Inferring protein-protein interaction networks from protein complex data

Present day approaches for the determination of protein-protein interaction networks are usually based on two hybrid experimental measurements. Here we consider a computational method that uses another type of experimental data: instead of direct information about protein-protein interactions, we consider data in the form of protein complexes. We propose a method for using these complexes to provide predictions of protein-protein interactions. When applied to a dataset obtained from a cat melanoma cell line we find that we are able to predict when a protein pair belongs to a complex with approximately 96% accuracy. Further, we are able to extrapolate the experimentally identified interaction pairs to the entire cat proteome.