Peptide retention time prediction for immobilized artificial membrane phosphatidylcholine stationary phase: method development and preliminary observations

Authors

  • Daniel Gussakovsky
  • Haley Neustaeter
  • Victor Spicer
  • Oleg Krokhine University of Manitoba

DOI:

https://doi.org/10.5599/admet.520

Keywords:

Peptide retention modelling, immobilized artificial membrane chromatography

Abstract

Development of the first peptide retention prediction model for immobilized artificial membrane phosphatidylcholine (IAM.PC) stationary phase is reported. 2D LC-MS/MS analysis of a whole cell lysate of S. cerevisiae yielded a retention dataset of ~29,500 tryptic peptides; sufficient for confident assignment of retention coefficients which determine the contribution of individual amino acids in peptide retention. Retention data from the first dimension was used for the modeling: IAM.PC DD2 column, pH 7.4 ammonium bicarbonate, and water/acetonitrile gradient. Peptide separation using IAM.PC was compared to a standard C18 phase (Luna C18(2)). There was a significant reduction in peptide retention (~14% acetonitrile on average), indicating that the phosphatidylcholine stationary phase is significantly more hydrophilic. In comparison to the C18 phase, we found a substantial increase in the relative retention contribution for the positively charged Arg and Lys, and the aromatic Tyr, Trp and His residues. We also observed a decrease in retention contribution for the negatively charged Asp and Glu. This indicates an involvement of electrostatic interactions with the glycerophosphate functional groups, and possibly, delocalization effects from a hydrogen bond between the phosphate group and aromatic side chains in the separation mechanism.

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Published

16-06-2018

Issue

Section

Original Scientific Articles

How to Cite

Peptide retention time prediction for immobilized artificial membrane phosphatidylcholine stationary phase: method development and preliminary observations. (2018). ADMET and DMPK, 6(2), 190-199. https://doi.org/10.5599/admet.520

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