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.

Citation

Aaron T Wecksler, Lawrie Veale, Maria Basanta-Sanchez, Marshall Bern. Development of Software Workflow for the Rapid Detection of Cross-Linked Dipeptides. Journal of the American Society for Mass Spectrometry. 2022 Mar 02;33(3):598-602

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PMID: 35157447

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