QSAR models guided by molecular dynamics applied to human glucokinase activators

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorAssis, Tamiris Maria de-
Autor(es): dc.creatorGajo, Giovanna Cardoso-
Autor(es): dc.creatorAssis, Letícia Cristina de-
Autor(es): dc.creatorGarcia, Letícia Santos-
Autor(es): dc.creatorSilva, Daniela Rodrigues-
Autor(es): dc.creatorRamalho, Teodorico Castro-
Autor(es): dc.creatorCunha, Elaine Fontes Ferreira da-
Data de aceite: dc.date.accessioned2026-02-09T12:05:45Z-
Data de disponibilização: dc.date.available2026-02-09T12:05:45Z-
Data de envio: dc.date.issued2018-09-27-
Data de envio: dc.date.issued2018-09-27-
Data de envio: dc.date.issued2016-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/30795-
Fonte completa do material: dc.identifierhttps://onlinelibrary.wiley.com/doi/10.1111/cbdd.12683-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1154207-
Descrição: dc.descriptionIn this study, quantitative structure–activity relationship studies which make use of molecular dynamics trajectories were performed on a set of 54 glucokinase protein activators. The conformations obtained by molecular dynamics simulation were superimposed according to the twelve alignments tested in a virtual three‐dimensional box comprised of 2 Å cells. The models were generated by the technique that combines genetic algorithms and partial least squares. The best alignment models generated with a determination coefficient (r2) between 0.674 and 0.743 and cross‐validation (q2) between 0.509 and 0.610, indicating good predictive capacity. The 4D‐QSAR models developed in this study suggest novel molecular regions to be explored in the search for better glucokinase activators.-
Idioma: dc.languageen-
Publicador: dc.publisherWiley-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceChemical Biology & Drug Design-
Palavras-chave: dc.subjectDiabetes mellitus-
Palavras-chave: dc.subjectGlucokinase-
Palavras-chave: dc.subjectGlucokinase activators and 4D-QSAR-
Palavras-chave: dc.subjectType 2 diabetes-
Título: dc.titleQSAR models guided by molecular dynamics applied to human glucokinase activators-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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