title: A benchmark testing ground for integrating homology modeling and protein docking.
abstract: Protein docking procedures carry out the task of predicting the structure of a protein-protein complex starting from the known structures of the individual protein components. More often than not, however, the structure of one or both components is not known, but can be derived by homology modeling on the basis of known structures of related proteins deposited in the Protein Data Bank (PDB). Thus, the problem is to develop methods that optimally integrate homology modeling and docking with the goal of predicting the structure of a complex directly from the amino acid sequences of its component proteins. One possibility is to use the best available homology modeling and docking methods. However, the models built for the individual subunits often differ to a significant degree from the bound conformation in the complex, often much more so than the differences observed between free and bound structures of the same protein, and therefore additional conformational adjustments, both at the backbone and side chain levels need to be modeled to achieve an accurate docking prediction. In particular, even homology models of overall good accuracy frequently include localized errors that unfavorably impact docking results. The predicted reliability of the different regions in the model can also serve as a useful input for the docking calculations. Here we present a benchmark dataset that should help to explore and solve combined modeling and docking problems. This dataset comprises a subset of the experimentally solved 'target' complexes from the widely used Docking Benchmark from the Weng Lab (excluding antibody-antigen complexes). This subset is extended to include the structures from the PDB related to those of the individual components of each complex, and hence represent potential templates for investigating and benchmarking integrated homology modeling and docking approaches. Template sets can be dynamically customized by specifying ranges in sequence similarity and in PDB release dates, or using other filtering options, such as excluding sets of specific structures from the template list. Multiple sequence alignments, as well as structural alignments of the templates to their corresponding subunits in the target are also provided. The resource is accessible online or can be downloaded at http://cluspro.org/benchmark, and is updated on a weekly basis in synchrony with new PDB releases. Proteins 2016; 85:10-16. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
authors.forename: Tanggis
authors.initials: T
authors.lastname: Bohnuud
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.
authors.forename: Lingqi
authors.initials: L
authors.lastname: Luo
authors.affiliation: VIB Structural Biology Research Center, VUB Pleinlaan 2, Brussels, 1050, Belgium.|Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Shoshana J
authors.initials: SJ
authors.lastname: Wodak
authors.affiliation: Bijvoet Center for Biomolecular Research, Faculty of Science, Chemistry, Utrecht University, Utrecht, 3584CH, The Netherlands.
authors.forename: Alexandre M J J
authors.identifier: 0000-0001-7369-1322
authors.initials: AM
authors.lastname: Bonvin
authors.affiliation: Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology University of Massachusetts Medical School, Worcester, Massachusetts.
authors.forename: Zhiping
authors.initials: Z
authors.lastname: Weng
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.|Department of Chemistry, Boston University, Boston, Massachusetts, 02215.
authors.forename: Sandor
authors.initials: S
authors.lastname: Vajda
authors.affiliation: Department of Microbiology and Molecular Genetics, Institute for Medical Research Israel-Canada, Hadassah Medical School Hebrew University, Jerusalem, Israel.
authors.forename: Ora
authors.initials: O
authors.lastname: Schueler-Furman
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts, 02215.|Department of Applied Mathematics and Statistics, Stony Brook University, New York.
authors.forename: Dima
authors.initials: D
authors.lastname: Kozakov
mesh_terms: D000595:Amino Acid Sequence; D019985:Benchmarking; D001665:Binding Sites; D053453:Caspase 9 / Q000737:chemistry* / Q000378:metabolism; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D008024:Ligands; D062105:Molecular Docking Simulation; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D055503:Protein Multimerization; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D016415:Sequence Alignment; D012984:Software; D040681:Structural Homology, Protein; D051636:X-Linked Inhibitor of Apoptosis Protein / Q000737:chemistry* / Q000378:metabolism
chemical_list: D008024:Ligands; D051636:X-Linked Inhibitor of Apoptosis Protein; C496866:XIAP protein, human; C506433:CASP9 protein, human; D053453:Caspase 9
keywords: CAPRI docking experiment; method development; protein structure prediction; protein-protein docking; user community