Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/41414
metadata.artigo.dc.title: Bi- and multilinear PLS coupled to MIA-QSAR in the prediction of antifungal activities of some benzothiazole derivatives
metadata.artigo.dc.creator: Bitencourt, Michelle
Freitas, Matheus P.
metadata.artigo.dc.subject: MIA-QSAR
Candida albicans
Benzothiazole
PLS
N-PLS
Multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR)
Partial least squares (PLS)
Multiway partial least squares (NPLS)
metadata.artigo.dc.publisher: Bentham Science Publishers
metadata.artigo.dc.date.issued: 2009
metadata.artigo.dc.identifier.citation: BITENCOURT, M.; FREITAS, M. P. Bi- and multilinear PLS coupled to MIA-QSAR in the prediction of antifungal activities of some benzothiazole derivatives. Medicinal Chemistry, [S.l.], v. 5, n. 1, p. 79-86, 2009. DOI: 10.2174/157340609787049208.
metadata.artigo.dc.description.abstract: The activities of a series of benzothiazole derivatives, some Candida albicans N-myristoyltransferase (Nmt) inhibitors, were modeled through MIA-QSAR (multivariate image analysis applied to quantitative structure-activity relationship) by using two different regression methods: N-PLS, applied to the three-way array, and PLS, applied to the unfolded array. Both models demonstrated excellent predictive ability, with results comparable to those obtained through 3D approaches. In order to compare the results obtained through MIA descriptors with the predictions of a classical 2D QSAR, some representative physicochemical descriptors were calculated and regressed against the experimental pIC50 values through multiple linear regression, demonstrating that MIA-QSAR was superior for this series of compounds.
metadata.artigo.dc.identifier.uri: http://www.eurekaselect.com/83752
http://repositorio.ufla.br/jspui/handle/1/41414
metadata.artigo.dc.language: en_US
Appears in Collections:DQI - Artigos publicados em periódicos

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