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Bioinformatics Resources for the Study of Glycan-Mediated Protein Interactions
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Resources and Methods for Engineering "Designer" Glycan-Binding Proteins.

Ruben Warkentin1,2, David H Kwan1,2,3

  • 1Department of Biology, Centre for Applied Synthetic Biology, and Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke Street West, Montreal, QC H4B 1R6, Canada.

Molecules (Basel, Switzerland)
|January 16, 2021
PubMed
Summary
This summary is machine-generated.

This review details methods for engineering glycan-binding proteins (GBPs). Advances in glycobiology enable the design of novel GBPs for diverse applications, overcoming previous limitations.

Keywords:
carbohydratesdirected evolutionglycan immobilizationglycan-binding proteinglycansglycobiologylectinsprotein engineering

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Area of Science:

  • Carbohydrate Chemistry
  • Protein Engineering
  • Biotechnology

Background:

  • Glycans play crucial roles in biological processes across all life forms and viruses.
  • Glycan-binding proteins (GBPs) are essential tools with diagnostic, therapeutic, and biotechnological potential.
  • Historically, GBP development was limited by scarce glycan targets and inadequate protein scaffolds.

Purpose of the Study:

  • To review current methodologies for engineering glycan-binding proteins (GBPs).
  • To guide the design of novel, customized GBPs by outlining key approaches.
  • To address challenges in developing sensitive and selective protein scaffolds for glycan recognition.

Main Methods:

  • Scaffold selection for GBP design.
  • Mutagenesis techniques for protein modification.
  • Selection and characterization strategies for engineered GBPs.

Main Results:

  • Recent advancements in glycobiology have facilitated the creation of new GBP development strategies.
  • The review outlines a systematic approach to designing "designer" GBPs.
  • Methods cover scaffold choice, mutagenesis, and rigorous selection/characterization processes.

Conclusions:

  • Engineering of glycan-binding proteins (GBPs) is now more accessible due to recent scientific progress.
  • The described methods provide a framework for creating novel GBPs with tailored functionalities.
  • This review empowers researchers to develop innovative GBP-based tools for various applications.