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The Recipe for Protein Sequence-Based Function Prediction and Its Implementation in the ANNOTATOR Software

Birgit Eisenhaber1, Durga Kuchibhatla1, Westley Sherman1

  • 1Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*Star), 30 Biopolis Street #07-01, Matrix Building, Singapore, 138671, Singapore.

Methods in Molecular Biology (Clifton, N.J.)
|April 27, 2016
PubMed
Summary
This summary is machine-generated.

Functional interpretation of protein sequences is crucial in bioinformatics. This study details methods for predicting protein function, distinguishing between globular and non-globular regions, and introduces the ANNOTATOR software.

Keywords:
ANNOTATORGenome annotationGlobular domainNon-globular segmentProtein function predictionProtein sequence analysis

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biomolecular sequencing is a primary technique in life sciences, increasing the need for in silico functional interpretation of sequences.
  • Current bioinformatics textbooks inadequately cover the concepts and technologies for protein function prediction.
  • Protein sequences comprise globular domains and non-globular segments, necessitating distinct prediction approaches.

Purpose of the Study:

  • To highlight the significance of in silico approaches for functional interpretation of biomolecular sequences.
  • To address the gap in bioinformatics literature regarding protein function prediction methodologies.
  • To present an updated description of the ANNOTATOR software as a platform for protein sequence-based function prediction.

Main Methods:

  • Differentiating between globular domains and non-globular segments within protein sequences.
  • Employing homology-based function transfer for globular domains using sequence similarity.
  • Utilizing lexical analysis and pattern-function correlations for non-globular segments characterized by compositional bias or repetitive patterns.

Main Results:

  • A recommended recipe for function prediction: first identify non-globular segments, then perform sequence similarity searches on the remaining sequence.
  • The ANNOTATOR software environment is presented as an advanced platform facilitating these protein sequence-based function prediction tasks.
  • Demonstration of distinct computational strategies required for predicting functions of globular versus non-globular protein regions.

Conclusions:

  • Accurate protein function prediction requires tailored in silico approaches for different sequence regions.
  • The ANNOTATOR software provides a valuable tool for researchers needing to predict protein functions from sequence data.
  • Improved bioinformatics education and tools are essential to keep pace with advances in biomolecular sequencing.