1
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Kossatz E, Diez-Alarcia R, Gaitonde SA, Ramon-Duaso C, Stepniewski TM, Aranda-Garcia D, Muneta-Arrate I, Tepaz E, Saen-Oon S, Soliva R, Shahraki A, Moreira D, Brea J, Loza MI, de la Torre R, Kolb P, Bouvier M, Meana JJ, Robledo P, Selent J. G protein-specific mechanisms in the serotonin 5-HT 2A receptor regulate psychosis-related effects and memory deficits. Nat Commun 2024; 15:4307. [PMID: 38811567 PMCID: PMC11137019 DOI: 10.1038/s41467-024-48196-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 04/23/2024] [Indexed: 05/31/2024] Open
Abstract
G protein-coupled receptors (GPCRs) are sophisticated signaling machines able to simultaneously elicit multiple intracellular signaling pathways upon activation. Complete (in)activation of all pathways can be counterproductive for specific therapeutic applications. This is the case for the serotonin 2 A receptor (5-HT2AR), a prominent target for the treatment of schizophrenia. In this study, we elucidate the complex 5-HT2AR coupling signature in response to different signaling probes, and its physiological consequences by combining computational modeling, in vitro and in vivo experiments with human postmortem brain studies. We show how chemical modification of the endogenous agonist serotonin dramatically impacts the G protein coupling profile of the 5-HT2AR and the associated behavioral responses. Importantly, among these responses, we demonstrate that memory deficits are regulated by Gαq protein activation, whereas psychosis-related behavior is modulated through Gαi1 stimulation. These findings emphasize the complexity of GPCR pharmacology and physiology and open the path to designing improved therapeutics for the treatment of stchizophrenia.
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Affiliation(s)
- Elk Kossatz
- Integrative Pharmacology and Systems Neuroscience Research Group, Hospital del Mar Research Institute, Barcelona, Spain
| | - Rebeca Diez-Alarcia
- Department of Pharmacology, University of the Basque Country/Euskal Herriko Unibertsitatea, Leioa, Bizkaia, Spain
- Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain
- Instituto de Investigación Sanitaria Biobizkaia, Barakaldo, Bizkaia, Spain
| | - Supriya A Gaitonde
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Carla Ramon-Duaso
- Cell-type mechanisms in normal and pathological behaviour Research Group, IMIM-Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain
- InterAx Biotech AG, PARK InnovAARE, 5234, Villigen, Switzerland
| | - David Aranda-Garcia
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain
- Department of Medicine and Life Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Itziar Muneta-Arrate
- Department of Pharmacology, University of the Basque Country/Euskal Herriko Unibertsitatea, Leioa, Bizkaia, Spain
- Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain
| | - Elodie Tepaz
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Suwipa Saen-Oon
- NBD NOSTRUM BIODISCOVERY, Av. de Josep Tarradellas, 8-10, 3-2, 08029, Barcelona, Spain
| | - Robert Soliva
- NBD NOSTRUM BIODISCOVERY, Av. de Josep Tarradellas, 8-10, 3-2, 08029, Barcelona, Spain
| | - Aida Shahraki
- Pharmaceutical Chemistry, University of Marburg, Marbacher Weg 8, Marburg, 35037, Germany
| | - David Moreira
- Innopharma Drug Screening and Pharmacogenomics Platform. BioFarma research group. Center for Research in Molecular Medicine and Chronic Diseases (CiMUS). Department of Pharmacology, Pharmacy and Pharmaceutical Technology, University of Santiago de Compostela, Santiago de Compostela, Spain
- Health Research Institute of Santiago de Compostela (IDIS), University Hospital of Santiago de Compostela (SERGAS), Trav. Choupana s/n, 15706, Santiago de Compostela, Spain
| | - Jose Brea
- Pharmaceutical Chemistry, University of Marburg, Marbacher Weg 8, Marburg, 35037, Germany
- Innopharma Drug Screening and Pharmacogenomics Platform. BioFarma research group. Center for Research in Molecular Medicine and Chronic Diseases (CiMUS). Department of Pharmacology, Pharmacy and Pharmaceutical Technology, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Maria Isabel Loza
- Innopharma Drug Screening and Pharmacogenomics Platform. BioFarma research group. Center for Research in Molecular Medicine and Chronic Diseases (CiMUS). Department of Pharmacology, Pharmacy and Pharmaceutical Technology, University of Santiago de Compostela, Santiago de Compostela, Spain
- Health Research Institute of Santiago de Compostela (IDIS), University Hospital of Santiago de Compostela (SERGAS), Trav. Choupana s/n, 15706, Santiago de Compostela, Spain
| | - Rafael de la Torre
- Integrative Pharmacology and Systems Neuroscience Research Group, Hospital del Mar Research Institute, Barcelona, Spain
| | - Peter Kolb
- Pharmaceutical Chemistry, University of Marburg, Marbacher Weg 8, Marburg, 35037, Germany
| | - Michel Bouvier
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - J Javier Meana
- Department of Pharmacology, University of the Basque Country/Euskal Herriko Unibertsitatea, Leioa, Bizkaia, Spain
- Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain
- Instituto de Investigación Sanitaria Biobizkaia, Barakaldo, Bizkaia, Spain
| | - Patricia Robledo
- Integrative Pharmacology and Systems Neuroscience Research Group, Hospital del Mar Research Institute, Barcelona, Spain.
