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

Detection and characterization of cross-linked peptides of unknown chemical nature and location is challenging. An analytical workflow based on the use of ¹⁸O-labeling tryptic digestion ( Anal. Chem. 2013, 85, 5900-5908) was previously utilized to identify reduction-resistant scrambled disulfide dipeptides within an IgG that was exposed to light under forced degradation conditions ( Mol. Pharmaceutics 2018, 15, 1598-1606). The analytical workflow denoted as XChem-Finder, while effective, is cumbersome and requires extensive manual effort for detection of ¹⁸O-incorporated peptides and subsequent de novo sequencing of partial peptide sequences to aid in the identification of cross-linked peptides. Here, we provide an automatic workflow using Byos (Protein Metrics Inc.) to facilitate the detection of cross-linked peptides. The LC-MS/MS data files that were subjected to the XChem-Finder workflow that identified the scrambled disulfides were utilized as the test-case data set for the automated ¹⁸O-labeling workflow in Byos. The new workflow resulted in the detection of a photoinduced cross-linked dipeptide with unknown linker chemistry, which was subsequently identified as a cross-linked dipeptide with a novel cysteine-tryptophan (thioether) linkage. This work demonstrates that combining ¹⁸O-labeling tryptic digestion with the Byos workflow enables rapid detection of cross-linked dipeptides.