Benzenesulfonamides incorporating cyanoacrylamide moieties with activity against tumour-associated human (h) isoforms hCA IX and XII (which are validated antitumor targets) were investigated for their quantitative structural activity relationships (QSAR). Multiple linear regression analysis was used to develop model relationships between molecular descriptors and inhibition constants (Ki). The molecular geometry optimization were performed on all molecules at DFT-B3LYP/6-311++G(d,p) level. Over 1250 molecular descriptors were calculated using Gaussian 09, Hyperchem and EDRAGON programs. Multiple linear regression equations have been developed and validated using leave-one-out cross-validated technique. The derived QSAR models are found to be statistically significant and show good predictive ability.
Exploring QSARs of some benzenesulfonamides incorporating cyanoacrylamide moieties as a carbonic anhydrase inhibitors (specifically against tumor-associated isoforms IX and XII) / Alafeefy, Ahmed M.*; Abdel-Aziz, Hatem A.; Carta, F.; Supuran, Claudiu T.; Pathak, Shilendra K.; Prasad, Onkar; Sinha, Leena. - In: JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY. - ISSN 1475-6366. - ELETTRONICO. - 30:(2015), pp. 519-523. [10.3109/14756366.2014.948435]
Exploring QSARs of some benzenesulfonamides incorporating cyanoacrylamide moieties as a carbonic anhydrase inhibitors (specifically against tumor-associated isoforms IX and XII)
Carta, F.;Supuran, Claudiu T.;
2015
Abstract
Benzenesulfonamides incorporating cyanoacrylamide moieties with activity against tumour-associated human (h) isoforms hCA IX and XII (which are validated antitumor targets) were investigated for their quantitative structural activity relationships (QSAR). Multiple linear regression analysis was used to develop model relationships between molecular descriptors and inhibition constants (Ki). The molecular geometry optimization were performed on all molecules at DFT-B3LYP/6-311++G(d,p) level. Over 1250 molecular descriptors were calculated using Gaussian 09, Hyperchem and EDRAGON programs. Multiple linear regression equations have been developed and validated using leave-one-out cross-validated technique. The derived QSAR models are found to be statistically significant and show good predictive ability.File | Dimensione | Formato | |
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