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DAPID: a 3D-domain annotated protein-protein interaction database.

Yung-Chiang Chen1, Heng-Chu Chen, Jinn-Moon Yang

  • 1Institute of Bioinformatics, National Chiao Tung University Hsinchu, 30050, Taiwan. smolljohn.bi93g@nctu.edu.tw

Genome Informatics. International Conference on Genome Informatics
|May 16, 2007
PubMed
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The DAPID database provides 3D domain-annotated protein interactions, aiding in the visualization of protein-protein interactions and molecular details. This resource enhances understanding of protein complex structures and functions.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Protein-protein interactions (PPIs) are fundamental to cellular processes.
  • Understanding the structural basis of PPIs is crucial for deciphering biological functions.
  • Existing databases often lack detailed 3D structural information for predicted interactions.

Purpose of the Study:

  • To develop and present DAPID, a novel database of domain-annotated protein interactions.
  • To enable visualization of 3D interacting domains, contact residues, and molecular details of PPIs.
  • To introduce the concept of '3D-domain interologs' for inferring PPIs.

Main Methods:

  • Inference of PPIs from 3D interacting domains in the Protein Data Bank (PDB).
  • Utilizing a new concept termed '3D-domain interologs'.

Related Experiment Videos

  • Development of a data model for visualizing structural and molecular details of interactions.

    • Main Results:

    • DAPID contains 1008 3D-interacting domain pairs and 11,511 predicted 3D-domain annotated PPIs.
    • 18.6% overlap was observed between DAPID predictions and the DIP database for S. cerevisiae.
    • Predicted interactions show significantly higher gene expression profile correlation and include novel, functionally consistent interactions.

    Conclusions:

    • DAPID offers a valuable resource for exploring 3D domain-annotated protein-protein interactions.
    • The '3D-domain interologs' approach effectively predicts PPIs with structural context.
    • DAPID facilitates deeper insights into protein complex structures and functional relationships.