Using multivariate statistical methods to model the electrospray ionization response of GXG tripeptides based on multiple physicochemical parameters

Misjudeen Raji, Fryčák P. Fryčák, Temiyasathit C. Temiyasathit, B. Kim S. B. Kim, Mavromaras G. Mavromaras, Ahn J.-M. Ahn, K. A. Schug

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    18 Scopus citations

    Abstract

    Response factors were determined for twelve GXG peptides (where G stands for glycine and X is any of alanine [A], arginine [R], asparagine [N], aspartic acid [D], glycine [G], histidine [H], leucine [L], lysine [K], phenylalanine [F], serine [S], tyrosine [Y], valine [V]) by electrospray ionization mass spectrometry (ESI-MS). The response factors were measured using a novel flow injection method. This new method is based on the Gaussian distribution of analyte concentration resulting from bandbroadening dispersion experienced by the analyte upon passage through an extended volume of PEEK tubing. This method removes the need for preparing a discrete series of standard solutions to assess concentration-dependent response. Relative response factors were calculated for each peptide with reference to GGG. The observed trends in the relative response factors were correlated with several analyte physicochemical parameters, chosen based on current understanding of ion release from charged droplets during the ESI process. These include analyte properties: nonpolar surface area; polar surface area; gas-phase basicity; proton affinity; and Log D. Multivariate statistical analysis using multiple linear regression, decision tree, and support vector regression models were investigated to assess their potential for predicting ESI response based on the analyte properties. The support vector regression model was more versatile and produced the least predictive error following 12-fold cross-validation. The effect of variation in solution pH on the relative response factors is highlighted, as evidenced by the different predictive models obtained for peptide response at two pH values (pH=6.0 and 9.0). The relationship between physicochemical parameters and associated ionization efficiencies forGXGtripeptides is discussed based on the equilibrium partitioning model.

    Original languageEnglish (US)
    Pages (from-to)2221-2232
    Number of pages12
    JournalRapid Communications in Mass Spectrometry
    Volume23
    Issue number14
    DOIs
    StatePublished - Jul 30 2009

    ASJC Scopus subject areas

    • Spectroscopy
    • Analytical Chemistry
    • Organic Chemistry

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