Predicting Isoform-specific Binding Selectivities of Benzensulfonamides Using QSAR and 3D-QSAR

Title:Predicting Isoform-specific Binding Selectivities of Benzensulfonamides Using QSAR and 3D-QSAR

Volume: 13 Issue: 1

Author(s): Vytautas Raskevicius and Visvaldas Kairys

Affiliation:

Keywords: 3D-QSAR, benzensulfonamide, carbonic anhydrase, drug design, E-DRAGON, phase, QSAR, specificity.

Abstract: 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 R² _ADJ. 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.

Cite this article as:

Raskevicius Vytautas and Kairys Visvaldas, Predicting Isoform-specific Binding Selectivities of Benzensulfonamides Using QSAR and 3D-QSAR, Current Computer-Aided Drug Design 2017; 13 (1) . https://dx.doi.org/10.2174/1573409912666161129153820

DOI https://dx.doi.org/10.2174/1573409912666161129153820	Print ISSN 1573-4099
Publisher Name Bentham Science Publisher	Online ISSN 1875-6697