QSAR analysis of some novel sulfonamides incorporating 1,3,5-triazine derivatives as carbonic anhydrase inhibitors

Abstract

A QSAR study on a series of sulfonamides incorporating 1,3,5-triazine derivatives was performed to explore the physicochemical parameters responsible for their inhibitory activity of carbonic anhydrase I (CA-I) inhibitors. Physicochemical parameters were calculated using WIN CAChe 6.1. Stepwise multiple linear regression analysis was carried out to derive QSAR models, which were further evaluated for statistical significance and predictive power by internal and external validation. The best QSAR model was selected, having a correlation coefficient R = 0.932, a standard error of estimation SEE = 0.224, and a cross-validated squared correlation coefficient Q 2 = 0.825. The predictive ability of the selected model was also confirmed by leaveone-out cross-validation. The QSAR model indicates that the descriptors (polarizability, DVY, 0v) play an important role in CA-I inhibition. The results of the present study may be useful in the design of more potent sulfonamide substituted 1,3,5-triazine derivatives as CA-I inhibitors.

COVID-19 pandemic: The deadly respiratory disease of 21st century

“…[20][21][22][23][24][25][26][27][28][29] Numerous drug design studies have been reported for search of novel compounds. [30][31][32][33][34][35][36][37][38] Numbers of novel drug delivery systems have been utilizes for effective drug delivery. [39][40][41][42][43][44][45][46][47][48] Several agents being used for COVID-19 are under clinical trial and few of them are available in market for sale.…”

A Systematic Review on Antitumor Agents with 1, 3, 5-triazines

“…Recent research has shown that several CA isozymes are drug targets for cancer and infective diseases. There are 11 active CA isozymes known in human [116,117]. Tumour-associated CAs are recognized as hCA IX and hCA XII (also hCA XIV).…”

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“…The structures of the 72 compounds used in this study, are given in Table 1. Generation of the Common Pharmacophore Hypotheses (CPHs): Pharmacophore modelling provides a qualitative picture of the geometry of the active site by identifying the chemical features for binding of ligands and their spatial arrangements in 3D space 12 . PHASE module of Schrodinger software 13 was used to generate 3D Pharmacophore models and QSAR studies for the present series of compounds.…”