An experimentally derived confidence score for binary protein-protein interactions

Information on protein-protein interactions is of central importance for many areas of biomedical research. Currently no method exists to systematically and experimentally assess the quality of individual interactions reported in interaction mapping experiments. To provide a standardized confidence-scoring method that can be applied to tens of thousands of protein interactions we have developed an interaction tool-kit consisting of four complementary high-throughput (HT) protein interaction assays. These assays were benchmarked against positive and random reference sets (PRS and RRS) consisting of well documented human interaction pairs and randomly chosen protein pairs, respectively. A logistic regression model was trained using the PRS/RRS data to combine the assay outputs and calculate the probability that any novel interaction pair is a true biophysical interaction once it has been tested in the tool-kit. This general approach will allow a systematic and empirical assignment of confidence scores to all individual protein-protein interactions in interactome networks.