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Pallante L, Cannariato M, Androutsos L, Zizzi EA, Bompotas A, Hada X, Grasso G, Kalogeras A, Mavroudi S, Di Benedetto G, Theofilatos K, Deriu MA. VirtuousPocketome: a computational tool for screening protein-ligand complexes to identify similar binding sites. Sci Rep 2024; 14:6296. [PMID: 38491261 PMCID: PMC10943019 DOI: 10.1038/s41598-024-56893-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 03/12/2024] [Indexed: 03/18/2024] Open
Abstract
Protein residues within binding pockets play a critical role in determining the range of ligands that can interact with a protein, influencing its structure and function. Identifying structural similarities in proteins offers valuable insights into their function and activation mechanisms, aiding in predicting protein-ligand interactions, anticipating off-target effects, and facilitating the development of therapeutic agents. Numerous computational methods assessing global or local similarity in protein cavities have emerged, but their utilization is impeded by complexity, impractical automation for amino acid pattern searches, and an inability to evaluate the dynamics of scrutinized protein-ligand systems. Here, we present a general, automatic and unbiased computational pipeline, named VirtuousPocketome, aimed at screening huge databases of proteins for similar binding pockets starting from an interested protein-ligand complex. We demonstrate the pipeline's potential by exploring a recently-solved human bitter taste receptor, i.e. the TAS2R46, complexed with strychnine. We pinpointed 145 proteins sharing similar binding sites compared to the analysed bitter taste receptor and the enrichment analysis highlighted the related biological processes, molecular functions and cellular components. This work represents the foundation for future studies aimed at understanding the effective role of tastants outside the gustatory system: this could pave the way towards the rationalization of the diet as a supplement to standard pharmacological treatments and the design of novel tastants-inspired compounds to target other proteins involved in specific diseases or disorders. The proposed pipeline is publicly accessible, can be applied to any protein-ligand complex, and could be expanded to screen any database of protein structures.
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Affiliation(s)
- Lorenzo Pallante
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, PolitoBIOMedLab, 10129, Torino, Italy
| | - Marco Cannariato
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, PolitoBIOMedLab, 10129, Torino, Italy
| | | | - Eric A Zizzi
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, PolitoBIOMedLab, 10129, Torino, Italy
| | - Agorakis Bompotas
- Industrial Systems Institute, Athena Research Center, 265 04, Patras, Greece
| | - Xhesika Hada
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, PolitoBIOMedLab, 10129, Torino, Italy
| | - Gianvito Grasso
- Dalle Molle Institute for Artificial Intelligence IDSIA USI-SUPSI, 6962, Lugano-Viganello, Switzerland
| | | | - Seferina Mavroudi
- Department of Nursing, School of Health Rehabilitation Sciences, University of Patras, 265 04, Patras, Greece
| | | | | | - Marco A Deriu
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, PolitoBIOMedLab, 10129, Torino, Italy.
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Kumar S, Teli MK, Kim MH. GPCR-IPL score: multilevel featurization of GPCR-ligand interaction patterns and prediction of ligand functions from selectivity to biased activation. Brief Bioinform 2024; 25:bbae105. [PMID: 38517694 PMCID: PMC10959162 DOI: 10.1093/bib/bbae105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/12/2024] [Accepted: 02/27/2024] [Indexed: 03/24/2024] Open
Abstract
G-protein-coupled receptors (GPCRs) mediate diverse cell signaling cascades after recognizing extracellular ligands. Despite the successful history of known GPCR drugs, a lack of mechanistic insight into GPCR challenges both the deorphanization of some GPCRs and optimization of the structure-activity relationship of their ligands. Notably, replacing a small substituent on a GPCR ligand can significantly alter extracellular GPCR-ligand interaction patterns and motion of transmembrane helices in turn to occur post-binding events of the ligand. In this study, we designed 3D multilevel features to describe the extracellular interaction patterns. Subsequently, these 3D features were utilized to predict the post-binding events that result from conformational dynamics from the extracellular to intracellular areas. To understand the adaptability of GPCR ligands, we collected the conformational information of flexible residues during binding and performed molecular featurization on a broad range of GPCR-ligand complexes. As a result, we developed GPCR-ligand interaction patterns, binding pockets, and ligand features as score (GPCR-IPL score) for predicting the functional selectivity of GPCR ligands (agonism versus antagonism), using the multilevel features of (1) zoomed-out 'residue level' (for flexible transmembrane helices of GPCRs), (2) zoomed-in 'pocket level' (for sophisticated mode of action) and (3) 'atom level' (for the conformational adaptability of GPCR ligands). GPCR-IPL score demonstrated reliable performance, achieving area under the receiver operating characteristic of 0.938 and area under the precision-recall curve of 0.907 (available in gpcr-ipl-score.onrender.com). Furthermore, we used the molecular features to predict the biased activation of downstream signaling (Gi/o, Gq/11, Gs and β-arrestin) as well as the functional selectivity. The resulting models are interpreted and applied to out-of-set validation with three scenarios including the identification of a new MRGPRX antagonist.
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Affiliation(s)
- Surendra Kumar
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, 191 Hambakmoeiro, Yeonsu-gu, Incheon, Republic of Korea
| | - Mahesh K Teli
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, 191 Hambakmoeiro, Yeonsu-gu, Incheon, Republic of Korea
| | - Mi-hyun Kim
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, 191 Hambakmoeiro, Yeonsu-gu, Incheon, Republic of Korea
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3
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Chiesa L, Sick E, Kellenberger E. Predicting the duration of action of β2-adrenergic receptor agonists: Ligand and structure-based approaches. Mol Inform 2023; 42:e202300141. [PMID: 37872120 DOI: 10.1002/minf.202300141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/17/2023] [Accepted: 10/23/2023] [Indexed: 10/25/2023]
Abstract
Agonists of the β2 adrenergic receptor (ADRB2) are an important class of medications used for the treatment of respiratory diseases. They can be classified as short acting (SABA) or long acting (LABA), with each class playing a different role in patient management. In this work we explored both ligand-based and structure-based high-throughput approaches to classify β2-agonists based on their duration of action. A completely in-silico prediction pipeline using an AlphaFold generated structure was used for structure-based modelling. Our analysis identified the ligands' 3D structure and lipophilicity as the most relevant features for the prediction of the duration of action. Interaction-based methods were also able to select ligands with the desired duration of action, incorporating the bias directly in the structure-based drug discovery pipeline without the need for further processing.
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Affiliation(s)
- Luca Chiesa
- Laboratoire d'Innovation Thérapeutique, Faculté de Pharmacie, UMR7200 CNRS Université de Strasbourg, 67400, Illkirch, France
| | - Emilie Sick
- Laboratoire de Conception et Application de Molécules Bioactives, Faculté de Pharmacie, UMR7199 CNRS Université de Strasbourg, 67400, Illkirch, France
| | - Esther Kellenberger
- Laboratoire d'Innovation Thérapeutique, Faculté de Pharmacie, UMR7200 CNRS Université de Strasbourg, 67400, Illkirch, France
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4
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Tricomi J, Landini L, Nieddu V, Cavallaro U, Baker JG, Papakyriakou A, Richichi B. Rational design, synthesis, and pharmacological evaluation of a cohort of novel beta-adrenergic receptors ligands enables an assessment of structure-activity relationships. Eur J Med Chem 2023; 246:114961. [PMID: 36495629 DOI: 10.1016/j.ejmech.2022.114961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 11/30/2022]
Abstract
Biomedical applications of molecules that are able to modulate β-adrenergic signaling have become increasingly attractive over the last decade, revealing that β-adrenergic receptors (β-ARs) are key targets for a plethora of therapeutic interventions, including cancer. Despite successes in β-AR drug discovery, identification of β-AR ligands that are useful as selective chemical tools in pharmacological studies of the three β-AR subtypes, or lead compounds for drug development is still a highly challenging task. This is mainly due to the intrinsic plasticity of β-ARs as G protein-coupled receptors in conjunction with the requirement for functional receptor subtype selectivity, tissue specificity and minimal off-target effects. With the aim to provide insight into structure-activity relationships for the three β-AR subtypes, we have synthesized and obtained the pharmacological profile of a series of structurally diverse compounds (named MC) that were designed based on the aryloxy-propanolamine scaffold of SR59230A. Comparative analysis of their predicted binding mode within the active and inactive states of the receptors in combination with their pharmacological profile revealed key structural elements that control their activity as agonists or antagonists, in addition to clues about substituents that mediate selectivity for one receptor subtype over the others. We anticipate that these results will facilitate selective β-AR drug development efforts.
