Statistical Characterization of the Charge State and Residue Dependence of Low-Energy CID Peptide Dissociation Patterns

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Abstract
Data mining was performed on 28 330 unique peptide tandem mass spectra for which sequences were assigned with high confidence. By dividing the spectra into different sets based on structural features and charge states of the corresponding peptides, chemical interactions involved in promoting specific cleavage patterns in gas-phase peptides were characterized. Pairwise fragmentation maps describing cleavages at all Xxx−Zzz residue combinations for b and y ions reveal that the difference in basicity between Arg and Lys results in different dissociation patterns for singly charged Arg- and Lys-ending tryptic peptides. While one dominant protonation form (proton localized) exists for Arg-ending peptides, a heterogeneous population of different protonated forms or more facile interconversion of protonated forms (proton partially mobile) exists for Lys-ending peptides. Cleavage C-terminal to acidic residues dominates spectra from singly charged peptides that have a localized proton and cleavage N-terminal to Pro dominates those that have a mobile or partially mobile proton. When Pro is absent from peptides that have a mobile or partially mobile proton, cleavage at each peptide bond becomes much more prominent. Whether the above patterns can be found in b ions, y ions, or both depends on the location of the proton holder(s) in multiply protonated peptides. Enhanced cleavages C-terminal to branched aliphatic residues (Ile, Val, Leu) are observed in both b and y ions from peptides that have a mobile proton, as well as in y ions from peptides that have a partially mobile proton; enhanced cleavages N-terminal to these residues are observed in b ions from peptides that have a partially mobile proton. Statistical tools have been designed to visualize the fragmentation maps and measure the similarity between them. The pairwise cleavage patterns observed expand our knowledge of peptide gas-phase fragmentation behaviors and may be useful in algorithm development that employs improved models to predict fragment ion intensities.