QSARINS-Based Development of Predictive Models for Aryl Sulphonamide Derivatives as Dual Enzyme Inhibitors

Objective: To develop and validate QSAR models of aryl sulphonamide derivatives for predicting dual inhibitory activity against Carbonic Anhydrase II and Acetylcholinesterase. Methods: Aryl sulphonamide derivatives were analysed using QSARINS software. Molecular descriptors were calculated via PaDEL, followed by Multiple Linear Regression (MLR) model generation. Models were validated through internal (LOO, LMO) and external (test set) statistics, alongside Y-scrambling for robustness. Descriptor selection ensured elimination of collinearity. Predicted inhibitory activities were compared with experimental pIC50 values to confirm model reliability and predictive performance. Findings: QSAR models developed for aryl sulphonamide derivatives demonstrated strong predictive power for dual inhibition of Carbonic Anhydrase II (CA II) and Acetylcholinesterase (AChE). The best CA II model showed R2 = 0.86, Q2 = 0.79, and external R2pred = 0.81, while the AChE model achieved R2 = 0.83, Q2 = 0.76, and R2pred = 0.79, confirming robustness and high predictive accuracy. Y-scrambling validated model reliability by eliminating chance correlations. Significant descriptors such as WTPT, BCUT, and electronic charge indices revealed that extended conjugation and specific electronic features enhance dual inhibitory activity. These findings align with existing reports emphasising the electronic influence of sulphonamide derivatives but provide a novel insight by correlating topological descriptors with dual-target inhibition. The developed models offer a valuable framework for designing new multifunctional agents targeting neurodegenerative and metabolic disorders, improving efficiency in lead optimisation and reducing the need for extensive experimental screening. Novelty: This study uniquely correlates topological and electronic descriptors of aryl sulphonamides with dual inhibition of CA II and AChE, offering predictive models for multifunctional drug design. Keywords: QSARINS, Carbonic Anhydrase II, Acetylcholinesterase, Dual-target inhibitors, Molecular descriptors, Validation

Authors

Publication Details

Journal
Indian Journal of Science and Technology
Published
2025-12-02
DOI
https://doi.org/10.17485/ijst/v18i42.1686
Primary Topic
Cholinesterase and Neurodegenerative Diseases
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

QSARINS-Based Development of Predictive Models for Aryl Sulphonamide Derivatives as Dual Enzyme Inhibitors

Sarita Karole, Birgit Jacob
Indian Journal of Science and Technology
Cholinesterase and Neurodegenerative Diseases
article

QSARINS-Based Development of Predictive Models for Aryl Sulphonamide Derivatives as Dual Enzyme Inhibitors

Sarita Karole, Birgit Jacob
article en

Abstract

Objective: To develop and validate QSAR models of aryl sulphonamide derivatives for predicting dual inhibitory activity against Carbonic Anhydrase II and Acetylcholinesterase. Methods: Aryl sulphonamide derivatives were analysed using QSARINS software. Molecular descriptors were calculated via PaDEL, followed by Multiple Linear Regression (MLR) model generation. Models were validated through internal (LOO, LMO) and external (test set) statistics, alongside Y-scrambling for robustness. Descriptor selection ensured elimination of collinearity. Predicted inhibitory activities were compared with experimental pIC50 values to confirm model reliability and predictive performance. Findings: QSAR models developed for aryl sulphonamide derivatives demonstrated strong predictive power for dual inhibition of Carbonic Anhydrase II (CA II) and Acetylcholinesterase (AChE). The best CA II model showed R2 = 0.86, Q2 = 0.79, and external R2pred = 0.81, while the AChE model achieved R2 = 0.83, Q2 = 0.76, and R2pred = 0.79, confirming robustness and high predictive accuracy. Y-scrambling validated model reliability by eliminating chance correlations. Significant descriptors such as WTPT, BCUT, and electronic charge indices revealed that extended conjugation and specific electronic features enhance dual inhibitory activity. These findings align with existing reports emphasising the electronic influence of sulphonamide derivatives but provide a novel insight by correlating topological descriptors with dual-target inhibition. The developed models offer a valuable framework for designing new multifunctional agents targeting neurodegenerative and metabolic disorders, improving efficiency in lead optimisation and reducing the need for extensive experimental screening. Novelty: This study uniquely correlates topological and electronic descriptors of aryl sulphonamides with dual inhibition of CA II and AChE, offering predictive models for multifunctional drug design. Keywords: QSARINS, Carbonic Anhydrase II, Acetylcholinesterase, Dual-target inhibitors, Molecular descriptors, Validation

Indian Journal of Science and TechnologyVol. 18(42)
Università degli Studi dell'Insubria
Openalex Percentile: Top 59%
Cholinesterase and Neurodegenerative Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.