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain.
- Department of Medicine and Life Sciences, Pompeu Fabra University, Barcelona, Spain.
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2
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Bertalan É, Rodrigues MJ, Schertler GFX, Bondar AN. Graph-based algorithms to dissect long-distance water-mediated H-bond networks for conformational couplings in GPCRs. Br J Pharmacol 2024. [PMID: 38636539 DOI: 10.1111/bph.16387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 02/03/2024] [Accepted: 03/02/2024] [Indexed: 04/20/2024] Open
Abstract
Changes in structure and dynamics elicited by agonist ligand binding at the extracellular side of G protein coupled receptors (GPCRs) must be relayed to the cytoplasmic G protein binding side of the receptors. To decipher the role of water-mediated hydrogen-bond networks in this relay mechanism, we have developed graph-based algorithms and analysis methodologies applicable to datasets of static structures of distinct GPCRs. For a reference dataset of static structures of bovine rhodopsin solved at the same resolution, we show that graph analyses capture the internal protein-water hydrogen-bond network. The extended analyses of static structures of rhodopsins and opioid receptors suggest a relay mechanism whereby inactive receptors have in place much of the internal core hydrogen-bond network required for long-distance relay of structural change, with extensive local H-bond clusters observed in structures solved at high resolution and with internal water molecules.
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Affiliation(s)
- Éva Bertalan
- Physikzentrum, RWTH-Aachen University, Aachen, Germany
| | | | | | - Ana-Nicoleta Bondar
- Forschungszentrum Jülich, Institute of Computational Biomedicine, Jülich, Germany
- Faculty of Physics, University of Bucharest, Măgurele, Romania
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3
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Nicoli A, Weber V, Bon C, Steuer A, Gustincich S, Gainetdinov RR, Lang R, Espinoza S, Di Pizio A. Structure-Based Discovery of Mouse Trace Amine-Associated Receptor 5 Antagonists. J Chem Inf Model 2023; 63:6667-6680. [PMID: 37847527 PMCID: PMC10647090 DOI: 10.1021/acs.jcim.3c00755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Indexed: 10/18/2023]
Abstract
Trace amine-associated receptors (TAARs) were discovered in 2001 as new members of class A G protein-coupled receptors (GPCRs). With the only exception of TAAR1, TAAR members (TAAR2-9, also known as noncanonical olfactory receptors) were originally described exclusively in the olfactory epithelium and believed to mediate the innate perception of volatile amines. However, most noncanonical olfactory receptors are still orphan receptors. Given its recently discovered nonolfactory expression and therapeutic potential, TAAR5 has been the focus of deorphanization campaigns that led to the discovery of a few druglike antagonists. Here, we report four novel TAAR5 antagonists identified through high-throughput screening, which, along with the four ligands published in the literature, constituted our starting point to design a computational strategy for the identification of TAAR5 ligands. We developed a structure-based virtual screening protocol that allowed us to identify three new TAAR5 antagonists with a hit rate of 10%. Despite lacking an experimental structure, we accurately modeled the TAAR5 binding site by integrating comparative sequence- and structure-based analyses of serotonin receptors with homology modeling and side-chain optimization. In summary, we have identified seven new TAAR5 antagonists that could serve as lead candidates for the development of new treatments for depression, anxiety, and neurodegenerative diseases.
