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The SUPERFAMILY database in structural genomics.

Julian Gough1

  • 1MRC Laboratory of Molecular Biology, Hills Road, cambridge CB2 2QH, England. gough@supfam.org

Acta Crystallographica. Section D, Biological Crystallography
|October 24, 2002
PubMed
Summary
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The SUPERFAMILY database predicts protein domain architecture across all sequenced genomes, aiding structural biology and high-throughput structure determination by identifying evolutionary relationships and novel protein targets.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Genomics

Background:

  • The SUPERFAMILY database utilizes hidden Markov models to represent proteins of known structure.
  • Accurate prediction of protein domain architecture is crucial for understanding protein function and evolution.

Purpose of the Study:

  • To analyze domain architecture across all completely sequenced genomes using the SUPERFAMILY database.
  • To explore the utility of the SUPERFAMILY database for crystallographers, particularly in high-throughput structure determination.
  • To suggest applications for target selection strategies, including novel folds, domain combinations, and genome-specific analyses.

Main Methods:

  • Application of the SUPERFAMILY hidden Markov model library to all completely sequenced genomes.
  • Classification of protein sequences at the SCOP superfamily level.

Related Experiment Videos

  • Analysis of evolutionary relationships using SCOP database, genome assignments, and multiple sequence alignments.

    • Main Results:

    • The SUPERFAMILY database successfully predicts domain architecture and classifies proteins across all sequenced genomes.
    • Identified potential applications for crystallographers, including high-throughput structure determination.
    • Proposed target selection strategies based on novel folds, domain combinations, and genomic context.

    Conclusions:

    • The SUPERFAMILY database is a valuable resource for structural biologists and bioinformaticians.
    • It facilitates high-throughput structure determination and informs target selection strategies.
    • The database enhances understanding of evolutionary relationships among proteins of known and unknown structures.