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Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for...

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Detalles Bibliográficos
Autores principales: Vidad, Ashley Ryan, Macaspac, Stephen, Ng, Ho Leung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475542/
https://www.ncbi.nlm.nih.gov/pubmed/34631323
http://dx.doi.org/10.7717/peerj.12219
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author Vidad, Ashley Ryan
Macaspac, Stephen
Ng, Ho Leung
author_facet Vidad, Ashley Ryan
Macaspac, Stephen
Ng, Ho Leung
author_sort Vidad, Ashley Ryan
collection PubMed
description GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.
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spelling pubmed-84755422021-10-08 Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation Vidad, Ashley Ryan Macaspac, Stephen Ng, Ho Leung PeerJ Biochemistry GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling. PeerJ Inc. 2021-09-24 /pmc/articles/PMC8475542/ /pubmed/34631323 http://dx.doi.org/10.7717/peerj.12219 Text en © 2021 Vidad et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Biochemistry
Vidad, Ashley Ryan
Macaspac, Stephen
Ng, Ho Leung
Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title_full Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title_fullStr Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title_full_unstemmed Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title_short Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation
title_sort locating ligand binding sites in g-protein coupled receptors using combined information from docking and sequence conservation
topic Biochemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8475542/
https://www.ncbi.nlm.nih.gov/pubmed/34631323
http://dx.doi.org/10.7717/peerj.12219
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