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分子对接和 3D-QSAR 研究三氮唑酮和哒嗪酮,HIV-1 逆转录酶非核苷抑制剂。

Molecular docking and 3D-QSAR studies on triazolinone and pyridazinone, non-nucleoside inhibitor of HIV-1 reverse transcriptase.

机构信息

Department of Chemistry, Nizam college, (O.U), Basheerbagh, Hyderabad, 500 001, India.

出版信息

J Mol Model. 2010 Jun;16(6):1169-78. doi: 10.1007/s00894-009-0625-8. Epub 2009 Dec 15.

Abstract

Nonnucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors of the HIV-1 reverse transcriptase. Recently a series of Triazolinone and Pyridazinone were reported as potent inhibitors of HIV-1 wild type reverse transcriptase. In the present study, docking and 3D quantitative structure activity relationship (3D QSAR) studies involving comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 31 molecules. Ligands were built and minimized using Tripos force field and applying Gasteiger-Hückel charges. These ligands were docked into protein active site using GLIDE 4.0. The docked poses were analyzed; the best docked poses were selected and aligned. CoMFA and CoMSIA fields were calculated using SYBYL6.9. The molecules were divided into training set and test set, a PLS analysis was performed and QSAR models were generated. The model showed good statistical reliability which is evident from the r2 nv, q2 loo and r2 pred values. The CoMFA model provides the most significant correlation of steric and electrostatic fields with biological activities. The CoMSIA model provides a correlation of steric, electrostatic, acceptor and hydrophobic fields with biological activities. The information rendered by 3D QSAR model initiated us to optimize the lead and design new potential inhibitors.

摘要

非核苷类逆转录酶抑制剂(NNRTIs)是 HIV-1 逆转录酶的别构抑制剂。最近,一系列三唑啉酮和哒嗪酮被报道为 HIV-1 野生型逆转录酶的有效抑制剂。在本研究中,对 31 个分子进行了对接和三维定量构效关系(3D QSAR)研究,包括比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)。使用 Tripos 力场和应用 Gasteiger-Hückel 电荷构建和最小化配体。使用 GLIDE 4.0 将这些配体对接进入蛋白质活性位点。分析对接构象,选择并对齐最佳对接构象。使用 SYBYL6.9 计算 CoMFA 和 CoMSIA 场。将分子分为训练集和测试集,进行 PLS 分析并生成 QSAR 模型。该模型显示出良好的统计可靠性,这从 r2 nv、q2 loo 和 r2 pred 值中可以明显看出。CoMFA 模型提供了与生物活性最相关的立体和静电场的最显著相关性。CoMSIA 模型提供了与生物活性相关的立体、静电、受体和疏水性场的相关性。3D QSAR 模型提供的信息使我们能够优化先导化合物并设计新的潜在抑制剂。

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