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Related Experiment Videos

NLSdb: database of nuclear localization signals.

Rajesh Nair1, Phil Carter, Burkhard Rost

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

Nucleic Acids Research
|January 10, 2003
PubMed
Summary

NLSdb is a new database detailing nuclear localization signals (NLSs) and nuclear proteins. It aids in identifying nuclear proteins and their targeting signals, with over 12,500 predicted proteins from sequenced eukaryotes.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Proteomics

Background:

  • Nuclear localization signals (NLSs) are crucial for transporting proteins into the nucleus.
  • Identifying and cataloging NLSs and nuclear proteins is essential for understanding cellular function.
  • Existing databases may lack comprehensive experimental and predicted data on NLSs.

Purpose of the Study:

  • To create a comprehensive database (NLSdb) of experimentally determined and predicted nuclear localization signals (NLSs) and nuclear proteins.
  • To facilitate the identification of nuclear proteins and their targeting mechanisms.
  • To provide a resource for studying the relationship between NLS motifs and other protein features, such as DNA-binding regions.

Main Methods:

  • Extensive literature search to identify experimentally determined NLSs.

Related Experiment Videos

  • 'In silico mutagenesis' to expand the set of known and potential NLSs.
  • Integration of data from Protein Data Bank (PDB) and SWISS-PROT/TrEMBL databases for predicted nuclear proteins and targeting signals.
  • Analysis of six fully sequenced eukaryotic proteomes (human, mouse, fruit fly, worm, thale cress, yeast) to predict nuclear proteins.
  • Annotation of DNA-binding proteins based on the co-localization of NLS motifs.

    • Main Results:

    • NLSdb contains 114 experimentally determined NLSs, extended to 308 experimental and potential NLSs using 'in silico mutagenesis'.
    • The NLS set matches over 43% of known nuclear proteins and shows no matches with known non-nuclear proteins.
    • The database includes over 6,000 predicted nuclear proteins and targeting signals from PDB and SWISS-PROT/TrEMBL.
    • Over 12,500 predicted nuclear proteins from six eukaryotic proteomes are included.
    • Approximately 1,500 DNA-binding proteins were annotated due to the co-localization of NLS motifs with DNA-binding regions.

    Conclusions:

    • NLSdb provides a valuable, curated resource for nuclear localization signals and nuclear proteins.
    • The database effectively identifies nuclear proteins and their targeting signals, with high accuracy.
    • NLSdb serves as a significant tool for researchers in molecular biology, bioinformatics, and proteomics, aiding in the study of nuclear transport and protein function.