Improving software performance for peptide electron transfer dissociation data analysis by implementation of charge state- and sequence-dependent scoring.
The use of electron transfer dissociation (ETD) fragmentation for analysis of peptides eluting in liquid chromatography tandem mass spectrometry experiments is increasingly common and can allow identification of many peptides and proteins in complex mixtures. Peptide identification is performed through the use of search engines that attempt to match spectra to peptides from proteins in a database. However, software for the analysis of ETD fragmentation data is currently less developed than equivalent algorithms for the analysis of the more ubiquitous collision-induced dissociation fragmentation spectra. In this study, a new scoring system was developed for analysis of peptide ETD fragmentation data that varies the ion type weighting depending on the precursor ion charge state and peptide sequence. This new scoring regime was applied to the analysis of data from previously published results where four search engines (Mascot, Open Mass Spectrometry Search Algorithm (OMSSA), Spectrum Mill, and X!Tandem) were compared (Kandasamy, K., Pandey, A., and Molina, H. (2009) Evaluation of several MS/MS search algorithms for analysis of spectra derived from electron transfer dissociation experiments. Anal. Chem. 81, 7170-7180). Protein Prospector identified 80% more spectra at a 1% false discovery rate than the most successful alternative searching engine in this previous publication. These results suggest that other search engines would benefit from the application of similar rules.
Department of Pharmaceutical Chemistry, University of California, San Francisco, California 94158-2517, USA.
Peter R
PR
Baker
Katalin F
KF
Medzihradszky
Robert J
RJ
Chalkley
D000465:Algorithms; D002853:Chromatography, Liquid; D004579:Electron Transport; D010455:Peptides / Q000737:chemistry*; D012984:Software; D053719:Tandem Mass Spectrometry
D010455:Peptides