PrePPI: a structure-informed database of protein-protein interactions

Abstract

PrePPI (http://bhapp.c2b2.columbia.edu/PrePPI) is a database that combines predicted and experimentally determined protein-protein interactions (PPIs) using a Bayesian framework. Predicted interactions are assigned probabilities of being correct, which are derived from calculated likelihood ratios (LRs) by combining structural, functional, evolutionary and expression information, with the most important contribution coming from structure. Experimentally determined interactions are compiled from a set of public databases that manually collect PPIs from the literature and are also assigned LRs. A final probability is then assigned to every interaction by combining the LRs for both predicted and experimentally determined interactions. The current version of PrePPI contains ∼2 million PPIs that have a probability more than ∼0.1 of which ∼60 000 PPIs for yeast and ∼370 000 PPIs for human are considered high confidence (probability > 0.5). The PrePPI database constitutes an integrated resource that enables users to examine aggregate information on PPIs, including both known and potentially novel interactions, and that provides structural models for many of the PPIs.

Figure 1.

The PrePPI page of predicted protein–protein interactions for query protein P03989.

Figure 2.

The structural interaction model for TGF-β receptor type I (green, UniProt ID P36897) and complement component C1q receptor (cyan, UniProt ID Q9NPY3) based on the structure of a designed protein (gold and red for A and B chains, respectively, of PDB file 1jy4).