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Sequence comparison by sequence harmony identifies subtype-specific functional sites.

Walter Pirovano1, K Anton Feenstra, Jaap Heringa

  • 1Centre for Integrative Bioinformatics VU (IBIVU), Vrije Universiteit, De Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands.

Nucleic Acids Research
|November 30, 2006
PubMed
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Sequence Harmony (SH) is a new method that identifies key protein positions distinguishing subfamilies using multiple sequence alignments. It accurately detects functional sites, outperforming existing methods and highlighting potential new research areas.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Protein Sequence Analysis

Background:

  • Multiple sequence alignments are crucial for identifying functionally important residues in protein families.
  • Distinguishing key residues between protein subfamilies is essential for understanding functional divergence.

Purpose of the Study:

  • To introduce Sequence Harmony (SH), a novel entropy-based method for detecting subfamily-specific positions in multiple sequence alignments.
  • To evaluate SH's performance against established methods for identifying functional sites.

Main Methods:

  • Developed a new entropy-based algorithm, Sequence Harmony (SH), utilizing a novel formula to score compositional differences.
  • Applied SH to analyze three well-characterized protein families: Smad MH2 domains, Ras GTPases, and MIP transporters.

Related Experiment Videos

  • Compared SH's performance with AMAS, TreeDet, and SDP-pred.

    • Main Results:

    • Sequence Harmony (SH) accurately identifies subfamily-specific positions.
    • SH demonstrated higher coverage in selecting known functional sites compared to AMAS, TreeDet, and SDP-pred across test cases.
    • The method successfully identified potential functional sites of unknown significance.

    Conclusions:

    • Compositional differences between protein subfamilies are sufficient for identifying functional sites.
    • Sequence Harmony (SH) offers an effective and accurate approach for functional site prediction.
    • SH provides valuable candidates for future experimental validation and research.