期刊
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
卷 45, 期 8, 页码 3394-3406出版社
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ejmech.2010.04.024
关键词
Quantitative structure-activity relationship; Multivariate linear regression; Partial least squares; General regression neural networks; Least squares support vector machine; CCR2 inhibitors
Quantitative relationships between structures of 26 diaryl substituted pyrazoles as CCR2 inhibitors and their activities were investigated by four linear and nonlinear methods namely MLR, PLS, GRNN and LS-SVM. The obtained models were able to describe about 83%, 87%, 86%. and 0.91% of the variance in the experimental activity of molecules in training set, respectively. The accuracy and predictability of the proposed models were illustrated using various evaluation techniques. Some of them were: cross-validation, validation through an external test set, and Y-randomization. Furthermore, various criteria suggested by Tropsha and Roy were applied for evaluation of predictability of developed models. A comparison between the four different developed methods indicates that LS-SVM can be preferred as supreme model. (C) 2010 Elsevier Masson SAS. All rights reserved.
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