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Proteomics Clin Appl. 2018 Sep;12(5):e1700069. doi: 10.1002/prca.201700069. Epub 2017 Oct 30.

PepSweetener: A Web-Based Tool to Support Manual Annotation of Intact Glycopeptide MS Spectra.

Author information

1
Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva, Switzerland.
2
Computer Science Department CUI, University of Geneva, Geneva, Switzerland.
3
Institute for Glycomics, Gold Coast Campus, Griffith University, Southport, QLD, Australia.
4
Section of Biology, University of Geneva, Geneva, Switzerland.

Abstract

PURPOSE:

PepSweetener is a web-based visualization tool designed to facilitate the manual annotation of intact glycopeptides from MS data regardless of the instrument that produced these data.

EXPERIMENTAL DESIGN:

This exploratory tool uses a theoretical glycopeptide dataset to visualize all peptide-glycan combinations that fall within the error range of the query precursor ion. PepSweetener simplifies the determination of the correct peptide and glycan composition of a glycopeptide based on its precursor mass. The theoretical glycopeptide search space can be customized in an advanced query mode that specifies potential proteins/peptides, glycan compositions, and several experimental parameters.

RESULTS:

PepSweetener displays the results on an interactive heat-map chart where theoretical glycopeptide tile colors correspond to ppm deviations from the query precursor mass. Additionally, a visualization chart incorporates glycan composition filtering, sorting by mass and tolerance, and an in silico peptide fragmentation diagram is provided to further support the correct glycopeptide identification.

CONCLUSIONS AND CLINICAL RELEVANCE:

PepSweetener efficiently allows the selection of the most probable intact glycopeptide mass matches and speeds up the verification process. It is validated on serum protein samples and immunoglobulins. The tool is publicly hosted on ExPASy, the SIB Swiss Institute of Bioinformatics resource portal (http://glycoproteome.expasy.org/pepsweetener/app/).

KEYWORDS:

MS; computer-assisted glycopeptide assignment; data analysis; glycoinformatics; glycoproteomics

PMID:
28975713
DOI:
10.1002/prca.201700069
[Indexed for MEDLINE]

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