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Affiliation(s)
- Jacopo Tricomi
- Department of Chemistry, University of Firenze, Via della Lastruccia 13, 50019 Sesto Fiorentino, Firenze, Italy
| | - Luca Landini
- Department of Chemistry, University of Firenze, Via della Lastruccia 13, 50019 Sesto Fiorentino, Firenze, Italy; Institute of Biosciences and Applications, National Centre for Scientific Research "Demokritos", 15341 Agia Paraskevi, Athens, Greece
| | - Valentina Nieddu
- Unit of Gynaecological Oncology Research, European Institute of Oncology IRCCS, Milan, Italy
| | - Ugo Cavallaro
- Unit of Gynaecological Oncology Research, European Institute of Oncology IRCCS, Milan, Italy
| | - Jillian G Baker
- Cell Signalling Research Group, School of Life Sciences, University of Nottingham, Nottingham, NG7 2UH, UK
| | - Athanasios Papakyriakou
- Institute of Biosciences and Applications, National Centre for Scientific Research "Demokritos", 15341 Agia Paraskevi, Athens, Greece.
| | - Barbara Richichi
- Department of Chemistry, University of Firenze, Via della Lastruccia 13, 50019 Sesto Fiorentino, Firenze, Italy.
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5
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Chiesa L, Kellenberger E. One class classification for the detection of β2 adrenergic receptor agonists using single-ligand dynamic interaction data. J Cheminform 2022; 14:74. [PMID: 36309734 PMCID: PMC9617447 DOI: 10.1186/s13321-022-00654-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/17/2022] [Indexed: 11/22/2022] Open
Abstract
G protein-coupled receptors are involved in many biological processes, relaying the extracellular signal inside the cell. Signaling is regulated by the interactions between receptors and their ligands, it can be stimulated by agonists, or inhibited by antagonists or inverse agonists. The development of a new drug targeting a member of this family requires to take into account the pharmacological profile of the designed ligands in order to elicit the desired response. The structure-based virtual screening of chemical libraries may prioritize a specific class of ligands by combining docking results and ligand binding information provided by crystallographic structures. The performance of the method depends on the relevance of the structural data, in particular the conformation of the targeted site, the binding mode of the reference ligand, and the approach used to compare the interactions formed by the docked ligand with those formed by the reference ligand in the crystallographic structure. Here, we propose a new method based on the conformational dynamics of a single protein–ligand reference complex to improve the biased selection of ligands with specific pharmacological properties in a structure-based virtual screening exercise. Interactions patterns between a reference agonist and the receptor, here exemplified on the β2 adrenergic receptor, were extracted from molecular dynamics simulations of the agonist/receptor complex and encoded in graphs used to train a one-class machine learning classifier. Different conditions were tested: low to high affinity agonists, varying simulation duration, considering or ignoring hydrophobic contacts, and tuning of the classifier parametrization. The best models applied to post-process raw data from retrospective virtual screening obtained by docking of test libraries effectively filtered out irrelevant poses, discarding inactive and non-agonist ligands while identifying agonists. Taken together, our results suggest that consistency of the binding mode during the simulation is a key to the success of the method.
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Affiliation(s)
- Luca Chiesa
- Laboratoire d'innovation Thérapeutique, Faculté de Pharmacie, UMR7200 CNRS Université de Strasbourg, 67400, Illkirch, France
| | - Esther Kellenberger
- Laboratoire d'innovation Thérapeutique, Faculté de Pharmacie, UMR7200 CNRS Université de Strasbourg, 67400, Illkirch, France.
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6
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Jiménez-Rosés M, Morgan BA, Jimenez Sigstad M, Tran TDZ, Srivastava R, Bunsuz A, Borrega-Román L, Hompluem P, Cullum SA, Harwood CR, Koers EJ, Sykes DA, Styles IB, Veprintsev DB. Combined docking and machine learning identify key molecular determinants of ligand pharmacological activity on β2 adrenoceptor. Pharmacol Res Perspect 2022; 10:e00994. [PMID: 36029004 PMCID: PMC9418666 DOI: 10.1002/prp2.994] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/21/2022] [Indexed: 11/06/2022] Open
Abstract
G protein‐coupled receptors (GPCRs) are valuable therapeutic targets for many diseases. A central question of GPCR drug discovery is to understand what determines the agonism or antagonism of ligands that bind them. Ligands exert their action via the interactions in the ligand binding pocket. We hypothesized that there is a common set of receptor interactions made by ligands of diverse structures that mediate their action and that among a large dataset of different ligands, the functionally important interactions will be over‐represented. We computationally docked ~2700 known β2AR ligands to multiple β2AR structures, generating ca 75 000 docking poses and predicted all atomic interactions between the receptor and the ligand. We used machine learning (ML) techniques to identify specific interactions that correlate with the agonist or antagonist activity of these ligands. We demonstrate with the application of ML methods that it is possible to identify the key interactions associated with agonism or antagonism of ligands. The most representative interactions for agonist ligands involve K972.68×67, F194ECL2, S2035.42×43, S2045.43×44, S2075.46×641, H2966.58×58, and K3057.32×31. Meanwhile, the antagonist ligands made interactions with W2866.48×48 and Y3167.43×42, both residues considered to be important in GPCR activation. The interpretation of ML analysis in human understandable form allowed us to construct an exquisitely detailed structure‐activity relationship that identifies small changes to the ligands that invert their pharmacological activity and thus helps to guide the drug discovery process. This approach can be readily applied to any drug target.
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Affiliation(s)
- Mireia Jiménez-Rosés
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Bradley Angus Morgan
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,School of Computer Science, University of Birmingham, Birmingham, UK.,The Alan Turing Institute, London, UK.,MRC IMPACT Doctoral Training Programme, Universities of Birmingham, Leicester and Nottingham, Midlands, UK
| | - Maria Jimenez Sigstad
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Thuy Duong Zoe Tran
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,MSc Programme in Drug Discovery & Pharmaceutical Sciences, University of Nottingham, Nottingham, UK
| | - Rohini Srivastava
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,MSc Programme in Drug Discovery & Pharmaceutical Sciences, University of Nottingham, Nottingham, UK
| | - Asuman Bunsuz
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Leire Borrega-Román
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK.,Department of Pharmacology, University of the Basque Country UPV/EHU, Vitoria-Gasteiz, Spain.,Bioaraba, Neurofarmacología Celular y Molecular, Vitoria-Gasteiz, Spain
| | - Pattarin Hompluem
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Sean A Cullum
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK.,MRC IMPACT Doctoral Training Programme, Universities of Birmingham, Leicester and Nottingham, Midlands, UK
| | - Clare R Harwood
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK.,MRC IMPACT Doctoral Training Programme, Universities of Birmingham, Leicester and Nottingham, Midlands, UK
| | - Eline J Koers
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - David A Sykes
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Iain B Styles
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,School of Computer Science, University of Birmingham, Birmingham, UK.,The Alan Turing Institute, London, UK
| | - Dmitry B Veprintsev
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, UK.,Division of Physiology, Pharmacology & Neuroscience, School of Life Sciences, University of Nottingham, Nottingham, UK
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7
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Laeremans T, Sands ZA, Claes P, De Blieck A, De Cesco S, Triest S, Busch A, Felix D, Kumar A, Jaakola VP, Menet C. Accelerating GPCR Drug Discovery With Conformation-Stabilizing VHHs. Front Mol Biosci 2022; 9:863099. [PMID: 35677880 PMCID: PMC9170359 DOI: 10.3389/fmolb.2022.863099] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 03/22/2022] [Indexed: 01/19/2023] Open
Abstract
The human genome encodes 850 G protein-coupled receptors (GPCRs), half of which are considered potential drug targets. GPCRs transduce extracellular stimuli into a plethora of vital physiological processes. Consequently, GPCRs are an attractive drug target class. This is underlined by the fact that approximately 40% of marketed drugs modulate GPCRs. Intriguingly 60% of non-olfactory GPCRs have no drugs or candidates in clinical development, highlighting the continued potential of GPCRs as drug targets. The discovery of small molecules targeting these GPCRs by conventional high throughput screening (HTS) campaigns is challenging. Although the definition of success varies per company, the success rate of HTS for GPCRs is low compared to other target families (Fujioka and Omori, 2012; Dragovich et al., 2022). Beyond this, GPCR structure determination can be difficult, which often precludes the application of structure-based drug design approaches to arising HTS hits. GPCR structural studies entail the resource-demanding purification of native receptors, which can be challenging as they are inherently unstable when extracted from the lipid matrix. Moreover, GPCRs are flexible molecules that adopt distinct conformations, some of which need to be stabilized if they are to be structurally resolved. The complexity of targeting distinct therapeutically relevant GPCR conformations during the early discovery stages contributes to the high attrition rates for GPCR drug discovery programs. Multiple strategies have been explored in an attempt to stabilize GPCRs in distinct conformations to better understand their pharmacology. This review will focus on the use of camelid-derived immunoglobulin single variable domains (VHHs) that stabilize disease-relevant pharmacological states (termed ConfoBodies by the authors) of GPCRs, as well as GPCR:signal transducer complexes, to accelerate drug discovery. These VHHs are powerful tools for supporting in vitro screening, deconvolution of complex GPCR pharmacology, and structural biology purposes. In order to demonstrate the potential impact of ConfoBodies on translational research, examples are presented of their role in active state screening campaigns and structure-informed rational design to identify de novo chemical space and, subsequently, how such matter can be elaborated into more potent and selective drug candidates with intended pharmacology.
