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Protein Glycosylation

Protein Glycosylation

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.
Glycosylation occurs in...

Oligosaccharide Assembly

Oligosaccharide Assembly

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.
Multiple sugar molecules that may or may...

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Updated: May 19, 2026

Microarray Polymer Profiling (MAPP) for High-Throughput Glycan Analysis

Microarray Polymer Profiling (MAPP) for High-Throughput Glycan Analysis

Published on: September 29, 2023

Automated motif discovery from glycan array data.

Sharath R Cholleti¹, Sanjay Agravat, Tim Morris

¹Center for Comprehensive Informatics, Emory University, Atlanta, Georgia, USA.

Omics : a Journal of Integrative Biology

|August 11, 2012

Summary

This summary is machine-generated.

GlycanMotifMiner is a new computational tool that identifies glycan structural motifs recognized by glycan-binding proteins (GBPs) from microarray data. This method aids in understanding GBP specificity and discovering novel binding patterns.

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Published on: February 14, 2019

Area of Science:

Carbohydrate Chemistry
Bioinformatics
Glycobiology

Background:

Glycan-binding proteins (GBPs) interact with glycans, but identifying specific binding motifs from large microarray datasets is challenging.
Understanding GBP-glycan interactions is crucial for deciphering biological processes and disease mechanisms.

Purpose of the Study:

To develop and validate a computational method, GlycanMotifMiner, for automatically identifying glycan structural motifs recognized by GBPs.
To provide a user-friendly web interface for visualizing these discovered motifs.

Main Methods:

Developed GlycanMotifMiner, a computational algorithm analyzing relative GBP binding to glycans on microarrays.
Implemented a web-based graphical user interface for motif exploration and visualization.
Validated the software using data from five plant lectins (SNA, HPA, PNA, Con A, UEA-I) and human galectin-8.

Main Results:

GlycanMotifMiner successfully identified known glycan motifs for the tested lectins.
The algorithm also revealed novel and unexpected binding motifs.
The software provides a ranked list of glycans based on relative binding strength.

Conclusions:

GlycanMotifMiner is an effective tool for defining glycan-binding specificity of GBPs.
The method facilitates the discovery of both established and novel glycan-binding patterns.
The web interface enhances accessibility for researchers studying glycan-protein interactions.