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dc.creatorBarigye, Stephen J.-
dc.creatorDuarte, Mariene H.-
dc.creatorNunes, Cleiton A.-
dc.creatorFreitas, Matheus P.-
dc.date.accessioned2018-07-09T10:21:40Z-
dc.date.available2018-07-09T10:21:40Z-
dc.date.issued2016-
dc.identifier.citationBARIGYE, S. J. et al. MIA-plot: a graphical tool for viewing descriptor contributions in MIA-QSAR. RSC Advances, [S. l.], v. 6, p. 49604-49612, 2016.pt_BR
dc.identifier.urihttp://pubs.rsc.org/en/content/articlelanding/2016/ra/c6ra09593c#!divAbstractpt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/29574-
dc.description.abstractA major challenge faced with the MIA-QSAR (Multivariate Image Analysis applied to Quantitative Structure–Activity Relationships) technique in molecular modeling is to obtain chemically intuitive information from the molecular descriptors that correlate to bioactivity values. This work reports a graphical tool that uses PLS regression coefficients (b) and the variable importance in projection (VIP) scores to give insight on the structural motifs responsible for increased or attenuated biological activities in a congeneric series of compounds. Three sets of compounds useful in food chemistry, namely fatty acids and derivatives (antimicrobial), anilides (antimicrobial) and disaccharides (sweeteners), were used to assess the practical contribution of these parameters in yielding more interpretable models. The MIA-QSAR models demonstrated satisfactory prediction performance and, most importantly, the relevance of single MIA predictors to the response variable could be assessed, thus allowing for the structural, electronic and physicochemical interpretation of the MIA-QSAR models. While VIP-based graphs were especially useful in providing insight on the molecular regions/substituents most affecting the property values, the b-based analysis indicated whether the particular regions/substituents negatively or positively influenced the dependent variables. It is therefore recommended that these parameters be employed as complementary tools for a more robust and lucid model interpretation.pt_BR
dc.languageen_USpt_BR
dc.publisherRoyal Society of Chemistrypt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceRSC Advancespt_BR
dc.subjectMolecular modelingpt_BR
dc.subjectVariable importance in projectionpt_BR
dc.subjectModelagem molecularpt_BR
dc.subjectImportância variável na projeçãopt_BR
dc.titleMIA-plot: a graphical tool for viewing descriptor contributions in MIA-QSARpt_BR
dc.typeArtigopt_BR
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