title: Modeling complexes of modeled proteins.
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. This 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 the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å CαRMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047, USA.
authors.forename: Ivan
authors.initials: I
authors.lastname: Anishchenko
authors.affiliation: Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047, USA.
authors.forename: Petras J
authors.initials: PJ
authors.lastname: Kundrotas
authors.affiliation: Center for Computational Biology, The University of Kansas, Lawrence, Kansas, 66047, USA.|Department of Molecular Biosciences, The University of Kansas, Lawrence, Kansas, 66047, USA.
authors.forename: Ilya A
authors.initials: IA
authors.lastname: Vakser
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D019985:Benchmarking; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D018360:Crystallography, X-Ray; D062105:Molecular Docking Simulation / Q000379:methods*; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012107:Research Design; D012984:Software; D013816:Thermodynamics
chemical_list: D011506:Proteins
keywords: interactome; protein docking; protein modeling; protein recognition; structure prediction