1
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Zhu H, Zheng X, Ou Y, Wang G, Qu L, Li Q, Zhao X, Zhao X. A universal method for surface-based binding assays by preparing immobilized β 2-adrenergic receptor stationary phase using solid binding peptide as a fusion tag. J Chromatogr A 2024; 1730:465037. [PMID: 38889580 DOI: 10.1016/j.chroma.2024.465037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 05/28/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024]
Abstract
Protein functionalized surface has the potential to develop new assays for determining the drug-like properties of potential compounds and discovering specific partners of G protein-coupled receptors (GPCRs). However, a universal method for purifying and immobilizing functional GPCRs has remained elusive. To this end, we developed a general and rapid way to purify and immobilize β2-adrenergic receptor (β2AR) by silicon-specific peptide. We screened CotB1p as a tag from six silica-binding peptides (minTBP-1, CotB1p, SB7, Car9, and Si4-1) by examining their affinity to macroporous silica gel. We investigated the adsorption and desorption of CotB1p-tagged β2-adrenoceptor (β2AR-CotB1p) under diverse conditions to propose a protocol for receptor purification and immobilization. Under optimized conditions, β2AR immobilization were achieved by directly immersing cell lysates harboring the receptor with silica gel, and the elution of the receptor without demonstratable contaminants was realized by including l-arginine/L-lysine in the elutes. This allows purification of the receptor from Escherichia coli (E.coli) lysates with a purity of 95 %. The immobilized receptor was utilized as a stationary phase to reveal the tag impact on ligand-binding outputs by comparing the CotB1p-strategy with a typical covalent method. The KAs of salbutamol, chlorprenaline, tulobuterol, and terbutaline on β2AR-CotB1p column were 1.26 × 106, 6.59 × 106, 7.90 × 106, and 8.97 × 105 M-1 respectively, which were two orders of magnitude higher than those on the Halo-β2AR column. The whole immobilization was accomplished within 30 min without the requirement of any special treatment, resulting in enhanced accuracy for determining receptor-ligand binding parameters. Taken together, CotB1p-mediated strategy is simple, rapid, and universal for purification or immobilization of unstable biomolecules like GPCRs for analytical and biological applications.
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Affiliation(s)
- Huiting Zhu
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Xinxin Zheng
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Yuanyuan Ou
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Ge Wang
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Lejing Qu
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Qian Li
- College of Life Sciences, Northwest University, Xi'an, 710069, China
| | - Xue Zhao
- College of Life Sciences, Northwest University, Xi'an, 710069, China.
| | - Xinfeng Zhao
- College of Life Sciences, Northwest University, Xi'an, 710069, China.
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2
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Comeo E, Goulding J, Lin CY, Groenen M, Woolard J, Kindon ND, Harwood CR, Platt S, Briddon SJ, Kilpatrick LE, Scammells PJ, Hill SJ, Kellam B. Ligand-Directed Labeling of the Adenosine A 1 Receptor in Living Cells. J Med Chem 2024; 67:12099-12117. [PMID: 38994645 DOI: 10.1021/acs.jmedchem.4c00835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
The study of protein function and dynamics in their native cellular environment is essential for progressing fundamental science. To overcome the requirement of genetic modification of the protein or the limitations of dissociable fluorescent ligands, ligand-directed (LD) chemistry has most recently emerged as a complementary, bioorthogonal approach for labeling native proteins. Here, we describe the rational design, development, and application of the first ligand-directed chemistry approach for labeling the A1AR in living cells. We pharmacologically demonstrate covalent labeling of A1AR expressed in living cells while the orthosteric binding site remains available. The probes were imaged using confocal microscopy and fluorescence correlation spectroscopy to study A1AR localization and dynamics in living cells. Additionally, the probes allowed visualization of the specific localization of A1ARs endogenously expressed in dorsal root ganglion (DRG) neurons. LD probes developed here hold promise for illuminating ligand-binding, receptor signaling, and trafficking of the A1AR in more physiologically relevant environments.
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Affiliation(s)
- Eleonora Comeo
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Joëlle Goulding
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Chia-Yang Lin
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Marleen Groenen
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Jeanette Woolard
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Nicholas D Kindon
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Clare R Harwood
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Simon Platt
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Stephen J Briddon
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Laura E Kilpatrick
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Peter J Scammells
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Stephen J Hill
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
| | - Barrie Kellam
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, U.K
- Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham and University of Nottingham, The Midlands NG7 2UH, U.K
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3
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Yang X, Zhou P, Shen S, Hu Q, Tian C, Xia A, Wang Y, Yang Z, Nan J, Zhou Y, Chen S, Tian X, Wu C, Lin G, Zhang L, Wang K, Zheng T, Zou J, Yan W, Shao Z, Yang S. Entropy drives the ligand recognition in G-protein-coupled receptor subtypes. Proc Natl Acad Sci U S A 2024; 121:e2401091121. [PMID: 39024109 PMCID: PMC11287286 DOI: 10.1073/pnas.2401091121] [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: 01/17/2024] [Accepted: 05/22/2024] [Indexed: 07/20/2024] Open
Abstract
Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.
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Affiliation(s)
- Xin Yang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Pei Zhou
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Siyuan Shen
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Qian Hu
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Chenyu Tian
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Anjie Xia
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- Department of Ophthalmology and Research Laboratory of Macular Disease, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Yifei Wang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Zhiqian Yang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Jinshan Nan
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Yangli Zhou
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Shasha Chen
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Xiaowen Tian
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Chao Wu
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Guifeng Lin
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Liting Zhang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Kexin Wang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Tao Zheng
- Engineering Research Center of Medical Information Technology, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Jun Zou
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Wei Yan
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
| | - Zhenhua Shao
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- Division of Nephrology and Kidney Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- Frontier Medical Center, Tianfu Jincheng Laboratory, Chengdu, Sichuan610212, China
| | - Shengyong Yang
- Department of Biotherapy, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- New Cornerstone Science Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan610041, China
- Frontier Medical Center, Tianfu Jincheng Laboratory, Chengdu, Sichuan610212, China
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4
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Tänzel V, Jäger M, Wolf S. Learning Protein-Ligand Unbinding Pathways via Single-Parameter Community Detection. J Chem Theory Comput 2024; 20:5058-5067. [PMID: 38865714 DOI: 10.1021/acs.jctc.4c00250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024]
Abstract
Understanding the dynamics of biomolecular complexes, e.g., of protein-ligand (un)binding, requires the comprehension of paths such systems take between metastable states. In MD simulations, paths are usually not observable per se, but they need to be inferred from simulation trajectories. Here, we present a novel approach to cluster trajectories based on a community detection algorithm that necessitates only the definition of a single parameter. The unbinding of the streptavidin-biotin complex is used as a benchmark system and the A2a adenosine receptor in complex with the inhibitor ZM241385 as an elaborate application. We demonstrate how such clusters of trajectories correspond to pathways and how the approach helps in the identification of reaction coordinates for a considered (un)binding process.