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Affiliation(s)
- Alessandro Nicoli
- Leibniz
Institute for Food Systems Biology at the Technical University of
Munich, 85354 Freising, Germany
- Chemoinformatics
and Protein Modelling, Department of Molecular Life Sciences, School
of Life Sciences, Technical University of
Munich, 85354 Freising, Germany
| | - Verena Weber
- Leibniz
Institute for Food Systems Biology at the Technical University of
Munich, 85354 Freising, Germany
- Institute
for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine
(INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany
- Faculty
of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, Aachen, 52062 Germany
| | - Carlotta Bon
- Istituto
Italiano di Tecnologia, 16163 Genova, Italy
| | - Alexandra Steuer
- Leibniz
Institute for Food Systems Biology at the Technical University of
Munich, 85354 Freising, Germany
- Chemoinformatics
and Protein Modelling, Department of Molecular Life Sciences, School
of Life Sciences, Technical University of
Munich, 85354 Freising, Germany
| | | | - Raul R. Gainetdinov
- Institute
of Translational Biomedicine and Saint Petersburg University Hospital,
Saint Petersburg State University, Saint Petersburg 199034, Russia
| | - Roman Lang
- Leibniz
Institute for Food Systems Biology at the Technical University of
Munich, 85354 Freising, Germany
| | - Stefano Espinoza
- Istituto
Italiano di Tecnologia, 16163 Genova, Italy
- Dipartimento
di Scienze della Salute, Università
del Piemonte Orientale, 28100 Novara, Italy
| | - Antonella Di Pizio
- Leibniz
Institute for Food Systems Biology at the Technical University of
Munich, 85354 Freising, Germany
- Chemoinformatics
and Protein Modelling, Department of Molecular Life Sciences, School
of Life Sciences, Technical University of
Munich, 85354 Freising, Germany
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4
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Llinas del Torrent C, Raïch I, Gonzalez A, Casajuana-Martin N, Lillo J, Rebassa JB, Ferreiro-Vera C, Sánchez de Medina V, Franco R, Navarro G, Pardo L. The Leu/Val 6.51 Side Chain of Cannabinoid Receptors Regulates the Binding Mode of the Alkyl Chain of Δ 9-Tetrahydrocannabinol. J Chem Inf Model 2023; 63:5927-5935. [PMID: 37644761 PMCID: PMC10523433 DOI: 10.1021/acs.jcim.3c01054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Indexed: 08/31/2023]
Abstract
(-)-Δ9-trans-tetrahydrocannabinol (THC), which is the principal psychoactive constituent of Cannabis, mediates its action by binding to two members of the G-protein-coupled receptor (GPCR) family: the cannabinoid CB1 (CB1R) and CB2 (CB2R) receptors. Molecular dynamics simulations showed that the pentyl chain of THC could adopts an I-shape conformation, filling an intracellular cavity between Phe3.36 and Trp6.48 for initial agonist-induced receptor activation, in CB1R but not in CB2R. This cavity opens to the five-carbon chain of THC by the conformational change of the γ-branched, flexible, Leu6.51 side chain of CB1R, which is not feasible by the β-branched, mode rigid, Val6.51 side chain of CB2R. In agreement with our computational results, THC could not decrease the forskolin-induced cAMP levels in cells expressing mutant CB1RL6.51V receptor but could activate the mutant CB2RV6.51L receptor as efficiently as wild-type CB1R. Additionally, JWH-133, a full CB2R agonist, contains a branched dimethyl moiety in the ligand chain that bridges Phe3.36 and Val6.51 for receptor activation. In this case, the substitution of Val6.51 to Leu in CB2R makes JWH-133 unable to activate CB2RV6.51L. In conclusion, our combined computational and experimental results have shown that the amino acid at position 6.51 is a key additional player in the initial mechanism of activation of GPCRs that recognize signaling molecules derived from lipid species.
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Affiliation(s)
- Claudia Llinas del Torrent
- Laboratory
of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Iu Raïch
- Department
of Biochemistry and Molecular Biomedicine, School of Biology, University of Barcelona, 08028 Barcelona, Spain
- Centro
de Investigación en Red, Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031 Madrid, Spain
| | - Angel Gonzalez
- Laboratory
of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Nil Casajuana-Martin
- Laboratory
of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain
| | - Jaume Lillo
- Department
of Biochemistry and Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, 08028 Barcelona, Spain
| | - Joan Biel Rebassa
- Department
of Biochemistry and Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, 08028 Barcelona, Spain
| | | | | | - Rafael Franco
- Department
of Biochemistry and Molecular Biomedicine, School of Biology, University of Barcelona, 08028 Barcelona, Spain
- Centro
de Investigación en Red, Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031 Madrid, Spain
| | - Gemma Navarro
- Centro
de Investigación en Red, Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, 28031 Madrid, Spain
- Department
of Biochemistry and Physiology, Faculty of Pharmacy and Food Sciences, Universitat de Barcelona, 08028 Barcelona, Spain
- Institute
of Neuroscience, University of Barcelona
(NeuroUB), Av Joan XXIII
27-31, 08028 Barcelona, Spain
| | - Leonardo Pardo
- Laboratory
of Computational Medicine, Biostatistics Unit, Faculty of Medicine, Universitat Autònoma Barcelona, 08193 Bellaterra, Barcelona, Spain
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5
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Maria-Solano MA, Choi S. Dynamic allosteric networks drive adenosine A 1 receptor activation and G-protein coupling. eLife 2023; 12:RP90773. [PMID: 37656635 PMCID: PMC10473838 DOI: 10.7554/elife.90773] [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] [Indexed: 09/03/2023] Open
Abstract
G-protein coupled receptors (GPCRs) present specific activation pathways and signaling among receptor subtypes. Hence, an extensive knowledge of the structural dynamics of the receptor is critical for the development of therapeutics. Here, we target the adenosine A1 receptor (A1R), for which a negligible number of drugs have been approved. We combine molecular dynamics simulations, enhanced sampling techniques, network theory and pocket detection to decipher the activation pathway of A1R, decode the allosteric networks and identify transient pockets. The A1R activation pathway reveal hidden intermediate and pre-active states together with the inactive and fully-active states observed experimentally. The protein energy networks computed throughout these conformational states successfully unravel the extra and intracellular allosteric centers and the communication pathways that couples them. We observe that the allosteric networks are dynamic, being increased along activation and fine-tuned in presence of the trimeric G-proteins. Overlap of transient pockets and energy networks uncover how the allosteric coupling between pockets and distinct functional regions of the receptor is altered along activation. By an in-depth analysis of the bridge between activation pathway, energy networks and transient pockets, we provide a further understanding of A1R. This information can be useful to ease the design of allosteric modulators for A1R.
