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Distant homology detection using a LEngth and STructure-based sequence Alignment Tool (LESTAT).

Marianne M Lee1, Ralf Bundschuh, Michael K Chan

  • 1The Ohio State Biophysics Program, The Ohio State University, Columbus, Ohio 43210, USA.

Proteins
|December 14, 2007
PubMed
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A new machine learning algorithm, LESTAT (LEngth and STructure-based sequence Alignment Tool), improves protein homolog detection. It shows higher sensitivity and specificity than PSI-BLAST for identifying distantly related protein sequences.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Machine Learning

Background:

  • Detecting protein homologs with low sequence identity is crucial for understanding protein function and evolution.
  • Existing methods like PSI-BLAST have limitations in sensitivity and specificity for identifying remote homologs.

Purpose of the Study:

  • To introduce LESTAT (LEngth and STructure-based sequence Alignment Tool), a novel machine learning algorithm for enhanced protein homolog detection.
  • To evaluate the performance of LESTAT compared to PSI-BLAST in identifying distantly related protein sequences.

Main Methods:

  • LESTAT employs an iterative, profile-based approach utilizing three structural homologs to build initial profiles.
  • Novel features include a 'lock-in' mechanism for retaining high-scoring sequences and an enhancement factor for position-specific scoring matrices.

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  • Profiles are iteratively refined using sequence information from previous alignment cycles.

    • Main Results:

    • LESTAT demonstrated increased sensitivity and specificity over PSI-BLAST in six out of seven tested systems.
    • The algorithm successfully identified true homologs and covered a broader range of protein families.
    • A significant number of unique hits were identified by LESTAT, highlighting its distinct approach.

    Conclusions:

    • LESTAT is a powerful and sensitive tool for detecting protein homologs with low sequence identity.
    • It serves as a valuable complementary method to existing tools like PSI-BLAST for identifying remote protein sequences.
    • The novel features of LESTAT contribute to its improved performance in sequence alignment and homolog detection.