Quantitative assessment of the structural bias in protein-protein interaction assays.

With recent publications of several large-scale protein-protein interaction (PPI) studies, the realization of the full yeast interaction network is getting closer. Here, we have analysed several yeast protein interaction datasets to understand their strengths and weaknesses. In particular, we investigate the effect of experimental biases on some of the protein properties suggested to be enriched in highly connected proteins. Finally, we use support vector machines (SVM) to assess the contribution of these properties to protein interactivity. We find that protein abundance is the most important factor for detecting interactions in tandem affinity purifications (TAP), while it is of less importance for Yeast Two Hybrid (Y2H) screens. Consequently, sequence conservation and/or essentiality of hubs may be related to their high abundance. Further, proteins with disordered structure are over-represented in Y2H screens and in one, but not the other, large-scale TAP assay. Hence, disordered regions may be important both in transient interactions and interactions in complexes. Finally, a few domain families seem to be responsible for a large part of all interactions. Most importantly, we show that there are method-specific biases in PPI experiments. Thus, care should be taken before drawing strong conclusions based on a single dataset.