K. Conrath, N. Triballeau, P. Mollat, A. Wohlkonig, R. Blanque, C. Cottereaux, B. Hrvacic, M. Borgonovi, A. Monjardet, E. Van der Aar, R. Brys and B. Heckmann, presented in part at the 251st ACS National Meeting & Exposition, San Diego, United States of America, 13–17 March 2016. 70. N. Desroy, C. Housseman, X. Bock, A. Joncour, N. Bienvenu, L. Cherel, V. Labeguere, E. Rondet, C. Peixoto, J.-­M. Grassot, O. Picolet, D. Annoot, N. Triballeau, A. Monjardet, E. Wakselman, V. Roncoroni, S. Le Tallec, R. Blanque, C. Cottereaux, N. Vandervoort, T. Christophe, P. Mollat, M. Lamers, M. Auberval, B. Hrvacic, J. Ralic, L. Oste, E. van der Aar, R. Brys and B. Heckmann, J. Med. Chem., 2017, 60, 3580.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00117

144

Chapter 4

71. E. M. van der Aar, B. Heckmann, R. Blanqué, N. Desroy, S. Dupont, C. Cottereaux, A. Monjardet, E. Wakselman, D. Dirven, T. Christophe, B. Hrvacic, J. Ralic, F. Marsais and R. Brys, Am. J. Respir. Crit. Care Med., 2016, 193, A4532. 72. X-­Rx Press Release, 24 January 2019, http://www.x-­r xdiscovery.com/news (accessed on 21 April 2019). 73. L. Babiss, M. Clark, A. D. Keefe, M. J. Mulvihill, H. Ni, L. Renzetti, F. Ruebsam, C. Wang, Z. Xie and Y. Zhang, Int. Pat. Appl., WO2015154023, 2015. 74. F. Ruebsam, C. Wang, H. Ni, M. J. Mulvihill, L. Babiss, L. Renzetti and Y. Zhang, Int. Pat. Appl., WO2015175171, 2015. 75. J. Sundy, Int. Pat. Appl., WO2017152062, 2017. 76. X-­Rx Press Release, 11 November 2015, http://www.x-­r xdiscovery.com/ news (accessed on 21 April 2019). 77. M. J. Mulvihill, F. Ruebsam, C. Wang, J. P. Shaw, R. Liu, H. Ni, J. Cui, L. Babiss and L. M. Renzetti, presented in part at the Pharmacologic Resolution of Inflammation as a Novel Therapeutic Approach, New-­York, United Sates of America, 28 October 2014. 78. Bridge Biotherapeutics News, 17 December 2018, http://www.bridge­ biorx.com/investments_view/209?l=en&t=news (accessed on 21 April 2019). 79. G. Lee, S. U. Kang, J.-­H. Ryou, J.-­J. Lim, D.-­Y. Lee, H.-­J. Kwon, G.-­H. Ha and Y.-­H. Lee, presented in part at the American Thoracic Society International Conference, Dallas, United States of America, 17–22 May 2019. 80. Bridge Biotherapeutics pipeline, http://www.bridgebiorx.com/pipe­ line?l=en#pipeline_section_3 (accessed on 21 April 2019). 81. Bridge Biotherapeutics News, 18 July 2019, http://bridgebiorx.com/ investments_view/245?l=en&t=news (accessed on 22 July 2019). 82. G. Lee, S. U. Kang, J.-­H. Ryou, J.-­J. Lim, D.-­Y. Lee, H.-­J. Kwon, G.-­H. Ha and Y.-­H. Lee, presented in part at the 2nd Annual IPF Summit, San Francisco, United States of America, 20–22 August 2018. 83. D. Y. Lee, S. E. Chae, E. M. Jung, E. H. Yang, Y. J. Choi, C.-­W. Chung, J. H. Shin, Y. K. Kim, H. J. Kwon, J. H. Ryu, E. H. Ban, Y. Z. Kim, Y. S. Oh and J. Chae, Int. Pat. Appl., WO2018212534, 2018. 84. BioSpace, https://www.biospace.com/article/unique-­sanofi-­abandons-­ multiple-­mid-­stage-­drug-­programs/ (accessed on 21 April 2019).

