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The CATH Database provides insights into protein structure/function relationships

C A Orengo1, F M Pearl, J E Bray

  • 1Department of Biochemistry and Molecular Biology, Darwin Building, Univeristy College London, Gower Street, London WC1E 6BT, UK. orengo@biochem.ucl.ac.uk

Nucleic Acids Research
|December 10, 1998
PubMed
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The CATH protein domain database (version 1.4) classifies protein structures, revealing strong links between 3D structure and function. This classification aids in interpreting genomic data through structural genomics.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • The CATH database provides a hierarchical classification of protein domain structures.
  • Understanding the relationship between protein structure and function is crucial for biological research.

Purpose of the Study:

  • To report the latest release (version 1.4) of the CATH protein domains database.
  • To analyze the correlation between protein 3D structure and function using the database's classification and associated functional data.
  • To highlight the contribution of structural determination to interpreting genome data.

Main Methods:

  • Hierarchical classification of 13,359 protein domain structures into evolutionary families and structural groupings.
  • Identification of 827 homologous families, 593 fold groups, and 32 distinct architectures.

Related Experiment Videos

  • Analysis of functional data (EC identifiers, SWISS-PROT keywords, Enzyme database, literature) linked to structural classifications.

    • Main Results:

    • Over 96% of protein data bank (PDB) folds are associated with a single homologous family.
    • Superfolds exhibit three or more different functions.
    • More than 95% of homologous families show single or closely related enzyme functions.

    Conclusions:

    • Protein 3D structure is strongly correlated with function.
    • The CATH database facilitates the analysis of structure-function relationships.
    • Structural genomics initiatives significantly contribute to genome data interpretation.