Prediction of Antitumor Activity for Epothilone Analogues Based on 3D Molecular Descriptors

In order to predict the antitumor activities of various epothilone analogues, a set of molecular descriptors, including electronic, topological, and geometrical descriptors and molecular shape indices (K-order moment shape indices), were calculated to characterize the structural and physicochemical properties for 150 compounds. The 30 descriptors selected with genetic algorithm were employed to establish the classification model of epothilone analogues by using support vector machine (SVM). This SVM system gives a total prediction accuracy of 83.3% by the 'leave-one-out' (LOO) method and that of 80.6% by the five-fold cross-validation method. The present study indicates that the K-order moment shape indices defined by us are useful for the description of configuration isomers, and SVM is a facilitating tool in prediction of the antitumor activity of epothilone analogues.