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Chapter 5

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes: Intervention at the Core of Fibrotic Pathology Alison Findlay, Craig Turner and Dieter Hamprecht* Pharmaxis Ltd, 20 Rodborough Road, Frenchs Forest, Sydney NSW 2086, Australia *E-­mail: [email protected]

5.1  Introduction Depending on the organ affected, fibrotic diseases are thought to be triggered by a number of causes, which often remain unknown. Common to fibrotic conditions is the excessive deposition of collagen and elastin. A key step in the formation of these extracellular matrix proteins is their stabilization by cross-­links between peptide strands. This process is mediated by lysyl oxidases, a group of five related enzymes consisting of lysyl oxidase (LOX) and lysyl oxidase like 1–4 (LOXL1–4). This chapter covers the promise of inhibitors of the enzymatic activity of lysyl oxidases as anti-­fibrotics, with focus on LOXL2, which is thought to be of particular relevance in many conditions of pathological fibrosis.

  Drug Discovery Series No. 73 Anti-fibrotic Drug Discovery Edited by Jehrod Brenneman and Malliga R. Iyer © The Royal Society of Chemistry 2020 Published by the Royal Society of Chemistry, www.rsc.org

145

View Online

146

Chapter 5

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

5.2  The Lysyl Oxidase Family of Enzymes In healthy tissues, collagen and elastin form the basis of all connective tissues and play a key role by providing strength, stability and integrity.1 Fibrosis is a progressive disease characterised by extensive scarring and tissue stiffening, which develop from chronic tissue damage, inflammation and incessant wound-­healing processes.2–4 During fibrosis, the excessive deposition, cross-­linking and accumulation of extracellular matrix proteins, in particular collagen and elastin, leads to tissue stiffening, scarring and disrupted organ function. If left unchecked, there is an almost inevitable progression to organ failure. Fibrosis can develop in nearly any organ and is an important driver of end-­stage organ failure and mortality in a number of chronic diseases.5,6 Thus, there is great interest in options to stop and revert fibrotic processes. The lysyl oxidases are a family of secreted enzymes responsible for the post-­translational modification essential for the biogenesis of cross-­linked collagen and elastin. Due to this role, lysyl oxidases are key players during the progression of fibrosis as they initiate cross-­linking via oxidation of side chain amino groups of lysine and hydroxylysine residues in collagen, or lysine residues in the case of elastin. This results in the formation of α-­ aminoadipic-­δ-­semialdehydes, also known as allysines (or hydroxyallysines, if derived from hydroxylysine) and is accompanied by the concomitant generation of ammonia and hydrogen peroxide. The reactive aldehyde species so-­generated subsequently dimerise to form immature, or trimerise to form mature, cross-­links. Lysyl oxidase and its activity were first described 50 years ago.7,8 Five members of the human lysyl oxidase protein family have since been discovered and designated lysyl oxidase (LOX) and lysyl oxidase-­like 1–4 (LOXL1–4) (Table 5.1).9–17 All five family members share a highly conserved C-­terminus that contains several unique structural motifs, including a lysine tyrosylquinone (LTQ), the only mammalian cofactor derived from the cross-­linking of two amino acid side chains18 and which is unique to the lysyl oxidase family. The other highly conserved motif is the copper-­binding motif, which contains four histidines,19 and the cytokine receptor-­like (CRL) domain. In contrast to the highly conserved C-­terminal domain, the N-­terminus varies greatly, and thus may impart distinct functions to these proteins in vivo.20 Four scavenger receptor cysteine-­rich (SRCR) domains make up the N-­terminal domain of LOXL2 (as well as LOXL3 and 4, with which it shares the closest homology).15,17,21 SRCR domains are found on secreted and cell-­surface bound proteins and are known to be involved in cell adhesion and signalling. Unique to the LOX and LOXL1 isoforms is the presence of bone morphogenetic protein-­1 (BMP-­1) cleavage sites. Consequently, these enzymes are processed into the corresponding active forms extracellularly by BMP-­1, also known as procollagen C-­proteinase (PCP).22,23 In most organisms, including humans, two families of mammalian amine oxidase enzymes are responsible for the metabolism of various monoamines, diamines and polyamines produced endogenously or

