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Predicting PDZ domain–peptide interactions from primary sequences

Nature Biotechnology volume 26, pages 10411045 (2008) | Download Citation

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  • A Corrigendum to this article was published on 01 October 2008

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Abstract

PDZ domains constitute one of the largest families of interaction domains and function by binding the C termini of their target proteins1,2. Using Bayesian estimation, we constructed a three-dimensional extension of a position-specific scoring matrix that predicts to which peptides a PDZ domain will bind, given the primary sequences of the PDZ domain and the peptides. The model, which was trained using interaction data from 82 PDZ domains and 93 peptides encoded in the mouse genome3, successfully predicts interactions involving other mouse PDZ domains, as well as PDZ domains from Drosophila melanogaster and, to a lesser extent, PDZ domains from Caenorhabditis elegans. The model also predicts the differential effects of point mutations in peptide ligands on their PDZ domain–binding affinities. Overall, we show that our approach captures, in a single model, the binding selectivity of the PDZ domain family.

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Change history

  • 09 October 2008

    In the version of this article initially published, a negative sign was omitted before the expression Punified(a, b) in the text on page 1043, col. 1, line 20 and the color key in Figure 2 was upside down. These errors have been corrected in the HTML and PDF versions of the article. In addition, a sentence was added to the legend of Figure 2 to clarify the significance of positive and negative values of Punified(a, b).

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Acknowledgements

We thank Anna M. Lone for experimental contributions and Eugene I. Shakhnovich for helpful discussions. This work was supported by awards from the Arnold and Mabel Beckman Foundation, the W.M. Keck Foundation and the Camille and Henry Dreyfus Foundation, and by a grant from the US National Institutes of Health (1 RO1 GM072872-01).

Author information

Author notes

    • Jiunn R Chen

    Present address: Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, 513 Parnassus Avenue, San Francisco, California 94143, USA.

    • Michael A Stiffler

    Present address: Department of Pharmacology, University of Texas Southwestern Medical Center, 6001 Forest Park Boulevard, Dallas, Texas 75390, USA.

    • Jiunn R Chen
    •  & Bryan H Chang

    These authors contributed equally to this work.

Affiliations

  1. Department of Molecular and Cellular Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA.

    • Jiunn R Chen
  2. Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA.

    • Bryan H Chang
    • , John E Allen
    • , Michael A Stiffler
    •  & Gavin MacBeath

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Contributions

J.R.C. conceived and implemented the model. B.H.C. and J.R.C. performed the mouse-related experiments. J.E.A., B.H.C., J.R.C., and M.A.S. performed the D. melanogaster- and C. elegans-related experiments. J.R.C., B.H.C., and G.M. interpreted the data. J.R.C. and G.M. wrote the manuscript, with contributions from B.H.C., J.E.A. and M.A.S. G.M. supervised the research.

Corresponding author

Correspondence to Gavin MacBeath.

Supplementary information

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    Figures 1–4, Tables 1,2, 4–13, Tutorial, Methods

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DOI

https://doi.org/10.1038/nbt.1489