Reynoso-García María Fernanda, Nicolás-Álvarez Dulce E, Tenorio-Barajas A Yair, Reyes-Chaparro Andrés
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.
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.
Int J Mol Sci. 2025 Apr 17;26(8):3781. doi: 10.3390/ijms26083781.
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.
乙酰胆碱酯酶（AChE）是一种关键酶，通过在突触间隙水解乙酰胆碱参与神经传递，使其成为药物发现的关键靶点，尤其是在治疗阿尔茨海默病等神经退行性疾病方面。计算方法，特别是分子对接和分子动力学（MD）模拟，已成为通过预测配体结合亲和力、相互作用机制和构象动力学来识别和优化AChE抑制剂的不可或缺的工具。本综述为未来使用分子对接和MD模拟研究AChE提供了全面指南。它汇编并分析了过去五年进行的研究，对最广泛使用的计算工具进行了批判性评估，包括AutoDock、AutoDock Vina和GROMACS，这些工具对AChE抑制剂筛选的进展做出了重大贡献。此外，我们确定了对接研究中最常用的AChE晶体结构PDB ID: 4EY7，并强调了多奈哌齐，这是一种成熟的参考分子，在新型抑制剂的计算筛选中广泛用作对照。通过研究这些关键方面，本综述旨在提高虚拟筛选方法的准确性和可靠性，并指导研究人员选择最合适的计算方法。对接和MD模拟的整合不仅改善了命中识别和先导优化，还为AChE-配体相互作用提供了更深入的机制见解，有助于合理设计更有效的AChE抑制剂。
