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Related Experiment Videos

Sensitive sequence comparison as protein function predictor.

K Pawłowski1, L Jaroszewski, L Rychlewski

  • 1Burnham Institute, La Jolla, CA 92037, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|July 21, 2000
PubMed
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Detecting low sequence similarity (10-15% identity) between proteins can reveal homology and shared functions. This study confirms that even subtle sequence similarities strongly correlate with functional similarity in E. coli proteins.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Protein function is often inferred from sequence similarity, a common practice in genome analysis.
  • Advanced algorithms now detect weak sequence similarities (e.g., 10-15% identity) previously missed.
  • The relationship between low sequence similarity and functional homology requires further investigation.

Purpose of the Study:

  • To analyze the correlation between sequence similarity and functional similarity in proteins.
  • To assess the practical significance of detecting low sequence similarities.
  • To explore the homology of proteins with subtle sequence similarities.

Main Methods:

  • Utilized a simplified functional similarity measure based on Enzyme Commission (E.C.) classification.

Related Experiment Videos

  • Employed statistical significance of alignment scores to quantify sequence similarity.
  • Focused analysis on well-characterized proteins from the Escherichia coli genome.

    • Main Results:

    • A strong correlation was observed between sequence similarity and functional similarity.
    • Proteins with low sequence identity (<15%) show a significantly higher probability of shared function compared to random pairs.
    • The statistical significance of alignment scores effectively measures functional relatedness.

    Conclusions:

    • Low sequence similarity, even below 15% identity, is a reliable indicator of potential protein homology and shared function.
    • Detecting subtle sequence similarities is practically significant for accurate genome annotation and functional prediction.
    • While generally true, notable exceptions to the sequence-function similarity rule exist and warrant further study.