Data-mining a Set of Truth Spectra to Determine Peptide Fragmentation Chemistry

Vicki H. Wysocki
University of Arizona

Although protein identification algorithms that utilize peptide MS/MS spectra data have made proteomics studies possible, there is a demand for a higher success rate. It is clear that the algorithms sometimes fail even when the peptide in question is in the database and produces a spectrum with high S/N. Approximately 30,000 MS/MS spectra have been analyzed to
determine the dominant and unusual fragmentation pathways of peptides. The spectra are a "truth" set because they have MS/MS sequence assignments that have been confirmed by parallel accurate mass measurements and correlated
retention times in MS and MS/MS experiments. Patterns of enhanced or supressed cleavage, and their dependence on charge state or terminal basic residue identity, will be presented. The data-mining effort provides fragmentation information that may be useful for improving protein identification algorithms.


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