Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/30795
metadata.artigo.dc.title: QSAR models guided by molecular dynamics applied to human glucokinase activators
metadata.artigo.dc.creator: Assis, Tamiris Maria de
Gajo, Giovanna Cardoso
Assis, Letícia Cristina de
Garcia, Letícia Santos
Silva, Daniela Rodrigues
Ramalho, Teodorico Castro
Cunha, Elaine Fontes Ferreira da
metadata.artigo.dc.subject: Diabetes mellitus
Glucokinase
Glucokinase activators and 4D-QSAR
Type 2 diabetes
metadata.artigo.dc.publisher: Wiley
metadata.artigo.dc.date.issued: 2016
metadata.artigo.dc.identifier.citation: ASSIS, 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.
metadata.artigo.dc.description.abstract: In 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.
metadata.artigo.dc.identifier.uri: https://onlinelibrary.wiley.com/doi/10.1111/cbdd.12683
http://repositorio.ufla.br/jspui/handle/1/30795
metadata.artigo.dc.language: en_US
Appears in Collections:DQI - Artigos publicados em periódicos

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