Abstract
Glycosylation is one of the most important and prevalent post-translational modifications of proteins. Identifying the structures of such protein-linked glycans has become necessary in biochemistry analysis. In the past decade, tandem mass spectrometry (MS/MS) has gradually served as an effective technique in glycoproteomics analysis because of its high throughput and sensitivity. Different approaches have emerged to address the challenges in computational analysis of mass spectrometry based glycoproteomics data. However, there are only a few available software tools characterizing glycans using the spectra produced from intact glycopeptides, which can conserve glycosylation site information. Furthermore, with the development of advanced mass spectrometry techniques, more accurate and complete spectra like HCD spectra can be applied to identify glycopeptides. In this paper, we proposed a heuristic algorithm for glycan de novo sequencing from HCD MS/MS spectra of N-linked glycopeptides. Experiments conducted on a dataset comprising of 46 MS/MS spectra showed that our results were comparable with those identified by GlycoMaster DB, which is designed based on database searching method.
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Sun, W., Lajoie, G.A., Ma, B., Zhang, K. (2015). A Novel Algorithm for Glycan de novo Sequencing Using Tandem Mass Spectrometry. In: Harrison, R., Li, Y., Măndoiu, I. (eds) Bioinformatics Research and Applications. ISBRA 2015. Lecture Notes in Computer Science(), vol 9096. Springer, Cham. https://doi.org/10.1007/978-3-319-19048-8_27
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DOI: https://doi.org/10.1007/978-3-319-19048-8_27
Publisher Name: Springer, Cham
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