View Online

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

147

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Table 5.1  Characteristics  of lysyl oxidase genes and gene products. Summary of

LOX(L) mRNA tissue distribution under healthy conditions and comparison of sequence homology against LOX and LOXL2, respectively. AA = amino acids. Adapted from ref. 24 with permission from American Society for Biochemistry and Molecular Biology, Copyright 2003. Catalytic domain percentage similarity

Family member

mRNA predicted protein size Tissue distribution

To LOX

To LOXL2

LOX

417 AA

100

63

LOXL1

574 AA

85

63

LOXL2

774 AA

58

100

LOXL3 LOXL4

753 AA 756 AA

65 62

78 79

Lung, aorta, skeletal muscle, kidney, heart Lung, aorta, heart, spleen, skeletal muscle, pancreas Lung, thymus, skin, testis, ovary Heart, uterus, testis, ovary Skeletal muscle, testis, pancreas

Figure 5.1  Schematic  representation of oxidative deamination by lysyl oxidases.

The lysyl oxidase family of enzymes deaminates primary amines to form aldehydes. Re-­oxidation of the reduced cofactor produces ammonia and hydrogen peroxide and restores catalytic activity.25

absorbed from exogenous sources. Lysyl oxidases belong to the copper-­ dependent subset of amine oxidase enzymes, and predominantly act upon the (hydroxy)lysine side chain of collagen and elastin substrates. This reaction occurs via the initial formation of a substrate Schiff base (Intermediate A, Figure 5.1) by condensation of the substrate lysine with the LTQ co-­ factor (catalytic centre). A rate-­limiting hydrogen shift switches oxidation stages within the adduct to form a product Schiff base, Intermediate B, and

View Online

148

Chapter 5 25

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

subsequent hydrolysis then yields the product aldehyde (allysine). Regeneration of catalytic activity is accompanied by the generation of ammonia and hydrogen peroxide.

5.3  L  ysyl Oxidases Catalyse the Formation of Cross-­ links Due to their aldehyde functionality, the product allysines spontaneously react, either with other allysines or with unmodified lysine residues, resulting in the formation of dimeric cross-­links. This step is, in principle, reversible and the cross-­links are referred to as immature. Reaction of immature cross-­links with another aldehyde then results in the irreversible formation of trimeric (collagen) or tetrameric (elastin), highly stable, mature cross-­ links.26 Under normal physiological conditions, cross-­links are essential for the stabilization of collagen fibrils and for the integrity and elasticity of mature elastin. However, in pathological settings, this process becomes aberrant, resulting in excessive cross-­link formation and, ultimately, fibrosis (Figure 5.2).27,28 Inappropriate extracellular matrix rigidity, which is a result of these processes, acts in its own right as a stressor to tissue, thus further activating myofibroblasts in a vicious circle, keeping the system from returning to a homeostatic state.29 The crucial importance of lysyl oxidase-­mediated cross-­linking was first identified in animal studies in which the activity of the enzyme was inhibited, either by nutritional copper-­deficiency or by supplementation of diets with β-­aminopropionitrile (BAPN), the archetypal small molecule inhibitor of the enzymatic activity of all lysyl oxidases (LOX and LOXL1–4).31 This unspecific pan-­LOX inhibition resulted in osteolathyrism, poor bone formation and strength, hyperextensible skin, weak ligaments and increased occurrence of aortic aneurysms.32 These abnormalities correlated well with decreased cross-­linking of collagen and elastin.33 Collagen is not merely a static matrix protein, but rather, is continuously renewed (turned over). This phenomenon has been analysed with different methodologies and described for several tissues.34,35 In a study of particular relevance to the context of this article, in vivo metabolic labelling with deuterated water was used to evaluate liver collagen renewal in human subjects with chronic liver disease. Turnover rates of 0.2–0.6% per day were found, with higher renewal rates associated with more severe disease stages.36 A subsequent study in non-­alcoholic fatty liver (NAFL) and non-­alcoholic steatohepatitis (NASH) patients confirmed a strong correlation between disease severity and increased collagen resynthesis rate, reporting up to 2.7% fractional resynthesis rate per day.37 Since cross-­linking of collagen fibrils reduces their susceptibility to proteolytic degradation,38 the important role of lysyl oxidase enzymes in determining the point of balance of this system becomes apparent. Indeed, the dynamics of this system opens up two enticing possibilities for inhibitors of lysyl oxidases: (1) Preferential effects on

