Evidence map›Paper›PMID 37855345›Full record

ArticleCurrent medicinal chemistry2024

Gerlane Salgueiro Barros, Débora Machado Barreto, Sandy Gabrielly Souza Cavalcanti, Tiago Branquinho Oliveira, Ricardo Pereira Rodrigues, Marcus Vinicius de Aragão Batista

Abstract read
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In one paragraph

Article in Current medicinal chemistry, 2024. 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
0.6field-weighted citation impact, top 29% of its field
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, 2 citations in OpenAlex.

  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

6 authors at 2 institutions in 1 country.

Gerlane Salgueiro BarrosLaboratory of Molecular Genetics and Biotechnology, Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.ORCID 0000-0002-6749-2375
Débora Machado BarretoLaboratory of Molecular Genetics and Biotechnology, Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.
Sandy Gabrielly Souza CavalcantiLaboratory of Molecular Genetics and Biotechnology, Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.
Tiago Branquinho OliveiraDepartment of Pharmacy, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.
Ricardo Pereira RodriguesLaboratory of Pharmacognosy, Federal University of Espirito Santo, Vitória, Espírito Santo, Brazil.ORCID 0000-0002-2924-0468
Marcus Vinicius de Aragão BatistaLaboratory of Molecular Genetics and Biotechnology, Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil.ORCID 0000-0003-4745-8919
Universidade Federal de Sergipe · BRUniversidade Federal do Espírito Santo · BR

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 307128/2022-9Coordenação de Aperfeiçoamento de Pessoal de Nível Superior finance code 001,23038.010050/2013-04Fundação de Apoio à Pesquisa e à Inovação Tecnológica do Estado de Sergipe
6 · The paper itself

Abstract

backgroundDecreased beef productivity due to papillomatosis has led to the development and identification of novel targets and molecules to treat the disease. Protein kinases are promising targets for the design of numerous chemotherapy drugs.

objectiveThis study aimed to screen and design new inhibitors of bovine Fyn, a protein kinase, using structure-based computational methods, such as molecular docking and molecular dynamics simulation (MDS).

methodsTo carry out the molecular docking analysis, five ligands obtained through structural similarity between active compounds along with the cross-inhibition function between the ChEMBL and Drugbank databases were used. Molecular modeling was performed, and the generated models were validated using PROCHECK and Verify 3D. Molecular docking was performed using Autodock Vina. The complexes formed between Fyn and the three best ligands had their stability assessed by MDS. In these simulations, the complexes were stabilized for 100 ns in relation to a pressure of 1 atm, with an average temperature of 300 k and a potential energy of 1,145,336 kJ/m converged in 997 steps.

resultsDocking analyses showed that all selected ligands had a high binding affinity with Fyn and presented hydrogen bonds at important active sites. MDS results support the docking results, as the ligand showed similar and stable interactions with amino acids present at the binding site of the protein. In all simulations, sorafenib obtained the best results of interaction with the bovine Fyn.

conclusionThe results highlight the identification of possible bovine Fyn inhibitors; however, further studies are important to confirm these results experimentally.

Indexed as

Molecular Docking SimulationMolecular Dynamics SimulationProtein Kinase InhibitorsProto-Oncogene Proteins c-fynAnimalsCattleCattle DiseasesLigandsPapillomavirus InfectionsLigandsProtein Kinase InhibitorsProto-Oncogene Proteins c-fynBovine papillomavirusFynMDSpapillomatosis.tyrosine-proteinvirtual screening

Identifiers

PMID37855345
OpenAlexW4387765235

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.