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Multiple‐Targeting and Conformational Selection in the Estrogen Receptor: Computation and Experiment
Author(s) -
Yuan Peng,
Liang Kaiwei,
Ma Buyong,
Zheng Nan,
Nussinov Ruth,
Huang Jian
Publication year - 2011
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2011.01119.x
Subject(s) - estrogen receptor , selection (genetic algorithm) , computation , computational biology , estrogen , estrogen receptor alpha , chemistry , computer science , bioinformatics , biology , algorithm , artificial intelligence , genetics , cancer , breast cancer
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.