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胆碱乙酰转移酶抑制剂的三维定量构效关系(3D-QSAR)分析

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses of choline acetyltransferase inhibitors.

作者信息

Chandrasekaran Vasudevan, McGaughey Georgia B, Cavallito Chester J, Bowen J Phillip

机构信息

Center for Biomolecular Structure and Dynamics, Department of Chemistry, University of Georgia, Athens 30602-2556, USA.

出版信息

J Mol Graph Model. 2004 Sep;23(1):69-76. doi: 10.1016/j.jmgm.2004.04.002.

Abstract

As a basis for predicting structural features that may lead to the design of more potent and selective inhibitors of choline acetyltransferase (ChAT), the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on a series of trans-1-methyl-4-(1-naphthylvinyl)pyridinium (MNVP+) analogs, which are known ChAT inhibitors. 3D-QSAR studies were carried out using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Since these inhibitors have extremely shallow potential energy minimum energy wells and low barriers to rotation, two dihedral angles unique to these inhibitors were systematically modified to reflect the energetically preferred conformations as determined by force field calculations. An optimum alignment rule was devised based on the conformations obtained from the molecular mechanics studies, using a common substructure alignment method. The studies involve a set of 21 compounds and experimentally determined molar IC50 values were used as the dependent variable in the analysis. The 3D-QSAR models have conventional r2-values of 0.953 and 0.954 for CoMFA and CoMSIA, respectively; similarly, cross-validated coefficient q2-values of 0.755 and 0.834 for CoMFA and CoMSIA, respectively, were obtained. On the basis of these predictive r2-values the model was tested using previously determined IC50 values. CoMSIA 3D-QSAR yielded better results than CoMFA.

摘要

作为预测可能有助于设计更有效、更具选择性的胆碱乙酰转移酶(ChAT)抑制剂的结构特征的基础,对一系列已知的ChAT抑制剂反式-1-甲基-4-(1-萘乙烯基)吡啶鎓(MNVP+)类似物进行了三维定量构效关系(3D-QSAR)研究。使用比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)方法进行了3D-QSAR研究。由于这些抑制剂具有极浅的势能最低能量阱和低旋转势垒,因此系统地修改了这些抑制剂特有的两个二面角,以反映由力场计算确定的能量上更有利的构象。基于从分子力学研究中获得的构象,使用共同子结构比对方法设计了最佳比对规则。该研究涉及一组21种化合物,并将实验测定得到的摩尔IC50值用作分析中的因变量。对于CoMFA和CoMSIA,3D-QSAR模型的传统r2值分别为0.953和0.954;类似地,CoMFA和CoMSIA的交叉验证系数q2值分别为0.755和0.834。基于这些预测r2值,使用先前测定的IC50值对模型进行了测试。CoMSIA 3D-QSAR产生的结果比CoMFA更好。

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