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Affiliation(s)
- Victor Tänzel
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
| | - Miriam Jäger
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
| | - Steffen Wolf
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Freiburg 79104, Germany
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5
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Zhang M, Chen T, Lu X, Lan X, Chen Z, Lu S. G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery. Signal Transduct Target Ther 2024; 9:88. [PMID: 38594257 PMCID: PMC11004190 DOI: 10.1038/s41392-024-01803-6] [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: 08/15/2023] [Revised: 02/19/2024] [Accepted: 03/13/2024] [Indexed: 04/11/2024] Open
Abstract
G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.
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Affiliation(s)
- Mingyang Zhang
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Peptide & Protein Drug Research Center, School of Pharmacy, Ningxia Medical University, Yinchuan, 750004, China
- Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ting Chen
- Department of Cardiology, Changzheng Hospital, Affiliated to Naval Medical University, Shanghai, 200003, China
| | - Xun Lu
- Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaobing Lan
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Peptide & Protein Drug Research Center, School of Pharmacy, Ningxia Medical University, Yinchuan, 750004, China
| | - Ziqiang Chen
- Department of Orthopedics, Changhai Hospital, Affiliated to Naval Medical University, Shanghai, 200433, China.
| | - Shaoyong Lu
- Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Peptide & Protein Drug Research Center, School of Pharmacy, Ningxia Medical University, Yinchuan, 750004, China.
- Medicinal Chemistry and Bioinformatics Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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6
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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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7
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Calderón JC, Plut E, Keller M, Cabrele C, Reiser O, Gervasio FL, Clark T. Extended Metadynamics Protocol for Binding/Unbinding Free Energies of Peptide Ligands to Class A G-Protein-Coupled Receptors. J Chem Inf Model 2024; 64:205-218. [PMID: 38150388 DOI: 10.1021/acs.jcim.3c01574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
A metadynamics protocol is presented to characterize the binding and unbinding of peptide ligands to class A G-protein-coupled receptors (GPCRs). The protocol expands on the one previously presented for binding and unbinding small-molecule ligands to class A GPCRs and accounts for the more demanding nature of the peptide binding-unbinding process. It applies to almost all class A GPCRs. Exemplary simulations are described for subtypes Y1R, Y2R, and Y4R of the neuropeptide Y receptor family, vasopressin binding to the vasopressin V2 receptor (V2R), and oxytocin binding to the oxytocin receptor (OTR). Binding free energies and the positions of alternative binding sites are presented and, where possible, compared with the experiment.
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Affiliation(s)
- Jacqueline C Calderón
- Computer-Chemistry-Center, Department of Chemistry and Pharmacy, Friedrich-Alexander-University Erlangen-Nuernberg, Naegelsbachstr. 25, Erlangen 91052, Germany
| | - Eva Plut
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, Regensburg 93040, Germany
| | - Max Keller
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, Regensburg D-93040, Germany
| | - Chiara Cabrele
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, Regensburg 93040, Germany
| | - Oliver Reiser
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, Regensburg 93040, Germany
| | | | - Timothy Clark
- Computer-Chemistry-Center, Department of Chemistry and Pharmacy, Friedrich-Alexander-University Erlangen-Nuernberg, Naegelsbachstr. 25, Erlangen 91052, Germany
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8
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Bobrovs R, Drunka L, Kanepe I, Jirgensons A, Caflisch A, Salvalaglio M, Jaudzems K. Exploring the Binding Pathway of Novel Nonpeptidomimetic Plasmepsin V Inhibitors. J Chem Inf Model 2023; 63:6890-6899. [PMID: 37801405 DOI: 10.1021/acs.jcim.3c00826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Predicting the interaction modes and binding affinities of virtual compound libraries is of great interest in drug development. It reduces the cost and time of lead compound identification and selection. Here we apply path-based metadynamics simulations to characterize the binding of potential inhibitors to the Plasmodium falciparum aspartic protease plasmepsin V (plm V), a validated antimalarial drug target that has a highly mobile binding site. The potential plm V binders were identified in a high-throughput virtual screening (HTVS) campaign and were experimentally verified in a fluorescence resonance energy transfer (FRET) assay. Our simulations allowed us to estimate compound binding energies and revealed relevant states along binding/unbinding pathways in atomistic resolution. We believe that the method described allows the prioritization of compounds for synthesis and enables rational structure-based drug design for targets that undergo considerable conformational changes upon inhibitor binding.
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Affiliation(s)
- Raitis Bobrovs
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Laura Drunka
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Iveta Kanepe
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Aigars Jirgensons
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Amedeo Caflisch
- Department of Biochemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Matteo Salvalaglio
- Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, United Kingdom
| | - Kristaps Jaudzems
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
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9
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Buigues P, Gehrke S, Badaoui M, Dudas B, Mandana G, Qi T, Bottegoni G, Rosta E. Investigating the Unbinding of Muscarinic Antagonists from the Muscarinic 3 Receptor. J Chem Theory Comput 2023; 19:5260-5272. [PMID: 37458730 PMCID: PMC10413856 DOI: 10.1021/acs.jctc.3c00023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Indexed: 08/09/2023]
Abstract
Patient symptom relief is often heavily influenced by the residence time of the inhibitor-target complex. For the human muscarinic receptor 3 (hMR3), tiotropium is a long-acting bronchodilator used in conditions such as asthma or chronic obstructive pulmonary disease (COPD). The mechanistic insights into this inhibitor remain unclear; specifically, the elucidation of the main factors determining the unbinding rates could help develop the next generation of antimuscarinic agents. Using our novel unbinding algorithm, we were able to investigate ligand dissociation from hMR3. The unbinding paths of tiotropium and two of its analogues, N-methylscopolamin and homatropine methylbromide, show a consistent qualitative mechanism and allow us to identify the structural bottleneck of the process. Furthermore, our machine learning-based analysis identified key roles of the ECL2/TM5 junction involved in the transition state. Additionally, our results point to relevant changes at the intracellular end of the TM6 helix leading to the ICL3 kinase domain, highlighting the closest residue L482. This residue is located right between two main protein binding sites involved in signal transduction for hMR3's activation and regulation. We also highlight key pharmacophores of tiotropium that play determining roles in the unbinding kinetics and could aid toward drug design and lead optimization.