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8
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Ballante F, Kooistra AJ, Kampen S, de Graaf C, Carlsson J. Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You? Pharmacol Rev 2021; 73:527-565. [PMID: 34907092 DOI: 10.1124/pharmrev.120.000246] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.
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Affiliation(s)
- Flavio Ballante
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Albert J Kooistra
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Stefanie Kampen
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Chris de Graaf
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden (F.B., S.K., J.C.); Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark (A.J.K.); and Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge, United Kingdom (C.d.G.)
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9
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Brown AJH, Bradley SJ, Marshall FH, Brown GA, Bennett KA, Brown J, Cansfield JE, Cross DM, de Graaf C, Hudson BD, Dwomoh L, Dias JM, Errey JC, Hurrell E, Liptrot J, Mattedi G, Molloy C, Nathan PJ, Okrasa K, Osborne G, Patel JC, Pickworth M, Robertson N, Shahabi S, Bundgaard C, Phillips K, Broad LM, Goonawardena AV, Morairty SR, Browning M, Perini F, Dawson GR, Deakin JFW, Smith RT, Sexton PM, Warneck J, Vinson M, Tasker T, Tehan BG, Teobald B, Christopoulos A, Langmead CJ, Jazayeri A, Cooke RM, Rucktooa P, Congreve MS, Weir M, Tobin AB. From structure to clinic: Design of a muscarinic M1 receptor agonist with potential to treatment of Alzheimer's disease. Cell 2021; 184:5886-5901.e22. [PMID: 34822784 PMCID: PMC7616177 DOI: 10.1016/j.cell.2021.11.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 04/29/2021] [Accepted: 11/01/2021] [Indexed: 12/31/2022]
Abstract
Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic.
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Affiliation(s)
- Alastair J H Brown
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Sophie J Bradley
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK; The Centre for Translational Pharmacology, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Fiona H Marshall
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Giles A Brown
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Kirstie A Bennett
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Jason Brown
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Julie E Cansfield
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - David M Cross
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK; Cross Pharma Consulting Ltd, 20-22 Wenlock Road, London, N17GU, UK
| | - Chris de Graaf
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Brian D Hudson
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Louis Dwomoh
- The Centre for Translational Pharmacology, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - João M Dias
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - James C Errey
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Edward Hurrell
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Jan Liptrot
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Giulio Mattedi
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Colin Molloy
- The Centre for Translational Pharmacology, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Pradeep J Nathan
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK; Brain Mapping Unit, University of Cambridge, Department of Psychiatry, Herchel Smith Building, Cambridge, CB20SZ, UK
| | - Krzysztof Okrasa
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Greg Osborne
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Jayesh C Patel
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Mark Pickworth
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Nathan Robertson
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Shahram Shahabi
- Eli Lilly & Co, Neuroscience Discovery, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - Christoffer Bundgaard
- Eli Lilly & Co, Neuroscience Discovery, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK; H. Lundbeck A/S, Neuroscience Research, Ottiliavej 9, 2500 Valby, Copenhagen, Denmark
| | - Keith Phillips
- Eli Lilly & Co, Neuroscience Discovery, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - Lisa M Broad
- Eli Lilly & Co, Neuroscience Discovery, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - Anushka V Goonawardena
- Center for Neuroscience, Biosciences Division, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 94025, USA
| | - Stephen R Morairty
- Center for Neuroscience, Biosciences Division, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 94025, USA
| | - Michael Browning
- University Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX12JD, UK; P1vital, Manor house, Howbery Buisness Park, Wallingford, OX108BA, UK
| | - Francesca Perini
- Centre for Cognitive Neuroscience - Duke-NUS Medical School, 8 College Road, 169857, Singapore
| | - Gerard R Dawson
- University Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX12JD, UK
| | - John F W Deakin
- Neuroscience and Psychiatry Unit, University of Manchester, Manchester, M139PT UK
| | - Robert T Smith
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Patrick M Sexton
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville 3052, Victoria, Australia; ARC Centre for Cryo-electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville 3052, Victoria, Australia
| | - Julie Warneck
- Protogenia Consulting Ltd, PO-Box 289, Ely, CB79DR, UK
| | - Mary Vinson
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Tim Tasker
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Benjamin G Tehan
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Barry Teobald
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Arthur Christopoulos
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville 3052, Victoria, Australia
| | - Christopher J Langmead
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK; Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville 3052, Victoria, Australia
| | - Ali Jazayeri
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Robert M Cooke
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Prakash Rucktooa
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Miles S Congreve
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK
| | - Malcolm Weir
- Sosei-Heptares, Steinmetz Building, Granta Park, Cambridge, CB21 6DG, UK.
| | - Andrew B Tobin
- The Centre for Translational Pharmacology, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK.
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10
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Wu Y, Zeng L, Zhao S. Ligands of Adrenergic Receptors: A Structural Point of View. Biomolecules 2021; 11:biom11070936. [PMID: 34202543 PMCID: PMC8301793 DOI: 10.3390/biom11070936] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/09/2021] [Accepted: 06/12/2021] [Indexed: 01/14/2023] Open
Abstract
Adrenergic receptors are G protein-coupled receptors for epinephrine and norepinephrine. They are targets of many drugs for various conditions, including treatment of hypertension, hypotension, and asthma. Adrenergic receptors are intensively studied in structural biology, displayed for binding poses of different types of ligands. Here, we summarized molecular mechanisms of ligand recognition and receptor activation exhibited by structure. We also reviewed recent advances in structure-based ligand discovery against adrenergic receptors.
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Affiliation(s)
- Yiran Wu
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; (Y.W.); (L.Z.)
| | - Liting Zeng
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; (Y.W.); (L.Z.)
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Suwen Zhao
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; (Y.W.); (L.Z.)
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- Correspondence:
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11
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CAVIAR: a method for automatic cavity detection, description and decomposition into subcavities. J Comput Aided Mol Des 2021; 35:737-750. [PMID: 34050420 DOI: 10.1007/s10822-021-00390-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/11/2021] [Indexed: 10/21/2022]
Abstract
The accurate description of protein binding sites is essential to the determination of similarity and the application of machine learning methods to relate the binding sites to observed functions. This work describes CAVIAR, a new open source tool for generating descriptors for binding sites, using protein structures in PDB and mmCIF format as well as trajectory frames from molecular dynamics simulations as input. The applicability of CAVIAR descriptors is showcased by computing machine learning predictions of binding site ligandability. The method can also automatically assign subcavities, even in the absence of a bound ligand. The defined subpockets mimic the empirical definitions used in medicinal chemistry projects. It is shown that the experimental binding affinity scales relatively well with the number of subcavities filled by the ligand, with compounds binding to more than three subcavities having nanomolar or better affinities to the target. The CAVIAR descriptors and methods can be used in any machine learning-based investigations of problems involving binding sites, from protein engineering to hit identification. The full software code is available on GitHub and a conda package is hosted on Anaconda cloud.
