Development of protein-protein docking methodology and benchmarking environment

Abstract

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. That fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of interactome. Yet it remains so far largely untested in a systematic way. This work presents development of comprehensive docking benchmark sets of protein models, and systematic validation of state-of-the-art docking methodologies on these sets. Thorough analysis of template-based and template-free docking performance reveals that even highly inaccurate protein models yield meaningful docking predictions. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy; the template-based docking is much less sensitive to inaccuracies of protein models than the free docking; and docking can be successfully applied to entire proteomes where most proteins are models of different accuracy.