Improving peptide identification with single-stage mass spectrum peaks

摘要

Motivation: Database searching is the major peptide identification method in shotgun proteomics. It searches tandem mass spectrometry (MS/MS) spectra against a protein database to identify target peptides. The success of such a database searching method relies on a scoring algorithm that can evaluate the quality of peptide-spectrum matches (PSMs) accurately. However, current scoring algorithms frequently generate inaccurate assignments due to variations and noises in the MS/MS spectra. To address this issue, we like to improve peptide identification by using additional information from other data sources.Results: Single-stage MS data is complementary to MS/MS data in the sense that it provides broader mass coverage but less sequence information. In this article, we show that single-stage MS data can be used to re-rank PSMs. The proposed method explores a linear combination of scores between MS and MS/MS data to perform re-ranking. Experimental results on real data show that such a re-ranking strategy improves the identification performance significantly.