Structure and Function of GPCRs [1st ed. 2019.] 9783030245917, 3030245918

This book introduces readers to the latest advances in G protein-coupled receptor (GPCR) biology. It reviews our current

211 19 8MB

English Pages 289 [299] Year 2019

Report DMCA / Copyright

DOWNLOAD FILE

Polecaj historie

Structure and Function of GPCRs [1st ed. 2019.]
 9783030245917, 3030245918

Table of contents :
Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography --
NMR Spectroscopy for the Characterization of GPCR Energy Landscapes --
Structure and Activation Mechanism of GPCRs --
Structure-Based Discovery of GPCR Ligands from Crystal Structures and Homology Models --
Integration on Ligand and Structure Based Approaches in GPCRs --
Biased Agonist Pharmacochaperones: Small Molecules in the Toolbox for Selectively Modulating GPCR Activity --
Endosomal PTH Receptor Signaling Through cAMP and Its Consequence for Human Medicine --
Structure and Function Studies of GPCRs by Site-Specific Incorporation of Unnatural Amino Acids --
Fluorescent-Based Strategies to Investigate G Protein-Coupled Receptors: Evolution of the Techniques to a Better Understanding --
Modulation of Metabotropic Glutamate Receptors by Orthosteric, Allosteric, and Light-Operated Ligands.

Citation preview

Topics in Medicinal Chemistry  30

Guillaume Lebon Editor

Structure and Function of GPCRs

30

Topics in Medicinal Chemistry

Series Editors P.R. Bernstein, Philadelphia, USA A.L. Garner, Ann Arbor, USA G.I. Georg, Minneapolis, USA T. Kobayashi, Tokyo, Japan J.A. Lowe, Stonington, USA N.A. Meanwell, Princeton, USA A.K. Saxena, Lucknow, India U. Stilz, Boston, USA C.T. Supuran, Sesto Fiorentino, Italy A. Zhang, Pudong, China

Aims and Scope Topics in Medicinal Chemistry (TMC) covers all relevant aspects of medicinal chemistry research, e.g. pathobiochemistry of diseases, identification and validation of (emerging) drug targets, structural biology, drugability of targets, drug design approaches, chemogenomics, synthetic chemistry including combinatorial methods, bioorganic chemistry, natural compounds, high-throughput screening, pharmacological in vitro and in vivo investigations, drug-receptor interactions on the molecular level, structure-activity relationships, drug absorption, distribution, metabolism, elimination, toxicology and pharmacogenomics. Drug research requires interdisciplinary team-work at the interface between chemistry, biology and medicine. To fulfil this need, TMC is intended for researchers and experts working in academia and in the pharmaceutical industry, and also for graduates that look for a carefully selected collection of high quality review articles on their respective field of expertise. Medicinal chemistry is both science and art. The science of medicinal chemistry offers mankind one of its best hopes for improving the quality of life. The art of medicinal chemistry continues to challenge its practitioners with the need for both intuition and experience to discover new drugs. Hence sharing the experience of drug research is uniquely beneficial to the field of medicinal chemistry. All chapters from Topics in Medicinal Chemistry are published OnlineFirst with an individual DOI. In references, Topics in Medicinal Chemistry is abbreviated as Top Med Chem and cited as a journal. More information about this series at http://www.springer.com/series/7355

Guillaume Lebon Editor

Structure and Function of GPCRs With contributions by F. Acher  J.-L. Banères  S.S. Bhunia  J. Carlsson  M. Casiraghi  L.J. Catoire  T. Durroux  O. Faklaris  A. Falco  C. Goudet  E. Goyet  J. Heuninck  F.G. Jean-Alphonse  G. Lebon  A. Llebaria  C. Mendre  B. Mouillac  C. Nasrallah  J. Perroy  J.-P. Pin  A. Ranganathan  D. Rodríguez  P. Rondard  X. Rovira  A.K. Saxena  M. Saxena  I. Sutkeviciute  M. Tian  A.J. Venkatakrishnan  J.-P. Vilardaga  Q. Wang  S. Ye  C. Yuan  J.M. Zwier

Editor Guillaume Lebon Institut de Génomique Fonctionnelle Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM) University of Montpellier Montpellier, France

ISSN 1862-2461 ISSN 1862-247X (electronic) Topics in Medicinal Chemistry ISBN 978-3-030-24589-4 ISBN 978-3-030-24591-7 (eBook) https://doi.org/10.1007/978-3-030-24591-7 © Springer Nature Switzerland AG 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

A Decade of GPCR Structure and Signalling in Three Dimensions

G protein-coupled receptors (GPCRs) are localised at the plasma membrane of eukaryotic cells, and by sensing external stimuli they are key receptors for cellular communication [1]. They are involved in all physiological function and many pathological disorders. They are tractable drug targets as illustrated by the large numbers of molecules approved by the Food and drug Administration, and they still offer a large amount of opportunities for the conception of therapeutic molecules [2]. However, designing drugs will be for sure facilitated by a deep and thorough understanding of their biological function, 3D structure and conformation as well as the structure–function relation that is now supported by a large number of ligandbound GPCR high-resolution structures. Nasrallah and Lebon present several strategies that were developed and successfully used to facilitate the structural determination of GPCR ligand-bound conformation [3–6]. This chapter also discusses the future challenges to be undertaken for solving structure of GPCR signalling complexes. Indeed, the first view of a GPCR signalling complex X-ray structure – the β2-adrenergic receptor bound to heterotrimeric G protein – was reported in 2012 by the laboratory of Brian Kobilka [7]. Since then, we now have access to the highresolution structures of GPCR signalling complexes for several GPCR types. Indeed, recent technological development in cryogenic electron microscopy (cryoEM), direct electron detector and images processing have strongly facilitated the structure determination of flexible GPCR signalling complexes [8–11]. We can only expect even deeper understanding of the signalling, ligand-binding kinetics and ligand selectivity of this large family of receptors during the next decade and hopefully the discovery of first in class molecules. GPCRs are not only a seven transmembrane receptor that can be modulated by a ligand that binds to the orthosteric site localised within the seven transmembrane domain (7TM), but should also be seen as highly dynamic proteins for which several strategies can be envisioned in order to modulate their biological activity [1, 12, 13]. For most receptor classes, ligands bind inside the 7TM helix bundle, at various depths from the extracellular side. Several examples reported the binding of ligands in unusual pockets, sometimes buried within the lipid bilayers or within an extracellular vestibule as for the PAR2 receptor, or even down to intracellular side for the v

vi

A Decade of GPCR Structure and Signalling in Three Dimensions

CCR9 and CCR2 receptor [14–16]. Such observations illustrate the dynamic aspect of GPCR 7TM domains, pushing the concept of modulating the GPCR activity to almost no limitation. AJ Venkatashriman describes here a general view of structural feature of GPCR ligand-binding sites and how drugs can stabilise receptor conformations. Class A GPCR activation mechanism is also discussed in detail based on recent structural information and their unbiased computational analysis [17]. It clearly appears that despite a large number of X-ray structures available, from different classes of receptors, including class A, B, C and F, we still have to explore the conformational landscape of GPCRs and how ligands and intracellular signalling partners are modulating together the type and efficacy of signal transduction. Dynamic properties of GPCRs require special care and attention in order to perform structural characterisation. Nuclear magnetic resonance (NMR) is a powerful technique for investing receptor dynamics and conformational changes that are required for GPCR activation upon agonist binding [18–20]. Despite the challenge of labelling the protein, NMR offers unique possibilities to identify and characterise discrete receptor states at atomic resolution. Casiraghi and colleagues present a detailed update on NMR spectroscopy for the characterization of GPCR energy landscape and associated kinetic barriers [21]. Structural studies of GPCRs have delivered new insights into their ligand-binding mode and activation mechanism at an atomic level, offering unprecedented information for designing and discovering new drugs with therapeutic potential [22–24]. One can ask the real impact of GPCR structures on drug discovery process. Two chapters in this book contributed by Saxena and colleagues and Ranganathan and colleagues highlight the importance and also the limitations of GPCR highresolution structures for ligand docking and screening to identify new compounds. Top hits are specific of the receptor conformation trapped during the crystallisation process. They also describe and highlight the importance of the starting model and the choice of ligand for generating an accurate homology model. Structure-based drug discovery (SBDD) provides an additional strategy to develop and optimise therapeutic molecules. As a consequence, pharmaceutical industry has now engaged in the determination of GPCR high-resolution structures, reinforcing their drug discovery pipeline and their chance of success in identifying new molecules. GPCRs are signalling receptors for which understanding of their major function has also undertaken major evolution during the last decade [13, 25]. Internalisation and desensitization of receptor signalling were considered for a long time as a secondary effect of agonist stimulation interfering with G protein signalling. However, by interacting with β-arrestin and G protein-coupled receptor kinases (GRKs), GPCRs have additional G protein-independent signallings to their signalling repertoire. The variety of the signalling repertoire led to the major concepts of biased signalling and consequently of ligand selectivity. These broaden further the possibility of developing new molecules, selective of a given receptor but also with a specific signalling signature. Indeed, the scientific community aims at designing molecules biased toward a single signalling pathway and that likely represents the solution for developing drugs devoid of side effect [26]. The concept of biased

A Decade of GPCR Structure and Signalling in Three Dimensions

vii

agonists is presented by Bernard Mouillac and Christiane Mendre. In addition, they also discuss a peculiar example at the Vasopressin 2 receptor subtype for which mutations found in patients induce the production of misfolded and inactive receptors. In this specific case biased agonist also acts as chaperone by rescuing misfolded receptors to the plasma membrane and by specifically activating the Gs signalling pathway, balancing undesired biological effect observed in the pathology. GPCRs are activated at the plasma membrane triggering G protein activation, and later internalised by interacting with the β-arrestin protein or desensitised, but in both cases G protein coupling is alleviated. New paradigm in GPCRs is about intracellular and compartmentalized signalling. It was recently reported that the internalised β-adrenergic receptor can maintain a certain level of signal transduction whilst being redirected and trafficked in endosomes within the cellular cytoplasm [27]. Sutkeviciute and colleagues describe this new phenomenon for the parathyroid hormone (PTH) type 1 receptor (PTHR) and discuss the whole process of GPCR signalling in endosomes and its biological consequences. GPCRs display an important signalling plasticity, in time, and must be looked at as unusual proteins, highly flexible for which dynamics is the basis of their biological functions. New concepts about their biological function rise from the increasing interest and arousing number of investigations aiming at deciphering their biology. Several methodologies play important role in understanding the GPCR pharmacology and function. In addition to the important breakthrough due to the improvement of the structural biology techniques, additional technologies are available and in continuous development to favour the understanding of GPCR molecular mechanisms. Among these technologies, we can cite the genetic code expansion and the development of unnatural amino acids (Uaas). Over the last decade, it has gained interest for monitoring GPCR dynamics, ligands–receptor interaction and protein– protein interactions [28–30]. Tian and colleagues detail the methodology available and the use of photo-cross-linking Uaas and site-specific fluorescent labelling to select and analyse GPCR conformational changes. This chapter is illustrated with several examples for which Uaa technology allowed to track either helical conformational changes using infrared Uaas, ligand-induced conformational dynamics or mapping protein–protein interaction between via Uaa cross linking [28, 31, 32]. Other technologies use fluorescent-based strategies and contributed to the understanding of GPCR signalling and oligomerisation. Flakaris and colleagues present the principle of resonance energy transfer strategies that include BRET, FRET and time-resolved FRET as well as fluorescent strategy such as fluorescence correlation microscopy that is used to analyse GPCR dynamics and oligomerisation. They are indispensable for investigating the molecular pharmacology of GPCRs [33–35]. The devolvement of fluorescent–based technology allows to follow all steps of a GPCR life cycle, from ligand binding to G protein activation, second messenger production, protein kinase-dependent phosphorylation, internalisation and the even more challenging phenomenon of GPCR oligomerisation. As illustrated in this book, GPCRs are very diverse family of protein. Amongst the GPCR classes from, A, B, C, Adhesion and F, Class C is a peculiar small class,

viii

A Decade of GPCR Structure and Signalling in Three Dimensions

with only 22 members that include metabotropic receptors for glutamate and GABA that are respectively the main excitatory and inhibitory neurotransmitters of the central nervous system [36]. Goudet and colleagues give a large overview of class C metabotropic glutamate receptor family. Metabotropic glutamate receptors are composed of a large extracellular domain (ECD) where glutamate binds and of a conserved 7TM domain. They present this unique and obligatory dimeric molecular organisation, in addition to having the binding site for glutamate in the ECD and for allosteric modulators in the 7TM. They discuss the several possibilities recently developed for modulating their activity. Nanobodies targeting the extracellular domain were discovered recently opening new avenue for allosteric modulation mGlu receptors [37]. Finally photo-switchable ligands targeting the 7TM also offer the possibility to turn on and off the receptor activity on demands by using laser light sources [38–40]. Indeed, photopharmacology makes possible to target endogenous receptors and to have a spatial and time control of compound activity, allowing the tuning of the receptor activity on request and in a tissue-specific manner. This methodology has great promise for therapeutic application and also complements the large and diverse toolbox available for scientists wishing to investigate this fascinating family of GPCRs. This book neither pretends to cover all aspects of GPCRs nor to present all techniques available to date for investigating GPCR biological functions. The chapters presented here cover some of the most recent advances in the field and provide accessible understanding of recent achievements and also of the major challenges that remain to be tackled in the GPCR field. A decade ago, GPCRs were considered as 7TM domain receptors, composed of an orthosteric ligandbinding site that accommodates ligands and activates intracellular G protein and of potential distinct allosteric binding site. Indeed, allosteric modulation was already of high interest as well as dimerization and oligomerisation. But today, the knowledge about GPCRs has built up, and I hope that reading the book will provide a totally different view on GPCRs and foster ideas for an even better understanding and also for new concepts that hopefully will lead to discovering new therapeutic molecules. IGF, CNRS UMR, INSERM, University of Montpellier, Montpellier, France

Guillaume Lebon

References 1. Venkatakrishnan AJ et al (2013) Molecular signatures of G-protein-coupled receptors. Nature 494:185–194 2. Hauser AS et al (2018) Pharmacogenomics of GPCR drug targets. Cell 172:41– 54.e19

