期刊
ANALYTICAL CHEMISTRY
卷 82, 期 23, 页码 9678-9685出版社
AMER CHEMICAL SOC
DOI: 10.1021/ac102228a
关键词
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资金
- Technology Transfer Office at the University of Manitoba Genome Canada
- Natural Sciences and Engineering Research Council of Canada
We have developed a sequence specific model for predicting slopes (S) in the fundamental equation of linear solvent strength theory for the reversed-phase HPLC separation of tryptic peptides detected in a typical bottom-up-proteomics experiment. These slopes control the variation in the separation selectivity observed when the physical parameters of chromatographic separation, such as gradient slope, flow rate, and column size are altered For example, with the use of an arbitrarily chosen set of tryptic peptides with a 4-times difference in the gradient slope between two experiments, the R(2) value of correlation between the observed retention times of identical species decreases to similar to 0 993-0 996 (compared to a theoretical value of similar to 1 00) The observed retention time shifts associated with variations or the gradient slope can be predicted a priori using the approach described here The proposed model is based on our findings for a set of synthetic species (Vu, H, Spicer, V, Gotfrid, A., Krokhin, 0 V J Chromatogr, A, 2010, 1217, 489-497), which postulate that slopes S can be predicted taking into account simultaneously pep tide length, charge, and hydrophobicity Here we extend this approach using an extensive set of real tryptic peptides We developed the procedure to accurately measure S-values in nano-RP HPLC MS experiments and introduced sequence-specific corrections for a more accurate prediction of the slopes S A correlation of 0 95 le-value between the predicted and experiment tal S-values was demonstrated Predicting S-values and calculating the expected retention time shifts when the physical parameters of separation like gradient slope are altered will facilitate a more accurate application of peptide retention prediction protocols, aid in the transfer of scheduled MRM (SRM) procedures between LC systems, and increase the efficiency of mterlaboratory data collection and comparison
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