Evidence map›Paper›PMID 41331377›Full record

ReviewJournal of computer-aided molecular design2025

Multitarget-directed ligands in Alzheimer's disease: identification of AChE and BACE1 inhibitors by in silico approaches.

Raissa Alves da Conceição, Maria Letícia de Castro Barbosa, Alessandra Mendonça Teles de Souza

Abstract readReview
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In one paragraph

Review in Journal of computer-aided molecular design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Raissa Alves da ConceiçãoLaboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.ORCID http://orcid.org/0000-0001-8264-7673
Maria Letícia de Castro BarbosaDepartment of Pharmaceutical Sciences, Faculty of Pharmacy, Federal University of Juiz de Fora, Juiz de Fora, MG, Brazil. marialeticia.barbosa@ufjf.br.ORCID http://orcid.org/0000-0002-1764-8650
Alessandra Mendonça Teles de SouzaLaboratory of Molecular Modeling & QSAR (ModMolQSAR), Faculty of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil. amtsouza@pharma.ufrj.br.ORCID http://orcid.org/0000-0001-9986-405X

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 312878/2022-2Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001
6 · The paper itself

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions of people worldwide, with its prevalence expected to rise in the coming years. Due to the complexity of AD and the intricate interplay among its pathological mechanisms, the development of multitarget-directed ligands (MTDLs) has emerged as a promising therapeutic strategy. These compounds could simultaneously modulate multiple pathogenic pathways. Specifically, cholinergic and amyloid mechanisms, implicated in the onset of the disease, are regulated by AChE and BACE1, respectively. Therefore, targeting both pathways offers substantial therapeutic potential for AD. Computational tools can be useful in the identification of potential MTDL for these enzymes, reducing both costs and time in the drug discovery process. This review explores the relevance of this approach in the research and development for novel AD therapies, highlighting ongoing efforts focused on the identification and development of MTDLs for AChE and BACE1 inhibition through in silico methods. Virtual screening was the most frequently applied technique for a fast selection of ligands based on their affinity for the enzymes of interest. The in silico ADMET prediction also appears with a technique that allows the screening of compounds with drug-likeness. Moreover, evidence suggests that combining multiple computational methods can effectively identify drug candidates with optimized properties for target modulation and brain bioavailability.

Indexed as

AcetylcholinesteraseAlzheimer DiseaseAmyloid Precursor Protein SecretasesAspartic Acid EndopeptidasesCholinesterase InhibitorsComputer SimulationDrug DiscoveryHumansLigandsMolecular Docking SimulationAcetylcholinesteraseAmyloid Precursor Protein SecretasesAspartic Acid EndopeptidasesBACE1 protein, humanCholinesterase InhibitorsLigandsBeta-secretase 1CholinesteraseDualLigandMolecular modelingNeurodegenerative

Identifiers

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.