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

Scott, Caitlin E. and Ahn, Kwang H. and Graf, Steven T. and Goddard, William A., III and Kendall, Debra A. and Abrol, Ravinder (2016) Computational Prediction and Biochemical Analyses of New Inverse Agonists for the CB1 Receptor. Journal of Chemical Information and Modeling, 56 (1). pp. 201-212. ISSN 1549-9596 . PMCID PMC4863456. http://resolver.caltech.edu/CaltechAUTHORS:20160111-104516976

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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.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1021/acs.jcim.5b00581DOIArticle
http://pubs.acs.org/doi/10.1021/acs.jcim.5b00581PublisherArticle
http://pubs.acs.org/doi/suppl/10.1021/acs.jcim.5b00581PublisherSupporting Information
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4863456/PubMed CentralArticle
ORCID:
AuthorORCID
Goddard, William A., III0000-0003-0097-5716
Abrol, Ravinder0000-0001-7333-6793
Additional Information:© 2015 American Chemical Society. ACS AuthorChoice - This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes. Received: September 22, 2015. Publication Date (Web): December 3, 2015. This work was supported in part by National Institutes of Health Grants DA020763 and DA038804 (to D.A.K.). C.E.S., W.A.G., and R.A. were partially supported by grants from NIH (R01NS073115 and R01AI040567). Author Contributions: The manuscript was written through contributions of all authors. C.E.S. designed experiments, performed experiments, analyzed data, and wrote the paper. K.A.H. designed experiments, performed experiments, analyzed data, and wrote the paper. S.T.G. designed experiments, performed experiments, analyzed data, and wrote the paper. W.A.G. designed experiments, analyzed data, and wrote the paper. D.A.K. designed experiments, analyzed data, and wrote the paper. R.A. designed experiments, analyzed data, and wrote the paper. The authors declare no competing financial interest.
Funders:
Funding AgencyGrant Number
NIHDA020763
NIHDA038804
NIHR01NS073115
NIHR01AI040567
PubMed Central ID:PMC4863456
Record Number:CaltechAUTHORS:20160111-104516976
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160111-104516976
Official Citation: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, III, Debra A. Kendall, and Ravinder Abrol Journal of Chemical Information and Modeling 2016 56 (1), 201-212 DOI: 10.1021/acs.jcim.5b00581
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:63543
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:13 Jan 2016 00:13
Last Modified:02 Mar 2017 22:04

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