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

149

Figure 5.2  Outline  of processes involved in formation and degradation of extra-

cellular collagen matrix. Following secretion, the extracellular collagens spontaneously aggregate (after processing of the procollagens) into ordered fibrillary structures.30 Myofibroblast-­derived lysyl oxidase (e.g. LOXL2) catalyses the formation of aldehydes from side chain amino groups of lysine and hydroxylysine (which, in turn, is formed by the action of lysyl hydroxylase). Subsequent, spontaneous reactions result in the formation of immature cross-­links. For example, as shown, hydroxylysine-­derived aldehydes may condense with adjacent molecules to form imine cross-­links. In subsequent lysyl oxidase-­ independent maturation processes involving condensation with a third molecule (e.g. hydroxylysyl aldehyde), mature trimeric cross-­links are formed (e.g. pyridinoline, shown). These intermolecular cross-­links are prerequisite for the physical and mechanical properties of collagen fibrils and formation of a stable network. Collagen is turned-­over by proteolytic enzymes (collagenases, matrix metalloproteases). Increases in the degree of cross-­linking confer greater resistance to enzyme-­ driven degradation and directly affect the balance between collagen synthesis and degradation. In the pathological setting, excessive cross-­ linked collagen leads to increased tissue stiffness which, in turn, promotes further myofibroblast activation in a vicious, positive feedback mechanism.

disease tissue compared with healthy tissue, due to the greater rate of re-­ modelling of the former, and, albeit on a longer time scale, (2) the reversal of established fibrosis due to a shift in the equilibrium between generation and degradation of fibrotic matrix. The effect of reduced stimulation of pro-­ fibrotic pathways due to reduced tissue stiffness will further help the return to normal homeostasis.

View Online

150

Chapter 5

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

5.4  Other Roles of Lysyl Oxidases While the primary role of the enzymatic activity of this protein family is extracellular matrix remodelling, a number of extracellular and intracellular functions independent of enzymatic activity have also been reported. These include regulation of biological processes such as cellular growth and homeostasis. Thus, LOX is formed and secreted as a proenzyme, which is cleaved proteolytically to reveal, besides the functional LOX enzyme, a LOX-­propeptide which is capable of reversing an invasive phenotype in breast cancer cells by interfering with the human epidermal growth factor receptor 2/neural tumour oncogene homologue (Her2/neu) signalling cascade.39 Extracellularly, LOXL2 has been shown to signal through β-­integrin in cancer-­associated fibroblasts40 and intracellularly, LOXL2 and LOXL3 have been associated with epithelial to mesenchymal transition.41–43 Additionally, LOXL2 is a key player in heterochromatin formation via Snail-­dependent mechanisms.41,42,44 Moreover, results from one study indicated that LOXL2 is a negative regulator of Notch1 transcription, thereby attenuating epidermal differentiation.45 Besides reducing collagen cross-­linking and deposition, LOXL2 downregulation or inhibition was also shown to attenuate PDGF-­ driven proliferation of fibrosis producing human gingival fibroblasts.46,47

