Abstract
Natural products are an abundant source of potential drugs, and their diversity makes them a rich and viable prospective source of bioactive cannabinoid ligands. Cannabinoid receptor 1 (CB1) antagonists are clinically established and well documented as potential therapeutics for treating obesity, obesity-related cardiometabolic disorders, pain, and drug/substance abuse, but their associated CNS-mediated adverse effects hinder the development of potential new drugs and no such drug is currently on the market. This limitation amplifies the need for new agents with reduced or no CNS-mediated side effects. We are interested in the discovery of new natural product chemotypes as CB1 antagonists, which may serve as good starting points for further optimization towards the development of CB1 therapeutics. In search of new chemotypes as CB1 antagonists, we screened the in silico purchasable natural products subset of the ZINC12 database against our reported CB1 receptor model using the structure-based virtual screening (SBVS) approach. A total of 18 out of 192 top-scoring virtual hits, selected based on structural diversity and key protein–ligand interactions, were purchased and subjected to in vitro screening in competitive radioligand binding assays. The in vitro screening yielded seven compounds exhibiting >50% displacement at 10 μM concentration, and further binding affinity (Ki and IC50) and functional data revealed compound 16 as a potent and selective CB1 inverse agonist (Ki = 121 nM and EC50 = 128 nM) while three other compounds—2, 12, and 18—were potent but nonselective CB1 ligands with low micromolar binding affinity (Ki). In order to explore the structure–activity relationship for compound 16, we further purchased compounds with >80% similarity to compound 16, screened them for CB1 and CB2 activities, and found two potent compounds with sub-micromolar activities. Most importantly, these bioactive compounds represent structurally new natural product chemotypes in the area of cannabinoid research and could be considered for further structural optimization as CB1 ligands.
Highlights
G-protein coupled receptors (GPCRs) represent the largest single group of targets for approximately 40% of FDA-approved drugs [1,2]
We previously reported an antagonist-bound Cannabinoid receptor 1 (CB1) homology model based on the bovine rhodopsin previously reported an antagonist-bound CB1 homology model based on the bovine templateWe structure
This model was understood to represent the inactive considering a set of known active and inactive CB1 antagonists. This model was understood to state of the CB1 receptor, following various characteristics of the inactive GPCR state identified through represent the inactive state of the CB1 receptor, following various characteristics of the inactive
Summary
G-protein coupled receptors (GPCRs) represent the largest single group of targets for approximately 40% of FDA-approved drugs [1,2]. Functional selectivity among these targets is highly recommended for successful drug discovery. CB1 receptor antagonists are clinically established to be effective in treating obesity [14], obesity-related cardiometabolic disorders [15], and substance abuse [16,17]. The druggability of CB1 receptor antagonists has been clinically validated through the drug rimonabant (SR141716A) [18], which showed progressive and prolonged weight loss in overweight patients [19] and improvements in associated metabolic disorders [20,21] in phase
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