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MitoProteome: mitochondrial protein sequence database and annotation system.

Dawn Cotter1, Purnima Guda, Eoin Fahy

  • 1San Diego Supercomputer Center, University of California, 9500 Gilman Drive, San Diego, CA 92037, USA.

Nucleic Acids Research
|December 19, 2003
PubMed
Summary
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MitoProteome is a new database of human mitochondrial proteins, offering detailed annotations and cross-links to external resources for researchers. This dynamic system ensures frequently updated information on mitochondrial protein sequences and functions.

Area of Science:

  • Mitochondrial biology
  • Bioinformatics
  • Proteomics

Background:

  • Mitochondria are crucial organelles with complex proteomes.
  • Existing databases often lack comprehensive, integrated mitochondrial protein data.
  • Manual annotation and data integration are time-consuming.

Purpose of the Study:

  • To develop MitoProteome, an object-relational database for human mitochondrial protein sequences and annotations.
  • To provide a dynamic and frequently updated resource for mitochondrial research.
  • To facilitate access to comprehensive protein data, including function, disease, and interaction information.

Main Methods:

  • Compilation of 847 human mitochondrial protein sequences from public databases and mass spectrometry.
  • Manual annotation of primary function, subfunction, and subcellular location.

Related Experiment Videos

  • Automated annotation using data from external databases (LocusLink, Ensembl, OMIM, MINT, DIP, Pfam, PRINTS, InterPro, PDB, PMD, NCBI NR, SWISS-PROT).

    • Main Results:

    • MitoProteome contains 847 human mitochondrial protein sequences with extensive manual and automated annotations.
    • Data includes gene information, disease associations, protein interactions, functional domains, structure, mutations, and homology.
    • The database is dynamically updated, reflecting changes in public resources.

    Conclusions:

    • MitoProteome provides a valuable, integrated resource for studying human mitochondrial proteins.
    • Automated data extraction ensures a dynamic and up-to-date database.
    • Public accessibility via http://www.mitoproteome.org/ enhances research collaboration and discovery.