Peptide Retention Time Prediction in Hydrophilic Interaction Liquid Chromatography: Data Collection Methods and Features of Additive and Sequence-Specific Models.

Anal Chem

Manitoba Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada.

Published: May 2017

The development of a peptide retention prediction model for hydrophilic interaction liquid chromatography (XBridge Amide column) is described for a collection of ∼40 000 tryptic peptides. Off-line 2D LC-MS/MS analysis (HILIC-RPLC) of S. cerevisiae whole cell lysate has been used to acquire retention information for a HILIC separation. The large size of the optimization data set (more than 2 orders of magnitude compared to previous reports) permits the accurate assignment of hydrophilic retention coefficients of individual amino acids, establishing both the effects of amino acid position relative to peptide termini and the influence of peptide secondary structure in HILIC. The accuracy of a simple additive model with peptide length correction (R value of ∼0.96) was found to be much higher compared to an algorithm of similar complexity applied to RPLC (∼0.91). This indicates significantly smaller influence of peptide secondary structure and interactions with counterions in HILIC. Nevertheless, sequence-specific features were found. Helical peptides that tend to retain stronger than predicted in RPLC exhibit negative prediction errors using an additive HILIC model. N-cap helix stabilizing motifs, which increase retention of amphipathic helical peptides in RP, reduce peptide retention in HILIC independently of peptide amphipathicity. Peptides carrying multiple Pro and Gly (residues with lowest helical propensity) retain stronger than predicted. We conclude that involvement of the peptide backbone's carbonyl and amide groups in hydrogen-bond stabilization of helical structures is a major factor, which determines sequence-dependent behavior of peptides in HILIC. The incorporation of observed sequence dependent features into our Sequence-Specific Retention Calculator HILIC model resulted in 0.98 R value correlation, significantly exceeding the predictive performance of all RP and HILIC models developed for complex mixtures of tryptic peptides.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acs.analchem.7b00537DOI Listing

Publication Analysis

Top Keywords

peptide retention
12
peptide
9
hydrophilic interaction
8
interaction liquid
8
liquid chromatography
8
tryptic peptides
8
hilic
8
retention hilic
8
influence peptide
8
peptide secondary
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!