Evidence map›Paper›PMID 40856973›Full record

ArticleCell biochemistry and biophysics2025

Bioisosteric and Virtual Screening Approach to Identify Natural Inhibitors of Chikunguya alphavirus nsP3.

Cássia Milene Ribeiro Lopes, Leonardo Pereira de Araújo, Caio Pacífico Mariano, Lorena Falleiros, Walter Filgueira de Azevedo Junior, Luiz Felipe Leomil Coelho, Nelson José Freitas da Silveira

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Article in Cell biochemistry and biophysics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Cássia Milene Ribeiro LopesLaboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil. cassia.lopes@sou.unifal-mg.edu.br.ORCID http://orcid.org/0009-0000-4822-9777
Leonardo Pereira de AraújoLaboratory of Molecular Biology of Microorganisms, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.ORCID http://orcid.org/0000-0003-0212-3365
Caio Pacífico MarianoLaboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.ORCID http://orcid.org/0009-0008-7676-7722
Lorena FalleirosLaboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.ORCID http://orcid.org/0009-0004-6937-7604
Walter Filgueira de Azevedo JuniorLaboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.ORCID http://orcid.org/0000-0001-8640-357X
Luiz Felipe Leomil CoelhoVaccine Laboratory, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil.ORCID http://orcid.org/0000-0003-4289-384X
Nelson José Freitas da SilveiraLaboratory of Molecular Modeling and Computer Simulation, Federal University of Alfenas (UNIFAL), Alfenas, Minas Gerais, Brazil. nelson.silveira@unifal-mg.edu.br.ORCID http://orcid.org/0000-0001-9257-7322

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) 001
6 · The paper itself

Abstract

Chikungunya fever is an arboviral disease characterized by high fever, rash, and intense polyarthralgia, which may persist and evolve into a chronic condition, significantly impairing quality of life. The etiological agent, Chikungunya virus (CHIKV), is an alphavirus transmitted by Aedes aegypti mosquitoes and represents an increasing global public health concern due to its epidemic potential, economic burden, and the lack of specific antiviral therapies. In this context, in silico methodologies have become valuable tools in drug discovery and repurposing. This study aimed to predict natural compounds capable of inhibiting CHIKV non-structural protein 3 (nsP3). A total of 84,215 natural compounds from the ZINC20 database were screened through molecular docking using AutoDock Vina, with nsP3 as the target receptor. Ligand-protein interactions were visualized and analyzed with LigPlot+ and PyMOL. The top candidates were further refined through bioisosteric modifications using MolOpt, and their pharmacokinetic properties were predicted via the pkCSM platform. Among the optimized molecules, three bioisosteres, Chikv_bio1, Chikv_bio2, and Chikv_bio3, demonstrated favorable docking scores, interaction profiles, and ADMET properties, suggesting promising inhibitory activity against nsP3. These findings support the potential of natural compound-based drug design and highlight the importance of advancing to in vitro and in vivo validation to confirm the therapeutic relevance of these candidates and contribute to the development of specific treatments for Chikungunya fever.

Indexed as

Antiviral AgentsBiological ProductsChikungunya virusViral Nonstructural ProteinsAnimalsDrug Evaluation, PreclinicalHumansLigandsMolecular Docking SimulationAntiviral AgentsBiological ProductsLigandsnsp3 protein, alphavirusViral Nonstructural ProteinsAlphavirusBioisosterismChikungunya feverChikungunya virusNatural productsVirtual screening

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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.