Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition
- Int J Mol Sci. 2025 Apr 17;26(8):3781. doi: 10.3390/ijms26083781.
- 1. Departamento de Morfología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Unidad Profesional Lázaro Cárdenas, Prolongación de Carpio y Plan de Ayala s/n, Col. Santo Tomás, Alcaldía Miguel Hidalgo, Mexico City 11340, Mexico.
- 2. Departamento de Fisiología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu S/N, Unidad Profesional Adolfo López Mateos, Mexico City 07738, Mexico.
- 3. Laboratorio de Nanobiotecnologia, Facultad de Ciencias Físico Matemáticas, Benemerita Universidad de Puebla, Av. San Cladio y 18 Sur, Col. San Manuel, Edif. FM6-108, Ciudad Universitaria, Puebla 72570, Mexico.
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.
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Cat. No.Product NameDescriptionTargetResearch Area
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target: Cholinesterase (ChE)