5.5  L  ysyl Oxidase Expression in Healthy and Disease Tissue It is known that the expression pattern of LOX family members can alter depending on cell type, differentiation state, development state and disease state. Indeed, protein expression has been positively correlated with fibrotic diseases in many different tissues including liver, lung and kidney.48–51 In addition, certain members of the family – in particular LOX and LOXL2 – have been widely associated with cancer progression and metastasis.48,52,53 Under normal physiological conditions, LOX is ubiquitously expressed in most human tissues at higher levels than other family members. Together with LOXL1 it can be considered a “housekeeping” enzyme with an important developmental function. The essential role that it plays is underscored by the fact that LOX knockout mice die shortly after birth because the connective tissue is too weak to support breathing. In addition, these mice have cardiac dysfunction and aortic aneurysms.24 These severe findings during development emphasise the significant physiological role of LOX in the generation of connective tissues. LOXL2 expression is more localised, with highest levels of mRNA found in human reproductive tissues.54 LOXL2 mRNA and protein are known to be upregulated in fibrotic tissues and diverse solid tumors when compared with normal human tissues.48 Serum LOXL2 levels positively correlate with a variety of disease states, including idiopathic pulmonary fibrosis (IPF),50 heart failure55 and liver fibrosis,48,49 indicating a pivotal role in various forms of fibrosis. Upon germline LOXL2 knockout in mice, 50% are found to be viable,

View Online

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

151

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

45

while the remainder have lethal congenital heart defects. Study of LOXL2 knockout or knockdown animals further highlighted the essential role of the enzyme in a variety of fibrotic conditions. For example, LOXL2 knockout prevents the development of transaortic constriction (TAC)-­induced cardiac interstitial fibrosis and dysfunction, as well as protecting the heart from TAC-­ induced chamber dilatation and functional decline.55 Furthermore, small interfering RNA (siRNA) knockdown of LOXL2 or LOXL3 in normal human lung fibroblasts significantly reduces fibroblast to myofibroblast transition.3 In general, LOXL3 and LOXL4 are present at much lower levels than the other members of the family,56 however, the important role of LOXL3 in pulmonary fibrosis has recently been described.3 Considering the important physiological role of LOX, in cases where it contributes to disease, therapeutic benefits of inhibition may be limited to intermittent treatment in severe disease or locally restricted action. On the other hand, due to the more specific expression of LOXL2 (and LOXL3) in the fully developed organism and their strong association with fibrotic disease states, selective inhibition can be expected to offer a favourable balance of efficacy and tolerability for long-­term systemic treatment.

5.6  Inhibitors of Lysyl Oxidase (Like) Enzymes In light of the fundamental contribution of the lysyl oxidase (like) enzymes to fibrotic disease and extracellular matrix modelling, there is significant interest in the modulation of their activity. Despite this, only a limited number of examples of lysyl oxidase inhibitors, covering a range of different profiles, have been described. The frequently used tool pan-­LOX inhibitor BAPN is a naturally occuring substance (found, for example, in some legumes). It is a nonselective mechanism-­based, irreversible lysyl oxidase inhibitor.57,58 The mechanism of LOX inhibition by BAPN has been probed using differentially [14C]-­labelled inhibitors, as well as measuring the copper content of preparations before and after incubation with BAPN.31 As mentioned above, BAPN treatment has been associated with a range of undesirable effects in animals. Nonetheless, given the fundamental interest in the mechanism by which lysyl oxidase inhibition diminishes, and potentially reverses fibrosis, BAPN was evaluated in human studies. Oral doses of gram quantities were administered to systemic scleroderma patients over periods of several months.59 In this limited trial, BAPN was found to increase the amount of soluble collagen but exhibited no beneficial effect on disease. Furthermore, longer courses of treatment appeared to be associated with prohibitive reactions, including the development of a lathyritic effect on bone in one patient. While BAPN had initially been identified as an inhibitor of LOX, it has subsequently been shown to be unselective, targeting all lysyl oxidase family members with modest potency. This promiscuity has rendered BAPN of little use for dissecting the differences in functional roles of lysyl oxidase family members in disease, necessitating the development of improved compounds to delineate the effect and consequence of selective isoform inhibition.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

