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Updated: Mar 17, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Molecular Docking Guided Comparative GFA, G/PLS, SVM and ANN Models of Structurally Diverse Dual Binding Site
Shikhar Gupta1, Adyary Fallarero2, Mikko J Vainio2
1Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector 67, S.A.S. Nagar-160 062, Punjab, India phone: 0091-172-2214682-2019, fax: 0091-172-2214692;
Abstract:
Recently discovered 42 AChE inhibitors binding at the catalytic and peripheral anionic site were identified on the basis of molecular docking approach, and its comparative quantitative structure-activity relationship (QSAR) models were developed. These structurally diverse inhibitors were obtained by our previously reported high-throughput in vitro screening technique using 384-well plate's assay based on colorimetric method of Ellman. QSAR models were developed using (i) genetic function algorithm, (ii) genetic partial least squares, (iii) support vector machine and (iv) artificial neural network techniques. The QSAR model robustness and significance was critically assessed using different cross-validation techniques on test data set. The generated QSAR models using thermodynamic, electrotopological and electronic descriptors showed that nonlinear methods are more robust than linear methods, and provide insight into the structural features of compounds that are important for AChE inhibition.
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