Underlying our general approach is the use of structural rather than sequence similarity to detect functional relationships between proteins. When combined with simple and fast filtering functions we are able to score billions of potential PPIs with relatively moderate computational demands. I will review how this is accomplished with a focus on our Predicting Protein-Protein Interactions (PrePPI) and Pathogen Host Interactions (P-HIPSTer) databases including recent features that have been introduced. An important extension has been the development of the OncoSig algorithm which combines PrePPI with context-specific regulatory networks developed in the Califano lab. Finally, we have used related methodologies to create the Predicting Protein Compound Interactions (PrePCI) database whose features will be described.

Structure-based proteome wide prediction of protein-protein and protein-compound interactions

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