首页> 外文期刊>Medicinal chemistry research: an international journal for rapid communications on design and mechanisms of action of biologically active agents >Three-dimensional quantitative structure-activity relationship CoMFA/CoMSIA on pyrrolidine-based tartrate diamides as TACE inhibitors
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Three-dimensional quantitative structure-activity relationship CoMFA/CoMSIA on pyrrolidine-based tartrate diamides as TACE inhibitors

机译:吡咯烷基酒石酸二酰胺作为TACE抑制剂的三维定量构效关系CoMFA / CoMSIA

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摘要

A series of pyrrolidine-based tartrate diamides having selective tumor necrosis factor-alpha converting enzyme (TACE) inhibitory activity was selected for the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies. Total 76 compounds were selected by considering a high deviation in the biological activity and structural variations. The quality and predictive power of 3D-QSAR, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the atom-based, centroid/atom-based, data-based alignments were performed. Various models were developed with the help of these alignments. The best model was developed with data-based alignment. The optimal predictive CoMFA model was obtained with cross-validated r2 = 0.53 with six component, non-cross-validated r2 = 0.94, standard error of estimates 0.23, F-value = 121.98 and optimal CoMSIA model was obtained with cross-validated r2 = 0.53 with five components, non-cross-validated r2 = 0.93, standard error of estimates = 0.24 and F-value = 138.83. These models also showed the best test set prediction with predictive r~2 value of 0.65 and 0.73, respectively. Thus, on the basis of predictive power COMSIA model appeared to be the best one. The statistical parameters from these models indicate that the data are being well fitted and also have high predictive ability. Moreover, the resulting 3D-CoMFA/CoMSIA contour maps provide useful guidance for designing of highly active TACE inhibitors.
机译:选择了一系列具有选择性肿瘤坏死因子-α转化酶(TACE)抑制活性的基于吡咯烷的酒石酸二酰胺,用于三维定量结构-活性关系(3D-QSAR)研究。考虑到生物学活性和结构变异的高偏差,共选择了76种化合物。进行了基于原子,质心/原子,基于数据的比对的3D-QSAR,比较分子场分析(CoMFA)和比较分子相似性指标分析(CoMSIA)模型的质量和预测能力。在这些比对的帮助下开发了各种模型。最佳模型是通过基于数据的对齐方式开发的。通过交叉验证的r2 = 0.53和六分量获得了最佳预测CoMFA模型,未交叉验证的r2 = 0.94,估计的标准误为0.23,F值= 121.98,并且通过交叉验证的r2 =获得了最佳的CoMSIA模型。包含五个成分的值为0.53,未经交叉验证的r2 = 0.93,估算的标准误为0.24,F值= 138.83。这些模型还显示了最佳的测试集预测,预测的r〜2值分别为0.65和0.73。因此,在预测能力的基础上,COMSIA模型似乎是最好的模型。这些模型的统计参数表明数据拟合良好,并且具有较高的预测能力。此外,所得的3D-CoMFA / CoMSIA等高线图为设计高活性TACE抑制剂提供了有用的指导。

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