title: Protein models docking benchmark 2.
abstract: Structural characterization of protein-protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template-free or template-based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high-resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have predefined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model-to-native C(α) RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the "real case scenario," as opposed to the previous set, where a significant number of structures were model-like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu.
authors.affiliation: Center for Bioinformatics, The University of Kansas, Lawrence, Kansas, 66047; United Institute of Informatics Problems, National Academy of Sciences, Minsk, 220012, Belarus.
authors.forename: Ivan
authors.initials: I
authors.lastname: Anishchenko
authors.forename: Petras J
authors.initials: PJ
authors.lastname: Kundrotas
authors.forename: Alexander V
authors.initials: AV
authors.lastname: Tuzikov
authors.forename: Ilya A
authors.initials: IA
authors.lastname: Vakser
mesh_terms: D000595:Amino Acid Sequence; D062105:Molecular Docking Simulation / Q000592:standards*; D008969:Molecular Sequence Data; D054730:Protein Interaction Domains and Motifs; D025941:Protein Interaction Mapping; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry; D012015:Reference Standards
chemical_list: D011506:Proteins
keywords: modeling of protein complexes; protein interactions; protein modeling; protein recognition; structure prediction