QSAR study of pyrazolo[4, 3-e][1, 2, 4]triazine sulfonamides against tumor-associated human carbonic anhydrase isoforms IX and XII. (December 2017)

• Record Type: Journal Article
• Authors: Matysiak, Joanna; Skrzypek, Alicja; Tarasiuk, Paweł; Mojzych, Mariusz
• Is Part Of: Computational biology and chemistry. Volume 71(2017)
• Page Start: 57
• Page End: 62
• Publication Date: 2017-12
• Subjects: Pyrazolotriazine sulfonamide -- Molecular descriptor -- Carbonic anhydrase -- QSAR -- MLR; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.09.006
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: A set of descriptors of pyrazolotriazine sulfonamides as carbonic anhydrase isoforms IX and XII inhibitors was determined. Four-variable QSAR equations were obtained for both isoforms. QSAR model of antiproliferative activity against human MCF-7 cells was obtained. Constructed models exhibited good predictive accuracy of inhibitory and antiproliferative activities. Abstract: The QSAR models for a set of pyrazolo[4, 3 -e ][1, 2, 4]triazines incorporating benzenesulfonamide moiety combined directly with the heterocyclic ring or by NH linkage were generated. The inhibitory potency of compounds against human carbonic anhydrase isoforms IX and XII and antiproliferative activity against human MCF-7 cells were used as the dependent variables. The Codessa pro software was used for the descriptors calculation and the Best Multi-Linear Regression (BMLR) algorithm was employed to build the QSAR models. It was found that quantum descriptors are critical of the compounds activities. The selected models have good predictive accuracy confirmed by a set of the statistical quantities recommended by OECD.