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Affiliation(s)
- Pedro
J. Buigues
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Sascha Gehrke
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Magd Badaoui
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Balint Dudas
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Gaurav Mandana
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Tianyun Qi
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
| | - Giovanni Bottegoni
- Dipartimento
di Scienze Biomolecolari (DISB), University
of Urbino, Urbino Piazza Rinascimento, 6, Urbino 61029, Italy
- Institute
of Clinical Sciences, University of Birmingham, Edgbaston, B15 2TT Birmingham, United Kingdom
| | - Edina Rosta
- Department
of Physics and Astronomy, University College
London, London WC1E 6BT, United
Kingdom
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10
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Plut E, Calderón JC, Stanojlović V, Gattor AO, Höring C, Humphrys LJ, Konieczny A, Kerres S, Schubert M, Keller M, Cabrele C, Clark T, Reiser O. Stereochemistry-Driven Interactions of α,γ-Peptide Ligands with the Neuropeptide Y Y 4-Receptor. J Med Chem 2023. [PMID: 37440703 DOI: 10.1021/acs.jmedchem.3c00363] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2023]
Abstract
The G-protein-coupled Y4-receptor (Y4R) and its endogenous ligand, pancreatic polypeptide (PP), suppress appetite in response to food intake and, thus, are attractive drug targets for body-weight control. The C-terminus of human PP (hPP), T32-R33-P34-R35-Y36-NH2, penetrates deep into the binding pocket with its tyrosine-amide and di-arginine motif. Here, we present two C-terminally amidated α,γ-hexapeptides (1a/b) with sequence Ac-R31-γ-CBAA32-R33-L34-R35-Y36-NH2, where γ-CBAA is the (1R,2S,3R)-configured 2-(aminomethyl)-3-phenylcyclobutanecarboxyl moiety (1a) or its mirror image (1b). Both peptides bind the Y4R (Ki of 1a/b: 0.66/12 nM) and act as partial agonists (intrinsic activity of 1a/b: 50/39%). Their induced-fit binding poses in the Y4R pocket are unique and build ligand-receptor contacts distinct from those of the C-terminus of the endogenous ligand hPP. We conclude that energetically favorable interactions, although they do not match those of the native ligand hPP, still guarantee high binding affinity (with 1a rivaling hPP) but not the maximum receptor activation.
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Affiliation(s)
- Eva Plut
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Jacqueline C Calderón
- Department of Chemistry and Pharmacy, Computer-Chemistry-Center, Friedrich-Alexander-University Erlangen-Nürnberg, 91052 Erlangen, Germany
| | - Vesna Stanojlović
- Department of Biosciences and Medical Biology, University of Salzburg, 5020 Salzburg, Austria
| | - Albert O Gattor
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Carina Höring
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Laura J Humphrys
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Adam Konieczny
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Sabine Kerres
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Mario Schubert
- Department of Biosciences and Medical Biology, University of Salzburg, 5020 Salzburg, Austria
| | - Max Keller
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
| | - Chiara Cabrele
- Department of Biosciences and Medical Biology, University of Salzburg, 5020 Salzburg, Austria
| | - Timothy Clark
- Department of Chemistry and Pharmacy, Computer-Chemistry-Center, Friedrich-Alexander-University Erlangen-Nürnberg, 91052 Erlangen, Germany
| | - Oliver Reiser
- Institute of Organic Chemistry, Faculty of Chemistry and Pharmacy, University of Regensburg, 93053 Regensburg, Germany
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11
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Hok L, Vianello R. Selective Deuteration Improves the Affinity of Adenosine A 2A Receptor Ligands: A Computational Case Study with Istradefylline and Caffeine. J Chem Inf Model 2023; 63:3138-3149. [PMID: 37155356 DOI: 10.1021/acs.jcim.3c00424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
We used a range of computational techniques to assess the effect of selective C-H deuteration on the antagonist istradefylline affinity for the adenosine A2A receptor, which was discussed relative to its structural analogue caffeine, a well-known and likely the most widely used stimulant. The obtained results revealed that smaller caffeine shows high receptor flexibility and exchanges between two distinct poses, which agrees with crystallographic data. In contrast, the additional C8-trans-styryl fragment in istradefylline locks the ligand within a uniform binding pose, while contributing to the affinity through the C-H···π and π···π contacts with surface residues, which, together with its much lower hydration prior to binding, enhances the affinity over caffeine. In addition, the aromatic C8-unit shows a higher deuteration sensitivity over the xanthine part, so when both of its methoxy groups are d6-deuterated, the affinity improvement is -0.4 kcal mol-1, which surpasses the overall affinity gain of -0.3 kcal mol-1 in the perdeuterated d9-caffeine. Yet, the latter predicts around 1.7-fold potency increase, being relevant for its pharmaceutical implementations, and also those within the coffee and energy drink production industries. Still, the full potential of our strategy is achieved in polydeuterated d19-istradefylline, whose A2A affinity improves by -0.6 kcal mol-1, signifying a 2.8-fold potency increase that strongly promotes it as a potential synthetic target. This knowledge supports deuterium application in drug design, and while the literature already reports about over 20 deuterated drugs currently in the clinical development, it is easily foreseen that more examples will hit the market in the years to come. With this in mind, we propose that the devised computational methodology, involving the ONIOM division of the QM region for the ligand and the MM region for its environment, with an implicit quantization of nuclear motions relevant for the H/D exchange, allows fast and efficient estimates of the binding isotope effects in any biological system.
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Affiliation(s)
- Lucija Hok
- Laboratory for the Computational Design and Synthesis of Functional Materials, Division of Organic Chemistry and Biochemistry, Ruđer Bošković Institute, 10000 Zagreb, Croatia
| | - Robert Vianello
- Laboratory for the Computational Design and Synthesis of Functional Materials, Division of Organic Chemistry and Biochemistry, Ruđer Bošković Institute, 10000 Zagreb, Croatia
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12
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Matricon P, Nguyen AT, Vo DD, Baltos JA, Jaiteh M, Luttens A, Kampen S, Christopoulos A, Kihlberg J, May LT, Carlsson J. Structure-based virtual screening discovers potent and selective adenosine A 1 receptor antagonists. Eur J Med Chem 2023; 257:115419. [PMID: 37301076 DOI: 10.1016/j.ejmech.2023.115419] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 06/12/2023]
Abstract
Development of subtype-selective leads is essential in drug discovery campaigns targeting G protein-coupled receptors (GPCRs). Herein, a structure-based virtual screening approach to rationally design subtype-selective ligands was applied to the A1 and A2A adenosine receptors (A1R and A2AR). Crystal structures of these closely related subtypes revealed a non-conserved subpocket in the binding sites that could be exploited to identify A1R selective ligands. A library of 4.6 million compounds was screened computationally against both receptors using molecular docking and 20 A1R selective ligands were predicted. Of these, seven antagonized the A1R with micromolar activities and several compounds displayed slight selectivity for this subtype. Twenty-seven analogs of two discovered scaffolds were designed, resulting in antagonists with nanomolar potency and up to 76-fold A1R-selectivity. Our results show the potential of structure-based virtual screening to guide discovery and optimization of subtype-selective ligands, which could facilitate the development of safer drugs.
