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Multilinear regression was used to build linear quantitative structure activity relationship models using 53 compounds with their quantum chemical descriptors. For each type of isozyme, separate quantitative structure activity relationship models were obtained. It was found that the hydration energy plays a significant role in the binding of ligands to the CAI isozyme, whereas the presence of five\u2010membered ring was detected as a major factor for the binding to the CAII isozyme. It was also found that the softness exhibited significant effect on the binding to CAIV isozyme. Principal component\u2010artificial neural network and correlation ranking\u2010principal component analysis analyses provide models with better prediction capability for the three types of the carbonic anhydrase isozyme inhibitory activity than those obtained by multilinear regression analysis. The best models, with improved prediction capability, were obtained for the hCAII isozyme activity. Models predictivity was evaluated by cross\u2010validation, using an external test set and chance correlation test.<\/jats:p>","DOI":"10.1111\/j.1747-0285.2011.01309.x","type":"journal-article","created":{"date-parts":[[2011,12,19]],"date-time":"2011-12-19T13:27:32Z","timestamp":1324301252000},"page":"514-522","source":"Crossref","is-referenced-by-count":6,"title":["Quantum Chemical QSAR Models to Distinguish Between Inhibitory Activities of Sulfonamides Against Human Carbonic Anhydrases I and II and Bovine IV Isozymes"],"prefix":"10.1111","volume":"79","author":[{"given":"Omar","family":"Deeb","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Goodarzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Padmaker 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