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12
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Yang D, Zhou Q, Labroska V, Qin S, Darbalaei S, Wu Y, Yuliantie E, Xie L, Tao H, Cheng J, Liu Q, Zhao S, Shui W, Jiang Y, Wang MW. G protein-coupled receptors: structure- and function-based drug discovery. Signal Transduct Target Ther 2021; 6:7. [PMID: 33414387 PMCID: PMC7790836 DOI: 10.1038/s41392-020-00435-w] [Citation(s) in RCA: 208] [Impact Index Per Article: 69.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/30/2020] [Accepted: 12/05/2020] [Indexed: 02/08/2023] Open
Abstract
As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.
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Affiliation(s)
- Dehua Yang
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China
| | - Qingtong Zhou
- School of Basic Medical Sciences, Fudan University, 200032, Shanghai, China
| | - Viktorija Labroska
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Shanshan Qin
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Sanaz Darbalaei
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yiran Wu
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Elita Yuliantie
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Linshan Xie
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Houchao Tao
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Jianjun Cheng
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China
| | - Qing Liu
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China
| | - Suwen Zhao
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, 201210, Shanghai, China. .,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China.
| | - Yi Jiang
- The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China.
| | - Ming-Wei Wang
- The National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China. .,The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 201203, Shanghai, China. .,School of Basic Medical Sciences, Fudan University, 200032, Shanghai, China. .,University of Chinese Academy of Sciences, 100049, Beijing, China. .,School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, China. .,School of Pharmacy, Fudan University, 201203, Shanghai, China.
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13
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Michel MC. α 1-adrenoceptor activity of β-adrenoceptor ligands - An expected drug property with limited clinical relevance. Eur J Pharmacol 2020; 889:173632. [PMID: 33038419 DOI: 10.1016/j.ejphar.2020.173632] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 09/11/2020] [Accepted: 10/02/2020] [Indexed: 12/19/2022]
Abstract
Many β-adrenoceptor agonists and antagonists including several clinically used drugs have been reported to also exhibit binding to α1-adrenoceptors. Such promiscuity within the adrenoceptor family appears to occur more often than off-target effects of drugs in general. It should not be considered surprising based on the amino acid homology among the nine adrenoceptor subtypes including the counter-ions for binding the endogenous catecholamines. When β-adrenoceptor ligands also bind to α1-adrenoceptors, they almost always act as antagonists, regardless of being agonists or antagonists at the β-adrenoceptor. The α1-adrenoceptor affinity of β-adrenoceptor ligands in most cases is at least one, and often more log units lower than at their cognate receptor. Consistent evidence from multiple investigators indicates that β-adrenoceptor ligands relatively have the highest affinity for α1A- and lowest for α1B-adrenoceptors. While promiscuity among adrenoceptor subtypes causes misleading interpretation of experimental in vitro data, it is proposed based on the law of mass action that α1-adrenoceptor binding of β-adrenoceptor ligands rarely contributes to the clinical profile of such drugs, particularly if they are agonists at the β-adrenoceptor.
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Affiliation(s)
- Martin C Michel
- Dept. of Pharmacology, Johannes Gutenberg University, Universitätsmedizin Main, Langenbeckstr. 1, 55131, Mainz, Germany.
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14
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A Systematic Review of Inverse Agonism at Adrenoceptor Subtypes. Cells 2020; 9:cells9091923. [PMID: 32825009 PMCID: PMC7564766 DOI: 10.3390/cells9091923] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 08/16/2020] [Accepted: 08/18/2020] [Indexed: 12/18/2022] Open
Abstract
As many, if not most, ligands at G protein-coupled receptor antagonists are inverse agonists, we systematically reviewed inverse agonism at the nine adrenoceptor subtypes. Except for β3-adrenoceptors, inverse agonism has been reported for each of the adrenoceptor subtypes, most often for β2-adrenoceptors, including endogenously expressed receptors in human tissues. As with other receptors, the detection and degree of inverse agonism depend on the cells and tissues under investigation, i.e., they are greatest when the model has a high intrinsic tone/constitutive activity for the response being studied. Accordingly, they may differ between parts of a tissue, for instance, atria vs. ventricles of the heart, and within a cell type, between cellular responses. The basal tone of endogenously expressed receptors is often low, leading to less consistent detection and a lesser extent of observed inverse agonism. Extent inverse agonism depends on specific molecular properties of a compound, but inverse agonism appears to be more common in certain chemical classes. While inverse agonism is a fascinating facet in attempts to mechanistically understand observed drug effects, we are skeptical whether an a priori definition of the extent of inverse agonism in the target product profile of a developmental candidate is a meaningful option in drug discovery and development.
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15
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Li Y, Sun Y, Song Y, Dai D, Zhao Z, Zhang Q, Zhong W, Hu LA, Ma Y, Li X, Wang R. Fragment-Based Computational Method for Designing GPCR Ligands. J Chem Inf Model 2019; 60:4339-4349. [PMID: 31652060 DOI: 10.1021/acs.jcim.9b00699] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors, which is arguably the most important family of drug target. With the technology breakthroughs in X-ray crystallography and cryo-electron microscopy, more than 300 GPCR-ligand complex structures have been publicly reported since 2007, covering about 60 unique GPCRs. Such abundant structural information certainly will facilitate the structure-based drug design by targeting GPCRs. In this study, we have developed a fragment-based computational method for designing novel GPCR ligands. We first extracted the characteristic interaction patterns (CIPs) on the binding interfaces between GPCRs and their ligands. The CIPs were used as queries to search the chemical fragments derived from GPCR ligands, which were required to form similar interaction patterns with GPCR. Then, the selected chemical fragments were assembled into complete molecules by using the AutoT&T2 software. In this work, we chose β-adrenergic receptor (β-AR) and muscarinic acetylcholine receptor (mAChR) as the targets to validate this method. Based on the designs suggested by our method, samples of 63 compounds were purchased and tested in a cell-based functional assay. A total of 15 and 22 compounds were identified as active antagonists for β2-AR and mAChR M1, respectively. Molecular dynamics simulations and binding free energy analysis were performed to explore the key interactions (e.g., hydrogen bonds and π-π interactions) between those active compounds and their target GPCRs. In summary, our work presents a useful approach to the de novo design of GPCR ligands based on the relevant 3D structural information.
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Affiliation(s)
- Yan Li
- State Key Laboratory of Bioorganic and Natural Products Chemistry, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China.,Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, People's Republic of China
| | - Yaping Sun
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Yunpeng Song
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Dongcheng Dai
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Zhixiong Zhao
- State Key Laboratory of Bioorganic and Natural Products Chemistry, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China
| | - Qing Zhang
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Wenge Zhong
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Liaoyuan A Hu
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Yingli Ma
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Xun Li
- Amgen Asia R&D Center, Amgen Biopharmaceutical R&D (Shanghai) Co., Ltd., Shanghai 201210, People's Republic of China
| | - Renxiao Wang
- State Key Laboratory of Bioorganic and Natural Products Chemistry, Center for Excellence in Molecular Synthesis, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China.,Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, People's Republic of China.,Shanxi Key Laboratory of Innovative Drugs for the Treatment of Serious Diseases Basing on Chronic Inflammation, College of Traditional Chinese Medicine, Shanxi University of Chinese Medicine, Taiyuan, Shanxi 030619, People's Republic of China
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16
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Arimont M, Hoffmann C, de Graaf C, Leurs R. Chemokine Receptor Crystal Structures: What Can Be Learned from Them? Mol Pharmacol 2019; 96:765-777. [PMID: 31266800 DOI: 10.1124/mol.119.117168] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 06/21/2019] [Indexed: 12/18/2022] Open
Abstract
Chemokine receptors belong to the class A of G protein-coupled receptors (GPCRs) and are implicated in a wide variety of physiologic functions, mostly related to the homeostasis of the immune system. Chemokine receptors are also involved in multiple pathologic processes, including immune and autoimmune diseases, as well as cancer. Hence, several members of this GPCR subfamily are considered to be very relevant therapeutic targets. Since drug discovery efforts can be significantly reinforced by the availability of crystal structures, substantial efforts in the area of chemokine receptor structural biology could dramatically increase the outcome of drug discovery campaigns. This short review summarizes the available data on chemokine receptor crystal structures, discusses the numerous applications from chemokine receptor structures that can enhance the daily work of molecular pharmacologists, and describes the challenges and pitfalls to consider when relying on crystal structures for further research applications. SIGNIFICANCE STATEMENT: This short review summarizes the available data on chemokine receptor crystal structures, discusses the numerous applications from chemokine receptor structures that can enhance the daily work of molecular pharmacologists, and describes the challenges and pitfalls to consider when relying on crystal structures for further research applications.