A Decade of GPCR Structure and Signalling in Three Dimensions

ix

3. Tate CG, Schertler GFX (2009) Engineering G protein-coupled receptors to facilitate their structure determination. Curr Opin Struct Biol 19:386–395 4. Warne T et al (2008) Structure of a beta1-adrenergic G-protein-coupled receptor. Nature 454:486–491 5. Manglik A, Kobilka BK, Steyaert J (2017) Nanobodies to study G proteincoupled receptor structure and function. Annu Rev Pharmacol Toxicol 57:19–37 6. Rosenbaum DM et al (2007) GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function. Science 318:1266–1273 7. Rasmussen SGF et al (2011) Crystal structure of the β2 adrenergic receptor-Gs protein complex. Nature 477:549–555 8. García-Nafría J, Nehmé R, Edwards PC, Tate CG (2018) Cryo-EM structure of the serotonin 5-HT1B receptor coupled to heterotrimeric Go. Nature 558:620– 623 9. Kang Y et al (2015) Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser. Nature 523:561–567 10. Draper-Joyce CJ et al (2018) Structure of the adenosine-bound human adenosine A1 receptor-Gi complex. Nature 558:559–563 11. Liang Y-L et al (2017) Phase-plate cryo-EM structure of a class B GPCR-Gprotein complex. Nature 546:118–123 12. Thal DM, Glukhova A, Sexton PM, Christopoulos A (2018) Structural insights into G-protein-coupled receptor allostery. Nature 559:45–53 13. Wootten D, Christopoulos A, Marti-Solano M, Babu MM, Sexton PM (2018) Mechanisms of signalling and biased agonism in G protein-coupled receptors. Nat Rev Mol Cell Biol. https://doi.org/10.1038/s41580-018-0049-3 14. Oswald C et al (2016) Intracellular allosteric antagonism of the CCR9 receptor. Nature 540:462–465 15. Zheng Y et al (2016) Structure of CC chemokine receptor 2 with orthosteric and allosteric antagonists. Nature 540:458–461 16. Cheng RKY et al (2017) Structural insight into allosteric modulation of protease-activated receptor 2. Nature 545:112–115 17. Venkatakrishnan AJ et al (2016) Diverse activation pathways in class A GPCRs converge near the G-protein-coupling region. Nature 536:484–487 18. Sounier R et al (2015) Propagation of conformational changes during μ-opioid receptor activation. Nature 524:375–378 19. Casiraghi M et al (2016) Functional modulation of a G protein-coupled receptor conformational landscape in a lipid bilayer. J Am Chem Soc 138:11170–11175 20. Isogai S et al (2016) Backbone NMR reveals allosteric signal transduction networks in the β1-adrenergic receptor. Nature 530:237–241 21. Casiraghi M, Damian M, Lescop E, Banères J-L, Catoire LJ (2018) Illuminating the energy landscape of GPCRs: the key contribution of solution-state NMR associated with Escherichia coli as an expression host. Biochemistry 57:2297– 2307 22. Congreve M, Dias JM, Marshall FH (2014) Structure-based drug design for G protein-coupled receptors. Prog Med Chem 53:1–63

x

A Decade of GPCR Structure and Signalling in Three Dimensions

23. Congreve M et al (2012) Discovery of 1,2,4-triazine derivatives as adenosine A (2A) antagonists using structure based drug design. J Med Chem 55:1898–1903 24. Christopher JA et al (2018) Structure-based optimization strategies for G protein-coupled receptor (GPCR) allosteric modulators: a case study from analyses of new metabotropic glutamate receptor 5 (mGlu5) X-ray structures. J Med Chem. https://doi.org/10.1021/acs.jmedchem.7b01722 25. Violin JD, Lefkowitz RJ (2007) Beta-arrestin-biased ligands at seventransmembrane receptors. Trends Pharmacol Sci 28:416–422 26. Manglik A et al (2016) Structure-based discovery of opioid analgesics with reduced side effects. Nature 537:185–190 27. Irannejad R et al (2013) Conformational biosensors reveal GPCR signalling from endosomes. Nature 495:534–538 28. Damian M et al (2015) Ghrelin receptor conformational dynamics regulate the transition from a preassembled to an active receptor:Gq complex. Proc Natl Acad Sci U S A 112:1601–1606 29. Grunbeck A, Huber T, Sachdev P, Sakmar TP (2011) Mapping the ligandbinding site on a G protein-coupled receptor (GPCR) using genetically encoded photocrosslinkers. Biochemistry 50:3411–3413 30. Naganathan S, Grunbeck A, Tian H, Huber T, Sakmar TP (2013) Geneticallyencoded molecular probes to study G protein-coupled receptors. J Vis Exp. https://doi.org/10.3791/50588 31. Tian H et al (2014) Bioorthogonal fluorescent labeling of functional G-proteincoupled receptors. Chembiochem 15:1820–1829 32. Ray-Saha S, Huber T, Sakmar TP (2014) Antibody epitopes on g proteincoupled receptors mapped with genetically encoded photoactivatable crosslinkers. Biochemistry 53:1302–1310 33. Scholler P et al (2013) Time-resolved Förster resonance energy transfer-based technologies to investigate G protein-coupled receptor machinery: highthroughput screening assays and future development. Prog Mol Biol Transl Sci 113:275–312 34. Briddon SJ, Kilpatrick LE, Hill SJ (2018) Studying GPCR pharmacology in membrane microdomains: fluorescence correlation spectroscopy comes of age. Trends Pharmacol Sci 39:158–174 35. Marullo S, Bouvier M (2007) Resonance energy transfer approaches in molecular pharmacology and beyond. Trends Pharmacol Sci 28:362–365 36. Pin J-P, Bettler B (2016) Organization and functions of mGlu and GABAB receptor complexes. Nature 540:60–68 37. Scholler P et al (2017) Allosteric nanobodies uncover a role of hippocampal mGlu2 receptor homodimers in contextual fear consolidation. Nat Commun 8:1967 38. Pittolo S et al (2014) An allosteric modulator to control endogenous G proteincoupled receptors with light. Nat Chem Biol 10:813–815

A Decade of GPCR Structure and Signalling in Three Dimensions

xi

39. Goudet C, Rovira X, Llebaria A (2018) Shedding light on metabotropic glutamate receptors using optogenetics and photopharmacology. Curr Opin Pharmacol 38:8–15 40. Font J et al (2017) Optical control of pain in vivo with a photoactive mGlu5 receptor negative allosteric modulator. elife 6:e23545

Contents

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chady Nasrallah and Guillaume Lebon

1

NMR Spectroscopy for the Characterization of GPCR Energy Landscapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marina Casiraghi, Jean-Louis Banères, and Laurent J. Catoire

27

Structure and Activation Mechanism of GPCRs . . . . . . . . . . . . . . . . . . . A. J. Venkatakrishnan Structure-Based Discovery of GPCR Ligands from Crystal Structures and Homology Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anirudh Ranganathan, David Rodríguez, and Jens Carlsson

53

65

Integration on Ligand and Structure Based Approaches in GPCRs . . . . 101 Anil K. Saxena, Shome S. Bhunia, and Mridula Saxena Biased Agonist Pharmacochaperones: Small Molecules in the Toolbox for Selectively Modulating GPCR Activity . . . . . . . . . . . . . . . . . . . . . . . 163 Bernard Mouillac and Christiane Mendre Endosomal PTH Receptor Signaling Through cAMP and Its Consequence for Human Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Ieva Sutkeviciute, Frederic G. Jean-Alphonse, and Jean-Pierre Vilardaga Structure and Function Studies of GPCRs by Site-Specific Incorporation of Unnatural Amino Acids . . . . . . . . . . . . . . . . . . . . . . . . 195 Meilin Tian, Qian Wang, Chonggang Yuan, and Shixin Ye Fluorescent-Based Strategies to Investigate G Protein-Coupled Receptors: Evolution of the Techniques to a Better Understanding . . . . 217 Orestis Faklaris, Joyce Heuninck, Amandine Falco, Elise Goyet, Jurriaan M. Zwier, Jean-Philippe Pin, Bernard Mouillac, Julie Perroy, and Thierry Durroux xiii

xiv

Contents

Modulation of Metabotropic Glutamate Receptors by Orthosteric, Allosteric, and Light-Operated Ligands . . . . . . . . . . . . . . . . . . . . . . . . . 253 Cyril Goudet, Xavier Rovira, Philippe Rondard, Jean-Philippe Pin, Amadeu Llebaria, and Francine Acher Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285

Top Med Chem (2019) 30: 1–26 DOI: 10.1007/7355_2017_28 © Springer International Publishing AG 2017 Published online: 5 October 2017

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography Chady Nasrallah and Guillaume Lebon

Abstract During the last decade, more than 130 structures of G Protein-Coupled Receptors were solved mostly using X-ray crystallography, either bound to antagonist, agonist or in complexes with intracellular partners such as G-proteins and arrestin. These structures shed light on molecular mechanisms of GPCR ligand recognition, activation, and allosteric modulation. This is primarily due to tremendous advances in protein engineering and micro-crystallography making GPCRs structure determination more straightforward. This chapter presents an overview of the widely used and successful approaches that led to atomic resolution structures of GPCR. Moreover, we briefly introduce recent technological advancements in the structural biology field that will undoubtedly accelerate solving GPCRs structure in the foreseeable future and provide a more complete understanding of GPCR signaling. Keywords Detergents solubilization, Stability, X-ray crystallography

Diffraction,

GPCRs,

Micro-crystals,

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Large-Scale Production of GPCRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solubilization of GPCRs Prior to Crystallization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Enhancing GPCRs Crystallizablity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Sample Homogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Binding Partners Stabilizing Receptor Conformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Increasing Receptor Hydrophilic Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Increasing Receptor Thermal Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

C. Nasrallah and G. Lebon (*) Institut de Ge´nomique Fonctionnelle, Centre National de la Recherche Scientifique (CNRS), Institut National de la Sante´ et de la Recherche Me´dicale (INSERM), Universite´ de Montpellier, Montpellier 34000, France e-mail: [email protected]

2 2 13 15 15 17 18 19

2

C. Nasrallah and G. Lebon

5 GPCR Sub-Micrometer and Micrometer-Size Crystals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

1 Introduction G Protein-Coupled Receptors (GPCRs) are the largest class of human extracellular cell-exposed receptors (800 members) that recognize a large array of ligands and mediate diverse intracellular signalling cascades [1]. In the last several years, the available high-resolution X-ray crystallography structures of GPCRs advanced our understanding of cell signalling and in particular of the molecular switches that occur upon receptor activation and the intimate connections that bind these receptors to their natural or synthetic ligands [2, 3]. In addition, these structures gave insights into the spectrum of conformational states that GPCRs could adapt starting from the inactive ground state (R) to the fully active state (R*) when coupled to heterotrimeric G proteins. Indeed, this high inherent conformational flexibility constitutes a major challenge for obtaining well-ordered crystals required for structural studies by X-ray crystallography [4]. Here, we give an overview of the limitations encountered when attempting to crystallize and solve GPCR highresolution structures, including expression and purification of large amount of functional receptors with controlled inherent conformational flexibility. We summarize the methodological advances that helped to overcome these limitations and enabled GPCR structural determination. This includes a variety of innovative strategies such as (a) the use of binding partners (e.g. Fabs or nanobodies) to lock the receptor in a single conformation (b) the replacement of flexible loops by a stable soluble fusion protein in order to increase the hydrophilic molecular surface of the receptor (c) the introduction of thermostablizing mutations and/or the mixture of these strategies (Fig. 1). Finally, we emphasize on how novel structural developments are likely to change the face of GPCR research in the near future paving the way for accelerating GPCR structure determination not only for ligandbound conformations but also for complexes with different intracellular partners.

2 Large-Scale Production of GPCRs With the exception of rhodopsin that is expressed at high level and can be extracted form native tissues, GPCRs are usually expressed at very low levels [5]. In order to perform crystallization trials, large quantities of proteins need to be produced. Several strategies can be followed for performing large scale GPCRs expression, all relying on heterologous expression systems. The choice of the expression system for the target protein is often empirical, yet it is admitted that the closer the chosen expression system is to the native environment of the target protein, the

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography

3

Fig. 1 Successful stabilization strategies enhancing GPCRs crystallization. (a) Structures of transmembrane domain (7TM) GPCR (cartoon mode; grey) crystallized with different binding partners (cartoon mode; green) are shown: The human β2 adrenergic receptor (β2AR) in complex with an antibody fragment (Fab) (upper left; PDB code 2R4S); the agonist-bound of the human M2 muscarinic acetylcholine receptor stabilized by a nanobody fragment (Nb) (upper right; PDB code 4MQS) and the adenosine A2A receptor (A2AR) bound to an engineered G protein, mini-Gs (bottom left; PDB code 5G53). (b) Structures of engineered 7TM domain GPCR crystallized with different fusion proteins (cartoon mode; cyan) are highlighted: The structure of the A2A receptor with apocytochrome b(562)RIL (BRIL) fusion protein replacing its third intracellular loop (upper; PDB code 4EIY) and the structure of the A2A receptor with T4 Lysozyme (T4L) fusion protein replacing its third intracellular loop (bottom; PDB code 4EML). (c) Structure of adenosine A2A receptor with 4 thermostabilizing point mutations (sphere mode; red) is shown (upper; PDB code 2YDO). (d) A mix of different stabilizing strategies (a–c) is highlighted: The structure of metabotropic glutamate receptor 5 (mGlu5) with 6 thermostabilizing point mutations and a T4L fusion protein replacing the ICl2 is shown (upper; PDB code 4OO9). The structure of beta2AR with T4L fusion protein replacing its third intracellular loop and bound to an engineered nanobody is shown (bottom left; PDB code 4QKX) and the structure of the ternary complex composed of beta2AR fused to the T4L lysozyme (N), the Nb and nucleotide-free Gs heterotrimer (bottom right; PDB code 3SN6). See Table 1 for more details

better are the chances to retrieve a well-folded and fully functional receptor. This is especially true for GPCRs that are difficult to express in prokaryote system in a functional state [6]. GPCR structures were solved for the majority from receptors produced using baculovirus expression system in insect cells, while only a minority were solved using other systems such bacteria (e.g. Escherichia coli) and yeast (e.g. Pichia Pastoris) (Table 1). Indeed, insect cell expression system has a more sophisticated cellular and enzymatic machinery than bacteria and yeast ensuring production of functional protein and performing post-translational modifications.

Lipid cubic phase Vapor diffusion

Sf9 Sf9 High five High five Sf9 Sf9 Sf9 Sf9 Sf9 Sf9 Sf9 P. pastoris High five High five High five High five

T4L-ICl3

T4L-ICl3

T.S mutations

T.S mutations

T.S mutations

T.S mutations

T.S mutations

T.S mutations

T.S mutations

T.S mutations

BRIL-ICl3

Fab

T.S mutations

T.S mutations

T.S mutations

T.S mutations

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Adenosine A2A receptor

Sf9

BRIL-ICl3

Crystallization method

Adenosine A1 receptor

Expression system

Class A Rhodopsin-like

Stabilization method

Receptors

GPCRs class

Modified ZM-compound 12 c (ANT)

ZM241385 (ANT)

CGS21680 (AGO)

CGS21680 (AGO)

4-(2-[7-amino-2-(2-furyl)-[1,2,4]triazolo-[2,3-a] [1,3,5] triazin-5-ylamino]ethyl)-phenol (ANT)

ZM241385 (ANT)

ZM241385 (ANT)

4-(3-Amino-5-phenyl-1, 2,4-triazin-6-yl)-2-chlorophenol (ANT)

6-(2,6-Dimethylpyridin-4-yl)-5-phenyl-1, 2,4-triazin-3amine (ANT)

Caffeine (ANT)

XAC (ANT)

ZM241385 (ANT)

NECA (AGO)

Adenosine (AGO)

UK432097 (AGO)

ZM241385 (ANT)

DU172 (ANT)

Ligand (type)

Table 1 Structures of non-rhodopsin GPCRSs solved by X-ray crystallography

R

R

R*

R*

R

R

R

R

R

R

R

R

R* int

R* int

R* int

R

R

Conf. state

5IU7 (1.9 A)

5IU4 (1.7 A)

4UHR (2.6 A)

4UG2 (2.6 A)

3VGA (3.1 A)

4EIY (1.8 A)

3VG9 (2.7 A)

3UZC (3.3 A)

3UZA (3.2 A)

3RFM (3.6 A)

3REY (3.3 A)

3PWH (3.3 A)

2YDV (2.6 A)

2YDO (3 A)

3QAK (2.7 A)

3EML (2.6 A)

5UEN (3.2 A)

PDB code (Resolution)

Segala et al. [16]

Lebon et al. [15]

Hino et al. [13]

Liu et al. [14]

Hino et al. [13]

Congreve et al. [12]

Dore et al. [11]

Lebon et al. [10]

Xu et al. [9]

Jaakola et al. [8]

Glukhova et al. [7]

Ref.

