QSAR study on cytotoxic activity (against KB cells) of some hederagenin diglycosides using support vector regression.

Quantitative structure-activity relationship (QSAR) study on the cytotoxic activity (against KB cells) of 19 hederagenin diglycosides was performed by using spatial and electronic descriptors based on support vector regression (SVR) techniques. The predictive power of the models was verified with the leave one out cross validation (LOOCV) test and independent test methods. For the LOOCV test, the cross validation squared correlation coefficient Q value for optimal SVR model was 0.8827. Compared with stepwise multiple linear regression (MLR) and back propagation artificial neural network (BPANN) models, the SVR model was the most powerful with a square of predictive correlation coefficient $${R_{pred}^2}$$ of 0.7285 for the test set, which indicates that the SVR model has better substantially predictive ability and be a useful and powerful tool to construct the QSAR model. [ABSTRACT FROM AUTHOR]