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Related Experiment Videos

EzCatDB: the Enzyme Catalytic-mechanism Database.

Nozomi Nagano1

  • 1Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-41-6 Aomi, Koto-ku, Tokyo 135-0064, Japan. n.nagano@aist.go.jp

Nucleic Acids Research
|December 21, 2004
PubMed
Summary

The Enzyme Catalytic-mechanism Database (EzCatDB) offers a comprehensive resource for enzyme catalytic mechanisms, including structures and ligand interactions. This database aids researchers by organizing and querying enzyme data for deeper mechanistic insights.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Enzyme catalytic mechanisms are crucial for understanding biological processes.
  • Integrating sequence, structure, and mechanistic data is essential for comprehensive enzyme analysis.
  • Existing databases may lack detailed catalytic mechanism information.

Purpose of the Study:

  • To develop and present the Enzyme Catalytic-mechanism Database (EzCatDB).
  • To provide a centralized resource for enzyme catalytic mechanisms, structures, and ligand interactions.
  • To facilitate querying and analysis of enzyme mechanistic data.

Main Methods:

  • Data integration from Protein Data Bank (PDB) and SWISS-PROT.
  • Grouping enzymes by domain composition, EC numbers, and catalytic mechanisms.

Related Experiment Videos

  • Development of a query system based on catalytic residues, ligand types, and enzyme properties.
  • Hierarchic classification of catalytic mechanisms incorporating active-site structures and ligand reactivity.

    • Main Results:

    • EzCatDB provides detailed enzyme catalytic mechanisms linked to sequences and tertiary structures.
    • The database groups enzymes with identical domain compositions, EC numbers, and mechanisms.
    • Query functionalities include catalytic residue, ligand type, and enzyme properties.
    • EzCatDB offers ligand annotation and literature information for PDB enzymes.
    • A hierarchic classification of catalytic mechanisms is integrated within the database.

    Conclusions:

    • EzCatDB serves as a valuable resource for studying enzyme catalytic mechanisms.
    • The database facilitates research in enzymology and drug discovery.
    • EzCatDB enhances the understanding of enzyme function through integrated data and classification.