Dockground: A comprehensive data resource for modeling of protein complexes

Abstract

Characterization of life processes at the molecular level requires structural details of protein interactions. The number of experimentally determined structures of protein-protein complexes accounts only for a fraction of known protein interactions. This gap in structural description of the interactome has to be bridged by modeling. An essential part of the development of structural modeling/docking techniques for protein interactions is databases of protein-protein complexes. They are necessary for studying protein interfaces, providing a knowledge base for docking algorithms, and developing intermolecular potentials, search procedures, and scoring functions. Development of protein-protein docking techniques requires thorough benchmarking of different parts of the docking protocols on carefully curated sets of protein-protein complexes. We present a comprehensive description of the DOCKGROUND resource (http://dockground.compbio.ku. edu) for structural modeling of protein interactions, including previously unpublished unbound docking benchmark set 4, and the X-ray docking decoy set 2. The resource offers a variety of interconnected datasets of protein-protein complexes and other data for the development and testing of different aspects of protein docking methodologies. Based on protein-protein complexes extracted from the PDB biounit files, DOCKGROUND offers sets of X-ray unbound, simulated unbound, model, and docking decoy structures. All datasets are freely available for download, as a whole or selecting specific structures, through a user-friendly interface on one integrated website.

2D Zernike polynomial expansion: Finding the protein-protein binding regions

“…These cases led to the formulation of the concept of “induced fit” model, where upon binding the molecular partners acquire a very different conformation [35] . Another possibility is the “conformational selection” model, where the binding event freezes the HOLO molecule in one of the conformation explored in the APO dynamics [36] . In a recent paper the importance of all these models have been widely analyzed for several protein-protein interactions [36] .…”

Gene ontology improves template selection in comparative protein docking

“…The individual , , and scores were calculated for 73 347 pairs corresponding to 477 targets (these pairs will be referred to as BP bound set), 75 966 pairs of 466 targets (MF bound set), and 54 857 pairs for 456 targets (CC bound set), respectively. The GO scores for all three ontology domains could be calculated for 46 613 target‐template pairs of 426 targets (three‐domain bound set). Unbound set comprised unbound structures for 223 binary complexes, extracted from the Dockground benchmark set 4 . The set is used to evaluate docking/scoring methodology on experimentally determined unbound protein structures.…”

“…Unbound set comprised unbound structures for 223 binary complexes, extracted from the DOCKGROUND benchmark set 4. 35 The set is used to evaluate docking/scoring methodology on experimentally determined unbound protein structures. In this set, the GO-scores for all three ontology domains could be calculated for 3029 targettemplate pairs of 152 targets (three-domain unbound set).…”

Computational approaches to macromolecular interactions in the cell

“…The amount of experimentally-determined information on macromolecules and their interactions [19] is rapidly growing, especially due to the new advances in techniques such as cryo-EM ( Figure 2), boosting development of data-driven modeling of macromolecular assemblies [20]. Emerging knowledge-based techniques range from template-based modeling of protein-protein (PPI) [21][22][23][24][25] and protein-RNA interactions [26], to predictions with statistical potentials [27].…”