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Affiliation(s)
- Marta Arimont
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Carsten Hoffmann
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Chris de Graaf
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Rob Leurs
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
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17
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Dilcan G, Doruker P, Akten ED. Ligand-binding affinity of alternative conformers of human β 2 -adrenergic receptor in the presence of intracellular loop 3 (ICL3) and their potential use in virtual screening studies. Chem Biol Drug Des 2019; 93:883-899. [PMID: 30637937 DOI: 10.1111/cbdd.13478] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 11/14/2018] [Accepted: 11/24/2018] [Indexed: 12/25/2022]
Abstract
This study investigates the structural distinctiveness of orthosteric ligand-binding sites of several human β2 adrenergic receptor (β2 -AR) conformations that have been obtained from a set of independent molecular dynamics (MD) simulations in the presence of intracellular loop 3 (ICL3). A docking protocol was established in order to classify each receptor conformation via its binding affinity to selected ligands with known efficacy. This work's main goal was to reveal many subtle features of the ligand-binding site, presenting alternative conformations, which might be considered as either active- or inactive-like but mostly specific for that ligand. Agonists, inverse agonists, and antagonists were docked to each MD conformer with distinct binding pockets, using different docking tools and scoring functions. Mostly favored receptor conformation persistently observed in all docking/scoring evaluations was classified as active or inactive based on the type of ligand's biological effect. Classified MD conformers were further tested for their ability to discriminate agonists from inverse agonists/antagonists, and several conformers were proposed as important targets to be used in virtual screening experiments that were often limited to a single X-ray structure.
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Affiliation(s)
- Gonca Dilcan
- Graduate School of Computational Biology and Bioinformatics, Kadir Has University, Istanbul, Turkey
| | - Pemra Doruker
- Department of Chemical Engineering and Polymer Research Center, Bogazici University, Istanbul, Turkey
| | - Ebru Demet Akten
- Department of Bioinformatics and Genetics, Faculty of Natural Sciences and Engineering, Kadir Has University, Istanbul, Turkey
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18
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Vass M, Podlewska S, de Esch IJP, Bojarski AJ, Leurs R, Kooistra AJ, de Graaf C. Aminergic GPCR-Ligand Interactions: A Chemical and Structural Map of Receptor Mutation Data. J Med Chem 2018; 62:3784-3839. [PMID: 30351004 DOI: 10.1021/acs.jmedchem.8b00836] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The aminergic family of G protein-coupled receptors (GPCRs) plays an important role in various diseases and represents a major drug discovery target class. Structure determination of all major aminergic subfamilies has enabled structure-based ligand design for these receptors. Site-directed mutagenesis data provides an invaluable complementary source of information for elucidating the structural determinants of binding of different ligand chemotypes. The current study provides a comparative analysis of 6692 mutation data points on 34 aminergic GPCR subtypes, covering the chemical space of 540 unique ligands from mutagenesis experiments and information from experimentally determined structures of 52 distinct aminergic receptor-ligand complexes. The integrated analysis enables detailed investigation of structural receptor-ligand interactions and assessment of the transferability of combined binding mode and mutation data across ligand chemotypes and receptor subtypes. An overview is provided of the possibilities and limitations of using mutation data to guide the design of novel aminergic receptor ligands.
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Affiliation(s)
- Márton Vass
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS) , VU University Amsterdam , 1081HZ Amsterdam , The Netherlands
| | - Sabina Podlewska
- Department of Medicinal Chemistry, Institute of Pharmacology , Polish Academy of Sciences , Smętna 12 , PL31-343 Kraków , Poland
| | - Iwan J P de Esch
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS) , VU University Amsterdam , 1081HZ Amsterdam , The Netherlands
| | - Andrzej J Bojarski
- Department of Medicinal Chemistry, Institute of Pharmacology , Polish Academy of Sciences , Smętna 12 , PL31-343 Kraków , Poland
| | - Rob Leurs
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS) , VU University Amsterdam , 1081HZ Amsterdam , The Netherlands
| | - Albert J Kooistra
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS) , VU University Amsterdam , 1081HZ Amsterdam , The Netherlands.,Department of Drug Design and Pharmacology , University of Copenhagen , Universitetsparken 2 , 2100 Copenhagen , Denmark
| | - Chris de Graaf
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS) , VU University Amsterdam , 1081HZ Amsterdam , The Netherlands.,Sosei Heptares , Steinmetz Building, Granta Park, Great Abington , Cambridge CB21 6DG , U.K
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19
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Ehrt C, Brinkjost T, Koch O. A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs). PLoS Comput Biol 2018; 14:e1006483. [PMID: 30408032 PMCID: PMC6224041 DOI: 10.1371/journal.pcbi.1006483] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 09/02/2018] [Indexed: 11/24/2022] Open
Abstract
The automated comparison of protein-ligand binding sites provides useful insights into yet unexplored site similarities. Various stages of computational and chemical biology research can benefit from this knowledge. The search for putative off-targets and the establishment of polypharmacological effects by comparing binding sites led to promising results for numerous projects. Although many cavity comparison methods are available, a comprehensive analysis to guide the choice of a tool for a specific application is wanting. Moreover, the broad variety of binding site modeling approaches, comparison algorithms, and scoring metrics impedes this choice. Herein, we aim to elucidate strengths and weaknesses of binding site comparison methodologies. A detailed benchmark study is the only possibility to rationalize the selection of appropriate tools for different scenarios. Specific evaluation data sets were developed to shed light on multiple aspects of binding site comparison. An assembly of all applied benchmark sets (ProSPECCTs–Protein Site Pairs for the Evaluation of Cavity Comparison Tools) is made available for the evaluation and optimization of further and still emerging methods. The results indicate the importance of such analyses to facilitate the choice of a methodology that complies with the requirements of a specific scientific challenge. Binding site similarities are useful in the context of promiscuity prediction, drug repurposing, the analysis of protein-ligand and protein-protein complexes, function prediction, and further fields of general interest in chemical biology and biochemistry. Many years of research have led to the development of a multitude of methods for binding site analysis and comparison. On the one hand, their availability supports research. On the other hand, the huge number of methods hampers the efficient selection of a specific tool. Our research is dedicated to the analysis of different cavity comparison tools. We use several binding site data sets to establish guidelines which can be applied to ensure a successful application of comparison methods by circumventing potential pitfalls.
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Affiliation(s)
- Christiane Ehrt
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
| | - Tobias Brinkjost
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
- Department of Computer Science, TU Dortmund University, Dortmund, Germany
| | - Oliver Koch
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
- * E-mail: ,
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20
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Miszta P, Jakowiecki J, Rutkowska E, Turant M, Latek D, Filipek S. Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists. Methods Mol Biol 2018; 1705:265-296. [PMID: 29188567 DOI: 10.1007/978-1-4939-7465-8_12] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Predicting the functional preferences of the ligands was always a highly demanding task, much harder that predicting whether a ligand can bind to the receptor. This is because of significant similarities of agonists, antagonists and inverse agonists which are binding usually in the same binding site of the receptor and only small structural changes can push receptor toward a particular activation state. For G protein-coupled receptors, due to a large progress in crystallization techniques and also in receptor thermal stabilization, it was possible to obtain a large number of high-quality structures of complexes of these receptors with agonists and non-agonists. Additionally, the long-time-scale molecular dynamics simulations revealed how the activation processes of GPCRs can take place. Using both theoretical and experimental knowledge it was possible to employ many clever and sophisticated methods which can help to differentiate agonists and non-agonists, so one can interconvert them in search of the optimal drug.
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Affiliation(s)
- Przemysław Miszta
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Jakub Jakowiecki
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Ewelina Rutkowska
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Maria Turant
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Dorota Latek
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Sławomir Filipek
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland.
