Computational evaluation of 2-amino-5-sulphonamido-1,3,4-thiadiazoles as human carbonic anhydrase-IX inhibitors: an insight into the structural requirement for the anticancer activity against HEK 293

Carbonic anhydrase inhibitors are very interesting target for designing anticancer agents. A computational procedure was performed on some thiadiazoles derived from carbonic anhydrase inhibitor acetazolamide. Two important procedures in computational drug discovery, namely docking for modeling ligand–receptor interactions and quantitative structure–activity relationships were employed. The relationship between cytotoxic activity and various descriptors was established by stepwise multiple regression analysis. The analyses have produced well predictive and statistically significant quantitative structure–activity relationships models, which were further cross validated. Among several models, one model has good statistical significance (r = 0.89, Ftest = 6.88, S = 0.33, chance correlation < 0.01), indicates that steric descriptors like EleE are contributing positively to the biological activity, electronic descriptors like connolly molecular surface area and Chi descriptors like chi0 and information theory index like IdAvg are contributing negatively to the biological activity and play a significant role in receptor binding which helps to design some expectedly potent compounds. In order to confirm the obtained results through this ligand-based method, docking was performed on the selected compounds by the use of Schrödinger GLIDE program. Incorporating available biochemical and computational data to the model by correcting the conformation of a single residue lining the binding pocket resulted in significantly improved docking poses. The molecular modeling study allowed confirming the preferential binding mode of reported compounds inside the active site.