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基于对接的萘基取代二芳基嘧啶作为非核苷类逆转录酶抑制剂的比较分子场分析和比较分子相似性指数分析研究

Docking-based CoMFA and CoMSIA studies on naphthyl-substituted diarylpyrimidines as NNRTIs.

作者信息

Wu Hai-Qiu, Yao Jin, He Qiu-Qin, Chen Fen-Er

机构信息

a Department of Chemistry , Fudan University , Shanghai , People's Republic of China.

出版信息

SAR QSAR Environ Res. 2014;25(10):761-75. doi: 10.1080/1062936X.2014.955054. Epub 2014 Sep 22.

Abstract

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) play a significant role in anti-HIV drug development. A series of naphthyl-substituted diarylpyrimidines with most EC50 values in the nanomolar range was reported as potent NNRTIs by our lab. In order to obtain the quantitative structure-activity relationship (QSAR) that can guide rational lead optimization, CoMFA and CoMSIA studies were carried out. Docking study based on the co-crystallized complex (PDB ID: 3MEC) was utilized as an approach to obtain reliable conformations for molecular alignment. Two different molecular alignments were performed, resulting in two CoMFA models and 34 CoMSIA models. The CoMSIA models correspond to all the possible combinations among five fields: steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor. Highly predictive models were achieved, in which the statistically reliable CoMFA model had a q(2) of 0.743 and an r(2) of 0.980, whereas the best CoMSIA model had a q(2) of 0.713 and an r(2) of 0.969. The best models were rigorously validated with an external test set, which gave satisfactory predictive r(2) values for CoMFA and CoMSIA models: 0.85 and 0.83, respectively. Contour maps obtained from selected models revealed important structural features and some rational guidance for further optimization.

摘要

非核苷类逆转录酶抑制剂(NNRTIs)在抗HIV药物研发中发挥着重要作用。我们实验室报道了一系列萘基取代的二芳基嘧啶,其大多数EC50值在纳摩尔范围内,是有效的NNRTIs。为了获得能够指导合理先导物优化的定量构效关系(QSAR),开展了比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)研究。基于共结晶复合物(PDB ID:3MEC)的对接研究被用作获得可靠构象以进行分子比对的方法。进行了两种不同的分子比对,得到了两个CoMFA模型和34个CoMSIA模型。CoMSIA模型对应于空间、静电、疏水、氢键供体和氢键受体这五个场之间的所有可能组合。获得了具有高度预测性的模型,其中统计上可靠的CoMFA模型的q(2)为0.743,r(2)为0.980,而最佳的CoMSIA模型的q(2)为0.713,r(2)为0.969。最佳模型通过外部测试集进行了严格验证,CoMFA和CoMSIA模型的预测r(2)值分别为0.85和0.83,令人满意。从选定模型获得的等高线图揭示了重要的结构特征以及一些用于进一步优化的合理指导。

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