Repurposing FDA‐Approved Drugs as Acetylcholinesterase Inhibitors for Alzheimer's Disease: An Integrated In Silico Approach

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and memory loss. Current therapies offer limited symptomatic relief and are often associated with adverse effects, necessitating the identification of safer and more effective molecules. In this study, an integrated computational approach involving e‐pharmacophore modelling, molecular mechanics, DFT analysis, and dynamics simulations were employed to identify acetylcholinesterase (AChE) inhibitors from FDA‐approved drugs. An e‐pharmacophore model (AHHRR) was generated using the AChE–Donepezil complex (PDB ID: 6O4W), and a library of 1123 FDA‐approved drugs were screened against the model. The top 30 hits were shortlisted, followed by docking analysis, which identified 10 promising candidates with Glide scores ranging from −13.92 to −12.02 kcal/mol. Among these, Ropinirole demonstrated significant binding affinity with a Glide score of −13.31 kcal/mol and a Δ G _bind of −93.72 kcal/mol, along with superior ligand efficiency compared to standard Donepezil. Key interactions of Ropinirole with residues TRP86, TYR337, PHE338, TRP286, and TYR341 suggest a binding mode similar to Donepezil. DFT studies confirmed its favorable electronic properties. Dynamics simulations demonstrated robust and stable binding of Ropinirole to the AChE active site throughout 200 ns. These findings highlight Ropinirole as a promising candidate for designing novel molecules for treating Alzheimer's disease.