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Tracking repeats using significance and transitivity.

Radek Szklarczyk1, Jaap Heringa

  • 1Centre for Integrative Bioinformatics (IBIVU), Faculty of Sciences and Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1081A, Amsterdam, The Netherlands. radek@cs.vu.nl

Bioinformatics (Oxford, England)
|July 21, 2004
PubMed
Summary

We developed TRUST, a novel method for identifying internal protein repeats. TRUST improves repeat prediction accuracy and sensitivity by using alignment transitivity, aiding protein structure and evolution studies.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Internal repeats in protein coding sequences represent functional and structural units.
  • Identifying these repeats is vital for understanding protein function, structure, and evolution.
  • Evolutionary divergence can obscure repeat homology, making identification challenging.

Purpose of the Study:

  • To introduce TRUST, a new ab initio method for determining internal repeats in proteins.
  • To enhance the prediction quality, sensitivity, and accuracy of repeat identification compared to existing methods.

Main Methods:

  • TRUST utilizes the concept of alignment transitivity to identify repeats.
  • It starts with local suboptimal alignments and applies transitivity to find distant homologues and refine repeat profiles.

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  • Rigid statistical testing is employed for self-sequence and profile-sequence alignments to ensure specificity.

    • Main Results:

    • TRUST demonstrates improved prediction quality over state-of-the-art methods.
    • The method successfully identifies distant repeat homologues and reduces the impact of non-homologous repeats.
    • TRUST achieves high fidelity in generating repeat profiles and superior specificity through statistical testing.

    Conclusions:

    • TRUST is a reliable tool for mining tandem and non-tandem repeats in protein sequences.
    • It can predict multiple repeat types with varying intervening segments within a single protein.
    • The TRUST server is publicly available for researchers.