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Development of a Computational Tool for Automatic Interpretation of Intact O-Glycopeptide Tandem Mass Spectra from Single Proteins.

Precise and automatic analysis of site-specific O-glycosylation on single proteins is crucial for comprehensive characterization of some important glycoproteins, such as tumor biomarkers and recombinant drug proteins. Mass spectrometry has been proven to be a powerful technique for protein sequencing and N-glycosylation analysis. However, challenges remain in developing computational tools for intact O-glycopeptide analysis, which has greatly hindered the development of mass spectrometry-based O-glycosylation analysis. Herein, an integrated strategy together with a dedicated automatic computational tool termed AOGP was developed for intact O-glycopeptide analysis on single proteins. AOGP utilized de novo sequencing for O-glycans and database search strategy for peptide backbones. The false discovery rate (FDR) of the identification results was controlled and validated by a mixed gaussian distribution estimation method. AOGP exhibited superior performance on identifying intact O-glycopeptides of the human erythropoietin with a total of 188 O-glycopeptide spectra reported under 1% FDR. AOGP is developed in Python, fully open-sourced and equipped with a user-friendly interface. Such easy-operating and robust tool would greatly facilitate O-glycosylation analysis on single proteins in tumor biomarker and recombinant drug protein development.