Ranking protein docking models using a consensus approach based on the conservation of inter-residue contacts

Nowadays, molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present a simple and effective set of tools to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed models ensemble.1-4 First it calculates a conservation rate for each inter-residue contact, then it ranks models according to their ability to match the more frequently observed contacts. We applied it to over 100 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve.