Substituent Effects on Electronic Properties and Acetylcholinesterase Inhibitory Potential of Donepezil Analogues: A DFT, Molecular Docking, and ADMET Study with Dynamics Validation of the Lead Candidate

Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is the leading cause of dementia in older people. Donepezil is an acetylcholinesterase inhibitor used for symptomatic management of AD. Due to its high efficacy, low hepatic toxicity, prolonged half-life, and enhanced bioavailability, it was used as a reference. In this study, a series of donepezil derivatives (MH-1 to MH-5) were designed through structural modification at the benzyl moiety and systematically investigated along with the reference using density functional theory, time-dependent DFT, molecular docking, and in silico pharmacokinetics analysis. The geometry optimization and electronic structure calculations were performed using the B3LYP/6-311G (d, p) level. Frontier molecular orbital analysis indicated reduced energy in MH-1 and MH-2 , while the optical study shows that all derivatives (MH-1 to MH-5) demonstrate a bathochromic shift. The molecular docking of all derivatives and the reference against the acetylcholinesterase receptor 4EY7 indicates strong predicted affinities, where MH-1 , MH-2 , and MH-4 show binding energy equivalent to the reference (-12.2 kcal/mol). A 300 ns molecular dynamics simulation of the AChE MH-4 complex showed a stable trajectory, as indicated by RMSD/RMSF profiles. Binding free energy calculated using MM-GBSA combined with the Interaction Entropy approximation yielded ΔG = -13.04 ± 3.73 kcal/mol, confirming favourable and thermodynamically stable binding. Moreover, the results of the ADME analysis indicated good oral absorption and blood-brain barrier penetration. Toxicity assessment predicted favourable safety profiles for most of the derivatives, except for a few that show potential concerns. In summary, all these results indicate that MH-4 has an encouraging physicochemical and computationally predicted bioactive profile for anti-Alzheimer drug development.