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• W3204207846 abstract "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." @default.
• W3204207846 created "2021-10-11" @default.
• W3204207846 creator A5044312129 @default.
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• W3204207846 creator A5086812348 @default.
• W3204207846 date "2021-09-24" @default.
• W3204207846 modified "2023-10-16" @default.
• W3204207846 title "Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation" @default.
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• W3204207846 doi "https://doi.org/10.7717/peerj.12219" @default.
• W3204207846 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8475542" @default.
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• W3204207846 hasPublicationYear "2021" @default.
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