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Affiliation(s)
- Miguel A Maria-Solano
- Global AI Drug Discovery Center, College of Pharmacy and Graduate School of Pharmaceutical Science, Ewha Womans UniversitySeoulRepublic of Korea
| | - Sun Choi
- Global AI Drug Discovery Center, College of Pharmacy and Graduate School of Pharmaceutical Science, Ewha Womans UniversitySeoulRepublic of Korea
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6
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Jobin ML, De Smedt-Peyrusse V, Ducrocq F, Baccouch R, Oummadi A, Pedersen MH, Medel-Lacruz B, Angelo MF, Villette S, Van Delft P, Fouillen L, Mongrand S, Selent J, Tolentino-Cortez T, Barreda-Gómez G, Grégoire S, Masson E, Durroux T, Javitch JA, Guixà-González R, Alves ID, Trifilieff P. Impact of membrane lipid polyunsaturation on dopamine D2 receptor ligand binding and signaling. Mol Psychiatry 2023; 28:1960-1969. [PMID: 36604603 DOI: 10.1038/s41380-022-01928-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 12/05/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023]
Abstract
Increasing evidence supports a relationship between lipid metabolism and mental health. In particular, the biostatus of polyunsaturated fatty acids (PUFAs) correlates with some symptoms of psychiatric disorders, as well as the efficacy of pharmacological treatments. Recent findings highlight a direct association between brain PUFA levels and dopamine transmission, a major neuromodulatory system implicated in the etiology of psychiatric symptoms. However, the mechanisms underlying this relationship are still unknown. Here we demonstrate that membrane enrichment in the n-3 PUFA docosahexaenoic acid (DHA), potentiates ligand binding to the dopamine D2 receptor (D2R), suggesting that DHA acts as an allosteric modulator of this receptor. Molecular dynamics simulations confirm that DHA has a high preference for interaction with the D2R and show that membrane unsaturation selectively enhances the conformational dynamics of the receptor around its second intracellular loop. We find that membrane unsaturation spares G protein activity but potentiates the recruitment of β-arrestin in cells. Furthermore, in vivo n-3 PUFA deficiency blunts the behavioral effects of two D2R ligands, quinpirole and aripiprazole. These results highlight the importance of membrane unsaturation for D2R activity and provide a putative mechanism for the ability of PUFAs to enhance antipsychotic efficacy.