152

Chapter 5

A group from Bayer has disclosed a series of substituted pyridazinones in patent applications.60 Example compounds are reported to have single to double-­digit nanomolar concentrations giving 50% of maximum inhibition (IC50) values for inhibiting LOX from bovine aorta. No data was provided regarding inhibition of other members of the enzyme family. Effects in a number of rat models of liver fibrosis have been described, e.g. Example 34 (Figure 5.3) significantly reduced total collagen in a pig serum-­induced liver fibrosis model. More recently, Springer and co-­workers have disclosed an aminomethylthiophene-­based inhibitor CCT365623 (Figure 5.3) with IC50 values in the micromolar range for both the LOX and LOXL2 isoforms and inhibitory effects on the growth of primary and metastatic tumour cells in vivo.61,62 Activities on LOXL1, 3 and 4 have not been disclosed. Researchers from TargetEx have reported substituted pyrazolines resulting from an in silico screen with inhibition IC50 values for LOX family enzymes in the micromolar range.63 As mentioned above, selective inhibition of isoforms with strong implication in disease (in particular LOXL2 and, probably, LOXL3), while not affecting those isoforms important for maintaining physiological homeostasis (especially LOX and LOXL1), would be expected to offer therapeutic benefit with the most favourable safety profile to patients. In this context, the development of a LOXL2-­selective antibody AB0023 by Arresto Biosciences and Gilead was followed with great expectation. The antibody, in combination with immunohistochemical methods, has proven useful in detecting LOXL2 protein changes in diseases, highlighting the role of LOXL2 in lung, liver and cardiac fibrosis as well as various cancers. Encouraging efficacy data in various pre-­clinical models of fibrosis and cancer have been reported.48,55 It was widely anticipated that this antibody would aid significantly in the elucidation of the specific role of LOXL2 in disease. However, when a humanised version of the antibody (AB0024, simtuzumab) was subsequently brought to testing for a range of indications in clinical settings, results were disappointing.64–68 This major setback for the field warranted thorough analysis aimed at understanding the significance of these results and the implications for

Figure 5.3  Structures  of some LOX inhibitors.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

