Integrated computational analysis of Garcinia kola phytochemicals as acetylcholinesterase inhibitors: molecular docking, molecular dynamics simulations, and DFT studies

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cholinergic dysfunction, making acetylcholinesterase (AChE) a key therapeutic target. Although Garcinia kola has been widely reported to possess anticholinesterase activity, the molecular basis underlying this effect remains poorly understood. In this study, a comprehensive in silico investigation was conducted to evaluate the AChE inhibitory potential of twenty-eight phytochemicals reported from G. kola . Molecular docking against human AChE (PDB ID: 4EY7) identified several compounds with strong binding affinities, notably amentoflavone (−12.0 kcal/mol), garcinoic acid (−11.4 kcal/mol), and tocotrienol (−11.4 kcal/mol), outperforming reference inhibitors. Binding interactions revealed effective engagement with key catalytic and peripheral site residues. Molecular dynamics simulations (100 ns) confirmed the stability of the top ligand–enzyme complexes, while MM/GBSA calculations identified garcinoic acid as the most thermodynamically favorable binder. Density functional theory (DFT) analyses further provided insights into the electronic properties and reactivity of the lead compounds, supporting their interaction profiles. ADMET predictions indicated favorable pharmacokinetic properties, with tocotrienol demonstrating superior blood–brain barrier permeability. Importantly, amentoflavone ranked highest based on docking affinity, garcinoic acid ranked highest based on MM/GBSA binding free energy and molecular dynamics stability, while tocotrienol exhibited the most favorable pharmacokinetic profile. Overall, integrated computational prioritization identified garcinoic acid and tocotrienol as the leading compounds for further experimental evaluation. These findings provide a molecular basis for the anticholinesterase activity of G. kola and support future validation studies.