4 C. Nasrallah and G. Lebon

Class A rhodopsin-like

Beta-1 adrenergic receptor

Angiotensin receptor (AT2R)

Angiotensin receptor (AT1R)

Sf9 Sf9 Sf9 Sf9

BRIL-ICl3

BRIL-ICl3

BRIL-ICl3

BRIL-ICl3

High five High five High five High five High five High five

T.S mutations

T.S mutations

T.S mutations

T.S mutations

T.S mutations

Sf9

BRIL (N)

T.S mutations

Sf9

BRIL (N)

Sf9

High five

Binding miniGs

BRIL (N)

High five

T.S mutations

Sf9

High five

T.S mutations

BRIL (N)

High five

T.S mutations

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Salbutamol (PAG)

Isoprenaline (AGO)

Carmoterol (AGO)

Dobutamine (PAG)

Dobutamine (PAG)

Cyanopindolol (ANT)

(N-[(furan-2-yl)methyl]-N-(4-oxo-2-propyl-3-{[20 -(2H-tetrazol-5-yl)[1,10 -biphenyl]-4-yl]methyl}-3,4dihydroquinazolin-6-yl)benzamide) (ANT)

(N-benzyl-N-(2-ethyl-4-oxo-3-{[20 -(2H-tetrazol-5-yl) [1,10 -biphenyl]-4-yl])methyl}-3,4-dihydroquinazolin-6yl)thiophene-2-carboxamide) (ANT)

ZD7155 (ANT)

Olmestran (IAG)

ZM241385 (ANT)

ZM241385 (ANT)

ZM241385 (ANT)

ZM241385 (ANT)

NECA (AGO)

Modified ZM-compound 12 x (ANT)

Modified ZM-compound 12 b (ANT)

Modified ZM-compound 12 f (ANT)

R* int

R*

R*

R* int

R* int

R

R

R

R

R* int

R

R

R

R

R*

R

R

R

2Y04 (3.05 A)

2Y03 (2.85 A)

2Y02 (2.6 A)

2Y01 (2.6 A)

2Y00 (2.5 A)

2VT4 (2.7 A)

5UNH (2.9 A)

5UNF (2.8 A)

4YAY (2.9 A)

4ZUD (2.8 A)

5K2D (1.9 A)

5K2C (1.9 A)

5K2B (2.5 A)

5K2A (2.5 A)

5G53 (3.4 A)

5IUB (2.1 A)

5IU4 (2.2 A)

5IU8 (2 A)

(continued)

Warne et al. [23]

Warne et al. [22]

Zhang et al. [20, 21]

Zhang et al. [20, 21]

Zhang et al. [19]

Batyuk et al. [18]

Carpenter et al. [17]

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography 5

Beta-2 adrenergic receptor

Table 1 (continued)

Sf9 Sf9

T4L-ICl3

Fab

High five

T.S mutations

Sf9

High five

T.S mutations

T4L-ICl3

High five

T.S mutations

Sf9

High five

T.S mutations

T4L-ICl3

High five

T.S mutations

Sf9

High five

T.S mutations

T4L-ICl3

High five

T.S mutations

Sf9

High five

T.S mutations

Fab

High five

T.S mutations

Sf9

High five

T.S mutations

Fab

High five

T.S mutations

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Vapor diffusion

Vapor diffusion

Vapor diffusion

Lipid cubic phase

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Vapor diffusion

Carazolol (IAG)

Ethyl-4-[2-hydroxy-3(isopropylamino)propoxy]-3methyl-1-benzofuran-2-carboxylate (IAG)

ICI (118,551) (2S, 3S)-1-[(7-methyl-2,3-dihydro-1Hinden-4-yl) oxy]-3-[(1-methylethyl) amino] butan-2-ol (IAG)

Timolol (IAG)

Carazolol (IAG)

Carazolol (IAG)

Carazolol (IAG)

7-Methylcyanopindolol (IAG)

Cyanopindolol (ANT)

4-(Piperazin-1-yl)-1H-indole (ANT)

4-Methyl-2-(piperazin-1-yl) quinolone (ANT)

(APO)

Carvedilol (BAG)

Bucindolol (BAG)

Iodocyanopindolol (ANT)

Cyanopindolol (ANT)

Cyanopindolol (ANT)

Carazolol (IAG)

R

R

R

R

R

R

R

R

R

R

R

R* int

R* int

R* int

R

R

R

R* int

3KJ6 (3.4 A)

3NY9 (2.84 A)

3NY8 (2.84 A)

3D4S (2.8 A)

2RH1 (2.4 A)

2R4S (3.4 A)

2R4R (3.4 A)

5A8E (2.4 A)

4BVN (2.1 A)

3ZPQ (2.8 A)

3ZPR (2.7 A)

4GPO (3.5 A)

4AMJ (2.3 A)

4AMI (3.2 A)

2YCZ (3.65 A)

2YCY (3.15 A)

2YCX (3.25 A)

2YCW (3.0 A)

Bokoch et al. [34]

Wacker et al. [33]

Hanson et al. [132]

Cherezov et al. [31]

Rasmussen et al. [30]

Sato et al. [29]

Miller-Gallacher et al. [28]

Christopher et al. [27]

Huang et al. [26]

Warne et al. [25]

Moukhametzianov et al. [24]

6 C. Nasrallah and G. Lebon

Class A rhodopsin- like

Rubredoxine

T.S mutations

(CCR5)

(CCR9)

Sf9

Sf9

Sf9

Sf9

PGS-ICl3 ; T.S mutation

T4L-ICL3

Lipid cubic phase

HEk293F

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

FlavodoxinICl3 ; T.S mutations

Sf9

T4L (N); Nb6B9

(CCR2)

CC Chemokine receptor

Cannabinoid receptor (CB1)

Sf9

T4L (N); Nb6B9

Lipid cubic phase

Lipid cubic phase

Sf9

T4L (N); Nb6B9

Lipid cubic phase

Sf9

Sf9

T4L (N); Nb6B9

Lipid cubic phase

Nb60

Sf9

T4L (N)

Lipid cubic phase

Sf9

Sf9

T4L (N); Nb35; trimeric Gp

Vapor diffusion

T4L-ICL3

Sf9

T4L-ICl3

Lipid cubic phase

Sf9

Sf9

T4L-ICl3

Lipid cubic phase

T4L-ICL3

Sf9

T4L-ICl3

Vercirnon (ANT)

Maraviroc (IAG)

BMS-681 (ANT)

Taranabant (ANT)

AM6538 (ANT)

Carazolol (IAG)

Carazolol (IAG)

Carazolol (IAG)

(2-Sulfanylethoxy) phenyl] ethyl} amino) ethyl] benzene-1,2-diol (AGO)

4-[(1R)-1-Hydroxy-2-({2-[3-methoxy-4-

Adrenaline (AGO)

Hydroxybenzyl isoproterenol (AGO)

BI-167107 (AGO)

Carazolol (IAG)

BI-167107 (AGO)

FAUC50 (IAGO)

BI-167107 (AGO)

Alprenolol (ANT)

R

R

R

R

R

R

R

R

R*

R*

R*

R*

R

R*

R* int

R* int

R

5LWE (2.8 A)

4MBS (2.71 A)

5T1A (2.81 A)

5U09 (2.6 A)

5TGZ (2.8 A)

5JQH (3.2 A)

5D5A (2.48 A)

5D5B (3.8 A)

4QKX (3.3 A)

4LDO (3.2 A)

4LDL (3.1 A)

4LDE (2.79 A)

4GBR (3.99 A)

3SN6 (3.2 A)

3PDS (3.5 A)

3P0G (3.5 A)

3NYA (3.16 A)

(continued)

Oswald et al. [47]

Tan et al. [46]

Zheng et al. [45]

Shao et al. [44]

Hua et al. [43]

Staus et al. [42]

Huang et al. [41]

Weichert et al. [40]

Ring et al. [39]

Zou et al. [38]

Rasmussen et al. [35, 36]

Rosenbaum et al. [37]

Rasmussen et al. [35, 36]

Wacker et al. [33]

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography 7

Class A rhodopsin-like

Sf9 Sf9 Sf9

T.S mutations; T4L-ICL3

T.S mutations; T4L-ICL3

M2 muscarinic acetylcholine receptor (CHRM2)

Sf9

Sf9

T4L-ICL3

Nb9-8

Sf9

Sf9

Disulfide engineering; BRILICL3

T4L-ICL3

Sf9

BRIL-ICL3

M1 muscarinic acetylcholine receptor (CHRM1)

Sf9

BRIL-ICL3

Lysophosphatidic acid receptor (LPA1)

Sf9

T4L-ICL3

Histamine receptor 1 (H1R)

Sf9

T.S mutations; T4L-ICL3

Sf9

n.d

Endothelin receptor B

Sf9

T.S mutations; T4L-ICL3

T.S Mutations; T4L-ICL3

Sf9

T.S mutations; T4L-ICL3

Dopamine receptor 3 (D3R)

Sf9

T.S mutations; T4L-ICL3

Sf9

Sf9

T.S mutations; T4L-ICL3

Disulfide engineering

Sf9

T.S mutations; T4L-ICL3

Cytomegalovirus US28

(CXCR4)

Table 1 (continued)

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Iperoxo (AGO)

3-Quinuclidinyl-benzilate (ANT)

Tiotropium (IAG)

ONO-3080573 (ANT)

R*

R

R* int

R

R

R

ONO9780307 (ANT) ONO-9910539 (ANT)

R

R* int

Apo

R* int

R

R

R

R

R

R

R

R

Doxepin (ANT)

TAK-875 (Fasiglifam) (PAG)

Apo

Endothelin 1 (Ago)

Eticlopride (ANT)

Fractalkine -CX3CL1 (Ago)

vMIP-II (ANT)

CVX15r (ANT)

IT1t (Isothiourea derivative) (ANT)

IT1t (Isothiourea derivative) (ANT)

IT1t (Isothiourea derivative) (ANT)

IT1t (Isothiourea derivative) (ANT)

4MQS (3.5 A)

3UON (3.0 A)

5CXV (2.7 A)

4Z36 (2.9A)

4Z35 (2.9 A)

4Z34 (3.0 A)

3RZE (3.1 A)

4PHU (2.33 A)

5GLI (2.5 A)

5GLH (2.8 A)

3PBL (2.89 A)

4XT1 (2.89 A)

4RWS (3.1 A)

3OE0 (2.9 A)

3OE9 (3.1 A)

3OE8 (3.1 A)

3ODU (2.5 A)

3OE6 (3.2 A)

Kruse et al. [58]

Haga et al. [57]

Thal et al. [56]

Chrencik et al. [55]

Shimamura et al. [54]

Srivastava et al. [53]

Shihoya et al. [52]

Chien et al. [51]

Burg et al. [50]

Qin et al. [49]

Wu et al. [48]

8 C. Nasrallah and G. Lebon

E. coli E. coli E. coli High five High five nd

T.S mutations

T.S mutations

T.S mutations

T.S mutations; T4L-ICL3

T.S mutations; T4L-ICL3

nd

Orexin receptor type 1 (Ox1)

Nociceptin/orphanin FQ receptor (NOP/ORL-1)

PGS domainICL3

Sf9

Sf9

E. coli

T.S mutations

BRIL (N)

Vapor diffusion

High five

T.S mutations; T4L-ICL3

Neurotensin receptor

Sf9

Vapor diffusion

Sf9

mT4L-ICL3

M4 muscarinic Acetylcholine Receptor (CHRM3)

BRIL (N)

Vapor diffusion

Sf9

T4L-ICL3

Sf9

Vapor diffusion

Sf9

T4L-ICL3

BRIL (N)

Lipid cubic phase

Sf9

T4L-ICL3

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

nd

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Sf9

T4L-ICL3

M3 muscarinic Acetylcholine Receptor (CHRM3)

Lipid cubic phase

Sf9

Nb9-8

Suvorexant (ANT)

C-35 (ANT)

SB-612111 (ANT)

1-Benzyl-N-(3-[spiroisobenzofuran-1(3H),40 -piperidin1-yl]propyl)pyrrolidine-2-carboxamide (ANT)

NT1 (Neurotensin) (AGO)

NTS8-13q (AGO)

NTS8-13q (AGO)

NT1 (Neurotensin) (AGO)

NT1 (Neurotensin) (AGO)

NT1 (Neurotensin) (AGO)

NT1 (Neurotensin) (AGO)

NTS8-13q (AGO)

R

R

R

R

R* int

R* int

R* int

R* int

R* int

R* int

R* int

R* int

R* int

R

N-methylscopolamine NMS (ANT) Tiotropium (IAG)

R* int

R* int

R* int

R*

Tiotropium (IAG)

Tiotropium (IAG)

Tiotropium (IAG)

Iperoxo +LY2119620p (AGO)

4ZJ8 (2.75 A)

5DHG (3.0 A)

5DHH (3.0 A)

4EA3 (3.01 A)

5T04 (3.3 A)

4XEE (2.9 A)

4XES (2.6 A)

4BWB (3.57 A)

4BV0 (3.1 A)

4BUO (2.75 A)

3ZEV (3 A)

4GRV (2.8 A)

5DSG (2.6 A)

4U16 (3.7 A)

4UI5 (2.8 A)

4U14 (3.57 A)

4DAJ (3.4 A)

4MQT (3.7 A)

(continued)

Yin et al. [65]

Miller et al. [64]

Thompson et al. [63]

Krumm et al. [62]

Krumm et al. [61]

Egloff et al. [6]

White et al. [60]

Thal et al. [56]

Thorsen et al. [59]

Kruse et al. [58]

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography 9

Sf9 Sf9 Sf9

dsT4L-ICL3

mT4L-ICL3

mT4L-ICL3

Sf9 Sf9

RubredoxineICL3

Sf9

BRIL-ICL3

RubredoxineICL3

Sf9

BRIL-ICL3

Purinoceptor 1 (P2Y1)

Sf9

Sf9

n.d

BRIL-ICL3

Sf9

BRIL (N)

Purinoceptor 12 (P2Y12)

Sf9

T4L-ICL3

Sf9

Sf9

nd

T4L-ICL3

Sf9

Fab

Protease-activated receptor1

δ-Opioid receptor

Sf9

T4L-ICL3

μ-Opioid receptor

Sf9

T4L-ICL3

κ-Opioid receptor

Sf9

PGS domainICL3

Orexin receptor type 2 (Ox2)

Table 1 (continued)

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

BPTU (ANT)

MRS2500 (ANT)

2MeSATP: methylthio-adenosine-50 -triphosphate (PAG)

2MeSADP: 2-methylthio-adenosine-50 -diphosphate (AGO)

AZD1283:Ethyl 6-(4-((benzylsulphonyl) carbamoyl) piperidin-1-yl)-5-cyano-2-methylnicotinate (ANT)

Vorapaxar (ANT)

DIPP-NH2 (ANT)

Naltrindole (ANT)

Naltrindole (ANT)

DIPP-NH2 (AGO)

BU72 (AGO)

NMS (ANT)

Tiotropium (ANT)

Tiotropium (ANT)

β-Funaltrexamine (β-FNA) (ANT)

(3R)-1,2,3,4-tetrahydro-7-hydroxy-N-[(1S)-1-[[(3R, 4R)4-(3-hydroxyphenyl)3,4-dimethyl-1-piperidinyl] methyl] 2-methylpropyl]-3-isoquinolinecarboxamide) (ANT)

Suvorexant (ANT)

SB-674042 (ANT)

R

R

R* int

R* int

R

R

R

R

R

R* int

R*

R

R

R

R

R

R

R

4XNV (2.2 A)

4XNW (2.7 A)

4PY0 (3.1 A)

4PXZ (2.5 A)

4NTJ (2.62 A)

3VW7 (2.2 A)

4RWA (3.28 A)

4N6H (1.8 A)

4EJ4 (3.4 A)

4RWD (2.7 A)

5C1M (2.1 A)

4U16 (3.7 A)

4U15 (2.8 A)

4U14 (3.57 A)

4DKL (2.8 A)

4DJH (2.9 A)

4S0V (2.5 A)

4ZJC (2.83 A)

Zhang et al. [19]

Zhang et al. [74]

Zhang et al. [73]

Fenalti et al. [70]

Fenalti et al. [72]

Granier et al. [71]

Fenalti et al. [70]

Huang et al. [69]

Thorsen et al. [59]

Thorsen et al. [59]

Manglik et al. [68]

Wu et al. [67]

Yin et al. [66]

10 C. Nasrallah and G. Lebon

Class C metabotropic glutamate

Class B secretin like

Sf9

T.S mutations

Sf21

Sf21 Sf21

BRIL (N)

T4L-ICl2; T.S mutations

T4L-ICl2; T.S mutations

T4L-ICl2; T.S mutations

Metabotropic glutamate receptor type 5

Sf9

Sf9

Sf21

T4L-ICL2; T.S mutations

T4L-ICL2; T.S mutations

Sf9

BRIL (N)

Sf9

Sf9

BRIL-ICL3; T. S mutations

T4L-ICL3

Sf9

Sf9

BRIL-ICL3; T. S mutations

BRIL-ICL3; T. S mutations

Sf9

BRIL-ICL3; T. S mutations

Metabotropic glutamate receptor type 1

Corticotropin-releasing factor receptor 1

Glucagon receptor

Sphingosine-1-phosphate receptor

Serotonin (5-hydroxytryptamine) type 2b receptor

Serotonin (5-hydroxytryptamine) type 1b receptor

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

HTL14242:3-chloro-4-fluoro-5-[6-(5-fluopyridin-2-yl) pyrimidin-4-yl]benzonitrile (ANT)

3-Chloro-4-fluoro-5-[6-(1H-pyrazol-1-yl)pyrimidin-4-yl] benzonitrile (ANT)

Mavoglurants: Methyl (3aR,4S,7aR)-4-hydroxy-4[(3-methylphenyl) ethynyl] octahydro-1H-indole 1-carboxylate (ANT)

