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Updated: Mar 11, 2026

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Published on: August 28, 2019
Predicting Isoform-specific Binding Selectivities of Benzensulfonamides Using QSAR and 3D-QSAR
Vytautas Raskevicius, Visvaldas Kairys1
1Department of Bioinformatics, Institute of Biotechnology, Vilnius University, Saul.etekio al. 7, LT- 10257 Vilnius, Lithuania.
Background:
Design of isoform-specific inhibitors is a major challenge in the new therapeutic agents development.
Methods:
The article describes the development of a robust selectivity for CA XII QSAR and 3DQSAR models of 40 benzenesulfonamide derivatives bearing pyrimidine moieties using PHASE module of Schrödinger for 3D-QSAR or E-DRAGON and R software for 2D-QSAR. Two QSAR protocols were explored: traditional (affinity) and selectivity (affinity ratio) based.
Results:
A total of 25 2D and 3D-QSAR models were developed using a training set of 30 compounds using the two protocols for 6 CA isoforms. A new ad hoc descriptor T(OH..Cl) was created targeting CA XII affinity. Satisfactory results were obtained in terms of model quality expressed statistically as F, R2 and R2ADJ. Developed models were analyzed using different statistical validation techniques, both by using the Leave One Out (LOO) criterion, and by applying a model on a test set. The Applicability Domains of the 2D-QSAR models were determined. Two PHASE (affinity and selectivity) 3D-QSAR models were rationalized by manual docking of the ligands into the X-ray crystal structures. The affinity and selectivity based protocols were compared.
Conclusion:
This study provides insights for designing sulfonamide compounds with a better isoform selectivity.
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