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dc.creatorAssis, Tamiris Maria de-
dc.creatorGajo, Giovanna Cardoso-
dc.creatorAssis, Letícia Cristina de-
dc.creatorGarcia, Letícia Santos-
dc.creatorSilva, Daniela Rodrigues-
dc.creatorRamalho, Teodorico Castro-
dc.creatorCunha, Elaine Fontes Ferreira da-
dc.date.accessioned2018-09-27T19:32:09Z-
dc.date.available2018-09-27T19:32:09Z-
dc.date.issued2016-
dc.identifier.citationASSIS, T. M. de et al. QSAR models guided by molecular dynamics applied to human glucokinase activators. Chemical Biology & Drug Design, [S.l.], v. 87, n. 3, p. 455–466, Mar. 2016.pt_BR
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1111/cbdd.12683pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/30795-
dc.description.abstractIn 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.pt_BR
dc.languageen_USpt_BR
dc.publisherWileypt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceChemical Biology & Drug Designpt_BR
dc.subjectDiabetes mellituspt_BR
dc.subjectGlucokinasept_BR
dc.subjectGlucokinase activators and 4D-QSARpt_BR
dc.subjectType 2 diabetespt_BR
dc.titleQSAR models guided by molecular dynamics applied to human glucokinase activatorspt_BR
dc.typeArtigopt_BR
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