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Tse LH, Cheung ST, Lee S, Wong YH. Real-Time Determination of Intracellular cAMP Reveals Functional Coupling of G s Protein to the Melatonin MT 1 Receptor. Int J Mol Sci 2024; 25:2919. [PMID: 38474167 DOI: 10.3390/ijms25052919] [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: 01/25/2024] [Revised: 02/23/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Melatonin is a neuroendocrine hormone that regulates the circadian rhythm and many other physiological processes. Its functions are primarily exerted through two subtypes of human melatonin receptors, termed melatonin type-1 (MT1) and type-2 (MT2) receptors. Both MT1 and MT2 receptors are generally classified as Gi-coupled receptors owing to their well-recognized ability to inhibit cAMP accumulation in cells. However, it remains an enigma as to why melatonin stimulates cAMP production in a number of cell types that express the MT1 receptor. To address if MT1 can dually couple to Gs and Gi proteins, we employed a highly sensitive luminescent biosensor (GloSensorTM) to monitor the real-time changes in the intracellular cAMP level in intact live HEK293 cells that express MT1 and/or MT2. Our results demonstrate that the activation of MT1, but not MT2, leads to a robust enhancement on the forskolin-stimulated cAMP formation. In contrast, the activation of either MT1 or MT2 inhibited cAMP synthesis driven by the activation of the Gs-coupled β2-adrenergic receptor, which is consistent with a typical Gi-mediated response. The co-expression of MT1 with Gs enabled melatonin itself to stimulate cAMP production, indicating a productive coupling between MT1 and Gs. The possible existence of a MT1-Gs complex was supported through molecular modeling as the predicted complex exhibited structural and thermodynamic characteristics that are comparable to that of MT1-Gi. Taken together, our data reveal that MT1, but not MT2, can dually couple to Gs and Gi proteins, thereby enabling the bi-directional regulation of adenylyl cyclase to differentially modulate cAMP levels in cells that express different complements of MT1, MT2, and G proteins.
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Affiliation(s)
- Lap Hang Tse
- Division of Life Science and the Biotechnology Research Institute, Hong Kong University of Science and Technology, Hong Kong, China
| | - Suet Ting Cheung
- Division of Life Science and the Biotechnology Research Institute, Hong Kong University of Science and Technology, Hong Kong, China
| | - Seayoung Lee
- Division of Life Science and the Biotechnology Research Institute, Hong Kong University of Science and Technology, Hong Kong, China
| | - Yung Hou Wong
- Division of Life Science and the Biotechnology Research Institute, Hong Kong University of Science and Technology, Hong Kong, China
- State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, Hong Kong University of Science and Technology, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, 17 Science Park West Avenue, Hong Kong Science Park, Shatin, Hong Kong, China
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2
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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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Yang PC, Rose A, DeMarco KR, Dawson JRD, Han Y, Jeng MT, Harvey RD, Santana LF, Ripplinger CM, Vorobyov I, Lewis TJ, Clancy CE. A multiscale predictive digital twin for neurocardiac modulation. J Physiol 2023; 601:3789-3812. [PMID: 37528537 PMCID: PMC10528740 DOI: 10.1113/jp284391] [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: 01/17/2023] [Accepted: 07/11/2023] [Indexed: 08/03/2023] Open
Abstract
Cardiac function is tightly regulated by the autonomic nervous system (ANS). Activation of the sympathetic nervous system increases cardiac output by increasing heart rate and stroke volume, while parasympathetic nerve stimulation instantly slows heart rate. Importantly, imbalance in autonomic control of the heart has been implicated in the development of arrhythmias and heart failure. Understanding of the mechanisms and effects of autonomic stimulation is a major challenge because synapses in different regions of the heart result in multiple changes to heart function. For example, nerve synapses on the sinoatrial node (SAN) impact pacemaking, while synapses on contractile cells alter contraction and arrhythmia vulnerability. Here, we present a multiscale neurocardiac modelling and simulator tool that predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the ANS on the cardiac SAN and ventricular myocardium. The model includes a layered representation of the ANS and reproduces firing properties measured experimentally. Model parameters are derived from experiments and atomistic simulations. The model is a first prototype of a digital twin that is applied to make predictions across all system scales, from subcellular signalling to pacemaker frequency to tissue level responses. We predict conditions under which autonomic imbalance induces proarrhythmia and can be modified to prevent or inhibit arrhythmia. In summary, the multiscale model constitutes a predictive digital twin framework to test and guide high-throughput prediction of novel neuromodulatory therapy. KEY POINTS: A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons generates firing patterns in close agreement with experiment. A key feature of the neurocardiac computational model is the connection between the autonomic nervous system and both pacemaker and contractile cells, where modification to pacemaker frequency drives initiation of electrical signals in the contractile cells. We utilized atomic-scale molecular dynamics simulations to predict the association and dissociation rates of noradrenaline with the β-adrenergic receptor. Multiscale predictions demonstrate how autonomic imbalance may increase proclivity to arrhythmias or be used to terminate arrhythmias. The model serves as a first step towards a digital twin for predicting neuromodulation to prevent or reduce disease.
