Better score function for peptide identification with ETD MS/MS spectra

peer-reviewed · BMC Bioinformatics · 2010

peer-reviewed · BMC Bioinformatics · 2010. Xiaowen Liu et al. Background Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in…
Date 2010-01-01
Type peer-reviewed
Venue BMC Bioinformatics
Publisher Springer Science and Business Media LLC
Contribution algorithm
DOI 10.1186/1471-2105-11-s1-s4
Citations (OpenAlex) 48
Venue 2-year citedness 4.71

Abstract

Background Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in proteomics. A good score function for measuring the match quality between a peptide and an MS/MS spectrum is instrumental for the protein identification. Traditionally the to-be-measured peptides are fragmented with the collision induced dissociation (CID) method. More recently, the electron transfer dissociation (ETD) method was introduced and has proven to produce better fragment ion ladders for larger and more basic peptides. However, the existing software programs that analyze ETD MS/MS data are not as advanced as they are for CID. Results To take full advantage of ETD data, in this paper we develop a new score function to evaluate the match between a peptide and an ETD MS/MS spectrum. Experiments on real data demonstrated that this newly developed score function significantly improved the de novo sequencing accuracy of the PEAKS software on ETD data. Conclusion A new and better score function for ETD MS/MS peptide identification was developed. The method used to develop our ETD score function can be easily reused to train new score functions for other types of MS/MS data.

Authors

  1. Xiaowen Liu · Indiana University Indianapolis, Indiana University School of Medicine, Indiana University-Purdue University Indianapolis, Tulane University, University of Waterloo
  2. Baozhen Shan · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  3. Lei Xin · Bioinformatics Solutions (Canada), Bioinformatics Solutions Inc., Western University
  4. Bin Ma · Rapid Novor Inc., University of Waterloo, University of Western Ontario, Western University

Methods and tools

  • PEAKS: Commercial DP-based de novo

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