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2D and 3D-QSAR studies on antiproliferative thiazolidine analogs

机译:抗增生噻唑烷类似物的2D和3D-QSAR研究

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Two-dimensional (2D) and three-dimensional (3D) quantitative structure-activity relationships (QSARs) of 22 thiazolidine analogs with antiproliferative activity expressed as pIC(50), which is defined as the negative value of the logarithm of necessary molar concentration of these compounds to cause 50% growth inhibition against melanoma cell lines WM-164, have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) method for 3D. The established 2D-QSAR model in training set comprised of random 18 compounds shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient (R-A(2) = 0.832) and the square of the cross-validation coefficient (q(2) = 0.803). The same model was further applied to predict pIC(50) values of the four compounds in the test set, and the resulting R-pred(2) reaching 0.784, further confirms that this 2D-QSAR model has high predictive ability. The 3D-QSAR model also shows good correlative and predictive capabilities in terms of R-2 (0.956) and q(2) (0.615) obtained from CoMFA model. Further, the robustness of the CoMFA model was verified by bootstrapping analysis (100 runs) with R-bs(2) (0.979) and SDbs (0.056). It is very interesting to find that the results from 2D- and 3D-QSAR analyses accord with each other, and they all show that the steric interaction plays a crucial role in determining the cytotoxicities of the compounds, and that selecting a moderate-size or appropriate-hydrophobicity substituent R as well as increasing the negative charges of C, on phenyl ring at the same time are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with antiproliferative activity. (C) 2008 Wiley Periodicals, Inc.
机译:具有抗增殖活性的22种噻唑烷类似物的二维(2D)和三维(3D)定量构效关系(QSAR),表示为pIC(50),定义为必要的摩尔浓度对数的对数的负值通过使用DFT,MM2和2D统计方法以及3D比较分子场分析(CoMFA)方法的组合研究了这些化合物对黑色素瘤细胞系WM-164造成50%生长抑制的方法。在由18种随机化合物组成的训练集中建立的2D-QSAR模型不仅显示出显着的统计质量,而且还具有预测能力,其校正系数的平方(RA(2)= 0.832)和交叉验证系数的平方(q(2)= 0.803)。将该模型进一步应用于预测测试集中四种化合物的pIC(50)值,并且所得R-pred(2)达到0.784,进一步证实了此2D-QSAR模型具有较高的预测能力。从CoMFA模型获得的R-2(0.956)和q(2)(0.615)方面,3D-QSAR模型也显示出良好的关联和预测能力。此外,通过自举分析(100次运行)使用R-bs(2)(0.979)和SDbs(0.056)验证了CoMFA模型的鲁棒性。有趣的是,发现2D-QSAR和3D-QSAR分析的结果相互吻合,它们都表明空间相互作用在确定化合物的细胞毒性,选择中等大小或适当的疏水性取代基R以及同时增加苯环上C的负电荷有利于改善细胞毒性。这些结果可为指导分子设计和理解这类具有抗增殖活性的化合物的作用机理提供一些有用的理论参考。 (C)2008 Wiley期刊公司

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