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Affiliation(s)
- Pei-Chi Yang
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | - Adam Rose
- Department of Mathematics, University of California Davis, Davis, CA
| | - Kevin R. DeMarco
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | - John R. D. Dawson
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | - Yanxiao Han
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | - Mao-Tsuen Jeng
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | | | - L. Fernando Santana
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | | | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
| | - Timothy J. Lewis
- Department of Mathematics, University of California Davis, Davis, CA
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA
- Center for Precision Medicine and Data Science, University of California Davis, Sacramento, CA
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Han Y, Dawson JRD, DeMarco KR, Rouen KC, Bekker S, Yarov-Yarovoy V, Clancy CE, Xiang YK, Vorobyov I. Elucidation of a dynamic interplay between a beta-2 adrenergic receptor, its agonist, and stimulatory G protein. Proc Natl Acad Sci U S A 2023; 120:e2215916120. [PMID: 36853938 PMCID: PMC10013855 DOI: 10.1073/pnas.2215916120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 01/27/2023] [Indexed: 03/01/2023] Open
Abstract
G protein-coupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligand-induced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta-2 adrenergic receptor (β2AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (Gs). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to β2AR by Gs protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from β2AR and the conformational interconversions of Gs between closed and open conformations in the NE(+)-β2AR-Gs ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter Gs α subunit (Gsα) conformational transitions. Our simulations showed that the interdomain movement and the stacking of Gsα α1 and α5 helices are significant for increasing the distance between the Gsα and β2AR, which may indicate a partial dissociation of Gsα The distance increase commences when Gsα is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of β2AR interacting with Gsα, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCR-mediated modulation of G protein activation.
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Affiliation(s)
- Yanxiao Han
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
| | - John R. D. Dawson
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Biophysics Graduate Group, University of California, Davis, CA95616
| | - Kevin R. DeMarco
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
| | - Kyle C. Rouen
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Biophysics Graduate Group, University of California, Davis, CA95616
| | - Slava Bekker
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Department of Science and Engineering, American River College, Sacramento, CA95841
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Department of Anesthesiology and Pain Medicine, University of California, Davis, CA95616
| | - Colleen E. Clancy
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Department of Pharmacology, University of California, Davis, CA95616
| | - Yang K. Xiang
- Department of Pharmacology, University of California, Davis, CA95616
- VA Northern California Health Care System, Mather, CA95655
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California, Davis, CA95616
- Department of Pharmacology, University of California, Davis, CA95616
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Barreto CAV, Baptista SJ, Preto AJ, Silvério D, Melo R, Moreira IS. Decoding Partner Specificity of Opioid Receptor Family. Front Mol Biosci 2021; 8:715215. [PMID: 34621786 PMCID: PMC8490921 DOI: 10.3389/fmolb.2021.715215] [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: 05/26/2021] [Accepted: 08/10/2021] [Indexed: 11/13/2022] Open
Abstract
This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (μ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.
