Evidence map›Paper›PMID 38835850›Full record

ArticleWorld journal of clinical oncology2024

Rafaela Viana Vieira, Gabrielle Caroline Peiter, Fabrício Freire de Melo, Ana Carla Zarpelon-Schutz, Kádima Nayara Teixeira

Abstract read
In one paragraph

Article in World journal of clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

5 authors.

Rafaela Viana VieiraUniversidade Federal do Paraná, Campus Toledo, Toledo 85919-899, Brazil.
Gabrielle Caroline PeiterUniversidade Tecnológica Federal do Paraná, Campus Toledo, Paraná 85902-490, Brazil.
Fabrício Freire de MeloUniversidade Federal da Bahia, Instituto Multidisciplinar em Saúde-Campus Anísio Teixeira, Vitória da Conquista 45029-094, Brazil.
Ana Carla Zarpelon-SchutzUniversidade Federal do Paraná, Campus Toledo, Toledo 85919-899, Brazil.
Kádima Nayara TeixeiraUniversidade Federal do Paraná, Campus Toledo, Toledo 85919-899, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColonization with

aimTo perform a computational prospecting of the interactions between phenolic compounds from medicinal plants and the CagA oncoprotein of

methodsIn this

resultsThe structure model obtained for the CagA oncoprotein exhibited high quality (C-score = 0.09) and was validated using parameters from the MolProbity platform. The GRaSP online platform identified 24 residues (phenylalanine and leucine) as potential binding sites on the CagA oncoprotein. Molecular docking simulations were conducted with the three-dimensional model of the CagA oncoprotein. No complexes were observed in the simulations between the carboxy-terminus region of CagA and the phenolic compounds; however, all phenolic compounds interacted with the central region of the oncoprotein. Phenolic compounds and CagA exhibited significant affinity energy (-7.9 to -9.1 kcal/mol): CagA/kaempferol formed 28 chemical bonds, CagA/myricetin formed 18 chemical bonds, CagA/quercetin formed 16 chemical bonds, CagA/ponciretin formed 13 chemical bonds, and CagA/chlorogenic acid formed 17 chemical bonds. Although none of the phenolic compounds directly bound to the amino acid residues of the K-Xn-R-X-R membrane binding motif, all of them bound to residues, mostly positively or negatively charged, located near this region.

conclusion

Indexed as

CagA oncoproteinHelicobacter pyloriIn silico analysesMedicinal plantsPhenolic compoundsProspective analysis

Identifiers

PMID38835850
PMCPMC11145963

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.