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The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD <2.5 Å by SPRING is 134% and 167% higher than these competing methods. SPRING is controlled with ZDOCK on 77 docking benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

Finding and identifying circular permuted protein pairs (CPP) is one of the harder tasks for structure alignment programs, because of the different location of the break in the polypeptide chain connectivity. The protein structure alignment tool GANGSTA+ was used to search for CPPs in a database of nearly 10,000 protein structures. It also allows determination of the statistical significance of the occurrence of circular permutations in the protein universe. The number of detected CPPs was found to be higher than expected, raising questions about the evolutionary processes leading to CPPs. The GANGSTA+ protein structure alignment tool is available online via the web server at http://gangsta.chemie.fu-berlin.de. On the same webpage the complete data base of similar protein structure pairs based on the ASTRAL40 set of protein domains is provided and one can select CPPs specifically., (Proteins 2010. (c) 2009 Wiley-Liss, Inc.)

Due to the large number of available protein structure alignment algorithms, a lot of effort has been made to define robust measures to evaluate their performances and the quality of generated alignments. Most quality measures involve the number of aligned residues and the RMSD. In this work, we analyze how these two properties are influenced by different residue assignment strategies as employed in common non-sequential structure alignment algorithms. Therefore, we implemented different residue assignment strategies into our non-sequential structure alignment algorithm GANGSTA+. We compared the resulting numbers of aligned residues and RMSDs for each residue assignment strategy and different alignment algorithms on a benchmark set of circular-permuted protein pairs. Unfortunately, differences in the residue assignment strategies are often ignored when comparing the performances of different algorithms. However, our results clearly show that this may strongly bias the observations. Bringing residue assignment strategies in line can explain observed performance differences between entirely different alignment algorithms. Our results suggest that performance comparison of non-sequential protein structure alignment algorithms should be based on the same residue assignment strategy.

Insights in structural biology can be gained by analyzing protein architectures and characterizing their structural similarities. Current computational approaches enable a comparison of a variety of structural and physicochemical properties in protein space. Here we describe the automated detection of rotational symmetries within a representative set of nearly 10,000 nonhomologous protein structures. To find structural symmetries in proteins initially, equivalent pairs of secondary structure elements (SSE), i.e., alpha-helices and beta-strands, are assigned. Thereby, we also allow SSE pairs to be assigned in reverse sequential order. The results highlight that the generation of symmetric, i.e., repetitive, protein structures is one of nature's major strategies to explore the universe of possible protein folds. This way structurally separated 'islands' of protein folds with a significant amount of symmetry were identified. The complete results of the present study are available at http://agknapp.chemie.fu-berlin.de/gplus, where symmetry analysis of new protein structures can also be performed.

Protein-protein docking is a major task in structural biology. In general, the geometries of protein pairs are sampled by generating docked conformations, analyzing them with scoring functions and selecting appropriate geometries for further refinement. Here, we present an algorithm in real space to sample geometries of protein pairs. Therefore, we initially determine uniformly distributed points on the surfaces of the two protein structures to be docked and additionally define a set of uniformly distributed rotations. Then, the sampling method generates structures of protein pairs as follows: (i) We rotate one protein of the protein pair according to a selected rotation and (ii) translate it along a line connecting two surface points belonging to different proteins such that these surface points coincide. The resulting protein pair geometries are then analyzed and selected using a scoring function that considers residues and atom pairs. We applied this approach to a set of 22 enzyme-inhibitor complexes and demonstrate that a discretisation of the rigid-body search in real space provides an efficient and robust sampling scheme. Our method generates decoy sets with a considerable fraction of near-native geometries for all considered enzyme-inhibitor complexes.