Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition

Abstract

Acetylcholinesterase (AChE) is a critical enzyme involved in neurotransmission by hydrolyzing acetylcholine at the synaptic cleft, making it a key target for drug discovery, particularly in the treatment of neurodegenerative disorders such as Alzheimer’s disease. Computational approaches, particularly molecular docking and molecular dynamics (MD) simulations, have become indispensable tools for identifying and optimizing AChE inhibitors by predicting ligand-binding affinities, interaction mechanisms, and conformational dynamics. This review serves as a comprehensive guide for future research on AChE using molecular docking and MD simulations. It compiles and analyzes studies conducted over the past five years, providing a critical evaluation of the most widely used computational tools, including AutoDock, AutoDock Vina, and GROMACS, which have significantly contributed to the advancement of AChE inhibitor screening. Furthermore, we identify PDB ID: 4EY7, the most frequently used AChE crystal structure in docking studies, and highlight Donepezil, a well-established reference molecule widely employed as a control in computational screening for novel inhibitors. By examining these key aspects, this review aims to enhance the accuracy and reliability of virtual screening approaches and guide researchers in selecting the most appropriate computational methodologies. The integration of docking and MD simulations not only improves hit identification and lead optimization but also provides deeper mechanistic insights into AChE–ligand interactions, contributing to the rational design of more effective AChE inhibitors.