FITMs: 4-fluoro-N-(4-(6-(isopropylamino)pyrimidin4yl) thiazol-2-yl) N-methylbenzamide (ANT)

CP-376395: 3,6-dimethyl-N-pentan-3-yl 2-(2,4,6trimethyl phenoxy)pyridin-4-amine (ANT)

MK-0893 (ANT)

NNC0640: 4-[1-(4-Cyclohexylphenyl) 3-(3-methanesulfonyl phenyl) ureidomethyl]-N(2H-tetrazol-5-yl) benzamide (ANT)

ML056: (R)-3-amino-(3-hexyl phenylamino)-4-oxobutyl phosphonicacid (ANT)

LSD (AGO)

Ergotamine (BAG)

Ergotamine (BAG)

Dihydroergotamine (AGO)

Ergotamine (AGO)

R

R

R

R

R

R

5CGD (2.6 A)

5CGC (3.1 A)

4OO9 (2.6 A)

4OR2 (2.8 A)

4K5Y (2.98 A)

5EE7 (2.5 A)

4L6R (3.4 A)

3V2Y (2.8 A)

R R

3V2W (3.35 A)

5TVN (2.9 A)

4NC3 (2.8 A)

4IB4 (2.7 A)

4IAQ (2.8 A)

4IAR (2.7 A)

R

R* int

R* int

R* int

R* int

R* int

(continued)

Christopher et al. [27]

Dore et al. [84]

Wu et al. [83]

Hollenstein et al. [82]

Jazayeri et al. [81]

Siu et al. [80]

Hanson et al. [79]

Walker et al. [78]

Liu et al. [77]

Wacker et al. [76]

Wang et al. [75]

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography 11

Smoothened receptor (SMO)

Sf9

Sf9 Sf9

Sf9

Sf9

Sf9 Sf9

BRIL (N)

BRIL (ICl3)

BRIL (N)

BRIL (ICl3)

BRIL (ICl3)

BRIL (ICl3)

BRIL (ICl3)

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Lipid cubic phase

Vismodegib (ANT)

Vismodegib (ANT)

SAG1.5: (3-chloro-4,7-difluoro-N-[trans-4(methylamino) cyclohexyl]-N-[[3-(4-pyridinyl) phenyl] methyl]-1-benzothio phene-2-carboxamide) (ANT)

Anta XV: (2-(6-(4-(4-benzylphthalazin-1-yl) piperazin1-yl)pyridin-3-yl)propan-2-ol) (ANT)

SANT1 ((N-[(1E)-(3,5-dimethyl-1phenyl-1H-pyrazol-4yl) methylidene]-4(phenylmethyl)-1-piperazinamine) (ANT)

Cyclopamine (ANT)

LY2940680: 4-fluoro-N-methyl-N-(1-(4-(1-methyl-1Hpyrazol-5yl)phthalazin-1-yl)piperidin-4-yl)2(trifluoromethyl)benzamide (ANT)

R

R

R*int

R

R

R

R

5L7D (3.2 A)

5L7I (3.3 A)

4QIN (2.6 A)

4QIM (2.6 A)

4N4W (2.8 A)

4O9R (3.2 A)

4JKV (2.45 A)

Byrne et al. [88]

Wang et al. [87]

Weierstall et al. [86]

Wang et al. [75]

IAG Inv agonist, ANT antagonist, AGO agonist, PAG partial agonist, APO no ligand, IAGO irreversible agonist, BAG biased agonist, Nb nanobody, Fab antigen binding fragment of antibody, ICL intracellular loop, PGS Pyrococcus abyssi glycogen synthase, T.S Mutations thermostabilized mutations, T4L T4 lysosyme fusion protein mT4L, dsT4L stabilized versions of T4L, BRIL apo-cytochrome b562RIL fusion protein Sf9, Sf21 Spodoptera frugiperda cell line, High five Trichoplusia ni cell line

Class F Frizzeled

Table 1 (continued)

12 C. Nasrallah and G. Lebon

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography

13

Additionally, the lipidic membrane composition is very different for each cell-type (bacteria, yeast or mammalian) and can impact the function of expressed receptors [89]. Finally, post-translational modifications, mentioned above, that including glycosylations and phosphorylations are essential for obtaining a mature functional receptor in membrane. For instance, it has been reported that N-linked glycosylation has a major impact on receptor folding in the endoplasmic reticulum and its trafficking to the plasma membrane [90] while phosphorylation by G protein Receptor Kinases is mandatory for receptor internalization and desensitization [91]. It is worthy to mention that not all GPCRs expressed in insect cells are properly folded, some receptors show considerable misfolded proportion and incapable of ligand binding as compared to expression in inducible stable mammalian cell lines [92]. Nevertheless, improvements in recombinant baculovirus have been made allowing their use for mammalian cell infection and subsequent protein production (BacMam, Invitrogen) [93]. Although sparsely used for structural study to date, mammalian expression systems start to emerge as an efficient way to produce fully functional GPCRs in sufficient amounts for structural studies [94]. For instance, bovine rhodopsin structure was solved using this approach in two different cell lines, COS7 [95] and HEK293-GnTi [96, 97]. It is worthy to mention that ligands complementation during expression often enhances the final GPCR yield in the membrane, in particular for antagonists or inverse agonists. Binding of the ligand within the transmembrane domain composed of 7 helices (7TM) stabilizes the inactive state of the receptor and acts as a chemical chaperone for improving the quantity of expressed and functional receptor at the cell surface [98]. In contrast agonist addition could adversely affect receptor expression level by triggering signalling cascade or internalization [99] (Fig. 1).

3 Solubilization of GPCRs Prior to Crystallization Before proceeding to purification that is required to set up crystallization trials, GPCRs need first to be extracted from their natural lipid environment using detergents. These amphiphatic molecules are capable of disrupting the membrane at concentrations higher than their defined critical micelle concentration (cmc) and of dispersing its components in the form of detergent-solubilized particles. Despite their solubilizing efficiency, detergents remain poor substitute to the membrane bilayer environment. Although a wide panel of synthetic detergents are available commercially, only few of them have been successful to maintain functional and viable GPCRs enough time to go through purification and/or crystallization trials. For instance, n-Dodecyl β-D-maltoside (DDM), a mild non-ionic detergent with large hydrophilic head and 12-carbon long hydrophobic tail was the detergent of choice to extract a wide variety of well-folded GPCRs. Moreover, different studies show improvement in stability when DDM was supplemented with additional lipids such as cholesteryl hemisuccinate (CHS) [100]. This is not surprising since many solved GPCR structures highlighted specific cholesterol binding sites within helices from transmembrane domain [32]. Lauryl maltose neopentyl glycol (MNG3), another

14

C. Nasrallah and G. Lebon

detergent synthetized based on DDM scaffold with further constraints on detergent conformation (i.e. two hydrophilic and two lipophilic subunits linked by a central quaternary carbon) also showed improved solubility and stability of GPCRs in recent case studies [101]. For instance, the measured thermal stability for ß2-adrenergic receptor was higher when solubilized with MNG3 as compared to DDM [101]. Of interest MNG3 provides stability to solubilized GPCRs even in absence of cholesterol derivatives. It is important to mention that a detergent with good solubilizing proprieties is not necessarily suitable for crystallization. Indeed, this depends on the choice of crystallization methods. In fact, GPCR crystals were obtained mainly from two approaches: the vapour diffusion method (in surfo) and the lipidic cubic phase method (LCP) (Table 1). When considering the conventional in surfo method, the choice of detergent is crucial and working with mild detergents that maintain the receptor native structure and function is important. Unfortunately, mild detergents such as DDM and MNG3 form large micelles that often occlude the hydrophilic part of the receptor making difficult to promote protein–protein interactions in crystal lattice while detergent forming smaller micelles are often denaturating for GPCRs [102]. Therefore when balance between shielding the hydrophobic domain of the target GPCR from the aqueous environment and fostering interactions between the hydrophilic domains fails to be achieved, other engineering strategies aiming at enhancing GPCR stability in detergent-solubilized conditions need to be considered such as increasing receptor thermostability by introducing point mutations (see Sect. 4.4). For example, the thermostabilized Adenosine (A2A), ß1-adrenergic receptor (ß1AR) and neurotensin (NT1) receptors were solved in detergent micelles (Table 1). For LCP crystallization, the detergent-micelles surrounding the receptor are exchanged with a lipidic matrix providing a more native-like environment [103]. Briefly, the bicontinuous cubic phase (i.e. both the aqueous and bilayer compartments are continuous in three dimensions) is formed when lipids such as monoacylglycerol (MAG) and water are mixed at a given ratio. The highly curved bilayer of the cubic phase could then host the target receptor. Under conditions leading to crystallization, the receptor could freely diffuse within the bilayer promoting nucleation and crystallization. Following this approach, large detergent micelles including DDM and MNG3 could be accommodated for receptor solubilization and subsequent purification. Although monoolein (MAG9.9) is the main component of the lipidic matrix for in meso crystallization, other additives including cholesterol derivatives have shown utility to furthermore improve GPCR stability and thereby increasing their probability to crystallize in lipidic environment. To date, the majority of GPCR structures were successfully solved following this approach (Table 1). Interestingly, the structure of the ß2-adrenergic receptor in complex with heterotrimeric Gs protein was crystallized with a short-chain MAG, the 2,3-dihydroxypropyl-(7Z)-tetradec-7-enoate (MAG7.7) supplemented with cholesterol [35]. This suggests that several lipid composition for in meso crystallization should be tested and optimized for each target, especially when considering GPCR signalling complexes.

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography

15

4 Enhancing GPCRs Crystallizablity GPCRs are sophisticated allosteric machineries that signal through multiple pathways once interacting with specific ligands. Indeed, the signalling mechanism relies on the intrinsic dynamic properties of the receptor that oscillates between different fluctuating conformational states [37, 97, 104]. For X-ray crystallography, the protein conformation with lower energy (i.e. more stable) is the most likely to be captured. Therefore, GPCRs are challenging for crystallogenesis and it is difficult to obtain high-resolution structures of the several conformation state of a receptor constituting is activation cycle. Accordingly, it is required to develop surrogates for shifting the energy landscape to the thermodynamically most favourable conformations, i.e. inactive (R) or fully active states (R*) [10]. We will describe the successful approaches that have been used to solve GPCR structures in the past decade. Indeed, the first structure of a diffusible ligand GPCR was solved in 2007 [31]. Nowadays, more than 130 non-rhodopsin GPCR structures are available in the protein data bank (PDB) representing a wide variety of individual receptors that belong to different GPCR classes (Table 1 and Fig. 2).

4.1 4.1.1

Sample Homogeneity Ligands Screening

GPCRs are targets for approximately 30–50% of drugs currently on the market. This in-depth characterization of the binding pocket from X-ray crystallographic GPCR

Fig. 2 A schematic representation of the different GPCR classes highlighting the structural differences. From the left to the right, class A GPCR family harbours an orthosteric-binding site within the transmembrane domain (7TM) where endogenous ligand is recognized. For class B, the ligand (i.e. peptide) binds to both the extracellular (ECD) and 7TM domains. Unlike Class A and B GPCRs, the orthosteric binding for class C receptors is located in the N-terminal extracellular bi-lobed domain (VFT) and not within the 7TM. The large VFT is connected via a cysteine-rich region to the 7TM domain. Class F receptors also possess a cysteine-rich region where endogenous ligand (lipoprotein) binds. Endogenous ligands are highlighted in red

16

C. Nasrallah and G. Lebon

structures available in the protein data bank (PDB) database facilitates the GPCR structure-based drug design [105]. To date, all the solved structures of GPCRs have a ligand bound, either in the orthosteric or allosteric binding sites except for the ligandfree structure of opsin [106] (Table 1; Fig. 2). This is not surprising, since in the free state, GPCRs are thought to adopt different conformations ranging from the R to R* states making them unstable and thus difficult to crystallize. Therefore, ligand binding is a prerequisite for receptor stabilization, which helps reducing conformational flexibility by driving receptors to adopt one major population [19]. Indeed, the ideal ligand should have the highest affinity with an extremely slow dissociation rate, which reflects a tight binding to the receptor, especially when dealing with the fully active agonist-bound conformation [35, 36]. Nevertheless, it is often difficult to obtain the ideal ligand commercially and screening synthetic derivatives need to be considered. In addition, ligands with different branching substituents may form additional interactions in the binding pocket making the ligand-receptor complex more stable thus better for structural studies. For instance, the structure of the A2A receptor co-crystallized with the high affinity agonist UK-432097 reveals a variety of molecular interactions such as salt bridges, hydrogen bonding, and aromatic-ring stacking as well as non-polar interactions [9].

4.1.2

Deglycosylation

GPCRs require post-translational modifications for proper folding and correct trafficking to the plasma membrane. In fact, the sequence prediction for the majority of GPCRs reveals at least one N-linked glycosylation site. Glycan moieties are heterogeneous and flexible in nature, hence hardly compatible with crystallization, and removing them is often detrimental to successful crystallization. This could be achieved either by single point mutations or by enzymatic de-glycosylation. Both approaches do not guarantee the optimal way to deal with the problem, since mutations might affect the receptor expression and/or folding while enzymatic digestion may be incomplete due to enzymatic steric inaccessibility. To circumvent these limitations, N-glycosylation defective cell lines are available, both for HEK293 [107] and CHO [108]. For instance, the HEK293 N-actetylglucosaminetransferase I (GnTI-) cell line lacking the N-actetylglucosaminetransferase I activity produces proteins with controlled length sugar unit (GlcNAc2Mn5) [107]. This alternative expression system ensures a well-folded and homogenous receptor preparation suitable for crystallization [96, 97].

4.1.3

N and C Termini Domains

GPCRs exhibit remarkably conserved protein architecture with seven transmembrane helices despite their large structural and pharmacological diversity [109]. Indeed, receptors from class B and C have a long N-terminal extracellular domain, which shares (class B) or contains (class C), the orthosteric binding site (Fig. 2). The length

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography

17

of the intracellular C-terminal tail is also variable ranging from few amino acids to long variants among receptors belonging to the same class [110]. To date, only few GPCRs were crystallized with both N- and C-termini domains intact; the human dopamine D3 [51], the M2 muscarinic acetylcholine [57], GPR40 [53] and P2Y12 [74] receptors (Table 1). While these domains play an important role in the activation process, they remain highly flexible and may hinder crystallization. Therefore, removing such domains by serial truncations while preserving the coupling to G proteins and ligand-binding activity of the receptor is often considered. Despite that significant portions of unstructured extracellular and/or intracellular tails were deleted in the majority of crystallized GPCRs, additional approaches were also required in order to achieve diffracting quality crystals including the use of binding partners, fusion proteins and stabilizing point mutations as described below.

4.2

Binding Partners Stabilizing Receptor Conformation

Binding partners with high affinity for GPCRs such as antibody fragments (Fab) or nanobodies are powerful tools that have shown their efficiency to lock the receptor in a single conformational state [13, 111]. As a consequence, receptor dynamics is significantly reduced. Fabs have even been successfully used to reduce the flexibility of large extracellular domain of class B Glucagon receptor and constrain loop conformation [112]. Thus, they facilitate well-ordered crystal formation by acting as crystallogenesis chaperones. Nanobodies present different advantages regarding conventional monoclonal antibodies [113]. Camelids naturally express a subtype of antibodies that are devoid of light chains and called heavy chain antibodies (HcAbs). HcAbs harbour a single variable domain (called VHH) recognizing the epitope on the target protein. These small domains (13 kDa), also called single domain antibodies (sdAbs) or nanobodies, are easily produced in bacteria or yeast. Moreover, they have an extensive antigen-binding repertoire, superior stability as compared to conventional antibodies and epitope recognition even in small cavities of proteins making them logical candidates for stabilizing specific GPCR conformations [114]. The structures of both A2A Adenosine and ß2 Adrenergic receptors were solved in the inactive state bound to Fab fragments [8] while the structure of ß2 Adrenergic receptor was solved in the active state bound to a trimeric G-protein and nanobodies [35]. It is worthy to mention that nanobodies have shown major utility to stabilize fully active conformation of M2 muscarinic acetylcholine and ß2 Adrenergic receptor, by mimicking the G protein [36, 58]. Indeed the nanobody-stabilized active conformation is identical to the ß2 Adrenergic receptor conformation solved in complex with heterotrimeric G protein Gαsß1γ2 (Table 1). In addition, to favour the production of nanobodies for a given state of the GPCR, the immunization of a camelid (mostly camels or llamas) should be done with purified target receptor stabilized in that given state. Thus, optimal condition for nanobody generation will require stabilizing the selected receptor conformation using, for example, a high affinity ligands, ideally with a very slow Koff, to prevent dissociation from the

18

C. Nasrallah and G. Lebon

receptor following immunization process and to guarantee optimal receptor conformation stability in its reconstituted form (e.g. liposome) [114]. For instance, the agonist BI-167107 used to solve the structure of ß2 Adrenergic receptor in active state, has an affinity of 84 pM and an extremely slow off-rate of 30 h [35] and the receptor detergent was exchanged to MNG3 prior to nanobodies screening.

