Predictive Liquid Chromatography of Peptides Based on Hydrophilic Interactions for Mass Spectrometry-Based Proteomics

• Published in: Journal of analytical chemistry (New York, N.Y.) Vol. 72; no. 14; pp. 1375 - 1382
• Main Authors: Lobas, A. A., Levitsky, L. I., Fichtenbaum, A., Surin, A. K., Pridatchenko, M. L., Mitulovic, G., Gorshkov, A. V., Gorshkov, M. V.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 30-12-2017; Springer; Springer Nature B.V
• Subjects: Analytical Chemistry; Chemistry; Chemistry and Materials Science; Chromatography; Complexity; Eluents; High performance liquid chromatography; Innovations; Mass spectrometry; Mathematical models; Model testing; Orthogonality; Peptides; Predictions; Properties; Proteomics; Retention; Scientific imaging; Separation; Silicon dioxide; Spectroscopy; Statistical analysis; Statistical methods; proteomics; HILIC; retention time prediction; peptide separation
• ISSN: 1061-9348; 1608-3199
• DOI: 10.1134/S1061934817140076

High-performance liquid chromatography (HPLC) is widely used for separation of complex peptide mixtures before mass spectrometry-based proteome analysis. In this analysis, reversed phase HPLC (RPHPLC) using non-polar stationary phases such as surface-modified silica containing alkyl groups (e.g., C18) is typically employed. Because of the high heterogeneity of proteomic samples, multidimensional separation approaches gained increasing attention recently to tackle this complexity and extremely high range of concentrations. In two-dimensional liquid chromatography, hydrophilic interaction chromatography (HILIC) is often a method of choice for combination with RP-HPLC because it uses reversed-phase type eluents and allows efficient separation of polar peptides. Due to the high degree of orthogonality in this two-dimensional separation space, it is tempting to develop approaches for predicting peptide retention times for HILIC-based separations similar to the ones for RP-HPLC. Recent successful efforts in this area were focused on developing retention coefficient (RC)-based approaches. Herein, we explored the feasibility of using a statistical thermodynamic model for prediction of peptide retention times in HILIC separations and determined the phenomenological parameters of the model for a bare silica column. The performance of the developed model was tested using HPLC-MS analysis of a set of synthetic peptides, as well as a tryptic peptide mixture.