QSAR and QSAAR modeling of nitroimidazole sulfonamide radiosensitizers: application of small dataset modeling

Abstract

In recent years, hypoxic cell radiosensitizers have evolved as potential molecules in the diagnosis of cancer and in clinical radiotherapy. Nitroimidazole and its sulfonamide analogues are effective radiosensitizers working on hypoxic tumor cells. The application of QSAR modeling technique has paved an easier way for the prediction of newly developed compounds. In the present study, we have used 21 nitroimidazole sulfonamide analogues to develop 2D quantitative structure-activity relationship (QSAR) models and determine their structural features essential for two radiosensitization properties, viz., sensitizer enhancement ratio and survival ratio. The models were developed using the small dataset modeler software ( http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/ ), and model validation was performed using various stringent validation criteria. The developed models are robust, predictive, and should be useful tools to predict the radiosensitization of nitroimidazole sulfonamides. Furthermore, we have used the “prediction reliability indicator” tool to check the predictive ability of the developed models using 14 external nitroimidazole sulfonamide derivatives. We have also developed quantitative structure-activity-activity relationship (QSAAR) models for the two endpoints.