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Title: Prediction of 13C chemical shifts in methoxyflavonol derivatives using MIA-QSPR
Keywords: MIA-QSPR
13C chemical shifts
Methoxyflavonol derivatives
Multivariate image analysis applied to quantitative-structure–property relationships (MIA-QSPR)
Gauge Iincluded atomic orbital (GIAO)
Issue Date: Oct-2009
Publisher: Elsevier
Citation: GOODARZI, M.; FREITAS, M. P.; RAMALHO, T. C. Prediction of 13C chemical shifts in methoxyflavonol derivatives using MIA-QSPR. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, [S.l.], v. 74, n. 2, p. 563-568, Oct. 2009. DOI: 10.1016/j.saa.2009.07.003.
Abstract: The 13C chemical shifts of 19 methoxyflavonol derivatives have been modeled through using a structure-based quantitative structure–property relationship approach, which is based on the treatment of 2D images. In MIA-QSPR (multivariate image analysis applied to quantitative-structure–property relationships), descriptors correlating with dependent variables are pixels (binaries) of 2D chemical structures; variant pixels in the structures (substituents) account for the explained variance in the chemical shifts. Thus, a predictive model may be built from the regression between descriptors and experimental data. The MIA-QSPR approach coupled to partial least squares (PLS) regression built for the series of flavonols revealed that the predictive ability of MIA descriptors is comparable, or even superior for the fused rings moiety, when compared to the well-known Gauge Included Atomic Orbital (GIAO) procedure for 13C chemical shifts calculations.
Appears in Collections:DQI - Artigos publicados em periódicos

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