Identification of novel cannabinoid CB1 receptor antagonists by using virtual screening with a pharmacophore model.
CB1 receptor antagonists have proven to be clinically effective in treating obesity and related disorders. We report here the identification of a novel class of azetidinone CB1 antagonists by using virtual screening methods. For this purpose, we developed a pharmacophore model based on known representative CB1 antagonists and employed it to screen a database of about a half million Schering-Plough compounds. We applied a stepwise filtering protocol based on molecular weight, compound availability, and a modified rule-of-five to reduce the number of hits. We then combined Bayesian modeling and clustering techniques to select a final set of 420 compounds for in vitro testing. Five compounds were found to have >50% inhibition at 100 nM in a CB1 competitive binding assay and were further characterized by using both CB1 and CB2 assays. The most potent compound has a CB1 K i of 53 nM and >5-fold selectivity against the CB2 receptor.
Wang
Hongwu
H
Department of Structural Chemistry, CNS Biological Research, and CNS/CV Chemistry, Schering-Plough Research Institute, 2015 Galloping Hill Road, Kenilworth, New Jersey 07033, USA. hongwu.wang@spcorp.com
Duffy
Ruth A
RA
Boykow
George C
GC
Chackalamannil
Samuel
S
Madison
Vincent S
VS
D001499:Bayes Theorem; D004353:Drug Evaluation, Preclinical; D008958:Models, Molecular; D011485:Protein Binding; D043884:Receptor, Cannabinoid, CB1 / Q000037:antagonists & inhibitors* / Q000378:metabolism
D043884:Receptor, Cannabinoid, CB1