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Related Concept Videos

Protein Glycosylation01:25

Protein Glycosylation

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Glycosylation, the most common post-translational modification for proteins, serves diverse functions. Adding sugars to proteins makes the proteins more resistant to proteolytic digestion. Glycosylated proteins can act as markers and receptors to promote cell-cell adhesion. Additionally, they have many essential quality control functions in the cell, such as correct protein folding and facilitating transport of misfolded proteins to the cytosol, which can be degraded.
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Glycosaminoglycans (GAGs), also known as mucopolysaccharides, are long and linear polymers comprising of specific repeating disaccharides - the amino sugar that can be N-acetylglucosamine or N-acetylgalactosamine, and a uronic acid that is usually glucuronic acid or iduronic acid.
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Protein glycosylation starts in the ER lumen and continues in the Golgi apparatus. Glycosyltransferases catalyze the addition of sugar molecules or glycosylation of proteins. Usually, these enzymes add sugars to the hydroxyl groups of selected serine or threonine residues to form O-linked glycans or the amino groups of asparagine residues to form N-linked glycans. Different positions on the same polypeptide chain can contain differently linked glycans.
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Related Experiment Video

Updated: Nov 5, 2025

Bioinformatics Resources for the Study of Glycan-Mediated Protein Interactions
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GAGrank: Software for Glycosaminoglycan Sequence Ranking Using a Bipartite Graph Model.

John D Hogan1, Jiandong Wu2, Joshua A Klein1

  • 1Program in Bioinformatics, Boston University, Boston, Massachusetts, USA; Department of Biochemistry, Center for Biomedical Mass Spectrometry, Boston University School of Medicine, Boston, Massachusetts, USA.

Molecular & Cellular Proteomics : MCP
|May 16, 2021
PubMed
Summary
This summary is machine-generated.

We developed GAGrank, a novel computational method for sequencing sulfated glycosaminoglycans (GAGs) using tandem mass spectrometry. GAGrank improves structural analysis of these complex carbohydrates, crucial for understanding growth factor signaling.

Keywords:
bipartite graphglycosaminoglycansequencingtandem mass spectrometry

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Analytical Chemistry

Background:

  • Sulfated glycosaminoglycans (GAGs) are vital polysaccharides with complex structures impacting physiological processes.
  • Electron activated dissociation tandem mass spectrometry (EAD-MS) is effective for GAG analysis, but manual interpretation is challenging.
  • Computational tools are needed for efficient and accurate GAG sequencing.

Purpose of the Study:

  • To introduce GAGrank, a novel network-based computational method for determining GAG structure from tandem mass spectrometry data.
  • To improve the accuracy and efficiency of GAG sequencing compared to manual interpretation.
  • To demonstrate GAGrank's capability in analyzing complex GAG structures and isomeric mixtures.

Main Methods:

  • Development of GAGrank, a network-based algorithm inspired by Google's PageRank, utilizing BiRank for bipartite networks.
  • Integration of GAGfinder, a peak picking and elemental composition assignment algorithm, with GAGrank.
  • Optimization of GAGrank parameters using simulated annealing on training sequences.
  • Validation of GAGrank performance on independent validation sequences and isomeric mixtures.

Main Results:

  • GAGrank successfully determines GAG structure by ranking possible sequences based on their linkage to tandem MS fragments.
  • Optimized GAGrank parameters were established using simulated annealing.
  • The method was validated on multiple GAG sequences and demonstrated effectiveness in sequencing isomeric mixtures.

Conclusions:

  • GAGrank provides an accurate and efficient computational approach for GAG structure determination from EAD-MS data.
  • This method addresses the limitations of manual spectral interpretation, facilitating GAG research.
  • GAGrank has the potential to advance the study of GAGs in various biological contexts.