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    Thomas Bourquard, Flavie Landomiel, Eric Reiter, Pascale Crépieux, David W. Ritchie, Jérôme Azé & Anne Poupon

    Unraveling the molecular architecture of a G protein-coupled receptor/β-arrestin/Erk module complex

    Scientific Reports 5, Article number : 10760 doi:10.1038/srep10760 Received 15 September 2014 Accepted 26 January 2015 Published 01 June 2015

    Complete complex model. The model can accommodate the presence of Clathrin and the SH2 domain of c-Src.

    Color code : β-arrestin in grey, c-Src in blue, Raf1 in green, Mek1 in yellow, Erk1 in dark red.

    Possible geometry of the complex including the β-arrestin/Erk1 module, including SH2 domain of c-Src (in orange) and clathrin (in marine blue).


    Abstract• Introduction• Results• Discussion• Conclusion• Methods• Additional Information• References• Acknowledgements• Author information• Supplementary information

    β-arrestins serve as signaling scaffolds downstream of G protein-coupled receptors, and thus play a crucial role in a plethora of cellular processes. Although it is largely accepted that the ability of β-arrestins to interact simultaneously with many protein partners is key in G protein-independent signaling of GPCRs, only the precise knowledge of these multimeric arrangements will allow a full understanding of the dynamics of these interactions and their functional consequences. However, current experimental procedures for the determination of the three-dimensional structures of protein-protein complexes are not well adapted to analyze these short-lived, multi-component assemblies. We propose a model of the receptor/β-arrestin/Erk1 signaling module, which is consistent with most of the available experimental data. Moreover, for the β-arrestin/Raf1 and the β-arrestin/ERK interactions, we have used the model to design interfering peptides and shown that they compete with both partners, hereby demonstrating the validity of the predicted interaction regions.

    Subject terms : Protein structure predictions Molecular modelling Signal processing Biochemical networks

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