Hydrophilic properties as a new contribution for computer-aided identification of short peptides in complex mixtures

A new method to predict elementary amino acid (AA) composition of peptides (molar mass <1,000 g/mol) is described. This procedure is based on a computer-aided method using three combined analyses-reversed phase liquid chromatography (RPLC), hydrophilic interaction chromatography (HILIC) and capillary electrophoresis coupled with mass spectrometry-and using a software calculating all possible amino acid combinations from the mass of any given peptide. The complementarity between HILIC and RPLC was demonstrated. Peptide retention prediction in HILIC was successfully modelled, and the achieved prediction accuracy was as high as r2=0.97. This mathematical model, based on amino acid retention contributions and peptide length, provided the information about peptide hydrophilicity that was not redundant with its hydrophobicity. Correlations between respectively the hydrophobicity coefficients and RPLC retention time, hydrophilicity and HILIC retention time, and electrophoretic mobility and migration time were used for ranking all potential AA combinations corresponding to the given mass. The essential contribution of HILIC in this identification strategy and the need to combine the three models to significantly increase identification capabilities were both shown. Applied to an 18-standard peptide mixture, the identification procedure enabled the actual AA combination determination of the 14 di- to pentapeptides, in addition to an over 98 % reduction of possible combination numbers for the four hexapeptides. This procedure was then applied to the identification of 24 unknown peptides in a rapeseed protein hydrolysate. The effective AA composition was found for ten peptides, whereas for the 14 other peptides, the number of possible combinations was reduced by over 95 % thanks to the association of the three analyses. Finally, as a result of the information provided by the analytical techniques about peptides present in the mixture, the proposed method could become a highly valuable tool to recover bioactive peptides from undefined protein hydrolysates.