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Computational function prediction of bacteria and phage proteins.

Susanna R Grigson1, George Bouras2,3, Bas E Dutilh4,5

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Annotating bacterial and bacteriophage (phage) proteins is vital for understanding microbial life. This review offers a toolbox of bioinformatics methods to improve protein function annotation, especially for unknown sequences.

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Area of Science:

  • Microbiology
  • Computational Biology
  • Bioinformatics

Background:

  • Accurate protein function annotation is essential for interpreting microbial life.
  • A significant percentage of bacterial (~30%) and bacteriophage (~65%) proteins remain unannotated.
  • Current bioinformatics tools face challenges in confidently annotating these unknown proteins.

Purpose of the Study:

  • To review state-of-the-art bioinformatics tools and methodologies for annotating bacterial and phage proteins.
  • To address the challenge of annotating proteins with unknown or poorly characterized functions.
  • To provide a comprehensive resource for researchers in the field.

Main Methods:

  • Examination of current bioinformatics tools and methodologies.
  • Description of protein-coding region identification processes.
  • Exploration of protein functionality classification systems.
  • Review of various annotation methods, including homology-based and machine learning approaches.

Main Results:

  • Identification of key bioinformatics tools and methods for protein annotation.
  • Overview of strategies for classifying protein functions.
  • Highlighting the strengths and weaknesses of different annotation approaches.
  • Compilation of a practical toolbox for researchers.

Conclusions:

  • Improved annotation of bacterial and phage proteins is achievable with advanced bioinformatics.
  • This review facilitates the discovery of novel protein functions.
  • Enhanced protein annotation deepens our understanding of microbial systems and their roles.