Mechanistic Insights into Thiazolidinones as Anticholinesterase Agents: 3D QSAR Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Studies for Alzheimer’s Therapy

Alertness toward multitarget, including acetylcholinesterase and butyrylcholinesterase, is crucial in addressing Alzheimer’s disease (AD). This study aims to explore the cholinesterase inhibitory potential of 37 thiazolidinone derivatives through computational techniques. In this study, in silico tools such as pharmacophore modeling, atom-based 3D QSAR study, molecular docking, binding free energy determination, molecular dynamics and density functional theory (DFT) studies were conducted by the software Schrodinger. Molecular docking against acetylcholinesterase (6O4W) displayed compound a6, with outstanding docking, complemented by MMGBSA for binding energy evaluation. Meanwhile, molecular dynamics (MD) simulations validated the stability of ligand-enzyme complexes and confirmed the stability of the a6/6O4W and a6/6EYF complexes. In DFT studies, based on the alpha_HOMO and alpha_LUMO energies, compound a6 was found to be electronically stable. Pharmacophore modeling and QSAR analysis identified structural features essential for inhibition. Pharmacophore modeling identified the five-feature hypotheses AAHHR_4 as the key structural feature for optimal inhibition. 3D-QSAR contour plot analysis was performed for the best compounds (in vitro and in silico studies) and compared with the weak compounds (in vitro studies). These findings emphasize the potential of thiazolidinone derivatives as potent acetylcholinesterase inhibitors. PASS tool predicted that all compounds would have anti-Alzheimer potential. Assessments of promiscuity showed that all thiazolidinones would be specific rather than promiscuous. These findings highlight the significance of computational studies in identifying promising compounds for treating AD.