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Using Phage Display to Develop Ubiquitin Variant Modulators for E3 Ligases
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Development and Application of Computational Methods in Phage Display Technology.

Bifang He1,2, Anthony Mackitz Dzisoo1, Ratmir Derda3

  • 1Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China.

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|June 30, 2018
PubMed
Summary
This summary is machine-generated.

This review highlights computational tools and databases for phage display, a technique for identifying peptide ligands. These resources aid researchers in analyzing biopanning data and excluding false positives, advancing diagnostics and therapeutics.

Keywords:
Phage displaycomputational methoddatabaseepitope predictionmimotopenext-generation sequencingtarget-unrelated peptide.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Phage display is a versatile technology for identifying peptide ligands for various applications.
  • Integrating next-generation sequencing enhances phage display productivity.
  • Phage display data accumulation necessitates robust databases and computational methods.

Purpose of the Study:

  • To review recent advancements in computational methods for phage display.
  • To discuss the development and application of these computational tools.
  • To provide an overview of available bioinformatics resources for phage display data analysis.

Main Methods:

  • Comprehensive literature search of bioinformatics resources and computational methods for phage display data.
  • Categorization of methods and tools based on their specific applications.
  • Review of databases and computational approaches for analyzing biopanning results.

Main Results:

  • Seven databases for phage display data were identified, aiding in cleaning biopanning results.
  • Databases help identify target-unrelated peptides (TUPs), reducing false positives.
  • Over 20 computational methods were reviewed, including those for TUP reporting, epitope prediction, and next-generation data analysis.

Conclusions:

  • Current bioinformatics tools and methods benefit the phage display research community.
  • The review discusses promising future directions for developing novel computational tools.
  • Enhanced computational resources are crucial for advancing phage display applications.