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Affiliation(s)
- Pierre Matricon
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden
| | - Anh Tn Nguyen
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Duc Duy Vo
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden
| | - Jo-Anne Baltos
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Mariama Jaiteh
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden
| | - Andreas Luttens
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden
| | - Stefanie Kampen
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden
| | - Arthur Christopoulos
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Jan Kihlberg
- Department of Chemistry - BMC, Uppsala University, SE-751 23, Uppsala, Sweden
| | - Lauren Therese May
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia.
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, SE-751 24, Uppsala, Sweden.
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13
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Chen X, Yuan Y, Chen Y, Yu J, Wang J, Chen J, Guo Y, Pu X. Biased Activation Mechanism Induced by GPCR Heterodimerization: Observations from μOR/δOR Dimers. J Chem Inf Model 2022; 62:5581-5600. [PMID: 36377848 DOI: 10.1021/acs.jcim.2c00962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
GPCRs regulate multiple intracellular signaling cascades. Biasedly activating one signaling pathway over the others provides additional clinical utility to optimize GPCR-based therapies. GPCR heterodimers possess different functions from their monomeric states, including their selectivity to different transducers. However, the biased signaling mechanism induced by the heterodimerization remains unclear. Motivated by the issue, we select an important GPCR heterodimer (μOR/δOR heterodimer) as a case and use microsecond Gaussian accelerated molecular dynamics simulation coupled with potential of mean force and protein structure network (PSN) to probe mechanisms regarding the heterodimerization-induced constitutive β-arrestin activity and efficacy change of the agonist DAMGO. The results show that only the lowest energy state of the μOR/δOR heterodimer, which adopts a slightly outward shift of TM6 and an ICL2 conformation close to the receptor core, can selectively accommodate β-arrestins. PSN further reveals important roles of H8, ICL1, and ICL2 in regulating the constitutive β-arrestin-biased activity for the apo μOR/δOR heterodimer. In addition, the heterodimerization can allosterically alter the binding mode of DAMGO mainly by means of W7.35. Consequently, DAMGO transmits the structural signal mainly through TM6 and TM7 in the dimer, rather than TM3 similar to the μOR monomer, thus changing the efficacy of DAMGO from a balanced agonist to the β-arrestin-biased one. On the other side, the binding of DAMGO to the heterodimer can stabilize μOR/δOR heterodimers through a stronger interaction of TM1/TM1 and H8/H8, accordingly enhancing the interaction of μOR with δOR and the binding affinity of the dimer to the β-arrestin. The agonist DAMGO does not change main compositions of the regulation network from the dimer interface to the transducer binding pocket of the μOR protomer, but induces an increase in the structural communication of the network, which should contribute to the enhanced β-arrestin coupling. Our observations, for the first time, reveal the molecular mechanism of the biased signaling induced by the heterodimerization for GPCRs, which should be beneficial to more comprehensively understand the GPCR bias signaling.
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Affiliation(s)
- Xin Chen
- College of Chemistry, Sichuan University, Chengdu610064, China
| | - Yuan Yuan
- College of Management, Southwest University for Nationalities, Chengdu610041, China
| | - Yichi Chen
- College of Chemistry, Sichuan University, Chengdu610064, China
| | - Jin Yu
- Department of Physics and Astronomy, University of California, Irvine, California92697, United States
| | - Jingzhou Wang
- College of Chemistry, Sichuan University, Chengdu610064, China
| | - Jianfang Chen
- College of Chemistry, Sichuan University, Chengdu610064, China
| | - Yanzhi Guo
- College of Chemistry, Sichuan University, Chengdu610064, China
| | - Xuemei Pu
- College of Chemistry, Sichuan University, Chengdu610064, China
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14
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The full activation mechanism of the adenosine A 1 receptor revealed by GaMD and Su-GaMD simulations. Proc Natl Acad Sci U S A 2022; 119:e2203702119. [PMID: 36215480 PMCID: PMC9586258 DOI: 10.1073/pnas.2203702119] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The full activation process of G protein-coupled receptor (GPCR) plays an important role in cellular signal transduction. However, it remains challenging to simulate the whole process in which the GPCR is recognized and activated by a ligand and then couples to the G protein on a reasonable simulation timescale. Here, we developed a molecular dynamics (MD) approach named supervised (Su) Gaussian accelerated MD (GaMD) by incorporating a tabu-like supervision algorithm into a standard GaMD simulation. By using this Su-GaMD method, from the active and inactive structure of adenosine A1 receptor (A1R), we successfully revealed the full activation mechanism of A1R, including adenosine (Ado)-A1R recognition, preactivation of A1R, and A1R-G protein recognition, in hundreds of nanoseconds of simulations. The binding of Ado to the extracellular side of A1R initiates conformational changes and the preactivation of A1R. In turn, the binding of Gi2 to the intracellular side of A1R causes a decrease in the volume of the extracellular orthosteric site and stabilizes the binding of Ado to A1R. Su-GaMD could be a useful tool to reconstruct or even predict ligand-protein and protein-protein recognition pathways on a short timescale. The intermediate states revealed in this study could provide more detailed complementary structural characterizations to facilitate the drug design of A1R in the future.
