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Hu S, Wang D, Liu W, Wang Y, Chen J, Cai X. Apelin receptor dimer: Classification, future prospects, and pathophysiological perspectives. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167257. [PMID: 38795836 DOI: 10.1016/j.bbadis.2024.167257] [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: 02/08/2024] [Revised: 04/25/2024] [Accepted: 05/17/2024] [Indexed: 05/28/2024]
Abstract
Apelin receptor (APJ), a member of the class A family of G protein-coupled receptor (GPCR), plays a crucial role in regulating cardiovascular and central nervous systems function. APJ influences the onset and progression of various diseases such as hypertension, atherosclerosis, and cerebral stroke, making it an important target for drug development. Our preliminary findings indicate that APJ can form homodimers, heterodimers, or even higher-order oligomers, which participate in different signaling pathways and have distinct functions compared with monomers. APJ homodimers can serve as neuroprotectors against, and provide new pharmaceutical targets for vascular dementia (VD). This review article aims to summarize the structural characteristics of APJ dimers and their roles in physiology and pathology, as well as explore their potential pharmacological applications.
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Affiliation(s)
- Shujuan Hu
- School of Basic Medical Sciences, Shandong Second Medical University, Weifang, Shandong 261042, PR China
| | - Dexiu Wang
- School of Basic Medical Sciences, Shandong Second Medical University, Weifang, Shandong 261042, PR China
| | - Wenkai Liu
- School of Basic Medical Sciences, Shandong Second Medical University, Weifang, Shandong 261042, PR China
| | - Yixiang Wang
- School of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong 261042, PR China
| | - Jing Chen
- Neurobiology Institute, Jining Medical University, Jining, Shandong 272067, PR China; Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK.
| | - Xin Cai
- School of Basic Medical Sciences, Shandong Second Medical University, Weifang, Shandong 261042, PR China.
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Shen Q, Tang X, Wen X, Cheng S, Xiao P, Zang S, Shen D, Jiang L, Zheng Y, Zhang H, Xu H, Mao C, Zhang M, Hu W, Sun J, Zhang Y, Chen Z. Molecular Determinant Underlying Selective Coupling of Primary G-Protein by Class A GPCRs. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2310120. [PMID: 38647423 PMCID: PMC11187927 DOI: 10.1002/advs.202310120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/02/2024] [Indexed: 04/25/2024]
Abstract
G-protein-coupled receptors (GPCRs) transmit downstream signals predominantly via G-protein pathways. However, the conformational basis of selective coupling of primary G-protein remains elusive. Histamine receptors H2R and H3R couple with Gs- or Gi-proteins respectively. Here, three cryo-EM structures of H2R-Gs and H3R-Gi complexes are presented at a global resolution of 2.6-2.7 Å. These structures reveal the unique binding pose for endogenous histamine in H3R, wherein the amino group interacts with E2065.46 of H3R instead of the conserved D1143.32 of other aminergic receptors. Furthermore, comparative analysis of the H2R-Gs and H3R-Gi complexes reveals that the structural geometry of TM5/TM6 determines the primary G-protein selectivity in histamine receptors. Machine learning (ML)-based structuromic profiling and functional analysis of class A GPCR-G-protein complexes illustrate that TM5 length, TM5 tilt, and TM6 outward movement are key determinants of the Gs and Gi/o selectivity among the whole Class A family. Collectively, the findings uncover the common structural geometry within class A GPCRs that determines the primary Gs- and Gi/o-coupling selectivity.
