In Silico Drug Design and Virtual Screening of Novel Donepezil Derivatives : ADMET Profiling, Molecular Docking, and Molecular Dynamics Simulations

Abstract

Alzheimer‘s disease (AD) remains one of the most pressing global neurological challenges, primarily driven by amyloid-beta (Aβ) aggregation and cholinergic system impairment, both of which contribute to progressive cognitive decline. Although Donepezil, an acetylcholinesterase (AChE) inhibitor, is commonly prescribed to alleviate symptoms, its clinical efficacy is often limited by poor long-term outcomes and side effects. In this study, a series of novel Donepezil analogues were designed and evaluated to enhance pharmacokinetic properties and binding efficiency against key AD targets, namely Aβ and AChE, using advanced computational techniques. Analogues were generated through computer-aided drug design methods and screened for ADMET properties using SwissADME and ProTox-II platforms. Molecular docking was conducted using Schrödinger Maestro to identify favorable binding interactions, followed by 100-nanosecond molecular dynamics (MD) simulations in Desmond to assess the structural stability of the most promising ligand-protein complexes under physiological conditions. The results showed that analogues Don11, Don12, and Don15 exhibited strong binding affinities and maintained stable interactions throughout the simulations, with RMSD values remaining below 2.5 Å. Notably, Don15 demonstrated superior stability and AChE inhibition potential, making it a particularly promising candidate. These findings suggest that Don11, Don12, and Don15 hold significant potential as next￾generation therapeutic agents for Alzheimer‘s disease.