Published January 25, 2016 | Version Published + Supplemental Material
Journal Article Open

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

  • 1. ROR icon California Institute of Technology
  • 2. ROR icon University of Connecticut

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.

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.

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Additional details

Identifiers

PMCID
PMC4863456
Eprint ID
63543
Resolver ID
CaltechAUTHORS:20160111-104516976

Funding

NIH
DA020763
NIH
DA038804
NIH
R01NS073115
NIH
R01AI040567

Dates

Created
2016-01-13
Created from EPrint's datestamp field
Updated
2022-05-13
Created from EPrint's last_modified field