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QSAR studies on hepatitis C virus NS5A protein tetracyclic inhibitors in wild type and mutants by CoMFA and CoMSIA

机译:COMFA和COMSIA的丙型肝炎病毒NS5A蛋白四环抑制剂的QSAR研究

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摘要

Several 3D-QSAR models were built based on 196 hepatitis C virus (HCV) NS5A protein inhibitors. The bioactivity values EC90 for three types of inhibitors, the wild type (GT1a) and two mutants (GT1a Y93H and GT1a L31V), were collected to build three datasets. The programs OMEGA and ROCS were used for generating conformations and aligning molecules of the dataset, respectively. Each dataset was randomly divided into a training set and a test set three times to reduce the contingency of only one random selection. QSAR models were computed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). For the datasets GT1a, GT1a Y93H, and GT1a L31V, the best models CoMFA-INDX, CoMSIA-SEHA, and CoMSIA-SEHA showed an r(2) value of 0.682 +/- 0.033, 0.779 +/- 0.036, and 0.782 +/- 0.022 on the test sets, respectively. From the contour maps of the three best models, we summarized the favourable and unfavourable substituents on the tetracyclic core, the Z group, the proline group, and the valine group of inhibitors. We guessed the mutants could change the electrostatic surfaces of the wild type active pocket. In addition, we used ECFP analyses to find important substructures and could intuitively understand the results from QSAR models.
机译:基于196个丙型肝炎病毒(HCV)NS5A蛋白抑制剂,构建了几种3D-QSAR模型。收集三种类型的抑制剂,野生型(GT1A)和两个突变体(GT1A Y93H和GT1A L31V)的生物活性值EC90以构建三个数据集。程序ω和Roc分别用于产生数据集的构象和对准分子。每个数据集随机分为培训集和测试设置三次,以减少只有一个随机选择的应急。通过比较分子场分析(COMFA)和比较分子相似索引分析(COMSIA)计算QSAR模型。对于数据集GT1A,GT1A Y93H和GT1A L31V,最佳型号COMFA-INDX,COMSIA-SEHA和COMSIA-SEHA显示R(2)值为0.682 +/- 0.033,0.779 +/- 0.036和0.782 + / - 试验组0.022。从三种最佳模型的轮廓图中,我们总结了四环核,Z组,脯氨酸基团和缬氨酸抑制剂的有利和不利的取代基。我们猜到了突变体可以改变野生型活性口袋的静电表面。此外,我们使用ECFP分析来查找重要的子结构,可以直观地了解QSAR模型的结果。

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