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TMPDB: a database of experimentally-characterized transmembrane topologies.

Masami Ikeda1, Masafumi Arai, Toshikatsu Okuno

  • 1Department of Electronic Information System Engineering, Faculty of Science and Technology, Hirosaki University, Hirosaki 036-8561, Japan.

Nucleic Acids Research
|January 10, 2003
PubMed
Summary

The Transmembrane Protein Database (TMPDB) provides experimentally verified transmembrane protein topologies. This resource aids in developing and validating methods for predicting protein structures, crucial for understanding cellular functions.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Structural Biology

Background:

  • Transmembrane (TM) proteins are vital cellular components with diverse structures.
  • Accurate characterization of TM protein topology is essential for understanding their function.
  • Existing databases may lack comprehensive, experimentally validated TM topology data.

Purpose of the Study:

  • To present TMPDB release 6.2, a curated database of experimentally determined TM protein topologies.
  • To provide a valuable resource for computational biologists and experimental scientists.
  • To facilitate the development and improvement of TM topology prediction algorithms.

Main Methods:

  • Compilation of TM protein sequences with experimentally determined topologies.
  • Inclusion of data derived from X-ray crystallography, NMR, and biochemical methods.

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  • Categorization of TM proteins based on structural characteristics (alpha-helical, beta-stranded).

    • Main Results:

    • TMPDB release 6.2 contains 302 TM protein sequences.
    • Includes 276 alpha-helical, 17 beta-stranded, and 9 pore-forming TM protein topologies.
    • Data is experimentally validated using diverse biochemical and biophysical techniques.

    Conclusions:

    • TMPDB serves as a high-quality benchmark dataset for TM topology prediction methods.
    • The database aids in advancing the understanding of TM protein structures and functions.
    • TMPDB is freely accessible online for research purposes.