Semiautomated glycoproteomics data analysis workflow for maximized glycopeptide identification and reliable quantification

• Steffen Lippold,
• Arnoud H. de Ru,
• Jan Nouta,
• Peter A. van Veelen,
• Magnus Palmblad,
• Manfred Wuhrer and
• Noortje de Haan

Beilstein J. Org. Chem. 2020, 16, 3038–3051, doi:10.3762/bjoc.16.253

• compared to Skyline, and GlycopeptideGraphMS. All quantification packages resulted in comparable glycosylation profiles but featured differences in terms of robustness and data quality control. Partial cysteine oxidation was identified as an unexpectedly abundant peptide modification and impaired the

• quantification. Keywords: bioinformatics; cysteine oxidation; glycoproteomics; immunoglobulins; mass spectrometry; Introduction Protein glycosylation mainly occurs in the form of N- and O-glycosylation. N-Glycans are attached to Asn within an amino acid consensus sequence (Asn-Xxx-Ser/Thr, Xxx ≠ Pro) and O