3D-QSAR analysis of anti-cancer agents by CoMFA and CoMSIA

Three-dimensional quantitative structure-activity relationships were performed for a series of isatin derivatives as anti-cancer agents using the CoMFA and CoMSIA methods. Statistically significant CoMFA (r(cv)(2) - 0: 869; r(ncv)(2) - 0: 962) and CoMSIA (r(cv)(2) - 0: 865; r(ncv)(2) - 0: 959) models were generated using the training set on the basis of the common substructure-based alignment. Further, the predictive ability of the CoMFA and CoMSIA models was determined using a test set of nine compounds. Based on the information derived from CoMFA and CoMSIA contour maps, we have identified some key features for increasing the activity of compounds and have been used to design new anti-cancer agents. The newly designed molecules in this series of compounds may be more potent anti-cancer agents.