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Identification of Selective ERR? Inverse Agonists.

ABSTRACT: GSK5182 (4) is currently one of the lead compounds for the development of estrogen-related receptor gamma (ERR?) inverse agonists. Here, we report the design, synthesis, pharmacological and in vitro absorption, distribution, metabolism, excretion, toxicity (ADMET) properties of a series of compounds related to 4. Starting from 4, a series of analogs were structurally modified and their ERR? inverse agonist activity was measured. A key pharmacophore feature of this novel class of ligands is the introduction of a heterocyclic group for A-ring substitution in the core scaffold. Among the tested compounds, several of them are potent ERR? inverse agonists as determined by binding and functional assays. The most promising compound, 15g, had excellent binding selectivity over related subtypes (IC50 = 0.44, >10, >10, and 10 ?M at the ERR?, ERR?, ERR?, and ER? subtypes, respectively). Compound 15g also resulted in 95% transcriptional repression at a concentration of 10 ?M, while still maintaining an acceptable in vitro ADMET profile. This novel class of ERR? inverse agonists shows promise in the development of drugs targeting ERR?-related diseases.

SUBMITTER: Kim J

PROVIDER: S-EPMC6273807 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Identification of Selective ERRγ Inverse Agonists.

Kim Jina J Im Chun Young CY Yoo Eun Kyung EK Ma Min Jung MJ Kim Sang-Bum SB Hong Eunmi E Chin Jungwook J Hwang Hayoung H Lee Sungwoo S Kim Nam Doo ND Jeon Jae-Han JH Lee In-Kyu IK Jeon Yong Hyun YH Choi Hueng-Sik HS Kim Seong Heon SH Cho Sung Jin SJ

Molecules (Basel, Switzerland) 20160112 1

GSK5182 (4) is currently one of the lead compounds for the development of estrogen-related receptor gamma (ERRγ) inverse agonists. Here, we report the design, synthesis, pharmacological and in vitro absorption, distribution, metabolism, excretion, toxicity (ADMET) properties of a series of compounds related to 4. Starting from 4, a series of analogs were structurally modified and their ERRγ inverse agonist activity was measured. A key pharmacophore feature of this novel class of ligands is the i ...[more]

PMID: 26771593

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Project description: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 ?M 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.

Dataset Information

Identification of Selective ERR? Inverse Agonists.

Publications

Identification of Selective ERRγ Inverse Agonists.

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