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.
Highlights
Modern applications of chromatography have spread far beyond its original role as a method for preparative separations
Biomimetic separations usually use physiological pH to maximize the similarity between biological systems and the artificial biphasic separation environment
IAM.PC.DD2 was found to be more hydrophilic and to exhibit lower peptide retention compared to octadecyl-silica (C18). 2D LC-MS/MS analysis of a complex S. cerevisiae digest with IAM.PC or C18 columns in the first dimension allowed the measurement of the retention properties of tens of thousands of peptides – sufficient for the confident assignment of retention coefficients and the development of a sequence-specific prediction algorithm
Summary
Modern applications of chromatography have spread far beyond its original role as a method for preparative separations. Peptide retention time prediction for IAM.PC stationary phases of various substances in the systems mimicking real biological environments [3] represent some of the most interesting fundamental biochemical applications of chromatography. The latter, known under the broad term of biomimetic chromatography, has found applications in developing fast assays to determine lipophilicity, protein binding, and phospholipid binding – all critically important parameters in drug design. Similar measurements on phospholipid-modified phases such as immobilized artificial membrane phosphatidylcholine (IAM.PC) provide more biologically relevant information on phospholipid binding, i.e. cell membrane permeability [4]
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