Improving peptide identification using an empirical peptide retention time database

Abstract

Peptide retention time (RT) is independent of tandem mass spectrometry (MS/MS) parameters and can be combined with MS/MS information to enhance peptide identification. In this paper, we utilized peptide empirical RT and MS/MS for peptide identification. This new approach resulted in the construction of an Empirical Peptide Retention Time Database (EPRTD) based on peptides showing a false-positive rate (FPR) <or=1%, detected in several liquid chromatography (LC)/MS/MS analyses. In subsequent experiments, the RT of peptides with FPR >1% was compared with empirical data derived from the EPRTD. If the experimental RT was within a specified time range of the empirical value, the corresponding MS/MS spectra were accepted as positive. Application of the EPRTD approach to simple samples (known protein mixtures) and complex samples (human urinary proteome) revealed that this method could significantly enhance peptide identification without compromising the associated confidence levels. Further analysis indicated that the EPRTD approach could improve low-abundance peptides and with the expansion of the EPRTD the number of peptide identifications will be increased. This approach is suitable for large-scale clinical proteomics research, in which tens of LC/MS/MS analyses are run for different samples with similar components.