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Mining a tandem mass spectrometry database to determine the trends and global factors influencing peptide fragmentation

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ANALYTICAL CHEMISTRY
卷 75, 期 22, 页码 6251-6264

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AMER CHEMICAL SOC
DOI: 10.1021/ac034616t

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A database of 5500 unique peptide tandem mass spectra acquired in an ion trap mass spectrometer was assembled for peptides derived from proteins digested with trypsin. Peptides were identified initially from their tandem mass spectra by the SEQUEST algorithm and subsequently validated manually. Two different statistical methods were used to identify sequence-dependent fragmentation patterns that could be used to improve fragmentation models incorporated into current peptide sequencing and database search algorithms. The currently accepted mobile proton model was expanded to derive a new classification scheme for peptide mass spectra, the relative proton mobility scale, which considers peptide ion charge state and amino acid composition to categorize peptide mass spectra into peptide ions containing nonmobile, partially mobile, or mobile protons. Quantitation of amide bond fragmentation, both N- and C-terminal to any given amino acid, as well as the positional effect of an amino acid in a peptide and peptide length on such fragmentation, has been determined. Peptide bond cleavage propensities, both positive (i.e., enhanced) and negative (i.e., suppressed), were determined and ranked in order of their cleavage preferences as primary, secondary, or tertiary cleavage effects. For example, primary positive cleavage effects were observed for Xaa-Pro and Asp-Xaa bond cleavage for mobile and nonmobile peptide ion categories, respectively. We also report specific pairwise interactions (e.g., Asn-Gly) that result in enhanced amide bond cleavages analogous to those observed in solution-phase chemistry. Peptides classified as nonmobile gave low or insignificant scores, below reported MS/MS score thresholds (cutoff filters), indicating that incorporation of the relative proton mobility scale classification would lead to improvements in current MS/MS scoring functions.

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