153

potential future development of LOXL2-­targeted therapeutics. Most importantly, the antibody is only a poor blocker of LOXL2 enzymatic activity (in an in vitro assay approximately 60% of the enzymatic activity remains at micromolar concentration of the antibody).20,69 Thus, reduction of LOXL2 enzymatic activity by simtuzumab in the clinical setting is expected to have been very low and thus insufficient to result in a significant effect. Furthermore, target engagement at the enzymatic activity level has not been demonstrated. Any pre-­clinically observed anti-­fibrotic effects are therefore more likely to be attributable to a protein–protein interaction. Thus, the clinical failure of simtuzumab should not be seen as an invalidation of the therapeutic concept of LOXL2 enzyme inhibition, but rather, underscores the importance of ensuring a sustained and verifiably high degree of enzyme inhibition. More recently, researchers from PharmAkea Therapeutics reported the identification of small molecule inhibitors of LOXL2.69,70 Starting from substrate-­based considerations, they identified 4-­aminomethyl pyridine as an inhibitor template for further elaboration. The primary amine is thought to form a covalent bond with the active site LTQ moiety. An imine bond results, which appears to be protected from rapid hydrolysis, presumably due to tight binding of other regions of the molecule. The observation that a trifluoromethyl substituent in the pyridyl 2-­position greatly improves selectivity was key to the successful exploration of this compound class, in which a LOXL2 inhibition assay in human whole blood was used as an important driver of the optimisation. Finally, modulation of physicochemical properties resulted in the preferred compound, PAT-­1251 (Figure 5.4). Encouragingly, the compound showed long lasting enzyme inhibition in vitro, consistent with the proposed covalent binding mode. Selectivity over LOX was over 440-­fold, while over LOXL3 it was more modest; LOXL1 and LOXL4 selectivities were not determined. In mice, the compound (tested in its racemic form) achieved lung tissue exposure and efficacy in a bleomycin-­induced model of lung fibrosis.69 Interestingly, on the company's internet site a direct comparison of the amine oxidation inhibitory activity between PAT-­1251 and AB0023/simtuzumab is reported, demonstrating very different profiles and confirming that simtuzumab is not an efficacious inhibitor of LOXL2 enzymatic activity.71 PAT-­1251 has been successfully progressed to dosing in humans and evaluated in Phase 1 clinical trials. Evaluation of the compound in healthy human volunteers was accompanied by measurements of plasma concentration and plasma LOXL2 target engagement. While a 1000 mg dose at 2 h post-­administration resulted in high plasma concentration (13 µM) and high target engagement (92%), at 24 h the compound had been essentially completely cleared (residual plasma concentration 0.008 µM) and LOXL2 target engagement lost (1% remaining target engagement).72 While the rather rapid clearance of the compound from the bloodstream may be expected, the apparent lack of long lasting target engagement is disappointing, as the in vitro data indicated a different profile. The reasons for this discrepancy are, to the best of our knowledge, not known. Possible explanations may be

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

154

Chapter 5

Figure 5.4  Key  steps in the identification of PAT-­1251. LOXL2 IC50s were determined in human whole blood; the selectivity factors refer to data determined in the presence of 0.1% BSA, using concentrated conditioned media from CHO cells stably expressing human LOXL2 (hLOXL2) and HEK cells stably expressing human LOX (hLOX), respectively.69

differences between the experimental conditions of the in vitro experiments and the in vivo situation, or a rather rapid turnover of the LOXL2 protein. Further studies will be needed to establish whether PAT-­1251 may serve to demonstrate the anti-­fibrotic potential of LOXL2 enzyme inhibition in humans. The drug discovery group at Pharmaxis also chose a substrate and mechanism-­based approach to identify dual LOXL2/3 inhibitors that are selective over LOX and LOXL1. In this case, a key finding early in the project was that a fluoroallylamine moiety allows significantly more potent LOX family enzyme inhibition when linked through the γ-­position (PXS-­4206) rather than the β-­position, a constitution different to that typically found in amine oxidase inhibitors such as mofegiline. The geometry of the vinyl bond is also of importance, with (Z)-­geometry (PXS-­4731) showing the greatest inhibitory potency. It is assumed that these fluoroallylamines (that are not electrophiles per se) initially bind to the active site LTQ moiety through the primary amino group in analogy to the lysyl side chain of the endogenous substrate. Oxidation to the iminium functionality then activates the vinyl bond to Michael addition of an active site peptide residue, with fluoride acting as a leaving group to stabilise the adduct (Figure 5.5).31,73 Selectivity over LOX (and LOXL1, which pharmacologically behaves very similarly) was achieved when an apparent additional pharmacophoric interaction point for LOXL2/3 (but not LOX and LOXL1) was discovered that may

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

155

Figure 5.5  Schematic  representation of a plausible mechanism of covalent inhibi-

tion of lysyl oxidases by fluoroallylamines. LG = Leaving group, in the case of fluoroallylamines F−. Note: The warhead, e.g. fluoroallylamine, is not per se a reactive electrophile. Activation occurs taking advantage of the enzyme's mechanism once bound within the active site. The hypothesis for this mechanism is in analogy to ref. 31.

