毒蕈碱受体M1-M5抑制的广义预测模型

A. Mikurova, Vladlen S. Skvortsov, V. Grigoryev
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引用次数: 1

摘要

建立了一种评估潜在配体对人乙酰胆碱毒蕈碱受体M1-M5抑制常数(Ki)值的通用预测模型。我们利用了人类M1、M2、M4和M5受体的三维结构信息,以及基于大鼠M3受体结构根据同源性构建的M3受体模型。通过分子对接的方式构建了一组已知抑制剂与目标受体的复合物,并使用了另一种选择:被测抑制剂的4个药效团点与噻托溴铵的空间位置重合,因为它们在晶体结构中的位置是已知的。对于5种类型的M受体,选取了Ki值已知的199个复合物。基于MM-PBSA/MM-GBSA方法对这些配合物进行分子动力学模拟得到的数据,计算了它们的能量特性。它们被用作线性回归方程中的自变量,用于pKi值预测。广义方程的R2预测值为0.7,平均预测误差为0.55对数单位,范围为pKi=4.7。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized predictive model of estimation of inhibition of muscarinic receptors M1-M5
A general predictive model for assessing the inhibition constant (Ki) value of human acetylcholine muscarinic receptors M1-M5 by potential ligands has been constructed. We used information on the three-dimensional structure of human M1, M2, M4, and M5 receptors, as well as a model of the M3 receptor constructed according to homology based on the structure of the rat M3 receptor. A set of complexes of known inhibitors with the target receptor constructed by means of molecular docking, was selected using an additional option: the coincidence of the spatial position of 4 pharmacophore points of a tested inhibitor and tiotropium, for which the position in the crystal structure was known. For five types of M receptors 199 complexes with known Ki values were selected. Based on the data obtained during molecular dynamics simulation of these complexes by means of the MM-PBSA/MM-GBSA methods, their energy characteristics were calculated. They were used as independent variables in linear regression equations for pKi value prediction. The R2 prediction for the generalized equation was 0.7, and the mean prediction error was 0.55 logarithmic units with a range for pKi=4.7.
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