Modeling of protein-protein interactions

The identification of protein-protein interactions (PPIs) is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. To improve the state-of-the-art in PPI modeling, we developed eFindSite^PPI to predict binding residues in a target protein structure with machine learning, and eRank^PPI to identify near-native conformations generated by protein docking with a new scoring function utilizing interface probability estimates and a contact-based symmetry score. Furthermore, we devised a high-throughput protocol for the bottom-up assembly of protein interaction networks based on all-to-all protein docking. These tools can be used to reliably identify and model biologically relevant protein assemblies at the proteome scale.