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Updated: Nov 22, 2025
Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Prediction of biological activity of compounds containing a 1,3,5-triazinyl sulfonamide scaffold by artificial neural
Eva Havránková1, E M Peña-Méndez2, Jozef Csöllei1
1Masaryk University, Faculty of Pharmacy, Department of Chemical Drugs, Palackého 1-3, CZ-612 42 Brno, Czech Republic.
Abstract:
Simple molecular descriptors of extensive series of 1,3,5-triazinyl sulfonamide derivatives, based on the structure of sulfonamides and their physicochemical properties, were designed and calculated. These descriptors were successfully applied as inputs for artificial neural network (ANN) modelling of the relationship between the structure and biological activity. The optimized ANN architecture was applied to the prediction of the inhibition activity of 1,3,5-triazinyl sulfonamides against human carbonic anhydrase (hCA) II, tumour-associated hCA IX, and their selectivity (hCA II/hCA IX).
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