Fragmentation pathways of protonated peptides

Area of Science:

• Analytical Chemistry
• Biochemistry
• Computational Chemistry

Background:

• Peptide fragmentation in tandem mass spectrometry (MS/MS) is crucial for proteomics.
• Existing models like the 'mobile proton' model offer qualitative insights but lack quantitative predictive power.
• A deeper understanding of peptide dissociation chemistry is needed for advanced bioinformatics algorithms.

Purpose of the Study:

• To review and classify known peptide fragmentation pathways.
• To introduce and detail the 'pathways in competition' (PIC) model for analyzing MS/MS spectra.
• To provide a framework for semi-quantitative prediction of MS/MS spectra for improved proteomics.

Main Methods:

• Review and classification of peptide fragmentation channels based on chemistry.
• Detailed description of major peptide fragmentation pathways (PFPs), including pre-dissociation, dissociation, and post-dissociation events.
• Reevaluation of experimental and computational data using the PIC model, focusing on mechanism, energetics, and kinetics.

Main Results:

• The 'mobile proton' model provides only qualitative understanding of MS/MS spectra.
• The PIC model offers a detailed energetic and kinetic characterization of peptide fragmentation.
• Evidence for semi-quantitative predictability of ion intensity relationships (IIRs) in MS/MS spectra was presented.

Conclusions:

• The PIC model enhances the understanding of MS/MS spectra for protonated peptides.
• Further development of the PIC model can lead to semi-quantitative spectral prediction.
• This approach can inform the development of refined bioinformatics algorithms for MS/MS-based proteomics.