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21
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Vass M, Kooistra AJ, Verhoeven S, Gloriam D, de Esch IJP, de Graaf C. A Structural Framework for GPCR Chemogenomics: What's In a Residue Number? Methods Mol Biol 2018; 1705:73-113. [PMID: 29188559 DOI: 10.1007/978-1-4939-7465-8_4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The recent surge of crystal structures of G protein-coupled receptors (GPCRs), as well as comprehensive collections of sequence, structural, ligand bioactivity, and mutation data, has enabled the development of integrated chemogenomics workflows for this important target family. This chapter will focus on cross-family and cross-class studies of GPCRs that have pinpointed the need for, and the implementation of, a generic numbering scheme for referring to specific structural elements of GPCRs. Sequence- and structure-based numbering schemes for different receptor classes will be introduced and the remaining caveats will be discussed. The use of these numbering schemes has facilitated many chemogenomics studies such as consensus binding site definition, binding site comparison, ligand repurposing (e.g. for orphan receptors), sequence-based pharmacophore generation for homology modeling or virtual screening, and class-wide chemogenomics studies of GPCRs.
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Affiliation(s)
- Márton Vass
- Department of Medicinal Chemistry, Amsterdam Institute for Molecules Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands
| | - Albert J Kooistra
- Department of Medicinal Chemistry, Amsterdam Institute for Molecules Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands
- Centre for Molecular and Biomolecular Informatics (CMBI), Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands
| | - Stefan Verhoeven
- Netherlands eScience Center, 1098 XG, Amsterdam, The Netherlands
| | - David Gloriam
- Department of Drug Design and Pharmacology, University of Copenhagen, 2100, Copenhagen, Denmark
| | - Iwan J P de Esch
- Department of Medicinal Chemistry, Amsterdam Institute for Molecules Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands
| | - Chris de Graaf
- Department of Medicinal Chemistry, Amsterdam Institute for Molecules Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HV, Amsterdam, The Netherlands.
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22
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Liang T, Yuan Y, Wang R, Guo Y, Li M, Pu X, Li C. Structural Features and Ligand Selectivity for 10 Intermediates in the Activation Process of β 2-Adrenergic Receptor. ACS OMEGA 2017; 2:8557-8567. [PMID: 30023586 PMCID: PMC6045391 DOI: 10.1021/acsomega.7b01031] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 09/14/2017] [Indexed: 06/08/2023]
Abstract
It has already been suggested by researchers that there should be multiple intermediate states in the activation process for G-protein-coupled receptors (GPCRs). However, the intermediate states are very short-lived and hardly captured by the experiments, leading to very limited understanding of their structural features and drug efficacies. In this work, a novel joint strategy of targeted molecular dynamics simulation, conventional molecular dynamics simulation, and virtual screening is developed to address the problems. The results from 10 intermediate conformations obtained from the work reveal that the ligand pocket is very unstable and fluctuates between the inactive state and the active one in the case of ligand-free, in particular for ECL2 as a gate-keeper of the ligand-binding. The ligand-binding site could be stable in the active state with a small volume and a completely closed ECL2, only when the G-protein-binding region is fully activated. In addition, the activations of the ligand-binding pocket and G-protein-binding site are relatively independent and exhibit a loose allosteric coupling, which contributes to the existence of multiple intermediate conformations. Interestingly, the screening performance of the agonists does not increase on increasing the overall activity of the intermediate state, but is dependent on the activated extent of the ligand pocket. The receptor is prone to bind the agonist when closing ECL2 and reducing the ligand-binding pocket volume, whereas it is more favorable for binding the antagonist when opening ECL2 and increasing the pocket volume. These observations added to previous studies could help us better understand the activation mechanism of GPCRs and provide valuable information for drug design.
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Affiliation(s)
- Tao Liang
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
| | - Yuan Yuan
- College
of Management, Southwest University for
Nationalities, No. 16 South Section 4, Yihuan Road, Chengdu 610041, People’s Republic
of China
| | - Ran Wang
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
| | - Yanzhi Guo
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
| | - Menglong Li
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
| | - Xuemei Pu
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
| | - Chuan Li
- College
of Chemistry and College of Computer Science, Sichuan University, No. 29 Jiuyanqiao Wangjiang Road, Chengdu 610064, People’s Republic
of China
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23
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Cross JB. Methods for Virtual Screening of GPCR Targets: Approaches and Challenges. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2017; 1705:233-264. [PMID: 29188566 DOI: 10.1007/978-1-4939-7465-8_11] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Virtual screening (VS) has become an integral part of the drug discovery process and is a valuable tool for finding novel chemical starting points for GPCR targets. Ligand-based VS makes use of biochemical data for known, active compounds and has been applied successfully to many diverse GPCRs. Recent progress in GPCR X-ray crystallography has made it possible to incorporate detailed structural information into the VS process. This chapter outlines the latest VS techniques along with examples that highlight successful applications of these methods. Best practices for increasing the likelihood of VS success, as well as ongoing challenges, are also discussed.
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Affiliation(s)
- Jason B Cross
- University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA.
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24
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Wolf S, Jovancevic N, Gelis L, Pietsch S, Hatt H, Gerwert K. Dynamical Binding Modes Determine Agonistic and Antagonistic Ligand Effects in the Prostate-Specific G-Protein Coupled Receptor (PSGR). Sci Rep 2017; 7:16007. [PMID: 29167480 PMCID: PMC5700038 DOI: 10.1038/s41598-017-16001-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 11/03/2017] [Indexed: 01/14/2023] Open
Abstract
We analysed the ligand-based activation mechanism of the prostate-specific G-protein coupled receptor (PSGR), which is an olfactory receptor that mediates cellular growth in prostate cancer cells. Furthermore, it is an olfactory receptor with a known chemically near identic antagonist/agonist pair, α- and β-ionone. Using a combined theoretical and experimental approach, we propose that this receptor is activated by a ligand-induced rearrangement of a protein-internal hydrogen bond network. Surprisingly, this rearrangement is not induced by interaction of the ligand with the network, but by dynamic van der Waals contacts of the ligand with the involved amino acid side chains, altering their conformations and intraprotein connectivity. Ligand recognition in this GPCR is therefore highly stereo selective, but seemingly lacks any ligand recognition via polar contacts. A putative olfactory receptor-based drug design scheme will have to take this unique mode of protein/ligand action into account.
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Affiliation(s)
- Steffen Wolf
- Department of Biophysics, ND 04 North, Ruhr-University Bochum, 44780, Bochum, Germany.
- Department of Biophysics, CAS-MPG Partner Institute for Computational Biology, Key Laboratory of Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 200031, Shanghai, P.R. China.
| | - Nikolina Jovancevic
- Department of Cellphysiology, ND 4, Ruhr-University Bochum, 44780, Bochum, Germany
| | - Lian Gelis
- Department of Cellphysiology, ND 4, Ruhr-University Bochum, 44780, Bochum, Germany
| | - Sebastian Pietsch
- Department of Biophysics, ND 04 North, Ruhr-University Bochum, 44780, Bochum, Germany
| | - Hanns Hatt
- Department of Cellphysiology, ND 4, Ruhr-University Bochum, 44780, Bochum, Germany
| | - Klaus Gerwert
- Department of Biophysics, ND 04 North, Ruhr-University Bochum, 44780, Bochum, Germany
- Department of Biophysics, CAS-MPG Partner Institute for Computational Biology, Key Laboratory of Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 200031, Shanghai, P.R. China
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25
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Coudrat T, Simms J, Christopoulos A, Wootten D, Sexton PM. Improving virtual screening of G protein-coupled receptors via ligand-directed modeling. PLoS Comput Biol 2017; 13:e1005819. [PMID: 29131821 PMCID: PMC5708846 DOI: 10.1371/journal.pcbi.1005819] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 11/30/2017] [Accepted: 10/12/2017] [Indexed: 11/22/2022] Open
Abstract
G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state. G protein-coupled receptors (GPCRs) are a major target for drug discovery. These receptors are highly dynamic membrane proteins, and have had limited tractability using with biophysical screens that are widely adopted for globular protein targets. Thus, structure-based virtual screening (SBVS) holds great promise as a complement to physical screening for rational design of novel drugs. Indeed, the increasing number of atomic-detail GPCR X-ray crystal structures has coincided with an increase in prospective SBVS studies that have identified novel compounds. However, experimentally solved GPCR structures do not meet the full demand for SBVS, as the GPCR structural landscape is incomplete, lacking both in coverage of available GPCRs, and diversity in both receptor conformations and the chemistry of co-crystalised ligands. Here we present a novel computational GPCR binding pocket refinement method that can generate predictive GPCR/ligand complexes with improved SBVS performance. This ligand-directed modeling workflow uses parallel processing and efficient algorithms to search the GPCR/ligand conformational space faster and more efficiently than the widely used protein refinement method molecular dynamics. In this study, the resulting models are evaluated both structurally, and in retrospective SBVS. We demonstrate improved performance of refined models over their starting structures in the majority of our test cases.