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Affiliation(s)
- Marie-Lise Jobin
- Université de Bordeaux, INRAE, Bordeaux INP, NutriNeuro, 33000, Bordeaux, France
| | | | - Fabien Ducrocq
- Université de Bordeaux, INRAE, Bordeaux INP, NutriNeuro, 33000, Bordeaux, France
| | - Rim Baccouch
- Institute of Chemistry & Biology of Membranes & Nanoobjects, CNRS UMR 5248, Université de Bordeaux, Bordeaux INP, 33600, Pessac, France
| | - Asma Oummadi
- Université de Bordeaux, INRAE, Bordeaux INP, NutriNeuro, 33000, Bordeaux, France
| | - Maria Hauge Pedersen
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)-Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003, Barcelona, Spain
| | | | - Sandrine Villette
- Institute of Chemistry & Biology of Membranes & Nanoobjects, CNRS UMR 5248, Université de Bordeaux, Bordeaux INP, 33600, Pessac, France
| | - Pierre Van Delft
- Laboratory of Membrane Biogenesis (LBM), Research Mix Unity (UMR) 5200, National Scientific Research Center (CNRS), University of Bordeaux, Bordeaux, France
| | - Laetitia Fouillen
- Laboratory of Membrane Biogenesis (LBM), Research Mix Unity (UMR) 5200, National Scientific Research Center (CNRS), University of Bordeaux, Bordeaux, France
| | - Sébastien Mongrand
- Laboratory of Membrane Biogenesis (LBM), Research Mix Unity (UMR) 5200, National Scientific Research Center (CNRS), University of Bordeaux, Bordeaux, France
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)-Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003, Barcelona, Spain
| | | | - Gabriel Barreda-Gómez
- Research Department, IMG Pharma Biotech S.L., BIC Bizkaia (612), 48160, Derio, Spain
| | - Stéphane Grégoire
- Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRAE, Université Bourgogne Franche-Comté, 21000, Dijon, France
| | - Elodie Masson
- Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRAE, Université Bourgogne Franche-Comté, 21000, Dijon, France
| | - Thierry Durroux
- Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
| | - Jonathan A Javitch
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, 10032, USA
- Department of Molecular Pharmacology and Therapeutics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, 10032, USA
| | - Ramon Guixà-González
- Condensed Matter Theory Group, Paul Scherrer Institute (PSI), 5232, Villigen, PSI, Switzerland.
| | - Isabel D Alves
- Institute of Chemistry & Biology of Membranes & Nanoobjects, CNRS UMR 5248, Université de Bordeaux, Bordeaux INP, 33600, Pessac, France.
| | - Pierre Trifilieff
- Université de Bordeaux, INRAE, Bordeaux INP, NutriNeuro, 33000, Bordeaux, France.
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7
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Heng J, Hu Y, Pérez-Hernández G, Inoue A, Zhao J, Ma X, Sun X, Kawakami K, Ikuta T, Ding J, Yang Y, Zhang L, Peng S, Niu X, Li H, Guixà-González R, Jin C, Hildebrand PW, Chen C, Kobilka BK. Function and dynamics of the intrinsically disordered carboxyl terminus of β2 adrenergic receptor. Nat Commun 2023; 14:2005. [PMID: 37037825 PMCID: PMC10085991 DOI: 10.1038/s41467-023-37233-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 03/07/2023] [Indexed: 04/12/2023] Open
Abstract
Advances in structural biology have provided important mechanistic insights into signaling by the transmembrane core of G-protein coupled receptors (GPCRs); however, much less is known about intrinsically disordered regions such as the carboxyl terminus (CT), which is highly flexible and not visible in GPCR structures. The β2 adrenergic receptor's (β2AR) 71 amino acid CT is a substrate for GPCR kinases and binds β-arrestins to regulate signaling. Here we show that the β2AR CT directly inhibits basal and agonist-stimulated signaling in cell lines lacking β-arrestins. Combining single-molecule fluorescence resonance energy transfer (FRET), NMR spectroscopy, and molecular dynamics simulations, we reveal that the negatively charged β2AR-CT serves as an autoinhibitory factor via interacting with the positively charged cytoplasmic surface of the receptor to limit access to G-proteins. The stability of this interaction is influenced by agonists and allosteric modulators, emphasizing that the CT plays important role in allosterically regulating GPCR activation.
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Affiliation(s)
- Jie Heng
- School of Medicine, Tsinghua University, Beijing, 100084, China
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua University, Beijing, 100084, China
- Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China
- Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Yunfei Hu
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Science, Wuhan, 430071, China
| | - Guillermo Pérez-Hernández
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Charitéplatz 1, 10117, Berlin, Germany
| | - Asuka Inoue
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, 980-8578, Japan
| | - Jiawei Zhao
- Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, 100084, China
- School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Xiuyan Ma
- School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Xiaoou Sun
- School of Medicine, Tsinghua University, Beijing, 100084, China
| | - Kouki Kawakami
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, 980-8578, Japan
| | - Tatsuya Ikuta
- Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi, 980-8578, Japan
| | - Jienv Ding
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
- College of Life Sciences, Peking University, Beijing, 100871, China
| | - Yujie Yang
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Lujia Zhang
- School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Sijia Peng
- School of Life Sciences, Tsinghua University, Beijing, 100084, China
| | - Xiaogang Niu
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Hongwei Li
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Ramon Guixà-González
- Condensed Matter Theory Group, Paul Scherrer Institute, CH-5232, Villigen, PSI, Switzerland
| | - Changwen Jin
- Beijing Nuclear Magnetic Resonance Center, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Peter W Hildebrand
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Charitéplatz 1, 10117, Berlin, Germany
- Institute of Medical Physics and Biophysics, University Leipzig, 04107, Leipzig, Germany
- Berlin Institute of Health, 10178, Berlin, Germany
| | - Chunlai Chen
- Beijing Advanced Innovation Center for Structural Biology, Tsinghua University, Beijing, 100084, China.
- Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, 100084, China.
- Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, 100084, China.
- School of Life Sciences, Tsinghua University, Beijing, 100084, China.
| | - Brian K Kobilka
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
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8
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Nicoli A, Haag F, Marcinek P, He R, Kreißl J, Stein J, Marchetto A, Dunkel A, Hofmann T, Krautwurst D, Di Pizio A. Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1. J Chem Inf Model 2023; 63:2014-2029. [PMID: 36696962 PMCID: PMC10091413 DOI: 10.1021/acs.jcim.2c00752] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here, we report two additional agonists and functional data of the most potent compound on two mutants, L1043.32 and L2556.51. Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.
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Affiliation(s)
- Alessandro Nicoli
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Franziska Haag
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Patrick Marcinek
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Ruiming He
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany.,Department of Chemistry, Technical University of Munich, 85748 Garching, Germany
| | - Johanna Kreißl
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Jörg Stein
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Alessandro Marchetto
- Computational Biomedicine, Institute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany.,Department of Biology, Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, 52074 Aachen, Germany
| | - Andreas Dunkel
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Thomas Hofmann
- Chair of Food Chemistry and Molecular Sensory Science, Technical University of Munich, 85354 Freising, Germany
| | - Dietmar Krautwurst
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
| | - Antonella Di Pizio
- Leibniz Institute for Food Systems Biology at the Technical University of Munich, 85354 Freising, Germany
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9
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Hamid M, Khalid MF, Chaudhary SU, Khan S. The Solvation of the E. coli CheY Phosphorylation Site Mapped by XFMS. Int J Mol Sci 2022; 23:ijms232112771. [PMID: 36361564 PMCID: PMC9659070 DOI: 10.3390/ijms232112771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 11/06/2022] Open
Abstract
The Escherichia coli CheY protein belongs to a large bacterial response regulator superfamily. X-ray hydroxy radical foot-printing with mass spectroscopy (XFMS) has shown that allosteric activation of CheY by its motor target triggers a concerted internalization of aromatic sidechains. We reanalyzed the XFMS data to compare polar versus non-polar CheY residue positions. The polar residues around and including the 57D phosphorylated site had an elevated hydroxy radical reactivity. Bioinformatic measures revealed that a water-mediated hydrogen bond network connected this ring of residues with the central 57D. These residues solvated 57D to energetically stabilize the apo-CheY fold. The abundance of these reactive residues was reduced upon activation. This result was supported by the bioinformatics and consistent with the previously reported activation-induced increase in core hydrophobicity. It further illustrated XFMS detection of structural waters. Direct contacts between the ring residues and the phosphorylation site would stabilize the aspartyl phosphate. In addition, we report that the ring residue, 18R, is a constant central node in the 57D solvation network and that 18R non-polar substitutions determine CheY diversity as assessed by its evolutionary trace in bacteria with well-studied chemotaxis. These results showcase the importance of structured water dynamics for phosphorylation-mediated signal transduction.
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Affiliation(s)
- Maham Hamid
- Biomedical Informatics and Engineering Research Laboratory (BIRL), Lahore University of Management Sciences (LUMS), Lahore 54792, Pakistan
| | - Muhammad Farhan Khalid
- Biomedical Informatics and Engineering Research Laboratory (BIRL), Lahore University of Management Sciences (LUMS), Lahore 54792, Pakistan
| | - Safee Ullah Chaudhary
- Biomedical Informatics and Engineering Research Laboratory (BIRL), Lahore University of Management Sciences (LUMS), Lahore 54792, Pakistan
- Correspondence: (S.U.C.); (S.K.)
| | - Shahid Khan
- Syed Babar Ali School of Science & Engineering, Lahore University of Management Sciences (LUMS), Lahore 54792, Pakistan
- Molecular Biology Consortium, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Correspondence: (S.U.C.); (S.K.)
