Prediction of 13C chemical shifts in methoxyflavonol derivatives using MIA-QSPR

Mohammad Goodarzi, Matheus P. Freitas, Teodorico C. Ramalho

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)563-568
Number of pages6
JournalSpectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
Volume74
Issue number2
DOIs
StatePublished - Oct 1 2009

Keywords

  • C chemical shifts
  • GIAO
  • MIA-QSPR
  • Methoxyflavonol derivatives

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Spectroscopy

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