4.3

Increasing Receptor Hydrophilic Area

Highly crystallizable soluble proteins replacing disordered segments within GPCRs have been widely used to obtain well-ordered diffracting crystals (Table 1). Indeed, among potential fusion partners, T4 lysozyme (T4L) was mostly used to replace the long unstructured intracellular loop 3 (ICL3) of mainly class A GPCRs without affecting its relative orientation to the membrane (Table 1). The T4L consists of two alpha helices perpendicular to each other and forms crystals under a wide range of conditions. Recently, two versions of T4L were engineered in order to improve the diffraction quality of GPCR crystals [59]. This was achieved either by introducing disulphide-stabilized point mutations (dsT4L) or by replacing the flexible N-terminal domain of T4L by a small linker (mT4L), as highlighted for the structure of muscarinic M3 receptor [59]. Interestingly, the 7TM domain of both class B corticotropin-releasing factor 1 (CRF1) [82] and class C metabotropic glutamate (mGlu5) [84] receptors was solved with T4L lysozyme fused to their second intracellular loop. Moreover, the T4L was also successfully used to replace the truncated N terminus domain as highlighted for ß2-adrenoreceptor [38]. In addition, this construct helped to solve the structure of the active conformation of the ß2-Adrenergic receptor in complex with intracellular binding partners such as Gs protein [36]. Other fusion proteins were also explored, such as the thermostabilized apocytochrome b562 (BRIL) replacing either the ICL3 (e.g. the structure of the A2A; 5-HT1B; 5HT2B; P2Y12 and SMO receptors) or the truncated version of N-terminus domain (e.g. the structure of the NOP; glucagon; SMO; mGlu1 and δ-Opioid receptors) [115] (Table 1). BRIL consists of two adjacent alpha helices anti-parallel to each other. It is worthy to mention that other potential fusion partners appeared as valid alternatives in few GPCR cases such as rubredoxin (Rd) for the CCR5 receptor [46] and the acid catalytic domain of Pyrococcus abysii glycogen synthase (PGS) for the OX2 receptor [66]. Another advantage for this approach for conventional vapour diffusion crystallogenesis method is that fusion proteins could serve as crystallogenesis chaperones by increasing the hydrophilic area of the target GPCR such that large detergents could still be accommodated. However, GPCRs are often unstable in detergent-solubilized conditions and it is required to couple other stabilization approaches, precisely if vapour diffusion technique is considered, such as increasing the thermostability of the receptor by single point mutations as described below. Otherwise, crystallization from the membrane-mimetic environment (LCP), where most GPCR structures to date

Structures of Non-rhodopsin GPCRs Elucidated Through X-Ray Crystallography

19

were obtained, has proven to be a powerful alternative to in surfo crystallization (Table 1).

4.4

Increasing Receptor Thermal Stability

Another successful approach to stabilize GPCRs for structural studies consists of introducing single point mutations (e.g. alanine mutations at first, or leucine if the residue is already an alanine), within the 7TM in order to increase the receptor stability in detergent-solubilized conditions [116]. This approach named conformational thermostabilization relies on the availability of a radioligand with high affinity for the target in order to measure the receptor binding from unpurified detergent-solubilized conditions. Such assay allows screening mutant libraries for identifying thermostabilizing mutations. Once identified, thermostable mutants can be combined in order to generate an optimally stable receptor which enhances the probability of obtaining high-quality diffracting crystals in both LCP and vapour diffusion methods. Structures of the inactive-like state GPCRs (e.g. B1-AR; A2AR; CCR5; FFA1R; CCR5, CCR9, Glucagon and mGlu5) as well as of the active-like state (e.g. A2AR and NTSR1) were solved following this approach (see Table 1 for more details). Interestingly structures solved either by the thermostabilizing approach or by using fusion protein partner were identical with some differences mainly the orientation of the loops which impact crystal packing [117]. The radioligands used to measure binding and to screen the mutants bind in the transmembrane domain. Interestingly, depending on the nature of the radioligand used, agonist or antagonist, the thermostabilization appears to alter the equilibrium between the inactive and active-like states such that the receptors will adopt preferentially either the inactive state upon antagonist binding or the active states upon agonist binding [11, 22]. Coupled to structure resolution, this strategy may uncover molecular transitions between inactive and active-like states. For instance, the conformational thermostabilization of A2A receptor using [3H]-ZM241385 antagonist led to a themostabilized A2A Star® receptor with reduced affinity for the agonist and no coupling to G-proteins while similar affinities for the antagonist were observed for both thermostablized and wild-type A2A receptors [11]. In contrast, when A2A receptor was stabilized bound to [3H]-NECA agonist, the affinity of the receptor for antagonist was considerably weaker while similar affinity for the agonist was observed for both thermostablized and wild-type A2A receptors [11]. High-resolution structure of A2A receptor ligand bound conformation reveals common features but also specificity for agonist and antagonist binding. Interestingly, the full-active conformation of the human A2A receptor was recently reported in complex with an engineered minimal G protein (mini-Gs) [118]. This structure is in perfect agreement with previous features revealed from thermostabilized A2A agonist bound conformation [17]. In addition, following this approach a large array of ligands could be co-crystallized for the same receptor making it a desirable strategy for drug development. For instance, the

20

C. Nasrallah and G. Lebon

thermostabilized ß1-AR receptor was solved bound to a wide variety of ligands including antagonists, inverse agonists, partial agonists and full agonists, giving a detailed insight into the ligand-binding pockets and opening new possibilities for hit-to-lead drug optimization [22–25, 27]. When required in difficult cases, this approach could be combined to other stabilization approaches such as protein fusion as highlighted in the structures of chemokine 4, dopamine D3, free fatty acid, neurotensin, serotonin, corticotropin-releasing factor, metabotropic glutamate 5 receptors, and most recently the GLP1 structure (Table 1; Fig. 1).

5 GPCR Sub-Micrometer and Micrometer-Size Crystals The main difficulty to solve GPCR structures is to obtain well-diffracting crystals of a descent size, in order to collect data from standard source of photon at the commonly accessible large synchrotron facilities. GPCRs often produce only sub-micrometer to micrometer-size crystals making data collection another tricky task to handle with care. In order to collect high-resolution data from GPCR microcrystals, microfocus X-ray beams with high intensity and sufficient exposure time are required. However, such radiation with very high-energy dose induces radiation damage and thus merging data from multiple micro-crystals is often required to obtain a complete data set, but still perfectly achievable for descent-size crystals. With recent technical progress and large effort by several groups, serial femtosecond crystallography (SFX) taking benefit from the free electron laser (FEL) source has been developed and demonstrated great promise for obtaining highresolution data from nano to sub-micrometer-size GPCR crystals [119]. FEL is a high-energy source (~2 mJ, 1012 photons per pulse) enabling the recording of data from individual crystals with a specific orientation and minimal radiation damage (ultrashort pulses 83-fold subtype selectivity.

2.7

Muscarinic Receptors

The muscarinic receptor family has five members (M1–M5) that recognize the neurotransmitter acetylcholine. Muscarinic receptors (MRs) have been extensively targeted by the pharmaceutical industry for the treatment of disorders such as type 2 diabetes, PD, and chronic obstructory pulmonary disease [112]. However, the therapeutic applicability of drugs acting via interactions with these receptors has been limited by lack of selectivity and the associated risks of causing adverse drug reactions. The release of the structures of the M2MR and M3MR bound to antagonists (PDB codes 3UON and 4DAJ, respectively) [113, 114] revealed strong similarities between the binding sites of these subtypes. Kruse et al. [85] used DOCK3.6 [51, 93] to carry out screens of 3.1 million commercially available chemicals against the M2MR crystal structure. From the top-ranked 500 compounds, 18 were tested in radioligand assays. Eleven novel M2MR ligands achieved Ki values better than 40 μM, corresponding to a hit-rate of 61%. Six ligands were fragment-sized molecules, which is in line with the fact that the orthosteric site of

82

A. Ranganathan et al.

the muscarinic receptors has evolved to recognize the small endogenous agonist acetylcholine. Encouraged by the successful discovery of novel M2MR chemotypes, the authors attempted to use crystal structures to bias the screens towards the discovery of ligands selective for the M3MR over the M2 subtype. This selectivity profile could be advantageous in the clinic, as activation of the M2MR can lead to undesired cardiac effects [115]. To investigate this, the same chemical library was docked to both M2MR and M3MR structures. From the 5,000 top-ranked compounds from the screen against the M3MR structure, 500 molecules with the largest rank differences between screens were visually inspected. Apart from good complementary to the M3MR binding site, typically involving a salt bridge to the conserved residue Asp1473.32, compounds were required to exploit interactions with Leu2255.33. This was the only residue difference in the orthosteric sites between the M3 and M2 receptors (the bulkier residue Phe1885.33 was found in the equivalent position of the antitarget). Of the 16 predicted ligands, eight were found to bind to the M3 receptor, corresponding to a hit-rate of 50%. One ligand was able to achieve >fivefold M3/M2 selectivity ratio, which highlights the difficulties in developing subtype-selective ligands for receptor families with strongly conserved orthosteric sites.

2.8

Serotonin Receptors

Serotonin (5-hydroxytryptamine, 5-HT) is a key neurotransmitter acting in functions concerning the gastrointestinal, cardiovascular, and central nervous (CNS) systems [116]. The function of several membrane proteins involves the recognition of this molecule, of which 13 are GPCRs [117]. Interactions with serotonin receptor subtypes are responsible for the mechanism of action of several widely used drugs such as atypical antipsychotics, antiobesity, and migraine medications. A drug class belonging to the latter category is the triptans, which are selective ligands for the 5-HT1B and 5-HT1D receptors [118]. Selectivity is a highly desired feature of serotonergic drugs given the potential adverse effects produced by cross-reactivity among the 5-HT receptor family. One example is the drug combination fen-phen, which was retracted from the market after causing cardiac disorders trigged by interactions with the 5-HT2B receptor [116]. Crystal structures of the 5-HT1B and 5-HT2B receptors bound to the agonist ergotamine were released in 2013 (PDB codes 4IAR and 4IB4, respectively) [119, 120]. These structures revealed atomiclevel details of the structural determinants for ligand recognition and receptor selectivity. As for other aminergic receptor structures, the co-crystallized ligand established a salt bridge with the conserved Asp3.32 residue. Docking of triptans to the two structures suggested that the impaired binding of triptans to the 5-HT2B receptor is due to sterical hindrance caused by an inward kink of TM5 and a bulkier side chain of residue Met2185.39 (Thr2095.39 in 5-HT1B) [120]. Based on these structural differences in the binding sites, Rodrı´guez et al. examined the possibility

Structure-Based Discovery of GPCR Ligands

83

of using the crystal structures to discover 5-HT1B selective ligands [86]. Docking screens of 1.3 million commercially available molecules were carried out with DOCK3.6 against these two structures. Compounds were required to achieve significantly better docking ranks for the target compared to the antitarget. From the top-ranked 4,000 molecules in the screen against the 5-HT1B receptor, the 500 compounds with the worst ranks for the 5-HT2B subtype were visually inspected. The 22 compounds that were selected for experimental evaluation formed a salt bridge to Asp1353.32, as well as hydrogen bonds to non-conserved 5-HT1B residues (e.g., Ser3346.55 and Thr2095.39) in the region where the binding site of 5-HT2B was relatively contracted. Eleven of the selected molecules achieved Ki values 40-fold selectivity over α1a/α1d (Figs. 12 and 13). The α1a Adr pharmacophore model was developed taking 27 compounds including active (Ki value less than 1 nM) eight and two compounds from class I and class II, respectively. Since the majority including two most active compounds of the training set belong to class I, the generated model favored class I pharmacophore. This α1a Adr pharmacophore model had four featured pharmacophores in which the isopropyl fragment, the phenyl ring of the phthalimide moiety, the keto group, and the piperazine nitrogen mapped the HAl, HAr, HBA, and PI features, respectively, for a substituted compound having 82 as core structure with R¼H, X¼4-CH3 (α1a Ki ¼ 0.16 nM: α1a/α1b ¼ >12,500: α1a/α1d ¼ 231) (Figs. 14a and b). Among the active ten compounds, all the eight class I antagonists mapped the PI feature while the two class II compounds failed to map the PI feature. Among the eight class I active compounds, the top three mapped all the features of the pharmacophore while the rest five failed to map the HBA feature. The α1b Adr pharmacophore was developed by using prazosin analogs. Interestingly after protonation of the quinazoline nitrogen atom N1, the pharmacophore model generated for α1b Adr subtype does not contain any PI feature that is considered to be an important feature for binding at the biogenic amine receptor site. A four-featured pharmacophore model consisting of two HBA, one HAl, and one HAr feature was observed in case of the α1b. The mapping of cyclazosin (18) (α1b Ki ¼ 0.13 nM: α1b/α1a ¼ 92: α1b/α1c ¼ 25) with the α1b pharmacophore is shown in Fig. 14c, d. The α1d Adr pharmacophore model was developed with compounds

Integration on Ligand and Structure Based Approaches in GPCRs

123

Fig. 11 The amino acid sequence alignment of the α1 adrenergic receptor (α1 Adr) subtypes with important binding residues highlighted in black rectangles

having >100-fold selectivity over α1a and >40-fold selectivity over α1b. Two compounds used for generation of the pharmacophore model belonged to class II ligands while the rest of the compounds having a single phenyl group cannot be classified to any class mentioned by Klabunde et al. Most of the compounds in the training set were structurally related to BMY-7378 that is having good selectivity for the α1d Adr subtype. The α1d Adr pharmacophore contained five features viz., HAr, two HAl, HBA, and PI features that mapped the phenyl ring, chloro group, pentane

124

A.K. Saxena et al.

Fig. 12 Structure of representative class of α1a Adr antagonists considered for selectivity study by MacDougall et al.

Fig. 13 Structure of representative class of α1b Adr (86–95) and α1d Adr (96–99) antagonists considered for selectivity study by MacDougall et al.

ring, keto group, and the basic nitrogen groups, respectively, for compound having the basic structure as compound 66 with R¼2,5-Cl2 (α1d Ki ¼ 0.11 nM: α1d/α1a ¼ 386: α1d/α1b ¼ 72) (Fig. 14e and f). Besides the pharmacophore models, subtype selectivity in the α1 receptor subtypes was also guided by the size of the antagonists as the average molecular weight of the compounds used as training set is highest for α1a Adr

Integration on Ligand and Structure Based Approaches in GPCRs

125

Fig. 14 (a) The pharmacophore model and (b) 2D representation of the selective α1a Adr antagonist. (c) The pharmacophore model and (d) representation of the selective α1b Adr antagonist. (e) The pharmacophore model and (f) representation of the selective α1d Adr antagonist. (g) Docked conformation of prazosin at the (g) α1a Adr and (h) α1b Adr. Mapping of Prazosin with the (i) α1a Adr pharmacophore model and (j) α1b Adr pharmacophore model (reproduced with permission from J. Mol. Graph. Model., 2006, 25, 146–157 Copyright 2005 Elsevier Inc.)

126

A.K. Saxena et al.

