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串联同源建模与 3D-QSAR 分析:描绘人类 CB2 受体激动剂结合位点的计算方法。

Homology modeling in tandem with 3D-QSAR analyses: a computational approach to depict the agonist binding site of the human CB2 receptor.

机构信息

Dipartimento di Scienze Farmaceutiche, Università di Genova, Viale Benedetto XV n 3, 16132 Genova, Italy.

出版信息

Eur J Med Chem. 2011 Sep;46(9):4489-505. doi: 10.1016/j.ejmech.2011.07.023. Epub 2011 Jul 23.

DOI:10.1016/j.ejmech.2011.07.023
PMID:21835510
Abstract

CB2 receptor belongs to the large family of G-protein coupled receptors (GPCRs) controlling a wide variety of signal transduction. The recent crystallographic determination of human β2 adrenoreceptor and its high sequence similarity with human CB2 receptor (hCB2) prompted us to compute a theoretical model of hCB2 based also on β2 adrenoreceptor coordinates. This model has been employed to perform docking and molecular dynamic simulations on WIN-55,212-2 (CB2 agonist commonly used in binding experiments), in order to identify the putative CB2 receptor agonist binding site, followed by molecular docking studies on a series of indol-3-yl-tetramethylcyclopropyl ketone derivatives, a novel class of potent CB2 agonists. Successively, docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were also performed. The CoMSIA model resulted to be the more predictive, showing r(ncv)(2) = 0.96, r(cv)(2) = 0.713, SEE = 0.193, F = 125.223, and r(2)(pred) = 0.78. The obtained 3D-QSAR models allowed us to derive more complete guidelines for the design of new analogues with improved potency so as to synthesize new indoles showing high CB2 affinity.

摘要

CB2 受体属于 G 蛋白偶联受体 (GPCRs) 大家族,可控制多种信号转导。最近人类β2 肾上腺素能受体的晶体结构测定及其与人 CB2 受体 (hCB2) 的高序列相似性促使我们根据β2 肾上腺素能受体坐标计算 hCB2 的理论模型。该模型已用于对 WIN-55,212-2 (常用于结合实验的 CB2 激动剂) 进行对接和分子动力学模拟,以确定潜在的 CB2 受体激动剂结合位点,然后对一系列吲哚-3-基-四甲基环丙基酮衍生物进行分子对接研究,这是一类新型强效 CB2 激动剂。随后,还进行了基于对接的比较分子场分析 (CoMFA) 和比较分子相似性指数分析 (CoMSIA) 研究。CoMSIA 模型更具预测性,r(ncv)(2) = 0.96、r(cv)(2) = 0.713、SEE = 0.193、F = 125.223 和 r(2)(pred) = 0.78。获得的 3D-QSAR 模型使我们能够得出更完整的设计新类似物的指导原则,以提高效力,从而合成具有高 CB2 亲和力的新型吲哚。

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