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Affiliation(s)
- Thomas Coudrat
- Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - John Simms
- School of Life and Health Sciences, Aston University, Birmingham, United Kingdom
| | - Arthur Christopoulos
- Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Denise Wootten
- Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- * E-mail: (DW); (PMS)
| | - Patrick M. Sexton
- Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
- * E-mail: (DW); (PMS)
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26
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Männel B, Jaiteh M, Zeifman A, Randakova A, Möller D, Hübner H, Gmeiner P, Carlsson J. Structure-Guided Screening for Functionally Selective D 2 Dopamine Receptor Ligands from a Virtual Chemical Library. ACS Chem Biol 2017; 12:2652-2661. [PMID: 28846380 DOI: 10.1021/acschembio.7b00493] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Functionally selective ligands stabilize conformations of G protein-coupled receptors (GPCRs) that induce a preference for signaling via a subset of the intracellular pathways activated by the endogenous agonists. The possibility to fine-tune the functional activity of a receptor provides opportunities to develop drugs that selectively signal via pathways associated with a therapeutic effect and avoid those causing side effects. Animal studies have indicated that ligands displaying functional selectivity at the D2 dopamine receptor (D2R) could be safer and more efficacious drugs against neuropsychiatric diseases. In this work, computational design of functionally selective D2R ligands was explored using structure-based virtual screening. Molecular docking of known functionally selective ligands to a D2R homology model indicated that such compounds were anchored by interactions with the orthosteric site and extended into a common secondary pocket. A tailored virtual library with close to 13 000 compounds bearing 2,3-dichlorophenylpiperazine, a privileged orthosteric scaffold, connected to diverse chemical moieties via a linker was docked to the D2R model. Eighteen top-ranked compounds that occupied both the orthosteric and allosteric site were synthesized, leading to the discovery of 16 partial agonists. A majority of the ligands had comparable maximum effects in the G protein and β-arrestin recruitment assays, but a subset displayed preference for a single pathway. In particular, compound 4 stimulated β-arrestin recruitment (EC50 = 320 nM, Emax = 16%) but had no detectable G protein signaling. The use of structure-based screening and virtual libraries to discover GPCR ligands with tailored functional properties will be discussed.
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Affiliation(s)
- Barbara Männel
- Department
of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University, Schuhstraße 19, 91052 Erlangen, Germany
| | - Mariama Jaiteh
- Science
for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, BMC, Box 596, SE-751 24 Uppsala, Sweden
| | - Alexey Zeifman
- Science
for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, BMC, Box 596, SE-751 24 Uppsala, Sweden
| | - Alena Randakova
- Department
of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University, Schuhstraße 19, 91052 Erlangen, Germany
| | - Dorothee Möller
- Department
of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University, Schuhstraße 19, 91052 Erlangen, Germany
| | - Harald Hübner
- Department
of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University, Schuhstraße 19, 91052 Erlangen, Germany
| | - Peter Gmeiner
- Department
of Chemistry and Pharmacy, Medicinal Chemistry, Friedrich-Alexander University, Schuhstraße 19, 91052 Erlangen, Germany
| | - Jens Carlsson
- Science
for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, BMC, Box 596, SE-751 24 Uppsala, Sweden
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27
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Coudrat T, Christopoulos A, Sexton PM, Wootten D. Structural features embedded in G protein-coupled receptor co-crystal structures are key to their success in virtual screening. PLoS One 2017; 12:e0174719. [PMID: 28380046 PMCID: PMC5381884 DOI: 10.1371/journal.pone.0174719] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Accepted: 03/14/2017] [Indexed: 11/25/2022] Open
Abstract
Structure based drug discovery on GPCRs harness atomic detail X-ray binding pockets and large libraries of potential drug lead candidates in virtual screening (VS) to identify novel lead candidates. Relatively small conformational differences between such binding pockets can be critical to the success of VS. Retrospective VS on GPCR/ligand co-crystal structures revealed stark differences in the ability of different structures to identify known ligands, despite being co-crystallized with the same ligand. When using the OpenEye toolkit and the ICM modeling package, we identify criteria associated with the predictive power of binding pockets in VS that consists of a combination of ligand/receptor interaction pattern and predicted ligand/receptor interaction strength. These findings can guide the selection and refinement of GPCR binding pockets for use in SBDD programs and may also provide a potential framework for evaluating the ability of computational GPCR binding pocket refinement tools in improving the predictive power of binding pockets.
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Affiliation(s)
- Thomas Coudrat
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Royal Parade, Parkville, Victoria, Australia
| | - Arthur Christopoulos
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Royal Parade, Parkville, Victoria, Australia
| | - Patrick Michael Sexton
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Royal Parade, Parkville, Victoria, Australia
- * E-mail: (DW); (PMS)
| | - Denise Wootten
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Royal Parade, Parkville, Victoria, Australia
- * E-mail: (DW); (PMS)
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28
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Arimont M, Sun SL, Leurs R, Smit M, de Esch IJP, de Graaf C. Structural Analysis of Chemokine Receptor-Ligand Interactions. J Med Chem 2017; 60:4735-4779. [PMID: 28165741 PMCID: PMC5483895 DOI: 10.1021/acs.jmedchem.6b01309] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
![]()
This
review focuses on the construction and application of structural chemokine
receptor models for the elucidation of molecular determinants of chemokine
receptor modulation and the structure-based discovery and design of
chemokine receptor ligands. A comparative analysis of ligand binding
pockets in chemokine receptors is presented, including a detailed
description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures,
and their implication for modeling molecular interactions of chemokine
receptors with small-molecule ligands, peptide ligands, and large
antibodies and chemokines. These studies demonstrate how the integration
of new structural information on chemokine receptors with extensive
structure–activity relationship and site-directed mutagenesis
data facilitates the prediction of the structure of chemokine receptor–ligand
complexes that have not been crystallized. Finally, a review of structure-based
ligand discovery and design studies based on chemokine receptor crystal
structures and homology models illustrates the possibilities and challenges
to find novel ligands for chemokine receptors.
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Affiliation(s)
- Marta Arimont
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Shan-Liang Sun
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Rob Leurs
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Martine Smit
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Iwan J P de Esch
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Chris de Graaf
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute of Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam , De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
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29
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Lenselink EB, Jespers W, van Vlijmen HWT, IJzerman AP, van Westen GJP. Interacting with GPCRs: Using Interaction Fingerprints for Virtual Screening. J Chem Inf Model 2016; 56:2053-2060. [PMID: 27626908 DOI: 10.1021/acs.jcim.6b00314] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The expanding number of crystal structures of G protein-coupled receptors (GPCRs) has increased the knowledge on receptor function and their ability to recognize ligands. Although structure-based virtual screening has been quite successful on GPCRs, scores obtained by docking are typically not indicative for ligand affinity. Methods capturing interactions between protein and ligand in a more explicit manner, such as interaction fingerprints (IFPs), have been applied as an addition or alternative to docking. Originally IFPs captured the interactions of amino acid residues with ligands with specific definitions for the various interaction types. More complex IFPs now capture atom-atom interactions, such as in SYBYL, or fragment-fragment co-occurrences such as in SPLIF. Overall, most of the IFPs have been studied in comparison with docking in retrospective studies. For GPCRs it remains unclear which IFP should be used, if at all, and in what manner. Thus, the performance between five different IFPs was compared on five different representative GPCRs, including several extensions of the original implementations,. Results show that the more detailed IFPs, SYBYL and SPLIF, perform better than the other IFPs (Deng, Credo, and Elements). SPLIF was further tuned based on the number of poses, fingerprint similarity coefficient, and using an ensemble of structures. Enrichments were obtained that were significantly higher than initial enrichments and those obtained by 2D-similarity. With the increase in available crystal structures for GPCRs, and given that IFPs such as SPLIF enhance enrichment in virtual screens, it is anticipated that IFPs will be used in conjunction with docking, especially for GPCRs with a large binding pocket.
