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LOC3D: annotate sub-cellular localization for protein structures.

Rajesh Nair1, Burkhard Rost

  • 1CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA. nair@cubic.bioc.columbia.edu

Nucleic Acids Research
|June 26, 2003
PubMed
Summary
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LOC3D is a database and web server that predicts eukaryotic protein sub-cellular localization using four methods. It aids structural genomics by providing localization predictions for proteins with known or predicted 3D structures.

Area of Science:

  • Bioinformatics
  • Structural Biology
  • Computational Biology

Background:

  • Sub-cellular localization is crucial for protein function and cellular processes.
  • Accurate prediction of protein localization aids in understanding cellular mechanisms and disease pathways.
  • Existing methods often lack comprehensive approaches for diverse eukaryotic proteins.

Purpose of the Study:

  • To present LOC3D, a comprehensive database and web server for predicting sub-cellular localization of eukaryotic proteins.
  • To integrate multiple prediction methods for enhanced accuracy and confidence.
  • To support structural genomics initiatives by providing localization data for proteins with known or predicted 3D structures.

Main Methods:

  • Utilizes four distinct prediction methods: PredictNLS (nuclear localization signals), LOChom (sequence homology), LOCkey (SWISS-PROT keyword analysis), and LOC3Dini (ab initio neural networks and support vector machines).

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  • Employs a confidence-based approach, selecting the prediction from the highest-confidence method.
  • Weekly updates ensure the database remains current with new protein structures.

    • Main Results:

    • The LOC3D database contains predictions for over 8700 eukaryotic protein chains from the Protein Data Bank (PDB).
    • The web server extends predictions to proteins with computationally predicted structures from threading servers.
    • Provides a valuable resource for researchers investigating protein function and cellular organization.

    Conclusions:

    • LOC3D offers a robust and integrated platform for predicting eukaryotic protein sub-cellular localization.
    • The resource significantly benefits structural genomics projects by enabling localization predictions for a wide range of proteins.
    • The combination of multiple prediction strategies enhances the reliability and utility of the localization data.