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Elucidating Common Structural Features of Human Pathogenic Variations Using Large-Scale Atomic-Resolution Protein Networks

Authors

  • Jishnu Das,

    1. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York
    2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
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  • Hao Ran Lee,

    1. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York
    2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
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    • These authors contributed equally.

  • Adithya Sagar,

    1. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
    2. Department of Biomedical Engineering, Cornell University, Ithaca, New York
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    • These authors contributed equally.

  • Robert Fragoza,

    1. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
    2. Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York
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    • These authors contributed equally.

  • Jin Liang,

    1. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
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  • Xiaomu Wei,

    1. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
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  • Xiujuan Wang,

    1. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York
    2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
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  • Matthew Mort,

    1. Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, UK
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  • Peter D. Stenson,

    1. Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, UK
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  • David N. Cooper,

    1. Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, UK
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  • Haiyuan Yu

    Corresponding author
    1. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York
    2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York
    • Correspondence to: Haiyuan Yu, 335 Weill Hall, 237 Tower Road, Ithaca, NY 14853, USA. E-mail: haiyuan.yu@cornell.edu

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  • Contract grant sponsors: National Cancer Institute (grant CA167824); National Institute of General Medical Sciences (grant GM104424); Weill Cornell Medical College Clinical and Translational Science Center Pilot Award; BIOBASE GmbH (through a License Agreement with Cardiff University).

  • Communicated by Mauno Vihinen

ABSTRACT

With the rapid growth of structural genomics, numerous protein crystal structures have become available. However, the parallel increase in knowledge of the functional principles underlying biological processes, and more specifically the underlying molecular mechanisms of disease, has been less dramatic. This notwithstanding, the study of complex cellular networks has made possible the inference of protein functions on a large scale. Here, we combine the scale of network systems biology with the resolution of traditional structural biology to generate a large-scale atomic-resolution interactome-network comprising 3,398 interactions between 2,890 proteins with a well-defined interaction interface and interface residues for each interaction. Within the framework of this atomic-resolution network, we have explored the structural principles underlying variations causing human-inherited disease. We find that in-frame pathogenic variations are enriched at both the interface and in the interacting domain, suggesting that variations not only at interface “hot-spots,” but in the entire interacting domain can result in alterations of interactions. Further, the sites of pathogenic variations are closely related to the biophysical strength of the interactions they perturb. Finally, we show that biochemical alterations consequent to these variations are considerably more disruptive than evolutionary changes, with the most significant alterations at the protein interaction interface.

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