Development of a Computational Tool for Automated Interpretation of Intact O-Glycopeptide Tandem Mass Spectra from Single Proteins.
Anal Chem
; 92(9): 6777-6784, 2020 05 05.
Article
em En
| MEDLINE
| ID: mdl-32275135
ABSTRACT
Precise and automated 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 automated computational tool termed AOGP was developed for intact O-glycopeptide analysis on single proteins. AOGP utilized de novo sequencing for O-glycans and a 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 in 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, is fully open-sourced, and is equipped with a user-friendly interface. Such an easy-operating and robust tool would greatly facilitate O-glycosylation analysis on single proteins in tumor biomarker and recombinant drug protein development.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Assialoglicoproteínas
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Automação
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Algoritmos
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Glicopeptídeos
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Eritropoetina
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Fetuínas
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article