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Affiliation(s)
- Carlos A. V. Barreto
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal
- PhD Programme in Experimental Biology and Biomedicine, Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Coimbra, Portugal
| | - Salete J. Baptista
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, University of Coimbra, Coimbra, Portugal
| | - António J. Preto
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal
- PhD Programme in Experimental Biology and Biomedicine, Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Coimbra, Portugal
| | - Daniel Silvério
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal
| | - Rita Melo
- CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Cantanhede, Portugal
- Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Irina S. Moreira
- Department of Life Sciences, University of Coimbra, Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology, Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
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6
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Höring C, Conrad M, Söldner CA, Wang J, Sticht H, Strasser A, Miao Y. Specific Engineered G Protein Coupling to Histamine Receptors Revealed from Cellular Assay Experiments and Accelerated Molecular Dynamics Simulations. Int J Mol Sci 2021; 22:10047. [PMID: 34576210 PMCID: PMC8467750 DOI: 10.3390/ijms221810047] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 09/15/2021] [Accepted: 09/15/2021] [Indexed: 01/29/2023] Open
Abstract
G protein-coupled receptors (GPCRs) are targets of extracellular stimuli and hence occupy a key position in drug discovery. By specific and not yet fully elucidated coupling profiles with α subunits of distinct G protein families, they regulate cellular responses. The histamine H2 and H4 receptors (H2R and H4R) are prominent members of Gs- and Gi-coupled GPCRs. Nevertheless, promiscuous G protein and selective Gi signaling have been reported for the H2R and H4R, respectively, the molecular mechanism of which remained unclear. Using a combination of cellular experimental assays and Gaussian accelerated molecular dynamics (GaMD) simulations, we investigated the coupling profiles of the H2R and H4R to engineered mini-G proteins (mG). We obtained coupling profiles of the mGs, mGsi, or mGsq proteins to the H2R and H4R from the mini-G protein recruitment assays using HEK293T cells. Compared to H2R-mGs expressing cells, histamine responses were weaker (pEC50, Emax) for H2R-mGsi and -mGsq. By contrast, the H4R selectively bound to mGsi. Similarly, in all-atom GaMD simulations, we observed a preferential binding of H2R to mGs and H4R to mGsi revealed by the structural flexibility and free energy landscapes of the complexes. Although the mG α5 helices were consistently located within the HR binding cavity, alternative binding orientations were detected in the complexes. Due to the specific residue interactions, all mG α5 helices of the H2R complexes adopted the Gs-like orientation toward the receptor transmembrane (TM) 6 domain, whereas in H4R complexes, only mGsi was in the Gi-like orientation toward TM2, which was in agreement with Gs- and Gi-coupled GPCRs structures resolved by X-ray/cryo-EM. These cellular and molecular insights support (patho)physiological profiles of the histamine receptors, especially the hitherto little studied H2R function in the brain, as well as of the pharmacological potential of H4R selective drugs.
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Affiliation(s)
- Carina Höring
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93040 Regensburg, Germany
| | - Marcus Conrad
- Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany
| | - Christian A Söldner
- Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany
| | - Jinan Wang
- Department of Computational Biology and Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA
| | - Heinrich Sticht
- Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054 Erlangen, Germany
- Erlangen National High Performance Computing Center (NHR@FAU), Friedrich-Alexander-University Erlangen-Nürnberg (FAU), 91058 Erlangen, Germany
| | - Andrea Strasser
- Institute of Pharmacy, Faculty of Chemistry and Pharmacy, University of Regensburg, 93040 Regensburg, Germany
| | - Yinglong Miao
- Department of Computational Biology and Molecular Biosciences, University of Kansas, Lawrence, KS 66047, USA
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Nubbemeyer B, Pepanian A, Paul George AA, Imhof D. Strategies towards Targeting Gαi/s Proteins: Scanning of Protein-Protein Interaction Sites To Overcome Inaccessibility. ChemMedChem 2021; 16:1696-1715. [PMID: 33615736 PMCID: PMC8252600 DOI: 10.1002/cmdc.202100039] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Indexed: 12/16/2022]
Abstract
Heterotrimeric G proteins are classified into four subfamilies and play a key role in signal transduction. They transmit extracellular signals to intracellular effectors subsequent to the activation of G protein-coupled receptors (GPCRs), which are targeted by over 30 % of FDA-approved drugs. However, addressing G proteins as drug targets represents a compelling alternative, for example, when G proteins act independently of the corresponding GPCRs, or in cases of complex multifunctional diseases, when a large number of different GPCRs are involved. In contrast to Gαq, efforts to target Gαi/s by suitable chemical compounds has not been successful so far. Here, a comprehensive analysis was conducted examining the most important interface regions of Gαi/s with its upstream and downstream interaction partners. By assigning the existing compounds and the performed approaches to the respective interfaces, the druggability of the individual interfaces was ranked to provide perspectives for selective targeting of Gαi/s in the future.
