BMC Bioinformatics | |
Scoring docking conformations using predicted protein interfaces | |
Reyhaneh Esmaielbeiki2  Jean-Christophe Nebel1  | |
[1] Faculty of Science, Engineering and Computing, Kingston University London, Kingston-Upon-Thames, Surrey KT1 2EE, UK | |
[2] Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK | |
关键词: Model ranking; Model scoring; Docking; Homology modelling; Interface prediction; Protein-protein interaction; | |
Others : 818475 DOI : 10.1186/1471-2105-15-171 |
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received in 2012-12-11, accepted in 2014-05-29, 发布年份 2014 | |
【 摘 要 】
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.
【 授权许可】
2014 Esmaielbeiki and Nebel; licensee BioMed Central Ltd.
【 预 览 】
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