As a part of our anticancer drug discovery programme, QSAR models were developed for the prediction of
anticancer activities of ursolic acid derivatives against the human hepatocellular carcinoma HepG2, breast carcinoma
MDA-MB-231 and the human ductal breast epithelial T47D cancer cell lines followed by wet lab semi-synthesis of
virtually active derivatives, their in-vitro biological evaluation and apoptosis. The development of QSAR models was
carried out by forward stepwise multiple linear regression method using a leave-one-out approach. Virtually active derivatives
were semi synthesized, spectroscopically characterized and then in-vitro tested against human cancer cell lines. Active
derivatives were checked via DNA fragmentation assay. The results exhibited regression coefficients (r2) and the
cross-validation regression coefficients (rCV2) for the human HepG2, MDA-MB-231 and T47D cancer cell lines as .95
and .90; .92 and .87; .89 and .83 respectively showing the prediction accuracy of the models against biological activities.
Computational molecular modeling is a valid modern approach, widely used in the identification of potential drug leads.
The most active virtual derivatives of UA were semi- synthesized and their in-vitro and ex-vivo evaluation showed similar
results with the predicted one, validating our QSAR models. Out of several active derivatives, the three UA2, UA7 and
UA10 were potentially active against the above human cancer cell lines. These findings may be of immense importance in
the anticancer drug development of an inexpensive and widely available natural product, ursolic acid.