Development of Predictive Quantitative Structure-Activity Relationship Models of Epipodophyllotoxin Derivatives

Abstract

Epipodophyllotoxins are the most important anticancer drugs used in chemotherapy for various types of cancers. To further, improve their clinical efficacy a large number of epipodophyllotoxin derivatives have been synthesized and tested over the years. In this study, a quantitative structure-activity relationship (QSAR) model has been developed between percentage of cellular protein-DNA complex formation and structural properties by considering a data set of 130 epipodophyllotoxin analogues. A systematic stepwise searching approach of zero tests, missing value test, simple correlation test, multicollinearity test, and genetic algorithm method of variable selection was used to generate the model. A statistically significant model (r2( train) = 0.721; q2 cv = 0.678) was obtained with descriptors such as solvent-accessible surface area, heat of formation, Balaban index, number of atom classes, and sum of E-state index of atoms. The robustness of the QSAR models was characterized by the values of the internal leave-one-out cross-validated regression coefficient (q2 cv) for the training set and r2( test) for the test set. The root mean square error between the experimental and predicted percentage of cellular protein–DNA complex formation (PCPDCF) was 0.194 and r2( test) = 0.689, revealing good predictability of the QSAR model. (Journal of Biomolecular Screening 2010:1194-1203)