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ProbIDtree: An automated software program capable of identifying multiple peptides from a single collision‐induced dissociation spectrum collected by a tandem mass spectrometer
Author(s) -
Zhang Ning,
Li Xiaojun,
Ye Mingliang,
Pan Sheng,
Schwikowski Benno,
Aebersold Ruedi
Publication year - 2005
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200401260
Subject(s) - fragmentation (computing) , tandem mass spectrometry , database search engine , peptide , collision induced dissociation , mass spectrometry , chemistry , search engine , computer science , dissociation (chemistry) , ion , collision , mass spectrum , analytical chemistry (journal) , chromatography , information retrieval , biochemistry , computer security , organic chemistry , operating system
In MS/MS experiments with automated precursor ion, selection only a fraction of sequencing attempts lead to the successful identification of a peptide. A number of reasons may contribute to this situation. They include poor fragmentation of the selected precursor ion, the presence of modified residues in the peptide, mismatches with sequence databases, and frequently, the concurrent fragmentation of multiple precursors in the same CID attempt. Current database search engines are incapable of correctly assigning the sequences of multiple precursors to such spectra. We have developed a search engine, ProbIDtree, which can identify multiple peptides from a CID spectrum generated by the concurrent fragmentation of multiple precursor ions. This is achieved by iterative database searching in which the submitted spectra are generated by subtracting the fragment ions assigned to a tentatively matched peptide from the acquired spectrum and in which each match is assigned a tentative probability score. Tentatively matched peptides are organized in a tree structure from which their adjusted probability scores are calculated and used to determine the correct identifications. The results using MALDI‐TOF‐TOF MS/MS data demonstrate that multiple peptides can be effectively identified simultaneously with high confidence using ProbIDtree.