Improving software performance for peptide electron transfer dissociation data analysis by implementation of charge state- and sequence-dependent scoring

Abstract

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.

Fig. 1.

Receiver operating characteristic plots showing numbers of spectral identifications for given number of matches to decoy part of database. a, results for all enzyme data. For each enzyme/chemical cleavage, the results for Protein Prospector (PP) version 5.3 are represented by a dashed line, whereas results for the newer version 5.4 are represented by a solid line. b, results for Lys-C data when searched using two versions of Protein Prospector and using X!Tandem allowing for c and z^· ion (cz) or c, y, and z^· ions (cyz).

Fig. 2.

Bar charts plotting overlap in spectral identifications for each search engine at each level of agreement between search engine results. The total height of the plot is the number of spectra matched at each level of agreement, and the dark bar is the number of spectra at a given level of agreement for which the particular search engine is one of the members. M, Mascot; O, OMSSA; P, Protein Prospector; S, Spectrum Mill; X, X!Tandem.

Fig. 3.

Total numbers and distribution of spectra identified to precursors of different charge states by search engines OMSSA, Mascot, Spectrum Mill (SM), X!Tandem, and two versions of Protein Prospector (PP). The values for search engines other than Protein Prospector were derived from filtering of the results created by Kandasamy et al. (17). For each charge state, the total number and percentage of identifications are indicated.