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首页> 外文期刊>RSC Advances >Molecular modeling studies of dihydro-alkyloxy-benzyl-oxopyrimidines (DABOs) as non-nucleoside inhibitors of HIV-1 reverse transcriptase using 3D-QSAR, Topomer CoMFA and molecular docking simulations
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Molecular modeling studies of dihydro-alkyloxy-benzyl-oxopyrimidines (DABOs) as non-nucleoside inhibitors of HIV-1 reverse transcriptase using 3D-QSAR, Topomer CoMFA and molecular docking simulations

机译：使用3D-QSAR，Topomer CoMFA和分子对接模拟研究作为HIV-1逆转录酶非核苷抑制剂的二氢-烷氧基-苄基-氧嘧啶（DABO）的分子模型研究

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摘要

The human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) is generally regarded as a target for the treatment of acquired immune deficiency syndrome (AIDS). Non-nucleoside RT inhibitors (commonly known as NNRTIs) are currently being used in the treatment of HIV-1 infections. In this work, a series of NNRTIs were studied using a combination of molecular modeling techniques including three-dimensional quantitative structure-activity relationship (3D-QSAR), Topomer CoMFA and molecular docking simulations. The best optimum comparative molecule field analysis (CoMFA) model yielded a leave-one-out correlation coefficient (q(2)) and a non-cross-validated correlation coefficient (r(2)) of 0.636 and 0.993, respectively. The respective q(2) and r(2) of the best comparative molecular similarity indices analysis (CoMSIA) model were 0.655 and 0.998. The models were validated by test sets, and predicted correlation coefficients (r(pred)(2)) of 0.907 and 0.886 obtained from the CoMFA and CoMSIA models, thus judging the robustness of the model. The analysis of Topomer CoMFA obtained a q(2) of 0.546 and a r(pred)2 value of 0.718 which suggested the model had a good predictive ability (q(2) > 0.2). The results indicated the steric, hydrophobic and electrostatic fields play key roles in the models. Molecular docking elucidated the conformations of the compounds and key amino acid residues at the docking pocket of RT protein.
机译：人类1型免疫缺陷病毒（HIV-1）逆转录酶（RT）通常被视为治疗获得性免疫缺陷综合症（AIDS）的靶标。非核苷RT抑制剂（通常称为NNRTIs）目前正用于治疗HIV-1感染。在这项工作中，使用分子建模技术（包括三维定量构效关系（3D-QSAR），Topomer CoMFA和分子对接模拟）组合研究了一系列的NNRTI。最佳最佳比较分子场分析（CoMFA）模型得出的留一法相关系数（q（2））和非交叉验证相关系数（r（2））分别为0.636和0.993。最佳比较分子相似性指数分析（CoMSIA）模型的q（2）和r（2）分别为0.655和0.998。通过测试集验证了模型，并从CoMFA和CoMSIA模型获得了0.907和0.886的预测相关系数（r（pred）（2）），从而判断了模型的稳健性。拓扑CoMFA的分析得出q（2）为0.546，r（pred）2值为0.718，表明该模型具有良好的预测能力（q（2）> 0.2）。结果表明，空间，疏水和静电场在模型中起关键作用。分子对接阐明了RT蛋白对接口袋中化合物和关键氨基酸残基的构象。

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