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Affiliation(s)
- Qingya Shen
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Xinyan Tang
- Department of Pharmacology and Department of Pharmacy of the Second Affiliated HospitalNHC and CAMS Key Laboratory of Medical NeurobiologySchool of Basic Medical SciencesZhejiang University School of MedicineHangzhou310058China
| | - Xin Wen
- Advanced Medical Research InstituteMeili Lake Translational Research ParkCheeloo College of MedicineShandong UniversityJinan250012China
- Department of Biochemistry and Molecular BiologyShandong University School of MedicineJinan250012China
| | - Shizhuo Cheng
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
- College of Computer Science and TechnologyZhejiang UniversityHangzhou310027China
| | - Peng Xiao
- Advanced Medical Research InstituteMeili Lake Translational Research ParkCheeloo College of MedicineShandong UniversityJinan250012China
- Department of Biochemistry and Molecular BiologyShandong University School of MedicineJinan250012China
| | - Shao‐Kun Zang
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Dan‐Dan Shen
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Lei Jiang
- Department of Pharmacology and Department of Pharmacy of the Second Affiliated HospitalNHC and CAMS Key Laboratory of Medical NeurobiologySchool of Basic Medical SciencesZhejiang University School of MedicineHangzhou310058China
| | - Yanrong Zheng
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang ProvinceZhejiang Chinese Medical UniversityHangzhou310053China
| | - Huibing Zhang
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Haomang Xu
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Chunyou Mao
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- Department of General SurgerySir Run Run Shaw HospitalZhejiang University School of MedicineHangzhouZhejiang310016China
- Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and EquipmentZhejiang UniversityHangzhou310016China
| | - Min Zhang
- College of Computer Science and TechnologyZhejiang UniversityHangzhou310027China
| | - Weiwei Hu
- Department of Pharmacology and Department of Pharmacy of the Second Affiliated HospitalNHC and CAMS Key Laboratory of Medical NeurobiologySchool of Basic Medical SciencesZhejiang University School of MedicineHangzhou310058China
| | - Jin‐Peng Sun
- Advanced Medical Research InstituteMeili Lake Translational Research ParkCheeloo College of MedicineShandong UniversityJinan250012China
- Department of Biochemistry and Molecular BiologyShandong University School of MedicineJinan250012China
- Department of Physiology and Pathophysiology, School of Basic Medical SciencesPeking UniversityKey Laboratory of Molecular Cardiovascular ScienceMinistry of EducationBeijing100191China
| | - Yan Zhang
- Department of Pharmacology and Department of Pathology of Sir Run Run Shaw Hospital & Liangzhu LaboratoryHangzhou310058China
- MOE Frontier Science Center for Brain Research and Brain‐Machine IntegrationZhejiang University School of MedicineHangzhou310058China
| | - Zhong Chen
- Department of Pharmacology and Department of Pharmacy of the Second Affiliated HospitalNHC and CAMS Key Laboratory of Medical NeurobiologySchool of Basic Medical SciencesZhejiang University School of MedicineHangzhou310058China
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang ProvinceZhejiang Chinese Medical UniversityHangzhou310053China
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Mukhaleva E, Ma N, van der Velden WJC, Gogoshin G, Branciamore S, Bhattacharya S, Rodin AS, Vaidehi N. Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling. J Biol Chem 2024; 300:107362. [PMID: 38735478 PMCID: PMC11176750 DOI: 10.1016/j.jbc.2024.107362] [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: 11/03/2023] [Revised: 05/03/2024] [Accepted: 05/04/2024] [Indexed: 05/14/2024] Open
Abstract
Cooperative interactions in protein-protein interfaces demonstrate the interdependency or the linked network-like behavior and their effect on the coupling of proteins. Cooperative interactions also could cause ripple or allosteric effects at a distance in protein-protein interfaces. Although they are critically important in protein-protein interfaces, it is challenging to determine which amino acid pair interactions are cooperative. In this work, we have used Bayesian network modeling, an interpretable machine learning method, combined with molecular dynamics trajectories to identify the residue pairs that show high cooperativity and their allosteric effect in the interface of G protein-coupled receptor (GPCR) complexes with Gα subunits. Our results reveal six GPCR:Gα contacts that are common to the different Gα subtypes and show strong cooperativity in the formation of interface. Both the C terminus helix5 and the core of the G protein are codependent entities and play an important role in GPCR coupling. We show that a promiscuous GPCR coupling to different Gα subtypes, makes all the GPCR:Gα contacts that are specific to each Gα subtype (Gαs, Gαi, and Gαq). This work underscores the potential of data-driven Bayesian network modeling in elucidating the intricate dependencies and selectivity determinants in GPCR:G protein complexes, offering valuable insights into the dynamic nature of these essential cellular signaling components.
