Evidence map›Paper›PMID 40332446›Full record

ReviewInternational journal of molecular sciences2025

Structural Bioinformatics Applied to Acetylcholinesterase Enzyme Inhibition.

María Fernanda Reynoso-García, Dulce E Nicolás-Álvarez, A Yair Tenorio-Barajas, Andrés Reyes-Chaparro

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

María Fernanda Reynoso-GarcíaDepartamento 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.
Dulce E Nicolás-ÁlvarezDepartamento de Fisiología, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Av. Wilfrido Massieu S/N, Unidad Profesional Adolfo López Mateos, Mexico City 07738, Mexico.ORCID 0000-0002-1717-9081
A Yair Tenorio-BarajasLaboratorio 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.ORCID 0000-0001-7256-5199
Andrés Reyes-ChaparroDepartamento 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.ORCID 0000-0002-6677-0740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AcetylcholinesteraseCholinesterase InhibitorsComputational BiologyAlzheimer DiseaseDrug DiscoveryHumansLigandsMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingAcetylcholinesteraseCholinesterase InhibitorsLigandsacetylcholinesterasebioinformaticsdockingdrug designvirtual screening

Identifiers

PMID40332446
PMCPMC12028328

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.