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DOCKGROUND resource for studying protein-protein interfaces.

Dominique Douguet1, Huei-Chi Chen, Andrey Tovchigrechko

  • 1Centre de Biochimie Structurale, CNRS, U5048, Université Montpellier 1, INSERM, U554, 29, rue de Navacelles, Montpellier F-34090, France. douguet@cbs.cnrs.fr

Bioinformatics (Oxford, England)
|August 25, 2006
PubMed
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DOCKGROUND is a new public database resource for protein-protein interactions. It provides a comprehensive collection of co-crystallized protein complexes to aid in understanding molecular recognition and predicting protein structures.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Developing accurate models of protein-protein interactions is crucial for understanding molecular recognition.
  • Publicly accessible resources are needed to support research in protein complex prediction and analysis.

Purpose of the Study:

  • To introduce DOCKGROUND, a novel relational database resource for protein-protein complexes.
  • To provide a foundation for developing and validating computational methods for modeling protein interactions.

Main Methods:

  • The first release of DOCKGROUND focuses on co-crystallized (bound-bound) protein-protein complexes.
  • Data is derived from the Biological Unit file (Biounit) provided by the RCSB, linked to Protein Data Bank (PDB) entries.
  • The database is automatically updated with new PDB entries and includes dynamic generation of non-redundant datasets based on structural similarity (SCOP) or sequence identity.

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Main Results:

  • The initial release contains 67,220 pairwise complexes from 14,913 Biounit entries (as of January 30, 2006).
  • DOCKGROUND offers annotated structures and supports the creation of diverse, non-redundant datasets for research.
  • The resource is designed for expansion to include unbound complexes, modeled complexes, and docking decoys.

Conclusions:

  • DOCKGROUND serves as a valuable, comprehensive public resource for the protein interaction modeling community.
  • This database will facilitate the development and validation of new computational approaches for predicting protein complexes.