Protein–Protein Interactions and Genetic Disease

The advent of high-throughput experiments to measure protein–protein interactions has created a flood of proteomic information parallel to the influx of data caused by the advent of next-generation sequencing technologies. The creation of whole organism protein interaction maps has opened new avenues of predicting genetic disease. Advances in network science now allow the association of genes with disease directly from the characteristics of the protein map without reference to the characteristics of the gene itself. However, none of these techniques has reached the ‘black box’ level and require careful consideration of the systematic errors in both the underlying experimental data and the computational methods to give reliable results. Here, we review the main methods to characterise protein interactions in vitro and in vivo, the methods by which protein networks are constructed and the characteristics of themajor protein interaction databases, and the techniques used to predict the functional impact of mutations on protein interaction networks.