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Affiliation(s)
- Elizaveta Mukhaleva
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Ning Ma
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Wijnand J C van der Velden
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Grigoriy Gogoshin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA
| | - Sergio Branciamore
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Andrei S Rodin
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
| | - Nagarajan Vaidehi
- Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, Duarte, California, USA; Irell and Manella Graduate School of Biological Sciences, Beckman Research Institute of the City of Hope, Duarte, California, USA.
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Arora C, Matic M, Bisceglia L, Di Chiaro P, De Oliveira Rosa N, Carli F, Clubb L, Nemati Fard LA, Kargas G, Diaferia GR, Vukotic R, Licata L, Wu G, Natoli G, Gutkind JS, Raimondi F. The landscape of cancer-rewired GPCR signaling axes. CELL GENOMICS 2024; 4:100557. [PMID: 38723607 PMCID: PMC11099383 DOI: 10.1016/j.xgen.2024.100557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 02/17/2024] [Accepted: 04/10/2024] [Indexed: 05/15/2024]
Abstract
We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).
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Affiliation(s)
- Chakit Arora
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Marin Matic
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Luisa Bisceglia
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Pierluigi Di Chiaro
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milano, Italy
| | - Natalia De Oliveira Rosa
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Francesco Carli
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Lauren Clubb
- Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA
| | - Lorenzo Amir Nemati Fard
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Giorgos Kargas
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
| | - Giuseppe R Diaferia
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milano, Italy
| | - Ranka Vukotic
- Azienda Ospedaliero-Universitaria Pisana, Via Roma, 67, 56126 Pisa, Italy
| | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Guanming Wu
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Gioacchino Natoli
- Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milano, Italy
| | - J Silvio Gutkind
- Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Francesco Raimondi
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy; Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy.
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Madhu MK, Shewani K, Murarka RK. Biased Signaling in Mutated Variants of β 2-Adrenergic Receptor: Insights from Molecular Dynamics Simulations. J Chem Inf Model 2024; 64:449-469. [PMID: 38194225 DOI: 10.1021/acs.jcim.3c01481] [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: 01/10/2024]
Abstract
The molecular basis of receptor bias in G protein-coupled receptors (GPCRs) caused by mutations that preferentially activate specific intracellular transducers over others remains poorly understood. Two experimentally identified biased variants of β2-adrenergic receptors (β2AR), a prototypical GPCR, are a triple mutant (T68F, Y132A, and Y219A) and a single mutant (Y219A); the former bias the receptor toward the β-arrestin pathway by disfavoring G protein engagement, while the latter induces G protein signaling explicitly due to selection against GPCR kinases (GRKs) that phosphorylate the receptor as a prerequisite of β-arrestin binding. Though rigorous characterizations have revealed functional implications of these mutations, the atomistic origin of the observed transducer selectivity is not clear. In this study, we investigated the allosteric mechanism of receptor bias in β2AR using microseconds of all-atom Gaussian accelerated molecular dynamics (GaMD) simulations. Our observations reveal distinct rearrangements in transmembrane helices, intracellular loop 3, and critical residues R1313.50 and Y3267.53 in the conserved motifs D(E)RY and NPxxY for the mutant receptors, leading to their specific transducer interactions. Moreover, partial dissociation of G protein from the receptor core is observed in the simulations of the triple mutant in contrast to the single mutant and wild-type receptor. The reorganization of allosteric communications from the extracellular agonist BI-167107 to the intracellular receptor-transducer interfaces drives the conformational rearrangements responsible for receptor bias in the single and triple mutants. The molecular insights into receptor bias of β2AR presented here could improve the understanding of biased signaling in GPCRs, potentially opening new avenues for designing novel therapeutics with fewer side-effects and superior efficacy.
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Affiliation(s)
- Midhun K Madhu
- Department of Biological Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal, Madhya Pradesh 462066, India
| | - Kunal Shewani
- Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal, Madhya Pradesh 462066, India
| | - Rajesh K Murarka
- Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal, Madhya Pradesh 462066, India
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