Peptide charge state determination for low-resolution tandem mass spectra
Aaron A. Klammer, Christine C. Wu Michael J. MacCoss and William Stafford Noble
The Computational Systems Bioinformatics Conference, Stanford, CA, August 8-11, 2005. pp. 175-185.
Abstract
Mass spectrometry is a particularly useful technology for the rapid and robust identification of peptides and proteins in complex mixtures. Peptide sequences can be identified by correlating their observed tandem mass spectra (MS/MS) with theoretical spectra of peptides from a sequence database. Unfortunately, to perform this search the charge of the peptide must be known, and current charge state determination algorithms only discriminate singly from multiply-charged spectra: distinguishing +2 from +3, for example, is unreliable. Thus, search software is forced to search multiply charged spectra multiple times.
To minimize this inefficiency, we present a support vector machine (SVM) that quickly and reliably classifies multiply-charged spectra as having either a +2 or +3 precursor peptide ion. By classifying all multiply charged spectra, we obtain a 40% reduction in search time while maintaining an average of 99% of peptide and 99% of protein identifications obtained in the original search from multiply charged spectra.
Supplementary data
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