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10
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Staritzbichler R, Ristic N, Goede A, Preissner R, Hildebrand PW. Voronoia 4-ever. Nucleic Acids Res 2021; 49:W685-W690. [PMID: 34107038 PMCID: PMC8265189 DOI: 10.1093/nar/gkab466] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 05/07/2021] [Accepted: 06/07/2021] [Indexed: 11/12/2022] Open
Abstract
We present an updated version of the Voronoia service that enables fully automated analysis of the atomic packing density of macromolecules. Voronoia combines previous efforts to analyse 3D protein and RNA structures into a single service, combined with state-of-the-art online visualization. Voronoia uses the Voronoi cell method to calculate the free space between neighbouring atoms to estimate van der Waals interactions. Compared to other methods that derive van der Waals interactions by calculating solvent-free surfaces, it explicitly considers volume or packing defects. Large internal voids refer either to water molecules or ions unresolved by X-ray crystallography or cryo-EM, cryptic ligand binding pockets, or parts of a structural model that require further refinement. Voronoia is, therefore mainly used for functional analyses of 3D structures and quality assessments of structural models. Voronoia 4-ever updates the database of precomputed packing densities of PDB entries, allows uploading multiple structures, adds new filter options and facilitates direct access to the results through intuitive display with the NGL viewer. Voronoia is available at: htttp://proteinformatics.org/voronoia.
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Affiliation(s)
- Rene Staritzbichler
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany
| | - Nikola Ristic
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany
| | - Andrean Goede
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Physiology, Structural Bioinformatics Group, Berlin 10117, Germany
| | - Robert Preissner
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Physiology, Structural Bioinformatics Group, Berlin 10117, Germany.,Charité -Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Information Technology, Science IT, Charitéplatz 1, 10117 Berlin, Germany
| | - Peter W Hildebrand
- University of Leipzig, Institute of Medical Physics and Biophysics, Leipzig, Germany.,Charité -Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and Biophysics, Charitéplatz 1, 10117 Berlin, Germany.,Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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11
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Lee TS, Allen BK, Giese TJ, Guo Z, Li P, Lin C, McGee TD, Pearlman DA, Radak BK, Tao Y, Tsai HC, Xu H, Sherman W, York DM. Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery. J Chem Inf Model 2020; 60:5595-5623. [PMID: 32936637 PMCID: PMC7686026 DOI: 10.1021/acs.jcim.0c00613] [Citation(s) in RCA: 169] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Predicting protein-ligand binding affinities and the associated thermodynamics of biomolecular recognition is a primary objective of structure-based drug design. Alchemical free energy simulations offer a highly accurate and computationally efficient route to achieving this goal. While the AMBER molecular dynamics package has successfully been used for alchemical free energy simulations in academic research groups for decades, widespread impact in industrial drug discovery settings has been minimal because of the previous limitations within the AMBER alchemical code, coupled with challenges in system setup and postprocessing workflows. Through a close academia-industry collaboration we have addressed many of the previous limitations with an aim to improve accuracy, efficiency, and robustness of alchemical binding free energy simulations in industrial drug discovery applications. Here, we highlight some of the recent advances in AMBER20 with a focus on alchemical binding free energy (BFE) calculations, which are less computationally intensive than alternative binding free energy methods where full binding/unbinding paths are explored. In addition to scientific and technical advances in AMBER20, we also describe the essential practical aspects associated with running relative alchemical BFE calculations, along with recommendations for best practices, highlighting the importance not only of the alchemical simulation code but also the auxiliary functionalities and expertise required to obtain accurate and reliable results. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative BFE simulations in AMBER20, with a focus on real-world drug discovery applications.
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Affiliation(s)
- Tai-Sung Lee
- Rutgers, the State University of New Jersey, Laboratory for Biomolecular Simulation Research, and Department of Chemistry and Chemical Biology, United States
| | - Bryce K. Allen
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Timothy J. Giese
- Rutgers, the State University of New Jersey, Laboratory for Biomolecular Simulation Research, and Department of Chemistry and Chemical Biology, United States
| | - Zhenyu Guo
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Pengfei Li
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Charles Lin
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - T. Dwight McGee
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - David A. Pearlman
- QSimulate Incorporated, Cambridge, Massachusetts 02139, United States
| | - Brian K. Radak
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Yujun Tao
- Rutgers, the State University of New Jersey, Laboratory for Biomolecular Simulation Research, and Department of Chemistry and Chemical Biology, United States
| | - Hsu-Chun Tsai
- Rutgers, the State University of New Jersey, Laboratory for Biomolecular Simulation Research, and Department of Chemistry and Chemical Biology, United States
| | - Huafeng Xu
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Woody Sherman
- Silicon Therapeutics, Boston, Massachusetts 02210, United States
| | - Darrin M. York
- Rutgers, the State University of New Jersey, Laboratory for Biomolecular Simulation Research, and Department of Chemistry and Chemical Biology, United States
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12
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Torrens-Fontanals M, Stepniewski TM, Aranda-García D, Morales-Pastor A, Medel-Lacruz B, Selent J. How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs. Int J Mol Sci 2020; 21:E5933. [PMID: 32824756 PMCID: PMC7460635 DOI: 10.3390/ijms21165933] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/11/2020] [Accepted: 08/15/2020] [Indexed: 01/08/2023] Open
Abstract
G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.
