Journal
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
Volume 45, Issue 10, Pages 4499-4508Publisher
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ejmech.2010.07.010
Keywords
QSAR; Anthranilic acid sulfonamides; Methionine aminopeptidase-2; Principal component analysis; General regression neural network; Least squares support vector machine
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Quantitative relationships between molecular structure and methionine aminopeptidase-2 inhibitory activity of a series of cytotoxic anthranilic acid sulfonamide derivatives were discovered. We have demonstrated the detailed application of two efficient nonlinear methods for evaluation of quantitative structure activity relationships of the studied compounds. Components produced by principal component analysis as input of developed nonlinear models were used The performance of the developed models namely PC-GRNN and PC-LS-SVM were tested by several validation methods The resulted PC-LS-SVM model had a high statistical quality (R(2) = 091 and R(CV)(2) = 0 81) for predicting the cytotoxic activity of the compounds. Comparison between predictability of PC-GRNN and PC-LS-SVM indicates that later method has higher ability to predict the activity of the studied molecules. (C) 2010 Elsevier Masson SAS. All rights reserved.
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