Templates are available to model nearly all complexes of structurally characterized proteins.
Traditional approaches to protein-protein docking sample the binding modes with no regard to similar experimentally determined structures (templates) of protein-protein complexes. Emerging template-based docking approaches utilize such similar complexes to determine the docking predictions. The docking problem assumes the knowledge of the participating proteins' structures. Thus, it provides the possibility of aligning the structures of the proteins and the template complexes. The progress in the development of template-based docking and the vast experience in template-based modeling of individual proteins show that, generally, such approaches are more reliable than the free modeling. The key aspect of this modeling paradigm is the availability of the templates. The current common perception is that due to the difficulties in experimental structure determination of protein-protein complexes, the pool of docking templates is insignificant, and thus a broad application of template-based docking is possible only at some future time. The results of our large scale, systematic study show that, surprisingly, in spite of the limited number of protein-protein complexes in the Protein Data Bank, docking templates can be found for complexes representing almost all the known protein-protein interactions, provided the components themselves have a known structure or can be homology-built. About one-third of the templates are of good quality when they are compared to experimental structures in test sets extracted from the Protein Data Bank and would be useful starting points in modeling the complexes. This finding dramatically expands our ability to model protein interactions, and has far-reaching implications for the protein docking field in general.
Center for Bioinformatics and Department of Molecular Biosciences, University of Kansas, 2030 Becker Drive, Lawrence, KS 66047, USA.
Petras J
PJ
Kundrotas
Zhengwei
Z
Zhu
Joël
J
Janin
Ilya A
IA
Vakser
D030562:Databases, Protein; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry*
D011506:Proteins