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Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM

Nature Protocols volume 6, pages 1341–1354 (2011)Cite this article

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Abstract

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank–formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.

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Figure 1: Description of the prediction algorithm.
Figure 2
Figure 3: The putative Chk1-p16ink complex predicted by PRISM using templates 1blxAB and 1fmaDE.

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Acknowledgements

We thank all members of the Koc University Computational Systems Biology group, especially C. Ulubas, A. Selim Aytuna and U. Ogmen (former PRISM development team). We thank former and current members of the Tel Aviv University Structural Bioinformatics group, particularly M. Shatsky (MultiProt) and E. Mashiach (FiberDock). This work has been supported by TUBITAK (Research Grant numbers: 109T343 and 109E207). This project has been funded in whole or in part with federal funds from the National Cancer Institute, US National Institutes of Health (contract number HHSN261200800001E). The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products or organizations imply endorsement by the U.S. Government. This research was supported (in part) by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Center for Cancer Research. O.K. acknowledges support from the Turkish Academy of Sciences (TUBA).

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Authors and Affiliations

  1. Center for Computational Biology and Bioinformatics, College of Engineering, Koc University, Rumelifeneri Yolu, Sariyer Istanbul, Turkey

    Nurcan Tuncbag, Attila Gursoy & Ozlem Keskin

  2. Basic Science Program, SAIC-Frederick Inc., Center for Cancer Research Nanobiology Program, NCI-Frederick, Frederick, Maryland, USA

    Ruth Nussinov

  3. Department of Human Genetics and Molecular Medicine, Sackler Institute of Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

    Ruth Nussinov

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  1. Nurcan Tuncbag
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  2. Attila Gursoy
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Contributions

A.G. and O.K. developed the initial PRISM concept. N.T., A.G., R.N. and O.K. contributed substantially to the design and implementation of the current flexible PRISM. N.T. did coding and wrote the initial manuscript. All authors contributed substantially to the discussion of the results and to the writing of the paper.

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Correspondence to Attila Gursoy or Ozlem Keskin.

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Tuncbag, N., Gursoy, A., Nussinov, R. et al. Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM. Nat Protoc 6, 1341–1354 (2011). https://doi.org/10.1038/nprot.2011.367

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