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首页> 外文期刊>Bulletin of the Korean Chemical Society >3D-QSAR Studies of 2-Arylbenzoxazoles as Novel Cholesteryl Ester Transfer Protein Inhibitors
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3D-QSAR Studies of 2-Arylbenzoxazoles as Novel Cholesteryl Ester Transfer Protein Inhibitors

机译:2-芳基苯并恶唑类作为新型胆固醇酯转移蛋白抑制剂的3D-QSAR研究

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摘要

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFA-RF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.
机译:通过比较分子场分析(CoMFA),CoMFA区域聚焦(CoMFA-RF)优化了用于最终PLS分析的区域以及比较分子相似性指数,对作为新型胆固醇酯转移蛋白抑制剂的2-芳基苯并恶唑进行了3D-QSAR研究分析(CoMSIA)方法来确定这些化合物活性所需的因素。通过使用AOS的全方向搜索策略搜索最佳方向,以最大程度地减小结构初始方向的影响。使用12种化合物的测试集确定CoMFA-RF和CoMSIA的预测能力,其预测相关系数分别为0.886和0.754,表明具有良好的预测能力。此外,分别通过自举和渐进式加扰分析来验证模型的稳健性和对机会相关性的敏感性。根据来自CoMFA(RF)和CoMSIA的信息,确定了一些关键特征,可用于设计胆固醇酯转移蛋白的新抑制剂。

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