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GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach
GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protei...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356834/ https://www.ncbi.nlm.nih.gov/pubmed/37468476 http://dx.doi.org/10.1038/s41467-023-40045-y |
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author | Matic, Marin Miglionico, Pasquale Tatsumi, Manae Inoue, Asuka Raimondi, Francesco |
author_facet | Matic, Marin Miglionico, Pasquale Tatsumi, Manae Inoue, Asuka Raimondi, Francesco |
author_sort | Matic, Marin |
collection | PubMed |
description | GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protein complexes. Interface contact analysis recapitulates structural hallmarks associated with G-protein-coupling specificity, including TM5, TM6 and ICLs. We employ interface contacts as fingerprints to cluster G(s) vs G(i) complexes in an unsupervised fashion, suggesting that interface residues contribute to selective coupling. We experimentally confirm on a promiscuous receptor (CCKAR) that mutations of some of these specificity-determining positions bias the coupling selectivity. Interestingly, G(s)-GPCR complexes have more conserved interfaces, while G(i/o) proteins adopt a wider number of alternative docking poses, as assessed via structural alignments of representative 3D complexes. Binding energy calculations demonstrate that distinct structural properties of the complexes are associated to higher stability of G(s) than G(i/o) complexes. AlphaFold2 predictions of experimental binary complexes confirm several of these structural features and allow us to augment the structural coverage of poorly characterized complexes such as G(12/13). |
format | Online Article Text |
id | pubmed-10356834 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103568342023-07-21 GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach Matic, Marin Miglionico, Pasquale Tatsumi, Manae Inoue, Asuka Raimondi, Francesco Nat Commun Article GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protein complexes. Interface contact analysis recapitulates structural hallmarks associated with G-protein-coupling specificity, including TM5, TM6 and ICLs. We employ interface contacts as fingerprints to cluster G(s) vs G(i) complexes in an unsupervised fashion, suggesting that interface residues contribute to selective coupling. We experimentally confirm on a promiscuous receptor (CCKAR) that mutations of some of these specificity-determining positions bias the coupling selectivity. Interestingly, G(s)-GPCR complexes have more conserved interfaces, while G(i/o) proteins adopt a wider number of alternative docking poses, as assessed via structural alignments of representative 3D complexes. Binding energy calculations demonstrate that distinct structural properties of the complexes are associated to higher stability of G(s) than G(i/o) complexes. AlphaFold2 predictions of experimental binary complexes confirm several of these structural features and allow us to augment the structural coverage of poorly characterized complexes such as G(12/13). Nature Publishing Group UK 2023-07-19 /pmc/articles/PMC10356834/ /pubmed/37468476 http://dx.doi.org/10.1038/s41467-023-40045-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Matic, Marin Miglionico, Pasquale Tatsumi, Manae Inoue, Asuka Raimondi, Francesco GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title | GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title_full | GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title_fullStr | GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title_full_unstemmed | GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title_short | GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach |
title_sort | gpcrome-wide analysis of g-protein-coupling diversity using a computational biology approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356834/ https://www.ncbi.nlm.nih.gov/pubmed/37468476 http://dx.doi.org/10.1038/s41467-023-40045-y |
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