(MW ¼ 485), lowest for α1d Adr (MW ¼ 443) while for α1b Adr (MW ¼ 400) it is between α1a and α1d Adr antagonists. The molecular weight variability in these antagonists suggests that the binding site of α1a Adr is large in size compared to α1b and α1d Adr subtypes. This pharmacophore model contained two additional hydrophobic features: one mapping the five-membered spiro ring and the other adjacent to the aromatic ring compared to the previous pharmacophore model on α1d Adr. The best part of the modeling experiment was the regression of each pharmacophore models by the training set of the other two subtypes that resulted in a bad correlation signifying the models to be selective ones. The generated pharmacophore model for α1a Adr has more similarity with the class I pharmacophore model reported earlier. Interestingly prazosin (9) was not able to map the pharmacophore model of α1a ADR by unsatisfying the HBA feature of the pharmacophore (Fig. 14i). This was also observed for prazosin in the model reported by Bremner et al. that was also a class I pharmacophore model. This suggests that the class I pharmacophore model may be useful for identification of selective α1a Adr antagonists. The α1b Adr pharmacophore developed here differed from the conventional α1 Adr models by not having the PI feature that interacts with Asp106 in TMIII. Interestingly prazosin mapped all the features of the α1b Adr pharmacophore (Fig. 14j) signifying a different binding site compared to the site of the conventional α1 Adr antagonists. This was further confirmed by the docking studies of prazosin performed at the α1 Adr subtypes. Prazosin was found to have no H-bond contact with the aspartate residue of TMIII in both α1a and α1b Adr and failed to even fit in the α1d binding site. For α1a Adr, the shortest distance between the charged Asp and positively charged nitrogen was found to be 3.94 Å (Fig. 14g) while for α1b Adr the distance of ASP-PI feature was found to be 8.00 Å that supported the pharmacophore model of the α1b Adr subtype (Fig. 14h). The interaction of prazosin with Asp 106 is controversial as mutation of D106A on α1b Adr was reported to have no effect on the binding of prazosin in one study while two other studies confirmed the importance of Asp106 in the binding of prazosin. However in a recent study, the homologous and heterologous binding experiments have demonstrated that the Asp106Ala had no effect on prazosin affinity. The inability of prazosin to form salt bridge with Asp106 at the α1a binding site has also been reported on a homology modeled α1a Adr receptor developed on β2 Adr template [160]. In this model, the di-methoxy groups attached to the quinazoline moiety of prazosin lie near S188 and S192 residue of the TMV that is similar in interaction like the β2 inverse agonists (carazolol, timolol, and ICI118551) while the furan ring made hydrophobic interaction with F312 in TM7. The inevitable importance of the α1a/d antagonists in BHP/LUTS has regenerated research interest with the aim of designing subtype selective antagonists and this has been evidenced by recent reports in this area [161] and several pharmacophore studies have been published [162–165]. However designing α1 selective antagonists based on receptor models is challenging due to high homology among the receptor subtypes. Hence integration of ligand based information may be helpful in validation of structure based models.

Integration on Ligand and Structure Based Approaches in GPCRs

4.2

127

Dopamine D2 Receptor Agonists

The dysregulation in the dopamine signaling pathway due to loss of dopaminergic neurons in the basal ganglia results in the pathogenesis of Parkinson’s disease (PD). Treatments of PD include L-dopa which is a precursor of dopamine and other orally administered D2 agonists such as pergolide, bromocriptine, ropinirole, and pramipexole [166–168]. However the D2 agonists used in PD have psychotic side effects due to D2 receptor activation. The earlier molecular modeling studies on dopamine receptors have been highly prioritized on the nature and alignment of the N-alkyl substituents at the dopamine receptor site to deduce the dopamine receptor topography. Most of these models were developed preferring the constrained structural analogs rather than the flexible analogs for easy determination of the N-alkyl substituents to characterize the topography of the D2 receptor. The first D2 agonist model was reported by McDermed et al. [169, 170] taking into account the constrained dopamine analogs such as S-5-OH-DPAT (100), apomorphine (APO) (101), and (6-amino-5,6,7,8-tetrahydronaphthalene-2,3-diol) ADTN (102) (Fig. 15). The study reported the active enantiomer of ADTN (102) to be opposite in conformation compared to S-5-OH-DPAT (100) and apomorphine (101). The model also postulated the location of the hydroxyl groups in one of the two possible meta positions that determine the orientation of the amino group binding in the D2 receptor and in order to fit at the receptor site, ADTN (102) must be rotated like APO to fit at the D2 receptor site (Fig. 17a). The D2 agonistic properties are mainly due to the phenylethylamine moiety. It also explains why iso-APO (iso-apomorphine) (103) is inactive at the receptor site (Fig. 17a). It is also stipulated from the model that the distance between the oxygen atom (meta hydroxyl group) and the basic nitrogen atom is 7.3 Å while the nitrogen atom is nearly orthogonal to the plane of the phenyl ring. Later, this distance of 7.3 Å has been found to be crucial for D2 agonism through a molecular modeling study on 2-(aminomethyl)chromans (2-AMCs) reported by Mewshaw et al. [171] where an increase in distance between N–O to 7.8 Å has been postulated to be responsible for decrease in D2 agonism affinity by 24-folds between two analogs 104 (D2 High: Ki ¼ 0.9  0.2, D2Low: Ki ¼ 15.9  6.7) and 105 (Fig. 15). It was also addressed by Seeman et al. [172] that potent D2 agonists have the hydroxyl group to nitrogen atom distance of 7.3 Å or less. However the pharmacophore model of Mewshaw et al. had the basic nitrogen atom situated 0.92 Å below the plane of the phenyl ring and has a difference from the earlier models where the nitrogen atom is coplanar to the plane of the phenyl ring and this may be due to the rigid structures considered during generation of earlier models. The dopamine D2 models were built on the basis of the interesting finding that stereochemical aspects in the 2aminotetralines determine the D2 receptor agonist activity. For example, the Senantiomer of 5-OH-DPAT (100) having 2-aminotetralin substructure was found to be active as D2 agonist and compared to apomorphine it was ten times more potent in eliciting stereotypy in the rat and emesis in the dog while the R-enantiomer of 5-OH-DPAT was inactive as D2 agonist [173]. Further pharmacological evaluation

128

A.K. Saxena et al.

Fig. 15 Structure of different chemical class of D2 agonists

of compounds 5,6-dihydroxy-2-(di-n-propylamino)tetralin (106), 6,7-dihydroxy-2aminotetralin (117), and 7-hydroxy-2-(di-n-propylamino)-tetralin (108) as D2 agonists revealed the S-enatiomers to be active in the compounds 100 and 106 while an opposite trend was observed for compounds 107 and 108 where the R-enantiomer was active as D2 agonist (Fig. 15) [174, 175]. Deriving the D2 receptor topography from ligand based information got further complicated when 3-(3-hydroxyphenyl)-N-npropylpiperidine (3-PPP) (109) was found to be a selective presynaptic (autoreceptors) D2 agonist [176, 177]. For compound 109, the (+)R enantiomer behaved as agonist at both presynaptic (low doses) and postsynaptic (high doses) DA (dopamine) receptors while the ()S enantiomer acted as agonist in the presynaptic (low doses) and as antagonist (high doses) at the postsynaptic DA receptors. This opposite behavior of the (+)R enantiomer and ()S enantiomer of 3-PPP (109) at the postsynaptic

Integration on Ligand and Structure Based Approaches in GPCRs

129

DA receptor resulted the racemic compound to be devoid of activity making 3-PPP (109) presynaptic DA selective compound. Encouraged by the behavior of 3-PPP (109) it appeared that the stereochemistry around the piperidine ring plays an important role in deciding the D2 agonist behavior. This was further supported by apomorphine where the (+)6aS enantiomer antagonizes the agonist behavior of the (+)6aR enantiomer [178]. Based on this information, further studies were carried out to establish a relationship between the stereochemistry of the piperidine ring and D2 agonist activity. In a series of monophenolic octahydrobenzo[f]quinolines, the trans isomer (111) was more active as D2 agonist than the cis isomer (110) [179]. In compound 111, the trans (4aS, 10bS) was found to be most active enantiomer whereas among the cis enatiomers, 110 (4aR, 10bS) showed weak D2 agonist activity supporting that the central DA receptors (pre- and postsynaptic) are activated by planar molecules [180]. In cis isomers, the piperidine ring of compound 110 (4aR, 10bS) protrudes downward the aromatic plane whereas in the trans isomer 111 (4aS, 10bS) the piperidine ring remains in the plane of the aromatic ring. This was further supported by the totally inactive isomer of 110 (4aR, 10bS). This proves that S-configuration at carbon 4a is necessary for activity and is further supported by the compounds 100, 103, and 105 all of which have S-configuration at this center with the stereochemistry of the carbon atom attached to the nitrogen atom. These findings strongly rationalize that the trans conformation with S-configuration at carbon 4a is required for D2 agonism. However interestingly for compound 112 the cis isomer was found to be as active as 109 with the 4aR (4aR, 10bR) enantiomer more active than the 4aS enantiomer thus differing with the previous hypothesis where the stereochemistry was to be of S-configuration at the 4a carbon atom attached to the nitrogen atom. Interestingly in the analogue series of compound 109, the nature of N-alkyl substituent largely determines the D2 agonistic activity rather than the configuration at the 4a carbon that suggests lipophilicity and/or steric factors to have effect on the intrinsic activity of these compounds [181]. With further investigation on a series of compounds, it was deduced that the nature of the substituent attached to the basic nitrogen is important for activity. Especially it was observed that certain compounds such as 113 and N-n-Bu-Apomorphine (115) where the N-alkyl substituents point downward a maximum substitution up to n-propyl (114) are favorable towards activity whereas compounds having n-butyl substitution are devoid of activity [179]. This has been the cause of inactivity for ergoline derivatives that have n-butyl substitutions. An alignment of the active conformations of 100, 106, 111, 112, 116, 117, and apomorphine (101) on the basis of interaction of the OH group at the receptor site resulted in two important conclusions that may complement the DA-receptor structure volume: (1) Aromatic functionality with m-OH group or instead a pyrrole or pyrazole ring imitating the m-hydroxyaryl group. (2) The distance criteria between the aromatic function and the basic nitrogen should be like the extended phenylethylamine structure. (3) The N-substituents may position them in two main directions viz., upward or downward direction, where the downward direction is sterically restricted and can accommodate maximum a piperidine ring or an n-propyl group, whereas the upward direction has less sterical requirements. (4) The stereochemistry of the carbon attached to the basic nitrogen atom is also important as it provides direction to the

130

A.K. Saxena et al.

carbon–nitrogen bond. For example, in compounds 100, 106, 111, 112, 116, 117 (Fig. 17b), and apomorphine, the active enantiomers have the carbon–nitrogen directed downwards, towards the plane of the paper. The model however failed to identify the structural requirement for D2 agonist activity of the unnatural ergoline derivatives relative to the natural ergoline. The chirality of the carbon atom next to the basic nitrogen atom in natural ergolines has 5R configuration while the 5S configuration is the inactive one. In order to map the natural ergolines, some of the unnatural ergolines (S-configuration) have to turn 180 down as shown for compound 118 at the D2 receptor site. The S-configuration of compound 119 has the piperidine ring fitting exactly in the well-defined cleft and substitution at position-8 will provide steric hindrance rendering compound 119 as inactive. So an unsubstituted 119 is expected to be active as D2 agonist. Hence no substitution at position-8 is preferable for compounds having S-configuration and having the pyrrolethylamine moiety responsible for D2 agonist activity. The partial agonist 120 fulfills these criteria of the ergoline pharmacophore like 119 when the pyrrole portion interacts at the receptor site, alternatively it was also postulated that 120 may get hydroxylated to 121 during metabolism and the active pharmacophore may be the phenyl ethylamine moiety. In further investigations, the compound 122 having both the R (pyrrolylethylamine moiety) and S (phenyl ethylamine) isomers were active as D2 agonist. Hence the structural requirements (pyrrolylethylamine or phenyl ethylamine) for D2 agonism in the ergolines and their mode of interaction at the receptor site remained unclear [180, 182, 183]. The nature of the substituents at the basic nitrogen and their orientation at the D2 receptor have been studied more elaborately with (S)-3-(3-hydroxyphenyl)-N-npropylpiperidine ((S)-3PPP) that can act both as agonist and antagonist in different rotamaric forms [184]. As mentioned previously, the (+)R enantiomer of 3-PPP (109) behaved as agonist at both presynaptic (low doses) and postsynaptic (high doses) DA (dopamine) receptors while the ()S enantiomer acted as agonist in the presynaptic (low doses) and as antagonist (high doses) at the postsynaptic DA receptors. The differences in response for 3-PPP have been attributed due to different interactions of the N-alkyl substituent at these receptor sites (presynaptic and postsynaptic). However as our main discussion is focused on D2 agonist pharmacophore so the agonist interactions of 3-PPP at the D2 receptor model will be described here. The study describes the existence of a propyl cleft in the downward direction and a sterically “unrestricted upward” direction at the D2 receptor site that accommodate the propyl chains attached to the basic nitrogen moiety (Fig. 17d). The alignments of compounds 125 and 126 both of which are active further depicted the upward and downward orientation of the propyl group (Fig. 17c). This unrestricted upward portion of the receptor can accommodate larger N-substituents such as phenethyl groups or the nonphenolic phenyl group in apomorphine (101). The receptor interaction points of the D2 agonists and the relative orientation of the propyl cleft at the receptor site have also been proposed keeping in view the McDermed receptor concept as shown in Fig. 17d. The D2 agonist pharmacophore was further extended to elaborate the D2 receptor topography near the basic nitrogen atom. The orientation of the propyl cleft was proposed to be situated above the plane of the ligand at the receptor

Integration on Ligand and Structure Based Approaches in GPCRs

131

site (Fig. 17e). The conclusion was made based on two compounds 123 and 124 having a cyclic structure embedded with the positively charged nitrogen. Although both these compounds are similar in structures to 109, they were inactive in vivo. The inactivity of compound 123 can be easily accounted due to its large ring size that is not able to fit properly in the well-defined propyl cleft but the inactivity of compound 123 is not expected as it has a small ring size that may easily fit the propyl cleft at the receptor site. The inactivity of compound 123 indicated that the basic nitrogen atom does not tolerate any steric bulk just in front of it and as a result an anti-conformation of the propyl group is more preferred as in the gauche conformation the propyl group will be oriented just in front of the nitrogen atom (Fig. 17f and g). Hence the propyl cleft was stated to lie orthogonal to the plane of the aromatic moiety [184]. A more detailed description about the D2 agonist pharmacophore model was reported by Chidester where molecular modeling studies have been carried out on a set of 11 tricyclic molecules (127–137) (Fig. 16) having X-ray crystal structures [185]. The D2 pharmacophore model generated had two H-bond requirements: (1) the one being involving the basic nitrogen atom and (2) the second being H-bond groups (OH, NH) as donors in the aromatic ring (secondary hydrogen bonding). The donor character of the substituents was determined on the basis of preference of the hydroxy group over O-methyl substituents on the aromatic ring. The model also describes the existence of an aromatic group with donor substituents and the propyl cleft. An area located south of the amine was proposed to confer antagonist or partial agonist character at the D2 receptor (Fig. 17h). However the 11 X-ray crystal structures used to develop the D2 pharmacophore model were having the propyl and allyl groups in gauche conformation rather than anti-conformation as proposed by Liljefors et al. Our study on the alignment of the active apomorphine analogue ()6a-R-apomorphine (101) and the active D2 antagonist ()12aS-centbutindole (138) showed similar stereochemical superposition at the adjacent carbon next to the basic nitrogen [186] (Fig. 18a ) that was further utilized to synthesize derivatives where the catechol portion of the apomorphine was replaced by the indole moiety to remove the emetic side effect of apomorphine. Two of the synthesized analogs 139 and 140 showed marked dopaminergic activity [187–191]. Thus the proper location of the propyl cleft remained elusive. A detailed study about these earlier classical D2 models has been studied and compared through receptor models with subsequent development of pharmacophore model [192]. It should be noted that most of the earlier models were developed by superimposition of the NH containing scaffold of ergolines with the hydroxy group attached to the aromatic ring but while doing so the large N-substituents will be guided towards the confined n-propyl cleft that is unwanted as groups larger than propyl are not accepted in this cleft. The unexplained binding of ergoline containing scaffolds as well as certain compounds with large n-alkyl groups has been studied by docking these molecules in a homology modeled D2 receptor developed on the co-crystallized structure of 5HT1b with ergotamine as template (sequence identity 57%). The selection of the template was made as the ergotamine scaffold co-crystallized with 5HT1b structure has a large C8 substituent. The compounds 125 ((4aS, 10bS) trans-7OH-OHBQ) and 126 ((4aR, 10bR) trans-9-OH-OHBQ) were docked at the D2 receptor to find the binding orientation of these two compounds at the D2 receptor

132

A.K. Saxena et al.

