Computational Prediction and Biochemical Analyses of New Inverse Agonists for the CB1 Receptor
Caitlin E. Scott, Kwang H. Ahn, Steven T. Graf, William A. Goddard, Debra A. Kendall, Ravinder Abrol
Abstract
Caitlin E. Scott, Kwang H. Ahn, Steven T. Graf, William A. Goddard, Debra A. Kendall, Ravinder Abrol
Abstract
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.
OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
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.
Key concepts: Inverse agonist, Cannabinoid receptor, Receptor, Computational biology, Chemistry, Neuroscience, Computer science, Biology