Understanding the antitumor activity of novel hydroxysemicarbazide derivatives as ribonucleotide reductase inhibitors using CoMFA and CoMSIA

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed on a series of Schiff bases of hydroxysemicarbazide analogues using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods with their antitumor activities against L1210 cells. The models were generated using 24 molecules, out of which one molecule was a commercially available ribonucleotide reductase (RR) inhibitor, hydroxyurea (HU), and the predictive ability of the resulting each model was evaluated against a test set of four molecules. Maximum common substructure (MCS)-based method was used for alignment and compared with the known alignment methods. The QSAR models from both methods exhibited considerable correlative and predictive properties. Inclusion of additional descriptor ClogP improved the statistics of CoMFA model significantly. Both methods strongly suggest the necessity of lipophilicity for antitumor activity. CoMFA and CoMSIA methods predicted HU optimally, indicating a similar mechanism of action for the molecules considered for generating the models and HU to inhibit the tumor cells. The analysis of CoMFA contour maps provided insight into the possible modification of the molecules for better activity.