Fig. 16 The chemical structures of D2 agonists

(Fig. 18b). The protonated nitrogen atom in compounds 125 and 126 formed a salt bridge with the Asp1143.32 and the hydroxy group in both the compounds formed H-bond contact with Ser1935.42. The aromatic scaffold in these compounds formed edge to face aromatic interactions with Phe1906.52 and cation–pi interactions with the protonated His3936.55. The docked conformations of compounds 125 and 126 are in agreement with conformations reported earlier viz., the propyl groups as nitrogen substituents are placed in upward (compound 125) and downward (compound 126) direction. The propyl cleft stated earlier was formed by the side chains of Cys1183.36, Trp386 6.48, Phe3896.51, Thr 4127.39, and Tyr4167.43 and the propyl group in compound 126 is resided in this cleft. The compounds 142 and 144 having the same configuration but having large alkyl substituents however failed to fit in this cavity and hence were inactive. For compound 125, the n-propyl substituent was directed upwards in the large spacious cavity heading towards the extracellular surface of the receptor demarcated by extracellular loop 2 (ECL2) that explains that compound 125 can have substituents larger than propyl groups at this position and this has been confirmed by the D2 agonistic activity of compounds 141, 143, and bifeprunox (148) (Fig. 18c). The docked conformation of ergotamine (146) and bromocriptine (145) also had the large N-substituents located in this spacious cavity. However the earlier presumption that the NH group in ergotamine and the OH group of the tetralin have the same binding site at receptor is not true and it has been observed that the NH

Integration on Ligand and Structure Based Approaches in GPCRs

133

Fig. 17 (a) The D2 receptor topography as proposed by McDermed et al. (b) The upward and downward conformation of the N-alkyl substituents of D2 agonist molecules. (c) Superimposition of 125 and 126 with the hydroxy groups in both the molecules being considered to interact at the same receptor site. (d) The existence of propyl cleft at the D2 receptor that can accommodate alkyl groups up to the length of propyl chain. (e) The proposed anti-conformation of the propyl group indicating N-substituents is not tolerated just in front of the N-atom. (f and g) In the gauche conformation, the N-substituent will lie in the plane of the N-atom while in anti-conformation it will lie above the plane. (f) The D2 receptor model proposed by Chidester et al.

group of ergotamine interacts with Ser1975.46 while the OH group of tetralin interacts with Ser1935.42. It was also interesting that the ergot derivatives have dual binding mode at the D2 receptor site where some of them may form H-bond with Ser1935.42 and Ser1975.46 and this dual binding behavior was observed for the docked conformation of 147R and 147S that also explained how the ergoline derivatives having large

134

A.K. Saxena et al.

Fig. 18 (a) The alignment of ()6a-R-apomorphine (101) and ()12aS-centbutindole (138). (b) The docked conformation of the compounds 125 and 126 at the D2 receptor. (c) The superposition of the compounds 125, 126, ergotamine (146), and bifeprunox (148) and the revised D2 agonist pharmacophore model. (d) Alignment of the compounds 125, 126, 146, and 147. (e) The docked conformation of R-147 (light pink) and S-147 (deep purple) at the D2 receptor binding site showing reversed binding mode of the enantiomers (reproduced with permission from Neurochem. Res., 2014, 39, 1997–2007 Copyright Springer Science+Business Media New York 2014)

C-8 substituents showed dopamine agonistic activity (Fig. 18e). The –NH group in the docked conformation of 147S has H-bond interactions with Ser1935.42 and occupies a similar position at the receptor site as observed for the hydroxy group in compounds 125 and 126. The –NH group of 147R however overlapped with ergotamine and formed an H-bond with Ser1975.46. The docked conformation of 147S and 147R showed partial structural overlap where the phenyl moiety in the indole group and the basic nitrogen group occupied the same position at the receptor site. From these docking studies, a refined pharmacophore model was defined that contains two donor sites, one aromatic region, a basic protonated nitrogen, the propyl cleft, and the large spacious cavity that can accommodate large substituents. This is different from the classical D2 pharmacophore in having one extra donor site (Fig. 18c). The dopamine D2 agonist pharmacophore was developed considering a set of full agonists and inactive compounds by Malo et al. [193] (Fig. 19). The study was performed to deduce the features responsible for selectivity between D1 and D2 agonist activity. A set of diverse structures active at the D1 and D2 receptors were selected and compared with structurally similar analogs that were inactive at both these receptors. However our discussion will focus on the D2 agonist pharmacophore model. The pharmacophore model was developed in two steps by using the Molecular Operating Environment

Integration on Ligand and Structure Based Approaches in GPCRs

135

(MOE) software package [194]. The development of pharmacophore model on the basis of projected features provided a more realistic view about the interactions of the ligand with the receptor models and at the same time did not force the important features in the active compounds to occupy the same position, instead ensured that the active ligands interact with the receptor residues in different orientations. The preliminary pharmacophore model was developed using the PCHD annotation scheme in MOE and further optimized using the unified annotation scheme. The preliminary D2 pharmacophore model was developed using two structurally different full agonists (R)-NPA (149) and talipexole (156) by selecting conformations for both the compounds where the n-propyl group was in an extended conformation. The alignment of these compounds was performed using the aromatic ring having the HBD group in (R)-NPA (149) with the amino group containing thiazole ring of talipexole (156) (Fig. 20a). The preliminary pharmacophore model consisted of two HBD and two HBA features representing the serine residues in TM5 (Ser193, Ser194) illustrated as SerTM-5 in Fig. 20a, one projected HBD feature representing the Asp114 in TM3 of the receptor. Besides this, the models consisted of aromatic features represented by inclusion volumes for the aromatic ring centroid and for two ring normals. The aromatic pharmacophore features represented the aromatic interactions with the aromatic residues in TM6 (mainly F390 but also W386 and F389). The Hyd feature of the model represented the N-substituents that are present in most of the potent D2 agonists and represented the propyl cleft. Among all the pharmacophore features, the aromatic ring system and the HBD feature around the cationic nitrogen were stated to be important for differentiating the active compound from the inactives. The hydroxy features were stated to be less important as D2 agonist (S)-DPAT (155) is a full agonist (intrinsic activity is lower than compounds having hydroxyl group) despite lacking the HBA or donor group features. The PCHD annotation scheme was next refined to fit all the active D2 agonists in the pharmacophore model (Fig. 20b). The only D2 active agonist sumanirole (151) was unable to fit the developed model for which slight outward adjustment of the top Ser-TM5 feature (A, increasing the distance to Aro) was done for fitting the sumanirole (151) in the model. In this optimized model, one HBA and HBD features were kept instead of two donor and acceptor features to fit the hydrogen bond accepting carbonyl function or a hydrogen bond donating –NH function as present in sumanirole (151). The retention of only one hydrogen bonding feature instead of two is acceptable as many monohydroxysubstituted full D2 agonists, such as (S)-5-OH-DPAT (100) and (R,R)-PHNO (150), contain only one H-bond feature. The existence of hydrophobic feature representing the propyl pocket was ignored in the final model so that it may not be a strong determinant for D1 and D2 selectivity. The final model for D2 selective agonist was developed by the unified annotation scheme implemented in MOE. The modifications in the pharmacophore included an increase: (1) in the distance of the hydrogen bonding feature from the heavy atoms in the unified model to 2.8 from 2.1 Å present in the PCHD model and (2) in the angle between the two possible projected features from an HBD or HBA (Ser-TM5). In the unified annotation scheme, the imidazole ring of sumanirole was identified as an aromatic feature while the cationic nitrogen was identified as N+

136

A.K. Saxena et al.

Fig. 19 Structure of the D2 agonists considered for model generation by Malo et al.

feature which was HBD in the PCHD model (Fig. 20c). This annotation of the cationic nitrogen as N+ group provided a more specific pharmacophore feature that is important in the GPCRs. The tolerance feature of the pharmacophore model was also set to 1.5 Å for introducing flexibility in the model. The refined model was able to identify all 12 active derivatives (12/12 hits), two of four partial agonists (2/4 hits), and in discriminating six of 14 inactives (8/14 hits). Further refinement of the pharmacophore model was performed by introducing excluded volumes to separate the active D2 agonists from the inactive ones. For this, nine excluded volumes (V1–V9) were incorporated and they included V1 (r ¼ 2.1) to exclude ()-DHX (177), V2,V4,V5,V6

Integration on Ligand and Structure Based Approaches in GPCRs

137

Fig. 20 (a) Mapping of full agonists (R)-NPA (149) (green) and talipexole (156) (purple) with the D2 agonist model using the PCHD annotation scheme. (b) Mapping of (R)-NPA with the refined PCHDgenerated D2 agonist model having excluded volume (Excl: grey). (c) Mapping of the full agonist sumanirole (151) on the pharmacophore models by PCHD (gold carbons) and unified annotation (green carbons) schemes. (d) The distance between the pharmacophore features of the D2 agonist models. (e and f) The pharmacophore features (unified annotation scheme) with excluded volumes (V1–V9 and Excl O) (reproduced with permission from ChemMedChem, 2010, 5, 232–246 Copyright 2010 Wiley-VCH Verlag GmbH & Co.)

(r ¼ 1.8 Å) and V3 (r ¼ 1.6 Å) to exclude A77636 (170) and A70108 (160). The excluded volume V7 (r ¼ 1.8 Å) was included to exclude the enantiomer A70360 (175) of compound 160 along with the compounds 173 and A77641 (174), V8 (r ¼ 1.8 Å) was added to exclude SKF38393 (171), and ()-sumanirole (166) was excluded by adding V9 (r ¼ 1.3 Å) (Fig. 20e and f). Another volume excluding oxygen (O) was added near the hydrophilic ether functionality that may be responsible for making the DHX analogue doxanthrine (172) less active at the D2 site. Finally the refined pharmacophore model with excluded volumes was able to recognize all full agonists (12/12), two out of four partial agonists (2/4) and all the inactives (14/14). Interestingly the mapped conformation of (R)-3-ppp (154) on the refined pharmacophore model had its aromatic ring in the same plane as piperidine ring and was in agreement with the agonist model reported by Liljefors and Wikstrom [65] where the crucial features essential for D2 agonism at the receptor site were: (1) the salt bridge between Asp114TM3 and the amino group of the ligand, (2) the hydrogen bond(s) with the serine residues in TMV by the phenolic groups, and (3) the aromatic interactions with the hydrophobic residues in TMVI. The distances between the important features for this model are shown in Fig. 20d. This developed D2 agonist pharmacophore model was further integrated with a structure based model developed by the docking of the agonist ()-(R)-2-OHNPA (161) on the homology modeled D2 receptor. In the docked conformation the C10 hydroxy group of ()-(R)-2-OHNPA (161) interacted with

138

A.K. Saxena et al.

Ser193 (H-bond distance ¼ 3.0 Å, O-HO (Ser1935.42) angle is 164 ) while the C11 hydroxy group interacted with the imidazole nitrogen atom of His393 (H-bond distance ¼ 2.9 Å, O-H-N (His3936.55) angle is 157 ). No hydrogen bond contact with the oxygen atom attached with C11 and Ser197 was observed due to unfavorable H-bond distance between them (4.9 Å). This was in support towards the mutational studies where the efficacy and affinity of (R)-NPA (149) was less hampered due to Ser1975.46Ala mutation. The positively ionizable nitrogen atom formed salt bridge with the side chain of Asp1143.32 while the hydroxy group attached to 2-position of ()-(R)-2-OHNPA made two H-bond interactions with the NH (H-bond distance ¼ 2.9 Å, O-H-N (Asp186) angle is 142 ) and carbonyl (H-bond distance ¼ 2.9 Å, O-H-O (Asp186) angle is 143 ) atom of Asn186 located at ECL2. The phenyl moiety of the catecholamine moiety formed face to edge pi–pi interactions with Phe3906.52 and hydrophobic contact with the side chain of Val111. The propyl chain of ()-(R)-2-OH-NPA (161) occupied the characteristic N-alkyl/propyl pocket that provided a hydrophobic environment formed by the residues Val832.53, Cys1183.36, Trp3866.48, Thr4127.39, and Tyr4167.43. The D2 agonist pharmacophore model developed earlier was superimposed in the structural model of D2 agonist to compare the features of the pharmacophore with important interacting binding site residues and for analysis of the correct location of excluded volumes (Fig. 21a and b). It was observed that location of all the features in the developed pharmacophore model was in agreement with the important interacting residues except for the Ser–TMV interaction that was shifted towards Val190. The location of the excluded volumes was also not correct regarding the shape of the binding cavity. All this mismatches were further rectified by the development of a refined pharmacophore model where the Ser-TM5 feature was placed near Ser1935.42 and the excluded volumes were adjusted according to the agonist-binding cavity (Fig. 21c and d). All the features of the generated pharmacophore model were treated as essential features except the modified Ser-TM5 feature as the full agonist (S)-DPAT (155) did not interact with this residue. Hence the Ser-TM5 feature was treated as an optional feature. The modified excluded volumes were constructed considering the H-atom of the amino acid residues that are within 3 Å of the docked conformation of ()-(R)-2OH-NPA (161) (1.2 Å for aliphatic and 1.0 Å for aromatic hydrogen atoms) with further radius optimizations until the model differentiated between the active and inactives. The excluded oxygen feature (exclO) was also retained to identify doxanthrine as an inactive. The decreased efficacy of DHX may be attributed due to lack of N-propyl substituent. Analysis was performed to compare the conformation of the hits fitting the pharmacophore model with their receptor interactions. The hits that mapped the pharmacophore model were suggested to have: (1) a distance of 2.4–3.8 Å from the Ser1935.42 and His3936.55, (2) the angle between the heavy atom and the hydrogen atom of the ligand to oxygen atom of the interacting residue (N/O-H-O (Ser1935.42) and N/O-H-N (His3936.55)) should ideally be 180  40, respectively. The refined pharmacophore model was then utilized to screen similar set of ligands as used previously. Among the 13 full agonists and five partial agonists, the 11 agonists except (R)-3-PPP (154) and A70108 (160) and four partial agonists except (S)-3-PPP (164) fitted the pharmacophore model. The model also failed to exclude one of the inactive compound ((S)-

Integration on Ligand and Structure Based Approaches in GPCRs

139

Fig. 21 (a and b) The alignment of the pharmacophore models (Fig. 20e and f) at the D2 receptor site. (c and d) The refined D2 agonist models with modified Ser–TMV and refined excluded volumes (reproduced with permission from ChemMedChem, 2012, 7, 471–482 Copyright 2012 Wiley-VCH Verlag GmbH & Co.)

7-OH-DPAT) (169) from the 12 inactive compounds. The 3-PPP failed to map the pharmacophore model due to perpendicular orientation of the piperidine and the phenyl ring instead of being in the same plane. When the pharmacophore conformation of these compounds was compared with the receptor interactions, it was observed that the agonists and the partial agonists did not fulfill the angular criteria ((N/O-H-O (Ser1935.42) and N/O-H-N (His3936.55)) that should ideally be 180  40). All the full agonists which fitted the pharmacophore model had one proper H-bond interaction at the receptor site except (S)-DPAT (155) that did not have H-bond functionalities. All the partial agonists also had one H-bond except (S)-6-OH-DPAT (163) that may interact differently at the binding site. Among the inactives, (S)-7OHDPAT (169) fits into the pharmacophore model while in the receptor model it failed to maintain H-bond contact with His3936.55 and Ser1935.42. The pharmacophore model also explained the interactions of the full agonist quinpirole (157). The best pharmacophore hit of quinpirole did not interact with the serine residues of TMV that was in full agreement with the mutational studies where Ser193-Ala mutation had no effect on the binding of quinpirole (157). However from the mutational studies it was observed that quinpirole is affected by His3936.55-Ala mutation. The pharmacophore mapped conformation of quinpirole (157) did satisfy the H-bond criteria with His3936.55. It was assumed that the interaction between the pyrazole nitrogen atom in quinpirole and His3936.55 may be water mediated or it may be possible that Asp186 and His3936.55 may

140

A.K. Saxena et al.

arrange in a conformation to interact with quinpirole. The study presented here integrates both ligand and structure based methods for identification of the crucial features for dopamine D2 agonism.

