Polanski Jarosław, Gieleciak Rafał
Department of Organic Chemistry, Institute of Chemistry, University of Silesia, PL-40-006 Katowice, Poland.
J Chem Inf Comput Sci. 2003 Mar-Apr;43(2):656-66. doi: 10.1021/ci020038q.
The application of the CoMSA method to analyze 3D QSAR of 50 steroid aromatase inhibitors is described. The 3D QSAR model obtained, reaching a value of cross-validated q(2) = 0.96 (s = 0.31), significantly outperforms those reported in the literature for the CoMFA or CoSA (CoSASA). It is shown that the Uniformative Variable Elimination UVE-PLS or modified iterative UVE procedure (IVE-PLS) can be used for indicating the regions contributing to the binding activity. Thus, after separating the series into two groups of the training and test molecules quite correct external predictions result from the processing of the training set. We proved that the procedure of the data elimination provides stable results, if tested in 50 random runs of the IVE-PLS-CoMSA with different training/test sets. Depending upon the procedure used the quality of the predictions for 25 test molecules is given by SDEP = sum(y(pred)-y(obs))(2)/n)(1/2) = 0.321 - 0.782.
描述了运用CoMSA方法分析50种甾体芳香酶抑制剂的3D QSAR。所获得的3D QSAR模型，交叉验证q(2)值达到0.96（s = 0.31），显著优于文献中报道的CoMFA或CoSA（CoSASA）模型。结果表明，均匀变量消除UVE-PLS或改进的迭代UVE程序（IVE-PLS）可用于指示对结合活性有贡献的区域。因此，将该系列分为训练分子和测试分子两组后，对训练集的处理产生了相当正确的外部预测结果。我们证明，如果在IVE-PLS-CoMSA的50次不同训练/测试集的随机运行中进行测试，数据消除程序会提供稳定的结果。根据所使用的程序，25个测试分子预测的质量由SDEP = sum(y(pred)-y(obs))(2)/n)(1/2) = 0.321 - 0.782给出。
