A Systematic Quantitative Approach to Rational Drug Design and Discovery of Novel Human Carbonic Anhydrase IX Inhibitors

Drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed for a series of carbonic anhydrase IX inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity … Continued

Docking, CoMFA and CoMSIA Studies of a Series of Sulfonamides Derivatives as Carbonic Anhydrase I Inhibitors

3D-QSAR methods, CoMFA region focusing (CoMFA-RF) and CoMSIA along with docking studies carried out for investigating 32 carbonic anhydrase I inhibitors. These inhibitors have been studied for the development of antiglaucoma, antitumor, antiobesity or anticonvulsant drugs. Docking analysis by GOLD provide conformations which have been realigned in CoMFA and CoMSIA models. Training set for the … Continued

Docking-based CoMFA and CoMSIA Analyses of Tetrahydro-β-carboline Derivatives as Type-5 Phosphodiesterase Inhibitors

Tetrahydro-β-carboline derivatives (THBCs) have been identified as a class of potent Type-5 Phosphodiesterase (PDE5) inhibitors, showing benefits for the treatment of erectile dysfunction and also bearing anticancer properties. A computational strategy based on molecular docking studies, followed by docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA), has been used to … Continued

Predicting Anti-cancer Activity of Quinoline Derivatives: CoMFA and CoMSIA Approach

The 3D quantitative structure-activity relationships of 31 quinoline nuclei containing compounds and their biological activity have been investigated to establish various models. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies resulted in reliable and significant computational models. The obtained CoMFA model showed high predictive ability with q2 = 0.592, … Continued

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