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15
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Bobrovs R, Basens EE, Drunka L, Kanepe I, Matisone S, Velins KK, Andrianov V, Leitis G, Zelencova-Gopejenko D, Rasina D, Jirgensons A, Jaudzems K. Exploring Aspartic Protease Inhibitor Binding to Design-Selective Antimalarials. J Chem Inf Model 2022; 62:3263-3273. [PMID: 35712895 DOI: 10.1021/acs.jcim.2c00422] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Selectivity is a major issue in the development of drugs targeting pathogen aspartic proteases. Here, we explore the selectivity-determining factors by studying specifically designed malaria aspartic protease (plasmepsin) open-flap inhibitors. Metadynamics simulations are used to uncover the complex binding/unbinding pathways of these inhibitors and describe the critical transition states in atomistic resolution. The simulation results are compared with experimentally determined enzymatic activities. Our findings demonstrate that plasmepsin inhibitor selectivity can be achieved by targeting the flap loop with hydrophobic substituents that enable ligand binding under the flap loop, as such a behavior is not observed for several other aspartic proteases. The ability to estimate the selectivity of compounds before they are synthesized is of considerable importance in drug design; therefore, we expect that our approach will be useful in selective inhibitor designs against not only aspartic proteases but also other enzyme classes.
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Affiliation(s)
- Raitis Bobrovs
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | | | - Laura Drunka
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Iveta Kanepe
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Sofija Matisone
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | | | - Victor Andrianov
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Gundars Leitis
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | | | - Dace Rasina
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Aigars Jirgensons
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
| | - Kristaps Jaudzems
- Latvian Institute of Organic Synthesis, Aizkraukles 21, Riga LV1006, Latvia
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16
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Molecular mechanism of allosteric modulation for the cannabinoid receptor CB1. Nat Chem Biol 2022; 18:831-840. [DOI: 10.1038/s41589-022-01038-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 04/13/2022] [Indexed: 02/07/2023]
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17
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Prediction of GPCR activity using Machine Learning. Comput Struct Biotechnol J 2022; 20:2564-2573. [PMID: 35685352 PMCID: PMC9163700 DOI: 10.1016/j.csbj.2022.05.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/08/2022] [Accepted: 05/09/2022] [Indexed: 11/20/2022] Open
Abstract
GPCRs are the target for one-third of the FDA-approved drugs, however; the development of new drug molecules targeting GPCRs is limited by the lack of mechanistic understanding of the GPCR structure–activity-function relationship. To modulate the GPCR activity with highly specific drugs and minimal side-effects, it is necessary to quantitatively describe the important structural features in the GPCR and correlate them to the activation state of GPCR. In this study, we developed 3 ML approaches to predict the conformation state of GPCR proteins. Additionally, we predict the activity level of GPCRs based on their structure. We leverage the unique advantages of each of the 3 ML approaches, interpretability of XGBoost, minimal feature engineering for 3D convolutional neural network, and graph representation of protein structure for graph neural network. By using these ML approaches, we are able to predict the activation state of GPCRs with high accuracy (91%–95%) and also predict the activation state of GPCRs with low error (MAE of 7.15–10.58). Furthermore, the interpretation of the ML approaches allows us to determine the importance of each of the features in distinguishing between the GPCRs conformations.
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18
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Val C, Rodríguez-García C, Prieto-Díaz R, Crespo A, Azuaje J, Carbajales C, Majellaro M, Díaz-Holguín A, Brea JM, Loza MI, Gioé-Gallo C, Contino M, Stefanachi A, García-Mera X, Estévez JC, Gutiérrez-de-Terán H, Sotelo E. Optimization of 2-Amino-4,6-diarylpyrimidine-5-carbonitriles as Potent and Selective A 1 Antagonists. J Med Chem 2022; 65:2091-2106. [PMID: 35068155 PMCID: PMC8842224 DOI: 10.1021/acs.jmedchem.1c01636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Indexed: 11/29/2022]
Abstract
We herein document a large collection of 108 2-amino-4,6-disubstituted-pyrimidine derivatives as potent, structurally simple, and highly selective A1AR ligands. The most attractive ligands were confirmed as antagonists of the canonical cyclic adenosine monophosphate pathway, and some pharmacokinetic parameters were preliminarilly evaluated. The library, built through a reliable and efficient three-component reaction, comprehensively explored the chemical space allowing the identification of the most prominent features of the structure-activity and structure-selectivity relationships around this scaffold. These included the influence on the selectivity profile of the aromatic residues at positions R4 and R6 of the pyrimidine core but most importantly the prominent role to the unprecedented A1AR selectivity profile exerted by the methyl group introduced at the exocyclic amino group. The structure-activity relationship trends on both A1 and A2AARs were conveniently interpreted with rigorous free energy perturbation simulations, which started from the receptor-driven docking model that guided the design of these series.
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Affiliation(s)
- Cristina Val
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Carlos Rodríguez-García
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Rubén Prieto-Díaz
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Department
of Cell and Molecular Biology, Uppsala University, Uppsala 75124, Sweden
| | - Abel Crespo
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Jhonny Azuaje
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Carlos Carbajales
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Maria Majellaro
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | | | - José M. Brea
- Centro
Singular de Investigación en Medicina Molecular y Enfermedades
Crónicas (CiMUS), Universidade de
Santiago de Compostela, Santiago
de Compostela 15782, Spain
| | - Maria Isabel Loza
- Centro
Singular de Investigación en Medicina Molecular y Enfermedades
Crónicas (CiMUS), Universidade de
Santiago de Compostela, Santiago
de Compostela 15782, Spain
| | - Claudia Gioé-Gallo
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Marialessandra Contino
- Dipartimento
di Farmacia-Scienze del Farmaco, Università
degli Studi di Bari ALDO MORO, via Orabona 4, Bari 70125, Italy
| | - Angela Stefanachi
- Dipartimento
di Farmacia-Scienze del Farmaco, Università
degli Studi di Bari ALDO MORO, via Orabona 4, Bari 70125, Italy
| | - Xerardo García-Mera
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | - Juan C. Estévez
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
| | | | - Eddy Sotelo
- Centro
Singular de Investigación en Química Biolóxica
e Materiais Moleculares (CiQUS), Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
- Departamento
de Química Orgánica, Universidade
de Santiago de Compostela, Santiago de Compostela 15782, Spain
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19
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Nicoli A, Dunkel A, Giorgino T, de Graaf C, Di Pizio A. Classification Model for the Second Extracellular Loop of Class A GPCRs. J Chem Inf Model 2022; 62:511-522. [PMID: 35113559 DOI: 10.1021/acs.jcim.1c01056] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The extracellular loop 2 (ECL2) is the longest and the most diverse loop among class A G protein-coupled receptors (GPCRs). It connects the transmembrane (TM) helices 4 and 5 and contains a highly conserved cysteine through which it is bridged with TM3. In this paper, experimental ECL2 structures were analyzed based on their sequences, shapes, and intramolecular contacts. To take into account the flexibility, we incorporated into our analyses information from the molecular dynamics trajectories available on the GPCRmd website. Despite the high sequence variability, shapes of the analyzed structures, defined by the backbone volume overlaps, can be clustered into seven main groups. Conformational differences within the clusters can be then identified by intramolecular interactions with other GPCR structural domains. Overall, our work provides a reorganization of the structural information of the ECL2 of class A GPCR subfamilies, highlighting differences and similarities on sequence and conformation levels.
