Development of Software Workflow for the Rapid Detection of Cross-Linked Dipeptides

Area of Science:

• Proteomics
• Analytical Chemistry
• Biochemistry

Background:

• Characterizing cross-linked peptides, especially those with unknown structures, presents significant analytical challenges.
• Previous methods like XChem-Finder, while effective, are labor-intensive and require manual de novo sequencing for identification.

Purpose of the Study:

• To develop and validate an automated workflow for detecting cross-linked peptides using 18O-labeling and Byos software.
• To streamline the identification of complex cross-linked peptides, reducing manual effort and analysis time.

Main Methods:

• Utilized LC-MS/MS data from a previous study involving 18O-labeling tryptic digestion.
• Applied an automated 18O-labeling workflow within Byos software for cross-linked peptide detection.
• Identified a novel photoinduced cross-linked dipeptide with unknown linker chemistry.

Main Results:

• Successfully detected a photoinduced cross-linked dipeptide using the automated Byos workflow.
• Identified the cross-link as a novel cysteine-tryptophan (thioether) linkage.
• Demonstrated the efficiency of combining 18O-labeling with the Byos workflow for rapid cross-linked dipeptide detection.

Conclusions:

• The automated 18O-labeling workflow in Byos significantly simplifies and accelerates the detection of cross-linked peptides.
• This approach enables rapid identification of novel cross-link structures, such as the cysteine-tryptophan thioether linkage.
• The combined methodology offers a powerful tool for characterizing complex post-translational modifications and degradation products.