Peptide charge state determination for low-resolution tandem mass spectra

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 change 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 a multiply-charged spectra, we obtain a 40% reduction in search time while maintaining an average of 99% of peptide and 99% of protein identifications originally-obtained from these spectra.