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Affiliation(s)
- Alessandro Nicoli
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Andreas Dunkel
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Toni Giorgino
- Biophysics Institute, National Research Council (CNR-IBF), 20133 Milan, Italy
| | - Chris de Graaf
- Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge CB21 6DG, U.K
| | - Antonella Di Pizio
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
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20
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Zhang Q, Zhao N, Meng X, Yu F, Yao X, Liu H. The prediction of protein-ligand unbinding for modern drug discovery. Expert Opin Drug Discov 2021; 17:191-205. [PMID: 34731059 DOI: 10.1080/17460441.2022.2002298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods. AREAS COVERED In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed. EXPERT OPINION Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.
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Affiliation(s)
| | - Nannan Zhao
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Xiaoxiao Meng
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Fansen Yu
- School of Pharmacy, Lanzhou University, Lanzhou, China
| | - Xiaojun Yao
- College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, China.,Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, China
| | - Huanxiang Liu
- School of Pharmacy, Lanzhou University, Lanzhou, China
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21
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Kapla J, Rodríguez-Espigares I, Ballante F, Selent J, Carlsson J. Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models? PLoS Comput Biol 2021; 17:e1008936. [PMID: 33983933 PMCID: PMC8186765 DOI: 10.1371/journal.pcbi.1008936] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 06/08/2021] [Accepted: 04/02/2021] [Indexed: 01/14/2023] Open
Abstract
The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy. In this work, we explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of GPCR structure prediction (GPCR Dock). Two simulation protocols were used to refine 30 models of the D3 dopamine receptor (D3R) in complex with an antagonist. Close to 60 μs of simulation time was generated and the resulting MD refined models were compared to a D3R crystal structure. In the MD simulations, the receptor models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode. The best refinement protocol improved agreement with the experimentally observed ligand binding mode for a majority of the models. Receptor structures with improved virtual screening performance, which was assessed by molecular docking of ligands and decoys, could also be identified among the MD refined models. Application of weak restraints to the transmembrane helixes in the MD simulations further improved predictions of the ligand binding mode and second extracellular loop. These results provide guidelines for application of MD refinement in prediction of GPCR-ligand complexes and directions for further method development.
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Affiliation(s)
- Jon Kapla
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Ismael Rodríguez-Espigares
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences of Pompeu Fabra University (UPF), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Flavio Ballante
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences of Pompeu Fabra University (UPF), Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
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22
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Egyed A, Kelemen ÁA, Vass M, Visegrády A, Thee SA, Wang Z, de Graaf C, Brea J, Loza MI, Leurs R, Keserű GM. Controlling the selectivity of aminergic GPCR ligands from the extracellular vestibule. Bioorg Chem 2021; 111:104832. [PMID: 33826962 DOI: 10.1016/j.bioorg.2021.104832] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 01/18/2021] [Accepted: 03/15/2021] [Indexed: 11/18/2022]
Abstract
In addition to the orthosteric binding pocket (OBP) of GPCRs, recent structural studies have revealed that there are several allosteric sites available for pharmacological intervention. The secondary binding pocket (SBP) of aminergic GPCRs is located in the extracellular vestibule of these receptors, and it has been suggested to be a potential selectivity pocket for bitopic ligands. Here, we applied a virtual screening protocol based on fragment docking to the SBP of the orthosteric ligand-receptor complex. This strategy was employed for a number of aminergic receptors. First, we designed dopamine D3 preferring bitopic compounds from a D2 selective orthosteric ligand. Next, we designed 5-HT2B selective bitopic compounds starting from the 5-HT1B preferring ergoline core of LSD. Comparing the serotonergic profiles of the new derivatives to that of LSD, we found that these derivatives became significantly biased towards the desired 5-HT2B receptor target. Finally, addressing the known limitations of H1 antihistamines, our protocol was successfully used to eliminate the well-known side effects related to the muscarinic M1 activity of amitriptyline while preserving H1 potency in some of the designed bitopic compounds. These applications highlight the usefulness of our new virtual screening protocol and offer a powerful strategy towards bitopic GPCR ligands with designed receptor profiles.
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Affiliation(s)
- Attila Egyed
- Medicinal Chemistry Research Group, Research Center for Natural Sciences Magyar tudósok krt. 2, Budapest, H-1117, Hungary
| | - Ádám A Kelemen
- Medicinal Chemistry Research Group, Research Center for Natural Sciences Magyar tudósok krt. 2, Budapest, H-1117, Hungary
| | - Márton Vass
- Medicinal Chemistry Research Group, Research Center for Natural Sciences Magyar tudósok krt. 2, Budapest, H-1117, Hungary; Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam, 1081 HZ, Netherlands
| | | | - Stephanie A Thee
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam, 1081 HZ, Netherlands
| | - Zhiyong Wang
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam, 1081 HZ, Netherlands
| | - Chris de Graaf
- Sosei Heptares, Steinmetz Granta Park, Great Abington, Cambridge CB21 6DG, UK
| | - Jose Brea
- Innopharma Screening Platform, BioFarma Research Group, Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela, 15782, Santiago de Compostela, Spain
| | - Maria Isabel Loza
- Innopharma Screening Platform, BioFarma Research Group, Center for Research in Molecular Medicine and Chronic Diseases (CIMUS), University of Santiago de Compostela, 15782, Santiago de Compostela, Spain
| | - Rob Leurs
- Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS), Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam, 1081 HZ, Netherlands
| | - György M Keserű
- Medicinal Chemistry Research Group, Research Center for Natural Sciences Magyar tudósok krt. 2, Budapest, H-1117, Hungary.