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Affiliation(s)
- Britta Nubbemeyer
- Pharmaceutical Biochemistry and BioanalyticsPharmaceutical InstituteUniversity of BonnAn der Immenburg 453121BonnGermany
| | - Anna Pepanian
- Pharmaceutical Biochemistry and BioanalyticsPharmaceutical InstituteUniversity of BonnAn der Immenburg 453121BonnGermany
| | | | - Diana Imhof
- Pharmaceutical Biochemistry and BioanalyticsPharmaceutical InstituteUniversity of BonnAn der Immenburg 453121BonnGermany
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Barreto CAV, Baptista SJ, Preto AJ, Matos-Filipe P, Mourão J, Melo R, Moreira I. Prediction and targeting of GPCR oligomer interfaces. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 169:105-149. [PMID: 31952684 DOI: 10.1016/bs.pmbts.2019.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.
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Affiliation(s)
- Carlos A V Barreto
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Salete J Baptista
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, CTN, LRS, Portugal
| | - António José Preto
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Pedro Matos-Filipe
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Joana Mourão
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal
| | - Rita Melo
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, CTN, LRS, Portugal
| | - Irina Moreira
- Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Science and Technology Faculty, University of Coimbra, Coimbra, Portugal.
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9
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Wang J, Miao Y. Mechanistic Insights into Specific G Protein Interactions with Adenosine Receptors. J Phys Chem B 2019; 123:6462-6473. [PMID: 31283874 DOI: 10.1021/acs.jpcb.9b04867] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Coupling between G-protein-coupled receptors (GPCRs) and the G proteins is a key step in cellular signaling. Despite extensive experimental and computational studies, the mechanism of specific GPCR-G protein coupling remains poorly understood. This has greatly hindered effective drug design of GPCRs that are primary targets of ∼1/3 of currently marketed drugs. Here, we have employed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method to decipher the mechanism of the GPCR-G protein interactions. Adenosine receptors (ARs) were used as model systems based on very recently determined cryo-EM structures of the A1AR and A2AAR coupled with the Gi and Gs proteins, respectively. Changing the Gi protein to the Gs led to increased fluctuations in the A1AR and agonist adenosine (ADO), while agonist 5'-N-ethylcarboxamidoadenosine (NECA) binding in the A2AAR could be still stabilized upon changing the Gs protein to the Gi. Free energy calculations identified one stable low-energy conformation for each of the A1AR-Gi and A2AAR-Gs complexes as in the cryo-EM structures, similarly for the A2AAR-Gi complex. In contrast, the ADO agonist and Gs protein sampled multiple conformations in the A1AR-Gs system. GaMD simulations thus indicated that the A1AR preferred to couple with the Gi protein to the Gs, while the A2AAR could couple with both the Gs and Gi proteins, being highly consistent with experimental findings of the ARs. More importantly, detailed analysis of the atomic simulations showed that the specific AR-G protein coupling resulted from remarkably complementary residue interactions at the protein interface, involving mainly the receptor transmembrane 6 helix and the Gα α5 helix and α4-β6 loop. In summary, the GaMD simulations have provided unprecedented insights into the dynamic mechanism of specific GPCR-G protein interactions at an atomistic level.
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Affiliation(s)
- Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences , University of Kansas , Lawrence , Kansas 66047 , United States
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences , University of Kansas , Lawrence , Kansas 66047 , United States
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