Computational Prediction and Biochemical Analyses of New Inverse Agonists for the CB1 Receptor

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• 作者：Caitlin E. Scott ; Kwang H. Ahn ; Steven T. Graf ; William A. Goddard III ; Debra A. Kendall ; Ravinder Abrol
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2016
• 出版时间：January 25, 2016
• 年：2016
• 卷：56
• 期：1
• 页码：201-212
• 全文大小：610K
• ISSN：1549-960X

文摘

Human cannabinoid type 1 (CB1) G-protein coupled receptor is a potential therapeutic target for obesity. The previously predicted and experimentally validated ensemble of ligand-free conformations of CB1 [Scott, C. E. et al. Protein Sci. 2013, 22, 101?113; Ahn, K. H. et al. Proteins 2013, 81, 1304–1317] are used here to predict the binding sites for known CB1-selective inverse agonists including rimonabant and its seven known derivatives. This binding pocket, which differs significantly from previously published models, is used to identify 16 novel compounds expected to be CB1 inverse agonists by exploiting potential new interactions. We show experimentally that two of these compounds exhibit inverse agonist properties including inhibition of basal and agonist-induced G-protein coupling activity, as well as an enhanced level of CB1 cell surface localization. This demonstrates the utility of using the predicted binding sites for an ensemble of CB1 receptor structures for designing new CB1 inverse agonists.