4.3

Histamine H1 Receptor Antagonists

The histamine mediates important physiological responses such as inflammation, gastric acid secretion, and neurotransmission by acting on four histamine receptors subtypes (H1–H4). The histamine H1 receptor is an attractive drug target due to its potential role in allergic reactions. Increased histamine levels are associated with several clinical conditions such as multiple sclerosis, rheumatoid arthritis, allergic asthma, and psoriatic arthritis. The first generations antihistaminics mepyramine (178), chlorpheniramine (179), diphenhydramine (180), and piperoxan (181) had sedation as the main CNS side effect while the second-generation drugs such as cetirizine (182), fexofenadine (183), terfenadine (184), and loratadine (185) have low BBB penetration with low sedation potential (Fig. 22). The classical H1 antagonists in general contain two aromatic rings and basic nitrogen atom separated by three to four carbon atoms. Pharmacophore models on classical antagonists taking the semirigid cyproheptadine (186) have been reported by several groups among which the pharmacophore model developed by Van Drooge et al. from triprolidine (187), phenindamine (188), and cyproheptadine (186) reported a boat conformation for the piperidylene ring of cyproheptadine (186). However the model was not satisfactory regarding the fitting of semirigid H1 antagonists that prompted Terlaack et al. to develop another pharmacophore model taking semirigid conformations of classical H1 receptor antagonists (cyproheptadine (186), phenindamine (188), triprolidine (187), epinastine (189), mequitazine (190), IBF28145 (191), and mianserine (192)). The model was developed by selecting the aromatic moieties as template and allowing freedom to the basic nitrogen atom that interacted with Asp116 of TM 3. The Asp116 was also incorporated in the model that helped in the development of a stereoselective models that can identify the absolute bioactive configuration of antihistamines such as phenindamine (S), epinastine (S), and IBF28145 (R). The nonclassical H1 antihistaminics generally have more than one aromatic ring and a basic nitrogen atom. However some of them have a single aromatic moiety such as the benzimidazole derivatives. The 2-substituted 1,2,3,4,5,6,7,12,12a-octahydropyrazino[20 ,10 :6,1]pyrido[3,4-b] indoles having a combination of tryptamine and piperazine moieties in rigid conformation have shown wide spectrum of biological activities such as antihistaminics, neuroleptics, and anti-inflammatory. The nature of the substituent at position 2 of the 1,2,3,4,5,6,7,12,12a-octahydropyrazino[20 ,10 :6,1]pyrido[3,4-b]indoles governed the biological activity in this class of compounds. The antihistamine compounds were designed by the introduction of aroylaminoethyl side chain at position 2 of octahydropyrazinopyridoindole core because a number of piperazine derivatives incorporating aroylaminoethyl substructure have shown antihistaminic H1 activity. In the QSAR studies on 2-β-aroylaminoethyl-1,2,3,4,6,7,12,1a-octahydropyrazino(20 , 10 :6,1) pyrido

Integration on Ligand and Structure Based Approaches in GPCRs

141

(3,4-b)indoles ((1) in Table 5), it was observed that hydrophobicity of the substituents at the ortho and para position and bulk at the ortho position of the aromatic ring of aroyl aminoethyl side chain increased the activity. Among the synthesized 34 compounds (Table 3), 28 compounds were used for model generation and the rest six compounds (217–222) were found to be outliers, the activities of which were not suitably predicted by the model [199]. In view of the similarity in terms of positive steric effect of substitution at the phenyl ring of these molecules and diphenhydramines, it was suggested that these molecules bind to H1-receptor in a folded conformation in which the phenyl and indole rings of these molecules occupy similar positions as the two phenyl rings of diphenhydramine (Fig. 25a). Based on these studies and SAR in semirigid analogs of diphenhydramine, benzylhydrylamine, and phenbenzamine, a model for H1 receptor was proposed. In order to gain more insights into the discussed topography of H1 receptor, it was considered of interest to study some semirigid analogs of known antihistaminics such as diphenylhydramine (180, R¼C6H5, X¼O), benzhydrylamine (193, R¼C6H5, X¼NH), and phenbenzamine (193, R¼H, X¼NC6H5) (Table 4). The locking of α and β carbons atoms of the ethyl side chain adjacent to the dimethylamino groups with one of the aromatic rings of 193 can produce two semirigid structures 194 and 195. Each of these compounds 194 and 195 having two asymmetric centers may produce two distereoisomers. Some of these compounds (194a–c, 195a–c) were synthesized and evaluated for H1-antagonistic activity in isolated guinea pig ileum. The five-membered semirigid analog 194 was equipotent to the parent open chain diphenylhydramine 193a while the corresponding six-membered semirigid analog 195b of benzhydrylamine (193a) and five-membered semirigid analog (194b) of phenbenzamine (193b) were less active than the parent compounds 193b and 193c, respectively. Further the analogs

Fig. 22 The structure of the antihistamine H1 compounds

142

A.K. Saxena et al.

194c and 195c of 194a and 195a in which the free phenyl ring is replaced by methyl group were less active than the 194a and 195a, respectively. The SAR study of these compounds based on their Dreiding models also revealed that π rich hydrophobic subsites A and D and electron density subsites C and anionic site B are essential for binding with the H1 receptor. All the above requirements were met by diphenylhydramine (180), and also by 194a. In the case of the corresponding six-membered analog (195a) though the distance of the basic nitrogen (subsite B) from the aromatic ring (subsite A) is almost the same, both the aromatic rings, being coplanar, inhibit the interactions at the subsite A and this may be the reason for the decreased activity. The same would be true for 195c. However in the case of semirigid analog of phenbenzamine (193b) though the noncoplanarity of the aromatic rings is maintained yet the distant between subsites A and B is reduced causing 1,000-fold decrease in activity. Further support for the noncoplanarity of the aromatic rings is evident from the observed 100-fold decrease in activity of fluorene analog (196) of diphenylhydramine where both rings are coplanar. These studies showed that: (1) pyrazinopyridoindoles (197), semirigid analogs of 193, and diphenylhydramine type of antihistaminics act on common receptor, (2) the o-substitution in the phenyl ring of the side chain of 197 has conformational effect causing noncoplanarity to the phenyl ring of the side chain, (3) hydrophobic interactions are more important in A region than electronic and steric interactions, (4) the distance of the anionic site B from A is of prime importance for the activity while the high electron density in C region also contributes to the activity. With a view to further explore this model, four different prototype molecules (Fig. 23) including the ones with the change in the side chain from aroylaminoethyl to arylaminocarbonylethyl were synthesized and evaluated for antihistaminic H1 activity. All these molecules incorporate the above suggested essential structural requirements to interact at proposed sites A, B, C, and D and the phenyl ring attached to the aroylaminoethyl side chain should experience the same biomolecular interactions being at the same site A which is also occupied by the phenyl ring of diphenhydramine. The QSARs were developed for each class in terms of antihistaminic activity as dependent and physicochemical parameters particularly hydrophobicity as independent variables. The almost identical slope values (0.375  0.045) with hydrophobicity parameters in all the four prototypes including pyrazinopyridoindoles clearly indicated that there is a similar change in activity for the same substructural variation in the side chain phenyl ring of all the prototypes. Equation (2) (Table 5) reported for only six compounds of the prototype pyrazinopyridoindoles with aroyl amino ethyl side chain in terms of all the three physicochemical effects parameterized as hydrophobic (π), electronic (σ), and steric (MR) compared well with the Eqn. (3) (Table 5) in terms of their slope values π (0.325  0.021), σ (0.154  0.01), and MR (0.0115  0.004) for all new 27 compounds belonging to other prototypes thus indicating that the side chain phenyl ring in all these prototypes occupies the same receptor site and at subsite A all these molecules experience the same kind of biomolecular interactions. The overall Eqn. (4) for 33 compounds is provided in Table 5. In order to further integrate the results of 2D-QSAR with the newly developing 3DQSAR techniques which had no limitations on the inclusion of similar congenic series, the HASL approach was used. In the HASL approach, a molecular representation lattice is constructed using the energy minimized Cartesian coordinates

Integration on Ligand and Structure Based Approaches in GPCRs

143

Table 3 The structure of the compounds synthesized with antihistamine H1 activity

Comp 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 197 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 a

R H CH2CN (CH2)2CH2NH2 (CH2)2NHC(¼O)C6H4-2-NO2 (CH2)2NHC(¼O)C6H4-3-NO2 (CH2)2NHC(¼O)C6H4-4-NO2 (CH2)2NHC(¼O)C6H4-2-NH2 (CH2)2NHC(¼O)C6H4-3-NH2 (CH2)2NHC(¼O)C6H4-4-NH2 (CH2)2NHC(¼O)C6H4-2-CH3 (CH2)2NHC(¼O)C6H4-4-CH3 (CH2)2NHC(¼O)C6H3-2,4-(CH3)2 (CH2)2NHC(¼O)C6H4-2-OCH3 (CH2)2NHC(¼O)C6H2-3,4,5-(OCH3)3 (CH2)2NHC(¼O)C6H4-2-Cl (CH2)2NHC(¼O)C6H4-4-Cl (CH2)2NHC(¼O)C6H4-3,4-Cl2 (CH2)2NHC(¼O)C6H4-4-CN (CH2)2NHC(¼O)C6H4-4-SO2CH3 (CH2)2NHC(¼O)C6H5 (CH2)2NHC(¼O)C6H4-3-CH3 (CH2)2NHC(¼O)C6H4-4-OCH3 (CH2)2NHC(¼O)C6H4-4F (CH2)2NHC(¼O)C6H4-4CO2C2H5 (CH2)2NHC(¼O)C6H4-CONH2 (CH2)2NHC(¼O)C5H4-4-N (CH2)2CN CH2CH2CH2-NH2 (CH2)3NHC(¼O)C6H4-2-CH3 (CH2)3NHC(¼O)C6H3-2,4-(CH3)2 (CH2)3NHC(¼O)C6H4-4-OCH3 (CH2)2OCH(C6H5)2 (CH2)2OCH(C6H5)-C6H4-4-F (CH2)OCH-C6H4-4-F C6H4-4-Cl (CH2)2NH-CH(C6H5)-C6H4-4-F (CH2)2N¼CHC6H4-4-NO2 (CH2)3(CH3)OH-C6H4-4F (CH2)2NH-CH2C6H4-4-NO2 (CH2)2NHC(¼S)NHC6H5

H1-receptor blocking activity (IC50 μg/mL)a – – – 0.157  0.06 0.19  0.06 0.41  0.02 0.36  0.19 0.24  0.048 0.51  0.05 0.11  0.08 0.15  0.02 0.068  0.034 0.147  0.06 0.172  0.05 0.07  0.009 0.14  0.03 0.095  0.03 0.177  0.04 0.48  0.2 0.2  0.02 0.54  0.2 0.07  0.0 0.56  0.06 0.345  0.02 0.08  0.03 2.2  0.12 – – 0.32  0.1 0.32  0.1 0.22  0.08 1.0  0.1 1.0  0.1 1.35  0.2 0.75  0.08 5.25  1.02 0.75  0.10 2.20  0.22 0.47  0.11

IC50 against histamine induced contraction in isolated guinea pig ileum: (–) described not done [199]

144

A.K. Saxena et al.

Table 4 The structure of the constrained analogs of diphenhydramine

Comp 180 194a 195a 193a 194b

Substituents IC50 (mg/mL)a R Diphenhydramine 0.001 R¼C6H5, X¼O 0.001 R¼C6H5, X¼O 0.5 R¼C6H5, X¼NH 0.03 R¼H,X¼N-C6H5 10

Structure 195b 193b 194c 195c

Substituents R¼C6H5, X¼NH R¼H, X¼N-C6H5 R¼CH3, X¼0 R¼CH3, X¼0

IC50 (mg/mL)a 3.5 0.01 0.75 1.0

a

In guinea pig ileum

of the molecule. A molecular volume is drawn enclosing the space within Van der Waals radii of all the atoms lying within this volume, and a set of equidistant lattice points are generated orthogonally to each other and separated by a distance called resolution. Additional information like electro density is incorporated as a fourth dimensional at the occupied lattice points and thus 4D lattice of a reference molecule is generated. Next the 4D lattices of other molecules are compared with this reference lattice by stepped progression of translational and rotational movements to find the best common points among the lattices (maximum FIT). The first application of the HASL approach not only included the β-benzoylaminoethyl and 2-(anilinocarbonyl)ethylpiperazines,-piperidines, -pyrazinopyrioindoles, and -pyrazinoiso-quinolines but also diphenhydramine and its semirigid analogs reinforced the importance of major sites for the interaction of the tertiary nitrogen and aromatic rings and showed that the β-aroylamino/arylaminocarbonyl ethylamine substructure is the possible antihistaminic H1 pharmacophore (Fig. 25b) for compounds 197, 245, 249, 254, 259, and 263 (Fig. 24). These studies were further improved by advanced pharmacophore models using the Apex 3D and CATALYST molecular modeling programs. The HipHop module in CATALYST was used for the generation of pharmacophore models where diphenhydramine was selected as a template and the rest 43 molecules were superimposed on it. The 3D structures of all the compounds considered were generated within a 20 Kcal cutoff by applying the poling algorithm by the application of CHARMm force field [195]. The common feature pharmacophore was generated to find the common chemical features present in all the training set molecules. The best alignments obtained from the common feature pharmacophore generation were used in the MOPAC for the calculation of different physicochemical and quantum chemical parameters such as π-population, atomic charge, H-bond acceptor and donor index, hydrophobicity, LUMO, HOMO, and molar refractivity on the basis of atom properties that were used by the Apex 3D program in the generation of 3D-QSAR and pharmacophore models. The common feature pharmacophore protocol in CATALYST generated eight hypotheses with the ranking score ranging from 80.3518 to 25.2954 units among which six hypotheses had similar combination of

Integration on Ligand and Structure Based Approaches in GPCRs

145

Fig. 23 Chemical structure of the compounds used for 2D-QSAR generation

Table 5 The 2D-QSAR equations for the generated models No 1 2 3 4

Equation log1/C ¼ 0.324 πo + 0.268 πp + 0.150 Io + 0.702 log1/I50 ¼ 0.304π(0.014) + 0.164σ(0.046) + 0.019MR (0.005) + 0.262(0.024) log1/I50 ¼ 0.347π(0.049) + 0.144σ(0.072) + 0.011MR (0.006)  0.224(0.038) log1/I50 ¼ 0.328π(0.034) + 0.143σ(0.059) + 0.013MR (0.005) + 0.53IA(0.041)  0.229(0.003)

na 17 6

rb 0.93 0.998

sc 0.11 0.021

Fd 27.57 188.4

27

0.915

0.090

39.3

33

0.953

0.083

68.7

a

Number of dataset Multiple correlation coefficient c Standard deviation d Statistical significance b

pharmacophore features: two ring aromatic and one PI features (Fig. 25d). The features of the developed pharmacophore model were in agreement to the earlier models and the model proposed by Ter Laack et al. However the interfeature distance in the model differed significantly from the model developed by Ter Laack et al. [196]. The differences in interfeature distance (Å) are summarized in Table 6. These differences in interfeature distances in these models may arise due to different chemical class of compounds used for model generation. The features of the catalyst pharmacophore complement with the homology model of H1 receptor developed by Wieland where one of the aromatic rings interacted with Phe 433 and Phe 436 while the other interacted with Trp167. The positively ionizable nitrogen atom made contact with Asp116 of TMIII. The Apex 3D-biophoric models were developed taking the alignment of training set molecules for hypothesis 1 of the CFP in CATALYST.

146

A.K. Saxena et al.

logðIC50 Þ ¼ 0 : 5640  ð0:140Þ  ½Hydrophobicity at ss1 þ 10:097ð1:287Þ  ðHydrophobicity at ss2Þ  1 : 638ð0:752Þ  ½Hydrophobicity at ss3 þ 2 : 209ð0:738Þ  ½Hydrophobicity at ss4  0:270ð0:44Þ ½Refractivity at ss5 þ 0:117ð0:034Þ ½Refractivity at ss6 þ 0:12 ðn ¼ 42; R ¼ 0:855; F6; 36 ¼ 16:376; Q ¼ 0:794; S ¼ 0:335Þ ð5Þ None of the generated biophoric models mapped all the molecules in the training set, hence a model that can map maximum number of compounds (42 out of 45) with good statistical parameters (correlation coefficient r2 > 0.7, the difference of RMSA and RMSP