Protein-Protein Docking Benchmark Version 3.0

Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA.
Proteins Structure Function and Bioinformatics (Impact Factor: 2.63). 11/2008; 73(3):705-9. DOI: 10.1002/prot.22106
Source: PubMed


We present version 3.0 of our publicly available protein-protein docking benchmark. This update includes 40 new test cases, representing a 48% increase from Benchmark 2.0. For all of the new cases, the crystal structures of both binding partners are available. As with Benchmark 2.0, Structural Classification of Proteins (Murzin et al., J Mol Biol 1995;247:536-540) was used to remove redundant test cases. The 124 unbound-unbound test cases in Benchmark 3.0 are classified into 88 rigid-body cases, 19 medium-difficulty cases, and 17 difficult cases, based on the degree of conformational change at the interface upon complex formation. In addition to providing the community with more test cases for evaluating docking methods, the expansion of Benchmark 3.0 will facilitate the development of new algorithms that require a large number of training examples. Benchmark 3.0 is available to the public at

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Available from: Joël Janin, Mar 13, 2015
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    • "This data-set has been widely used for training and testing protein docking algorithms, developing re-ranking algorithms, formulating energy functions, and performing protein structure 2 N. Saranya et al. analysis. This set contains crystal structures of both the monomers and the complexes (Hwang et al., 2008). Among the 124 protein–protein complexes reported, we have removed one complex (1QFW) as it was considered redundant for our analysis with change only in chain id though sequence remained the same. "
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    ABSTRACT: Conformation switching in protein-protein complexes is considered important for the molecular recognition process. Overall analysis of 123 protein-protein complexes in a benchmark dataset showed that 6.8% of residues switched over their secondary structure conformation upon complex formation. Amino acid residue wise preference for conformation change has been analyzed in binding and nonbinding site residues separately. In this analysis, residues such as Ser, Leu, Glu and Lys had higher frequency of secondary structural conformation change. The change of helix to coil and sheet to coil conformation and vice versa has been observed frequently whereas the conformation change of helix to extended sheet occurred rarely in the studied complexes. Influence of conformation change towards the N and C terminal on either side of the binding site residues has been analyzed. Further, analysis on φ and ψ angle variation, conservation, stability and solvent accessibility have been performed on binding site residues. Knowledge obtained from the present study could be effectively employed in the protein-protein modelling and docking studies.
    Journal of biomolecular Structure & Dynamics 05/2015; DOI:10.1080/07391102.2015.1050695 · 2.92 Impact Factor
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    • "Interface predictors and docking model ranking approaches are evaluated using three standard benchmark datasets: Ds56unbound [44], Docking Benchmark 3.0 (DBMK3.0) [47] and Docking Benchmark 4.0 (DBMK4.0) [76]. "
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    ABSTRACT: Background Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP). Results First, exhaustive evaluation of interface predictors demonstrates that T-PIP, whose predictions are customised to target complexity, is a state-of-the-art method. Second, comparative study between T-PioDock and other state-of-the-art scoring methods establishes T-PioDock as the best performing approach. Moreover, there is good correlation between T-PioDock performance and quality of docking models, which suggests that progress in docking will lead to even better results at recognising near-native conformations. Conclusion Accurate identification of near-native conformations remains a challenging task. Although availability of 3D complexes will benefit from template-based methods such as T-PioDock, we have identified specific limitations which need to be addressed. First, docking software are still not able to produce native like models for every target. Second, current interface predictors do not explicitly consider pairwise residue interactions between proteins and their interacting partners which leaves ambiguity when assessing quality of complex conformations.
    BMC Bioinformatics 06/2014; 15(1):171. DOI:10.1186/1471-2105-15-171 · 2.58 Impact Factor
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    • "Vulnerable hydrogen bonds (Vbonds) were defined as the bonds in the tail of the wrapping distribution, in agreement with Fernández and Scheraga definitions [44]. The background wrapping distribution was obtained by running the analysis on the transient and obligates complexes as listed by Mintseris and collaborators [45-47]. A maximum of 16 CH groups in the desolvation area was determined as threshold for the Vbond definition. "
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    ABSTRACT: The p53 family of genes and their protein products, namely, p53, p63 and p73, have over one billion years of evolutionary history. Advances in computational biology and genomics are enabling studies of the complexities of the molecular evolution of p53 protein family to decipher the underpinnings of key biological conditions spanning from cancer through to various metabolic and developmental disorders and facilitate the design of personalised medicines. However, a complete understanding of the inherent nature of the thermodynamic and structural stability of the p53 protein family is still lacking. This is due, to a degree, to the lack of comprehensive structural information for a large number of homologous proteins and to an incomplete knowledge of the intrinsic factors responsible for their stability and how these might influence function. Here we investigate the thermal stability, secondary structure and folding properties of the DNA-binding domains (DBDs) of a range of proteins from the p53 family using biophysical methods. While the N- and the C-terminal domains of the p53 family show sequence diversity and are normally targets for post-translational modifications and alternative splicing, the central DBD is highly conserved. Together with data obtained from Molecular Dynamics simulations in solution and with structure based homology modelling, our results provide further insights into the molecular properties of evolutionary related p53 proteins. We identify some marked structural differences within the p53 family, which could account for the divergence in biological functions as well as the subtleties manifested in the oligomerization properties of this family.
    PLoS ONE 10/2013; 8(10):e76014. DOI:10.1371/journal.pone.0076014 · 3.23 Impact Factor
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