Due to the high mortality rate in India, the identification of novel molecules is important in the development of novel and potent anticancer drugs.
Xanthones are natural constituents of plants in the families Bonnetiaceae and Clusiaceae, and comprise oxygenated heterocycles with a variety of
biological activities along with an anticancer effect. To explore the anticancer compounds from
xanthone derivatives, a quantitative structure activity relationship (QSAR) model was developed by the multiple linear regression method. The structure-activity relationship represented by the QSAR model yielded a high activity-descriptors relationship accuracy (84%) referred by regression coefficient (r(2)=0.84) and a high activity prediction accuracy (82%). Five molecular descriptors - dielectric energy, group count (
hydroxyl), LogP (the logarithm of the partition coefficient between
n-octanol and water), shape index basic (order 3), and the
solvent-accessible surface area - were significantly correlated with anticancer activity. Using this QSAR model, a set of virtually designed
xanthone derivatives was screened out. A molecular docking study was also carried out to predict the molecular interaction between proposed compounds and
deoxyribonucleic acid (
DNA) topoisomerase IIα. The pharmacokinetics parameters, such as absorption, distribution, metabolism, excretion, and toxicity, were also calculated, and later an appraisal of synthetic accessibility of organic compounds was carried out. The strategy used in this study may provide understanding in designing novel
DNA topoisomerase IIα inhibitors, as well as for other
cancer targets.