MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions

Area of Science:

• Computational biology
• Bioinformatics
• Structural biology

Background:

• Protein-protein interactions (PPIs) are crucial for cellular functions.
• Computational PPI prediction, particularly using 3D structures, is vital for designing inhibitors.
• Existing databases lack sufficient entries for novel PPI discovery.

Purpose of the Study:

• To develop MEGADOCK-Web, an integrated database of MEGADOCK PPI predictions.
• To provide a comprehensive and accessible resource for computational PPI predictions.
• To facilitate the discovery of novel PPIs and protein functions.

Main Methods:

• Utilized MEGADOCK software for rapid protein-protein docking calculations.
• Constructed a database integrating prediction results and 3D complex structures.
• Included annotations for PDB ID, UniProt AC, KEGG pathways, and known PPIs.

Main Results:

• MEGADOCK-Web contains over 28 million predicted PPIs from 7528 protein chains.
• The database offers more than 10 times the predictions of previous resources.
• Features include searching predictions, annotation with known PPIs, pathway visualization, and 3D structure viewing.

Conclusions:

• MEGADOCK-Web provides extensive PPI predictions, aiding in assessing interaction feasibility.
• The database supports the discovery of new PPIs and protein functions.
• MEGADOCK-Web is freely accessible online for research purposes.