{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Yuan P"],"funding":["CCR NIH HHS","Intramural NIH HHS","NCI NIH HHS"],"pagination":["137-49"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC3115459"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["78(1)"],"pubmed_abstract":["Conformational selection is a primary mechanism in biomolecular recognition. The conformational ensemble may determine the ability of a drug to compete with a native ligand for a receptor target. Traditional docking procedures which use one or few protein structures are limited and may not be able to represent a complex competition among closely related protein receptors in agonist and antagonist ensembles. Here, we test a protocol aimed at selecting a drug candidate based on its ability to synergistically bind to distinct conformational states. We demonstrate, for the case of estrogen receptor α (ERα) and estrogen receptor β (ERβ), that the functional outcome of ligand binding can be inferred from its ability to simultaneously bind both ERα and ERβ in agonist and antagonist conformations as calculated docking scores. Combining a conformational selection method with an experimental reporter gene system in yeast, we propose that several phytoestrogens can be novel estrogen receptor β selective agonists. Our work proposes a computational protocol to select estrogen receptor subtype selective agonists. Compared with other models, present method gives the best prediction in ligands' function."],"journal":["Chemical biology & drug design"],"pubmed_title":["Multiple-targeting and conformational selection in the estrogen receptor: computation and experiment."],"pmcid":["PMC3115459"],"funding_grant_id":["HHSN261200800001E","HHSN261200800001C"],"pubmed_authors":["Ma B","Yuan P","Zheng N","Huang J","Liang K","Nussinov R"],"additional_accession":[]},"is_claimable":false,"name":"Multiple-targeting and conformational selection in the estrogen receptor: computation and experiment.","description":"Conformational selection is a primary mechanism in biomolecular recognition. The conformational ensemble may determine the ability of a drug to compete with a native ligand for a receptor target. Traditional docking procedures which use one or few protein structures are limited and may not be able to represent a complex competition among closely related protein receptors in agonist and antagonist ensembles. Here, we test a protocol aimed at selecting a drug candidate based on its ability to synergistically bind to distinct conformational states. We demonstrate, for the case of estrogen receptor α (ERα) and estrogen receptor β (ERβ), that the functional outcome of ligand binding can be inferred from its ability to simultaneously bind both ERα and ERβ in agonist and antagonist conformations as calculated docking scores. Combining a conformational selection method with an experimental reporter gene system in yeast, we propose that several phytoestrogens can be novel estrogen receptor β selective agonists. Our work proposes a computational protocol to select estrogen receptor subtype selective agonists. Compared with other models, present method gives the best prediction in ligands' function.","dates":{"release":"2011-01-01T00:00:00Z","publication":"2011 Jul","modification":"2026-05-05T04:55:25.596Z","creation":"2026-04-07T21:23:28.013Z"},"accession":"S-EPMC3115459","cross_references":{"pubmed":["21443691"],"doi":["10.1111/j.1747-0285.2011.01119.x"]}}