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Related Experiment Videos

Benchmarking PSI-BLAST in genome annotation.

A Müller1, R M MacCallum, M J Sternberg

  • 1Biomolecular Modelling Laboratory, Imperial Cancer Research Fund, 44 Lincoln's Inn Fields, London, WC2A 3PX, England.

Journal of Molecular Biology
|November 5, 1999
PubMed
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This study benchmarks PSI-BLAST for remote protein homology detection in genome annotation. It found PSI-BLAST successfully annotates 40% of domains, significantly improving genome analysis.

Area of Science:

  • Bioinformatics
  • Genomics
  • Structural Biology

Background:

  • Remote protein homology recognition is crucial for annotating newly sequenced genomes.
  • Accurate annotation relies on effective homology searching tools.
  • Existing benchmarks often use one-to-one recognition, which may not reflect real-world genome annotation scenarios.

Purpose of the Study:

  • To benchmark the coverage and error rate of genome annotation using PSI-BLAST (position-specific iterated basic local alignment search tool).
  • To evaluate the one-to-many success rate of PSI-BLAST in identifying remote protein homologies.
  • To compare one-to-many recognition performance against traditional one-to-one recognition benchmarks.

Main Methods:

  • Constructed a model genome from the Structural Classification of Protein (SCOP) database.

Related Experiment Videos

  • Searched the model genome against a library of remote homologous domains (<20% identity).
  • Evaluated PSI-BLAST's performance using a structural benchmark for accurate homology assignments.

    • Main Results:

    • PSI-BLAST successfully annotated 40% of domains with at least one homolog in the target library.
    • This one-to-many coverage (40%) is over three times higher than one-to-one recognition (11%).
    • The benchmark provides reliable data on correct and false homology assignments.

    Conclusions:

    • PSI-BLAST demonstrates significant effectiveness in recognizing remote protein homologies for genome annotation.
    • The one-to-many approach offers substantially improved domain coverage compared to one-to-one methods.
    • Findings are applicable to both structural and sequence-based homology searches, aiding functional and structural genome annotations.