PrePPI
PrePPI (Predicting Protein-Protein Interactions) is a computational structure-based database of predicted protein-protein interactions for the human proteome, developed by the Honig Laboratory at Columbia University. The database employs a Bayesian framework that integrates structural information with non-structural supporting evidence to predict protein-protein interactions. PrePPI uses structural modeling to generate putative protein interaction interfaces, scores these structural models, and combines the structural scores with functional clues and other evidence sources to produce confidence scores for predicted interactions. The database provides comprehensive coverage of the human interactome, going beyond experimentally determined interactions to include computationally predicted interactions with varying levels of confidence. PrePPI is particularly valuable for identifying novel protein interactions that may not yet have been experimentally validated but show promise based on structural compatibility and functional context. Users can query the database by entering UniProt accession numbers or common gene/protein names to retrieve interaction partners and supporting evidence. The resource includes a high-confidence interactome subset that can be downloaded, representing predictions with the strongest supporting evidence. PrePPI complements experimental protein interaction databases by providing structure-based predictions that can guide experimental validation efforts and inform systems biology studies of protein interaction networks. The database is freely accessible through a web interface that allows interactive exploration of predicted interactions and their confidence scores.

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