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23
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Comeo E, Trinh P, Nguyen AT, Nowell CJ, Kindon ND, Soave M, Stoddart LA, White JM, Hill SJ, Kellam B, Halls ML, May LT, Scammells PJ. Development and Application of Subtype-Selective Fluorescent Antagonists for the Study of the Human Adenosine A 1 Receptor in Living Cells. J Med Chem 2021; 64:6670-6695. [PMID: 33724031 DOI: 10.1021/acs.jmedchem.0c02067] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The adenosine A1 receptor (A1AR) is a G-protein-coupled receptor (GPCR) that provides important therapeutic opportunities for a number of conditions including congestive heart failure, tachycardia, and neuropathic pain. The development of A1AR-selective fluorescent ligands will enhance our understanding of the subcellular mechanisms underlying A1AR pharmacology facilitating the development of more efficacious and selective therapies. Herein, we report the design, synthesis, and application of a novel series of A1AR-selective fluorescent probes based on 8-functionalized bicyclo[2.2.2]octylxanthine and 3-functionalized 8-(adamant-1-yl) xanthine scaffolds. These fluorescent conjugates allowed quantification of kinetic and equilibrium ligand binding parameters using NanoBRET and visualization of specific receptor distribution patterns in living cells by confocal imaging and total internal reflection fluorescence (TIRF) microscopy. As such, the novel A1AR-selective fluorescent antagonists described herein can be applied in conjunction with a series of fluorescence-based techniques to foster understanding of A1AR molecular pharmacology and signaling in living cells.
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Affiliation(s)
- Eleonora Comeo
- Medicinal Chemistry, Monash University, Parkville, Victoria 3052, Australia.,Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Phuc Trinh
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Anh T Nguyen
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Cameron J Nowell
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Nicholas D Kindon
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Mark Soave
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Leigh A Stoddart
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Jonathan M White
- School of Chemistry and the Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Stephen J Hill
- Division of Physiology, Pharmacology and Neuroscience, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham NG7 2UH, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Barrie Kellam
- Division of Biomolecular Sciences and Medicinal Chemistry, School of Pharmacy, Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, United Kingdom.,Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, B15 2TT and University of Nottingham, Birmingham NG7 2UH, United Kingdom
| | - Michelle L Halls
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Lauren T May
- Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Peter J Scammells
- Medicinal Chemistry, Monash University, Parkville, Victoria 3052, Australia
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24
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Matricon P, Suresh RR, Gao ZG, Panel N, Jacobson KA, Carlsson J. Ligand design by targeting a binding site water. Chem Sci 2020; 12:960-968. [PMID: 34163862 PMCID: PMC8179138 DOI: 10.1039/d0sc04938g] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Solvent reorganization is a major driving force of protein–ligand association, but the contribution of binding site waters to ligand affinity is poorly understood. We investigated how altered interactions with a water network can influence ligand binding to a receptor. A series of ligands of the A2A adenosine receptor, which either interacted with or displaced an ordered binding site water, were studied experimentally and by molecular dynamics simulations. An analog of the endogenous ligand that was unable to hydrogen bond to the ordered water lost affinity and this activity cliff was captured by molecular dynamics simulations. Two compounds designed to displace the ordered water from the binding site were then synthesized and evaluated experimentally, leading to the discovery of an A2A agonist with nanomolar activity. Calculation of the thermodynamic profiles resulting from introducing substituents that interacted with or displaced the ordered water showed that the gain of binding affinity was enthalpy driven. Detailed analysis of the energetics and binding site hydration networks revealed that the enthalpy change was governed by contributions that are commonly neglected in structure-based drug optimization. In particular, simulations suggested that displacement of water from a binding site to the bulk solvent can lead to large energy contributions. Our findings provide insights into the molecular driving forces of protein–ligand binding and strategies for rational drug design. Solvent reorganization is a major driving force of protein–ligand association, but the contribution of binding site waters to ligand affinity is poorly understood.![]()
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Affiliation(s)
- Pierre Matricon
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University SE-75124 Uppsala Sweden
| | - R Rama Suresh
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health Bethesda Maryland 20892 USA
| | - Zhan-Guo Gao
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health Bethesda Maryland 20892 USA
| | - Nicolas Panel
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University SE-75124 Uppsala Sweden
| | - Kenneth A Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health Bethesda Maryland 20892 USA
| | - Jens Carlsson
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University SE-75124 Uppsala Sweden
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25
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Ligand binding free-energy calculations with funnel metadynamics. Nat Protoc 2020; 15:2837-2866. [PMID: 32814837 DOI: 10.1038/s41596-020-0342-4] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2018] [Accepted: 04/17/2020] [Indexed: 11/09/2022]
Abstract
The accurate resolution of the binding mechanism of a ligand to its molecular target is fundamental to develop a successful drug design campaign. Free-energy calculations, which provide the energy value of the ligand-protein binding complex, are essential for resolving the binding mode of the ligand. The accuracy of free-energy calculation methods is counteracted by their poor user-friendliness, which hampers their broad application. Here we present the Funnel-Metadynamics Advanced Protocol (FMAP), which is a flexible and user-friendly graphical user interface (GUI)-based protocol to perform funnel metadynamics, a binding free-energy method that employs a funnel-shape restraint potential to reveal the ligand binding mode and accurately calculate the absolute ligand-protein binding free energy. FMAP guides the user through all phases of the free-energy calculation process, from preparation of the input files, to production simulation, to analysis of the results. FMAP delivers the ligand binding mode and the absolute protein-ligand binding free energy as outputs. Alternative binding modes and the role of waters are also elucidated, providing a detailed description of the ligand binding mechanism. The entire protocol on the paradigmatic system benzamidine-trypsin, composed of ~105 k atoms, took ~2.8 d using the Cray XC50 piz Daint cluster at the Swiss National Supercomputing Centre.
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26
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Yu F, Zhu C, Xie Q, Wang Y. Adenosine A 2A Receptor Antagonists for Cancer Immunotherapy. J Med Chem 2020; 63:12196-12212. [PMID: 32667814 DOI: 10.1021/acs.jmedchem.0c00237] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Currently, the most promising therapeutic modality for cancer treatment is the blockade of immune checkpoint pathways, which has revolutionized cancer therapy in the past 15 years. Strategies targeting and modulating adenosine A2A receptor (A2AR), an emerging alternative immune checkpoint, have shown the potential to produce significant therapeutic effects. In this review, we describe the immunosuppressive activities of A2AR and A2BR in the tumor microenvironment (TME), followed by a summary and discussion of the structure-activity relationship (SAR) of the A2AR (and dual A2AR/A2BR) antagonists that have been experimentally confirmed to exert oncoimmunological effects. This review also provides an update on the compounds under clinical evaluation and insights into the ligand binding modes of the receptor.
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Affiliation(s)
- Fazhi Yu
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
| | - Chenyu Zhu
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
| | - Qiong Xie
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
| | - Yonghui Wang
- Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 826 Zhangheng Road, Shanghai 201203, China
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27
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Evans R, Hovan L, Tribello GA, Cossins BP, Estarellas C, Gervasio FL. Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies. J Chem Theory Comput 2020; 16:4641-4654. [PMID: 32427471 PMCID: PMC7467642 DOI: 10.1021/acs.jctc.0c00075] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calculate, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal pathlike variable obtained using machine learning or with the Hamiltonian replica-exchange algorithm SWISH, this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.
