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用于GPCR抗肥胖靶点的配体的计算机辅助识别

Computer-aided identification of ligands for GPCR anti-obesity targets.

作者信息

Min Kyung Hoon, Yoo Jakyung, Park Hyun-Ju

机构信息

College of Pharmacy, Chung-Ang University, Seoul 156-756, Korea.

出版信息

Curr Top Med Chem. 2009;9(6):539-53. doi: 10.2174/156802609788897871.

Abstract

Many orphan G-protein-coupled receptors (GPCR) have emerged as potential obesity targets. The authors are interested in the computer-aided discovery and development of small molecule anti-obesity agents targeting GPCR. Computational modeling studies have mainly been conducted on ghrelin receptor (GHS-R), melanocortin 4-receptor (MC4R), melanin-concentrating hormone 1 receptor (MCH1R) and cannabinoid 1 receptor (CB1R) in recent publications. Here, a homology modeling strategy for these receptors will be introduced, and the key structural features of their active and inactive conformations will be reviewed. In addition, the authors describe the uses of virtual screening methods to identify novel antagonists of MCH1R and CB1R, which provide valuable examples of the computer-aided design and structural optimization of GPCR ligands.

摘要

许多孤儿G蛋白偶联受体(GPCR)已成为潜在的肥胖治疗靶点。作者对靶向GPCR的小分子抗肥胖药物的计算机辅助发现和开发感兴趣。最近的出版物中,计算建模研究主要针对胃饥饿素受体(GHS-R)、黑皮质素4受体(MC4R)、促黑素细胞激素1受体(MCH1R)和大麻素1受体(CB1R)进行。在此,将介绍这些受体的同源建模策略,并综述其活性和非活性构象的关键结构特征。此外,作者描述了使用虚拟筛选方法来鉴定MCH1R和CB1R的新型拮抗剂,这些方法为GPCR配体的计算机辅助设计和结构优化提供了有价值的实例。

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