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多种受体构象对接和对接构象聚类作为 CoMFA 和 CoMSIA 分析的工具 - 以 HIV-1 蛋白酶抑制剂为例。

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

机构信息

Department of Chemistry, Nizam College, Osmania University, Hyderabad 500001, India.

出版信息

J Mol Model. 2012 Feb;18(2):569-82. doi: 10.1007/s00894-011-1048-x. Epub 2011 May 6.

Abstract

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

摘要

多受体构象对接(MRCD)和对接构象聚类允许将分子的受体结合构象无缝地纳入具有不同结构支架的广泛配体中。该方法的准确性在一组具有 HIV-1 蛋白酶抑制活性的 120 个环状脲分子上进行了测试,使用了 12 个高分辨率 X 射线晶体结构和一个从蛋白质数据库中提取的 HIV-1 蛋白酶的 NMR 分辨率构象。对具有不同结构的 25 个非环状脲 HIV-1 蛋白酶抑制剂进行了交叉验证。通过应用留一法交叉验证方法,在训练集中使用 60 个分子生成了比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)模型,CoMFA 和 CoMSIA 的 r(loo)(2)值分别为 0.598 和 0.674,非交叉验证回归系数 r(2)值分别为 0.983 和 0.985。使用 60 个环状脲分子的测试集来确定这些模型的预测能力,得到 CoMFA 和 CoMSIA 的预测相关系数(r(pred)(2))分别为 0.684 和 0.64,表明具有良好的内部预测能力。基于此信息,将 25 个非环状脲分子作为测试集,以检查这些模型的外部预测能力。这给出了显著的结果,CoMFA 和 CoMSIA 的 r(pred)(2)值分别为 0.61 和 0.53。结果始终表明,该方法可用于对具有不同结构基序的分子进行 3D-QSAR 分析。

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