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Affiliation(s)
| | | | - Gareth A Tribello
- Atomistic Simulation Centre, Queen's University, Belfast BT7 1NN, United Kingdom
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28
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Salmaso V, Jacobson KA. In Silico Drug Design for Purinergic GPCRs: Overview on Molecular Dynamics Applied to Adenosine and P2Y Receptors. Biomolecules 2020; 10:E812. [PMID: 32466404 PMCID: PMC7356333 DOI: 10.3390/biom10060812] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/21/2020] [Accepted: 05/22/2020] [Indexed: 12/14/2022] Open
Abstract
Molecular modeling has contributed to drug discovery for purinergic GPCRs, including adenosine receptors (ARs) and P2Y receptors (P2YRs). Experimental structures and homology modeling have proven to be useful in understanding and predicting structure activity relationships (SAR) of agonists and antagonists. This review provides an excursus on molecular dynamics (MD) simulations applied to ARs and P2YRs. The binding modes of newly synthesized A1AR- and A3AR-selective nucleoside derivatives, potentially of use against depression and inflammation, respectively, have been predicted to recapitulate their SAR and the species dependence of A3AR affinity. P2Y12R and P2Y1R crystallographic structures, respectively, have provided a detailed understanding of the recognition of anti-inflammatory P2Y14R antagonists and a large group of allosteric and orthosteric antagonists of P2Y1R, an antithrombotic and neuroprotective target. MD of A2AAR (an anticancer and neuroprotective target), A3AR, and P2Y1R has identified microswitches that are putatively involved in receptor activation. The approach pathways of different ligands toward A2AAR and P2Y1R binding sites have also been explored. A1AR, A2AAR, and A3AR were utilizes to study allosteric phenomena, but locating the binding site of structurally diverse allosteric modulators, such as an A3AR enhancer LUF6000, is challenging. Ligand residence time, a predictor of in vivo efficacy, and the structural role of water were investigated through A2AAR MD simulations. Thus, new MD and other modeling algorithms have contributed to purinergic GPCR drug discovery.
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Affiliation(s)
| | - Kenneth A. Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA;
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29
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Burggraaff L, van Vlijmen HWT, IJzerman AP, van Westen GJP. Quantitative prediction of selectivity between the A 1 and A 2A adenosine receptors. J Cheminform 2020; 12:33. [PMID: 33431012 PMCID: PMC7222572 DOI: 10.1186/s13321-020-00438-3] [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: 12/10/2019] [Accepted: 05/04/2020] [Indexed: 11/10/2022] Open
Abstract
The development of drugs is often hampered due to off-target interactions leading to adverse effects. Therefore, computational methods to assess the selectivity of ligands are of high interest. Currently, selectivity is often deduced from bioactivity predictions of a ligand for multiple targets (individual machine learning models). Here we show that modeling selectivity directly, by using the affinity difference between two drug targets as output value, leads to more accurate selectivity predictions. We test multiple approaches on a dataset consisting of ligands for the A1 and A2A adenosine receptors (among others classification, regression, and we define different selectivity classes). Finally, we present a regression model that predicts selectivity between these two drug targets by directly training on the difference in bioactivity, modeling the selectivity-window. The quality of this model was good as shown by the performances for fivefold cross-validation: ROC A1AR-selective 0.88 ± 0.04 and ROC A2AAR-selective 0.80 ± 0.07. To increase the accuracy of this selectivity model even further, inactive compounds were identified and removed prior to selectivity prediction by a combination of statistical models and structure-based docking. As a result, selectivity between the A1 and A2A adenosine receptors was predicted effectively using the selectivity-window model. The approach presented here can be readily applied to other selectivity cases.
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Affiliation(s)
- Lindsey Burggraaff
- Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Herman W T van Vlijmen
- Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.,Janssen Research & Development, Turnhoutseweg 30, Beerse, Belgium
| | - Adriaan P IJzerman
- Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Gerard J P van Westen
- Division of Drug Discovery & Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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30
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New Insights into Key Determinants for Adenosine 1 Receptor Antagonists Selectivity Using Supervised Molecular Dynamics Simulations. Biomolecules 2020; 10:biom10050732. [PMID: 32392873 PMCID: PMC7278174 DOI: 10.3390/biom10050732] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 04/27/2020] [Accepted: 04/28/2020] [Indexed: 12/13/2022] Open
Abstract
Adenosine receptors (ARs), like many otherGprotein-coupledreceptors (GPCRs), are targets of primary interest indrug design. However, one of the main limits for the development of drugs for this class of GPCRs is the complex selectivity profile usually displayed by ligands. Numerous efforts have been madefor clarifying the selectivity of ARs, leading to the development of many ligand-based models. The structure of the AR subtype A1 (A1AR) has been recently solved, providing important structural insights. In the present work, we rationalized the selectivity profile of two selective A1AR and A2AAR antagonists, investigating their recognition trajectories obtained by Supervised Molecular Dynamics from an unbound state and monitoring the role of the water molecules in the binding site.
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31
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A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands. J Comput Aided Mol Des 2020; 34:697-707. [PMID: 32112287 PMCID: PMC7190583 DOI: 10.1007/s10822-020-00301-5] [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: 06/19/2019] [Accepted: 02/14/2020] [Indexed: 11/08/2022]
Abstract
Among still comparatively few G protein-coupled receptors, the adenosine A2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context, multiple adenosine A1 receptor (A1AR) homology models had been previously obtained and a library of lead-like compounds had been docked. As a result, a number of potent and one selective ligand toward the intended target have been identified. However, in in vitro experimental verification studies, many ligands also bound to the A2AAR and the A3AR subtypes. In this work we asked the question whether a classification of the ligands according to their selectivity was possible based on docking scores. Therefore, we built an A3AR homology model and docked all previously found ligands to all three receptor subtypes. As a metric, we employed an in vitro/in silico selectivity ranking system based on taxicab geometry and obtained a classification model with reasonable separation. In the next step, the method was validated with an external library of, selective ligands with similarly good performance. This classification system might also be useful in further screens.
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32
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Limongelli V. Ligand binding free energy and kinetics calculation in 2020. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2020. [DOI: 10.1002/wcms.1455] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Vittorio Limongelli
- Faculty of Biomedical Sciences, Institute of Computational Science – Center for Computational Medicine in Cardiology Università della Svizzera italiana (USI) Lugano Switzerland
- Department of Pharmacy University of Naples “Federico II” Naples Italy
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