Computational Investigation of Natural Flavonoids as Inhibitors of Human Acetylcholinesterase (AChE) in Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and cholinergic dysfunction. Acetylcholinesterase (AChE) inhibition remains a validated therapeutic approach to alleviate cholinergic deficits by sustaining acetylcholine levels at synapses. Currently approved AChE inhibitors, including donepezil, rivastigmine, and galantamine, offer only symptomatic relief and are limited by adverse effects. Natural flavonoids, a diverse class of polyphenolic compounds, have emerged as promising neuroprotective agents due to their antioxidant, anti-inflammatory, and cholinesterase-inhibitory properties. In this study, we performed a comprehensive computational investigation of six flavonoids epicatechin gallate, luteolin, quercetin, kaempferol, apigenin, and naringenin as potential inhibitors of human AChE. Molecular docking against the crystal structure of human AChE (PDB ID: 4EY7) revealed binding energies ranging from −8.6 to −10.6 kcal/mol, with epicatechin gallate and luteolin outperforming the reference drug donepezil (−9.2 kcal/mol). Binding poses indicated multi-site engagement involving catalytic and peripheral residues, with consistent π–π stacking interactions with Trp86 and hydrophobic contacts with Phe295 and Tyr337. Molecular dynamics (MD) simulations over 100 ns confirmed the stability of the flavonoid–AChE complexes, particularly for epicatechin gallate, which maintained persistent hydrogen-bonding networks and exhibited the lowest ligand RMSD values. MM-PBSA free energy calculations supported these findings, yielding binding free energies of −56.2 kcal/mol for epicatechin gallate and −51.0 kcal/mol for luteolin, both superior to donepezil. These results suggest that specific flavonoids, particularly epicatechin gallate and luteolin, possess strong inhibitory potential against AChE, with implications for developing safer, natural-product-based therapeutics for Alzheimer’s disease. Experimental validation is recommended to confirm these computational predictions.