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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.
Glycosylation occurs in...
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Oligosaccharide Assembly01:24

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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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Proteoglycans01:05

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Glycans, a class of complex heterogeneous molecules, can be covalently attached to proteins to form glycosylated proteins that regulate various physiological and pathological processes. Glycosylated proteins or glycoproteins comprise N-linked and O-linked oligosaccharides. O-glycosylation is the most common type of protein glycosylation. Here, glycans attach to the oxygen atom of the hydroxyl groups of Serine or Threonine residues. O-linked glycosylation occurs later in protein processing,...
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Glycocalyx and its Functions01:14

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The glycocalyx is a carbohydrate-rich, fuzzy-appearing layer on the outer surface of the cell membrane. It is highly hydrophilic, because of this it attracts large amounts of water to the cell's surface. This aids the cell's interaction with the watery environment and also helps it to obtain substances dissolved in the water. It is also important for cell identification, self/non-self determination, and embryonic development and is used in cell-to-cell attachments to form tissues.
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Glycosaminoglycans01:23

Glycosaminoglycans

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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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Biosynthesis of Polysaccharides

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Polysaccharides such as glycogen and starch are synthesized from nucleoside diphosphate sugars, primarily uridine diphosphate glucose (UDPG) and adenosine diphosphate glucose (ADPG). These activated glucose donors act as key intermediates in carbohydrate metabolism and biosynthesis. UDPG primarily involves glycogen synthesis in animals and many bacteria, while ADPG plays a fundamental role in starch synthesis in plants and certain bacteria.UDPG is formed when glucose-1-phosphate reacts with...
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Systems glycobiology for glycoengineering.

Philipp N Spahn1, Nathan E Lewis2

  • 1Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, United States.

Current Opinion in Biotechnology
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Summary

Computational models are advancing glycosylation prediction and glycoengineering for biopharmaceutical manufacturing. These tools offer faster, cheaper alternatives to screening, aiding cell line development and optimizing protein glycosylation.

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Area of Science:

  • Biotechnology and biopharmaceutical manufacturing
  • Glycoscience and glycomics
  • Computational biology and bioinformatics

Background:

  • Glycosylation is crucial for protein function in biopharmaceuticals.
  • Glycoengineering aims to control glycosylation through culture or genetic changes.
  • Traditional screening methods for glycosylation are expensive and time-consuming.

Purpose of the Study:

  • To highlight the role of computational models in glycosylation research.
  • To demonstrate the application of these models in predicting glycosylation.
  • To emphasize their value in glycoengineering and cell line development.

Main Methods:

  • Development and application of computational models for glycosylation prediction.
  • Systems-level analysis of glycan diversity.
  • Leveraging glycomics data for model refinement.

Main Results:

  • Computational models successfully predict glycosylation for industrially relevant products.
  • Systems-level analyses provide deeper insights into glycosylation mechanisms.
  • Models are becoming essential for analyzing glycomics data.

Conclusions:

  • Computational models are cost-effective and efficient alternatives to experimental screening.
  • These models are invaluable for rational glycoengineering and cell line development.
  • Continued expansion and refinement of models will enhance biopharmaceutical production.