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Affiliation(s)
- Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
- InterAx Biotech AG, PARK innovAARE, 5234 Villigen, Switzerland
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, 02-093 Warsaw, Poland
| | - David Aranda-García
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Adrián Morales-Pastor
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
| | - Jana Selent
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)—Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), 08003 Barcelona, Spain; (M.T.-F.); (T.M.S.); (D.A.-G.); (A.M.-P.); (B.M.-L.)
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13
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Rodríguez-Espigares I, Torrens-Fontanals M, Tiemann JKS, Aranda-García D, Ramírez-Anguita JM, Stepniewski TM, Worp N, Varela-Rial A, Morales-Pastor A, Medel-Lacruz B, Pándy-Szekeres G, Mayol E, Giorgino T, Carlsson J, Deupi X, Filipek S, Filizola M, Gómez-Tamayo JC, Gonzalez A, Gutiérrez-de-Terán H, Jiménez-Rosés M, Jespers W, Kapla J, Khelashvili G, Kolb P, Latek D, Marti-Solano M, Matricon P, Matsoukas MT, Miszta P, Olivella M, Perez-Benito L, Provasi D, Ríos S, R Torrecillas I, Sallander J, Sztyler A, Vasile S, Weinstein H, Zachariae U, Hildebrand PW, De Fabritiis G, Sanz F, Gloriam DE, Cordomi A, Guixà-González R, Selent J. GPCRmd uncovers the dynamics of the 3D-GPCRome. Nat Methods 2020; 17:777-787. [PMID: 32661425 DOI: 10.1038/s41592-020-0884-y] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 05/29/2020] [Indexed: 11/08/2022]
Abstract
G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.
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Affiliation(s)
- Ismael Rodríguez-Espigares
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Mariona Torrens-Fontanals
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Johanna K S Tiemann
- Institute of Medical Physics and Biophysics, Charite University Medicine Berlin, Berlin, Germany
- Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen, Germany
| | - David Aranda-García
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Juan Manuel Ramírez-Anguita
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Tomasz Maciej Stepniewski
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Nathalie Worp
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Alejandro Varela-Rial
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
- Acellera, Barcelona, Spain
| | - Adrián Morales-Pastor
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Brian Medel-Lacruz
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - Gáspár Pándy-Szekeres
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Eduardo Mayol
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Toni Giorgino
- Biophysics Institute, National Research Council of Italy, Milan, Italy
- Department of Biosciences, University of Milan, Milan, Italy
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Xavier Deupi
- Laboratory of Biomolecular Research, Paul Scherrer Institute (PSI), Villigen PSI, Switzerland
- Condensed Matter Theory Group, PSI, Villigen PSI, Switzerland
| | - Slawomir Filipek
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Marta Filizola
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - José Carlos Gómez-Tamayo
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Angel Gonzalez
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Hugo Gutiérrez-de-Terán
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Mireia Jiménez-Rosés
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Willem Jespers
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Jon Kapla
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - George Khelashvili
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, NY, USA
| | - Peter Kolb
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
| | - Dorota Latek
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Maria Marti-Solano
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Pierre Matricon
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Minos-Timotheos Matsoukas
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
- Department of Pharmacy, University of Patras, Patras, Greece
| | - Przemyslaw Miszta
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Mireia Olivella
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Laura Perez-Benito
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Davide Provasi
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Santiago Ríos
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Iván R Torrecillas
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Jessica Sallander
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Agnieszka Sztyler
- Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland
| | - Silvana Vasile
- Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Uppsala, Sweden
| | - Harel Weinstein
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, NY, USA
- Institute for Computational Biomedicine, Weill Cornell Medical College of Cornell University, New York, NY, USA
| | - Ulrich Zachariae
- Computational Biology, School of Life Sciences, University of Dundee, Dundee, UK
- Physics, School of Science and Engineering, University of Dundee, Dundee, UK
| | - Peter W Hildebrand
- Institute of Medical Physics and Biophysics, Charite University Medicine Berlin, Berlin, Germany
- Institute of Medical Physics and Biophysics, Medical University Leipzig, Leipzig, Sachsen, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Gianni De Fabritiis
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
- Acellera, Barcelona, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
| | - David E Gloriam
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Arnau Cordomi
- Laboratori de Medicina Computacional, Unitat de Bioestadistica, Facultat de Medicina, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Ramon Guixà-González
- Laboratory of Biomolecular Research, Paul Scherrer Institute (PSI), Villigen PSI, Switzerland.
- Condensed Matter Theory Group, PSI, Villigen PSI, Switzerland.
| | - Jana Selent
- Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute-Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain.
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