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Affiliation(s)
- Eelke B Lenselink
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University , 2333 CC Leiden, The Netherlands
| | - Willem Jespers
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University , 2333 CC Leiden, The Netherlands
| | - Herman W T van Vlijmen
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University , 2333 CC Leiden, The Netherlands
| | - Adriaan P IJzerman
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University , 2333 CC Leiden, The Netherlands
| | - Gerard J P van Westen
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University , 2333 CC Leiden, The Netherlands
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30
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Kuhne S, Kooistra AJ, Bosma R, Bortolato A, Wijtmans M, Vischer HF, Mason JS, de Graaf C, de Esch IJP, Leurs R. Identification of Ligand Binding Hot Spots of the Histamine H1 Receptor following Structure-Based Fragment Optimization. J Med Chem 2016; 59:9047-9061. [DOI: 10.1021/acs.jmedchem.6b00981] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Sebastiaan Kuhne
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Albert J. Kooistra
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Reggie Bosma
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Andrea Bortolato
- Heptares Therapeutics Ltd., BioPark,
Broadwater Road, Welwyn Garden City, Herts AL7 3AX, U.K
| | - Maikel Wijtmans
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Henry F. Vischer
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Jonathan S. Mason
- Heptares Therapeutics Ltd., BioPark,
Broadwater Road, Welwyn Garden City, Herts AL7 3AX, U.K
| | - Chris de Graaf
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Iwan J. P. de Esch
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
| | - Rob Leurs
- Amsterdam
Institute for Molecules, Medicines and Systems (AIMMS), Division of
Medicinal Chemistry, Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands
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31
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Molecular interaction fingerprint approaches for GPCR drug discovery. Curr Opin Pharmacol 2016; 30:59-68. [PMID: 27479316 DOI: 10.1016/j.coph.2016.07.007] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2016] [Revised: 07/11/2016] [Accepted: 07/12/2016] [Indexed: 01/23/2023]
Abstract
Protein-ligand interaction fingerprints (IFPs) are binary 1D representations of the 3D structure of protein-ligand complexes encoding the presence or absence of specific interactions between the binding pocket amino acids and the ligand. Various implementations of IFPs have been developed and successfully applied for post-processing molecular docking results for G Protein-Coupled Receptor (GPCR) ligand binding mode prediction and virtual ligand screening. Novel interaction fingerprint methods enable structural chemogenomics and polypharmacology predictions by complementing the increasing amount of GPCR structural data. Machine learning methods are increasingly used to derive relationships between bioactivity data and fingerprint descriptors of chemical and structural information of binding sites, ligands, and protein-ligand interactions. Factors that influence the application of IFPs include structure preparation, binding site definition, fingerprint similarity assessment, and data processing and these factors pose challenges as well possibilities to optimize interaction fingerprint methods for GPCR drug discovery.
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32
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Function-specific virtual screening for GPCR ligands using a combined scoring method. Sci Rep 2016; 6:28288. [PMID: 27339552 PMCID: PMC4919634 DOI: 10.1038/srep28288] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2016] [Accepted: 05/26/2016] [Indexed: 12/20/2022] Open
Abstract
The ability of scoring functions to correctly select and rank docking poses of small molecules in protein binding sites is highly target dependent, which presents a challenge for structure-based drug discovery. Here we describe a virtual screening method that combines an energy-based docking scoring function with a molecular interaction fingerprint (IFP) to identify new ligands based on G protein-coupled receptor (GPCR) crystal structures. The consensus scoring method is prospectively evaluated by: 1) the discovery of chemically novel, fragment-like, high affinity histamine H1 receptor (H1R) antagonists/inverse agonists, 2) the selective structure-based identification of ß2-adrenoceptor (ß2R) agonists, and 3) the experimental validation and comparison of the combined and individual scoring approaches. Systematic retrospective virtual screening simulations allowed the definition of scoring cut-offs for the identification of H1R and ß2R ligands and the selection of an optimal ß-adrenoceptor crystal structure for the discrimination between ß2R agonists and antagonists. The consensus approach resulted in the experimental validation of 53% of the ß2R and 73% of the H1R virtual screening hits with up to nanomolar affinities and potencies. The selective identification of ß2R agonists shows the possibilities of structure-based prediction of GPCR ligand function by integrating protein-ligand binding mode information.
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Ehrt C, Brinkjost T, Koch O. Impact of Binding Site Comparisons on Medicinal Chemistry and Rational Molecular Design. J Med Chem 2016; 59:4121-51. [PMID: 27046190 DOI: 10.1021/acs.jmedchem.6b00078] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Modern rational drug design not only deals with the search for ligands binding to interesting and promising validated targets but also aims to identify the function and ligands of yet uncharacterized proteins having impact on different diseases. Additionally, it contributes to the design of inhibitors with distinct selectivity patterns and the prediction of possible off-target effects. The identification of similarities between binding sites of various proteins is a useful approach to cope with those challenges. The main scope of this perspective is to describe applications of different protein binding site comparison approaches to outline their applicability and impact on molecular design. The article deals with various substantial application domains and provides some outstanding examples to show how various binding site comparison methods can be applied to promote in silico drug design workflows. In addition, we will also briefly introduce the fundamental principles of different protein binding site comparison methods.
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Affiliation(s)
- Christiane Ehrt
- Faculty of Chemistry and Chemical Biology, TU Dortmund University , Otto-Hahn-Straße 6, 44227 Dortmund, Germany
| | - Tobias Brinkjost
- Faculty of Chemistry and Chemical Biology, TU Dortmund University , Otto-Hahn-Straße 6, 44227 Dortmund, Germany.,Department of Computer Science, TU Dortmund University , Otto-Hahn-Straße 14, 44224 Dortmund, Germany
| | - Oliver Koch
- Faculty of Chemistry and Chemical Biology, TU Dortmund University , Otto-Hahn-Straße 6, 44227 Dortmund, Germany
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34
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Drugging specific conformational states of GPCRs: challenges and opportunities for computational chemistry. Drug Discov Today 2016; 21:625-31. [DOI: 10.1016/j.drudis.2016.01.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Revised: 01/04/2016] [Accepted: 01/19/2016] [Indexed: 01/14/2023]
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35
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Kaczor AA, Silva AG, Loza MI, Kolb P, Castro M, Poso A. Structure-Based Virtual Screening for Dopamine D2Receptor Ligands as Potential Antipsychotics. ChemMedChem 2016; 11:718-29. [DOI: 10.1002/cmdc.201500599] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Revised: 01/06/2016] [Indexed: 02/04/2023]
Affiliation(s)
- Agnieszka A. Kaczor
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Lab; Faculty of Pharmacy with Division for Medical Analytics; Medical University of Lublin; 4A Chodźki St. 20059 Lublin Poland
- School of Pharmacy; University of Eastern Finland; Yliopistonranta 1, P.O. Box 1627 70211 Kuopio Finland
| | - Andrea G. Silva
- Department of Pharmacology; Universidade de Santiago de Compostela; Center for Research in Molecular Medicine and Chronic Diseases (CIMUS); Avda de Barcelona 15782 Santiago de Compostela Spain
| | - María I. Loza
- Department of Pharmacology; Universidade de Santiago de Compostela; Center for Research in Molecular Medicine and Chronic Diseases (CIMUS); Avda de Barcelona 15782 Santiago de Compostela Spain
| | - Peter Kolb
- Department of Pharmaceutical Chemistry; Philipps University Marburg; Marbacher Weg 6 35032 Marburg Germany
| | - Marián Castro
- Department of Pharmacology; Universidade de Santiago de Compostela; Center for Research in Molecular Medicine and Chronic Diseases (CIMUS); Avda de Barcelona 15782 Santiago de Compostela Spain
| | - Antti Poso
- School of Pharmacy; University of Eastern Finland; Yliopistonranta 1, P.O. Box 1627 70211 Kuopio Finland
- University Hospital Tübingen; Department of Internal Medicine I; Division of Translational Gastrointestinal Oncology; Otfried-Müller-Strasse 10 72076 Tübingen Germany
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