be addressed with a sulfonyl group. Phenyl or benzyl substituted indoles were identified as preferred scaffolds to present these features and PXS-­5120 resulted as a useful compound to explore efficacy in vivo (Figure 5.6).74 An important driver of compound optimisation was to ensure these primary amine containing compounds would not behave as substrates at amine oxidases, thus avoiding undesired metabolic clearance pathways. In particular, amine oxidase copper containing 1 [AOC1, also known as diamine oxidase (DAO)], AOC3 amine oxidase copper containing 3 [AOC3, also known as semicarbazide-­sensitive amine oxidase (SSAO)] and amine oxidase copper containing 4 (AOC4; an amine oxidase mainly of relevance for preclinical development, as it is present in most mammals with the exception of humans and rats) were identified as being capable of recognising early chemotypes as substrates. Choice of the scaffold and its substitution pattern were found to be ways to effectively avoid such potential liabilities, with appropriately substituted azaindoles achieving best results. An example of these, PXS-­5153 was shown to dose‐dependently reduce LOXL2‐mediated collagen oxidation and collagen cross-­linking in vitro. In line with these effects, in vivo it reduced disease severity and improved liver function by diminishing collagen content in rodent liver fibrosis models (carbon tetrachloride model in rats;

View Online

Chapter 5

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

156

Figure 5.6  Identification  and optimisation of fluoroallylamine-­based LOXL2/3 inhibitors.

Figure 5.7  Structures  of Pharmaxis' LOXL2/3 inhibitors in clinical development. streptozotocin/high-­fat diet model in mice) and improved cardiac output in myocardial infarction (coronary artery occlusion in mice).75 Based on the same azaindole scaffold, the best overall profiles were achieved following optimisation of substituent patterns, resulting in PXS-­ 5338 and PXS-­5382, both of which were progressed to further development (Figure 5.7). The compounds are potent inhibitors of LOXL2 with inhibition also at LOXL3 (PXS-­5382) and to a lesser extent LOXL4 (PXS-­5338), respectively (Table 5.2). Importantly, there is a significant margin of selectivity over LOX and LOXL1 inhibition. In addition, inhibition of LOXL2 and LOXL3 (which behave in similar ways pharmacologically) has been found to be irreversible, while interactions with LOX and LOXL1 are reversible. This difference in inhibition mode may further increase the effective selectivity at target engagement level, as inhibited LOX and LOXL1 enzyme would recover activity with declining drug concentration, while inhibited LOXL2 and LOXL3 would be dependent only on the rate of enzyme protein resynthesis.

View Online

Published on 17 February 2020 on https://pubs.rsc.org | doi:10.1039/9781788015783-00145

Inhibition of LOXL2 and Other Lysyl Oxidase (Like) Enzymes

157

Table 5.2  Inhibition  of lysyl oxidase enzymatic activity by a range of inhibitors in the same assay format, as determined at Pharmaxis. *The racemic form of the compound was used. The recombinant human form of the enzymes was used except for LOX (enzyme from bovine aorta). Ref. 75 for details. Negative log of the IC50 (pIC50) values are averages of at least two determinations (except **, single test occasion). SD, standard deviation. PXS-­5338 PXS-­5382 PXS-­5120 PXS-­5153 PAT-­1251* CCT365623 BAPN pIC50 ± SD LOX LOXL1 LOXL2 LOXL3 LOXL4

5.8 ± 0.1 5.6 ± 0.1 7.5 ± 0.2 6.4 ± 0.1 7.0 ± 0.1

6.0 ± 0.1 5.8 ± 0.2 8.1 ± 0.2 7.7 ± 0.1 6.9 ± 0.1

5.8 ± 0.1 5.7 ± 0.2 8.3 ± 0.2 7.8 ± 0.1 6.6 ± 0.1

5.9 ± 0.1 5.9 ± 0.2 7.7 ± 0.2 7.3 ± 0.2 7.0 ± 0.1