Evidence map›Paper›PMID 39583212›Full record

ArticleF1000Research2024

Identification of compounds from natural Peruvian sources as potential inhibitors of SARS-CoV-2 Mpro mutations by virtual screening and computational simulations.

Haruna Luz Barazorda-Ccahuana, Eymi Gladys Cárcamo Rodriguez, Angela Emperatriz Centeno-Lopez, Margot Paco-Chipana, Luis Daniel Goyzueta-Mamani, Miguel Angel Chavez-Fumagalli

Abstract read
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Article in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

6 authors.

Haruna Luz Barazorda-CcahuanaComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.ORCID https://orcid.org/0000-0001-8791-0506
Eymi Gladys Cárcamo RodriguezComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.
Angela Emperatriz Centeno-LopezComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.ORCID https://orcid.org/0000-0002-8670-963X
Margot Paco-ChipanaComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.ORCID https://orcid.org/0000-0002-2674-4281
Luis Daniel Goyzueta-MamaniComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.ORCID https://orcid.org/0000-0003-0308-1160
Miguel Angel Chavez-FumagalliComputational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Catolica de Santa Maria de Arequipa, Pedro Vilcapaza, Arequipa, 04000, Peru.ORCID https://orcid.org/0000-0002-8394-4802

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although the COVID-19 pandemic has diminished in intensity, the virus continues to circulate globally. The SARS-CoV-2 main protease (Mpro) is a key enzyme in the life cycle of the virus, making it important for the development of treatments against future variants of the virus. In this work, Peruvian natural compounds were evaluated against different mutations of the SARS-CoV-2 Mpro. Methods: In silico techniques such as virtual screening, all-atom molecular dynamics simulations, and energy estimation analysis were applied. Results: Of the tested compounds by virtual screening, rutin was identified as the best binding agent against the different proposed Mpro mutations. In addition, computational simulations and energy estimation analysis demonstrated the high structural and energetic stability between the Mpro-rutin systems. Conclusions: Overall, our study identified rutin as the most promising compound with a strong affinity for various Mpro mutations, potentially playing a key role in the development of new treatments for emerging viral variants.

Indexed as

Antiviral AgentsCoronavirus 3C ProteasesMolecular Dynamics SimulationMutationRutinSARS-CoV-2Biological ProductsComputer SimulationCOVID-19Drug Evaluation, PreclinicalHumansMolecular Docking SimulationPandemics3C-like proteinase, SARS-CoV-2Antiviral AgentsBiological ProductsCoronavirus 3C ProteasesRutinMain proteasemutationsPeruvian sourcesrutinSARS-CoV-2

Identifiers

PMID39583212
PMCPMC11585855

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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.