Prediction of electrophoretic enantioseparation of aromatic amino acids/esters through MIA-QSPR

Mohammad Goodarzi, Matheus P. Freitas

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Multivariate image analysis (MIA) descriptors have been applied to predict the enantiomer migration orders of a series of aromatic amino acids and aromatic amino esters. In MIA-QSPR, pixels of chemical structures (2D images) stand for descriptors, and structural changes account for the variance in relative migration times (RMTs). R and S enantiomers were differentiated by drawing up or down stereo bonds at the chiral carbon, and the RMT predictions of the title compounds in specific medium (20 mM Tris-citric acid background electrolyte (pH 2.50) containing 5.0 mM of (+)-18-crown-6-tetracarboxylic acid) were reliably obtained (r2 = 0.992, qLOO - CV2 = 0.926, and qL - 20 % - O - CV2 = 0.910) after removing two outliers from the dataset. MIA descriptors were capable to recognize the physicochemical information and may be useful to predict enantiomer migration orders of amino acids and amino esters whose pure enantiomers are unavailable.

Original languageEnglish (US)
Pages (from-to)363-366
Number of pages4
JournalSeparation and Purification Technology
Volume68
Issue number3
DOIs
StatePublished - Aug 25 2009

Keywords

  • Aromatic amino acids and esters
  • Chiral capillary electrophoresis
  • Enantiomer migration orders
  • MIA-QSPR

ASJC Scopus subject areas

  • Analytical Chemistry
  • Filtration and Separation

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