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Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets

Author

Listed:
  • Xiaowen Lu

    (Centre for Molecular Life Sciences, Radboud University Medical Centre)

  • Philip R. Kensche

    (Centre for Molecular Life Sciences, Radboud University Medical Centre)

  • Martijn A. Huynen

    (Centre for Molecular Life Sciences, Radboud University Medical Centre
    Centre for Systems Biology and Bioenergetics (CSBB), Radboud University Medical Centre)

  • Richard A. Notebaart

    (Centre for Molecular Life Sciences, Radboud University Medical Centre
    Centre for Systems Biology and Bioenergetics (CSBB), Radboud University Medical Centre)

Abstract

Genetic interactions reveal insights into cellular function and can be used to identify drug targets. Here we construct a new model to predict negative genetic interactions in protein complexes by exploiting the evolutionary history of genes in parallel converging pathways in metabolism. We evaluate our model with protein complexes of Saccharomyces cerevisiae and show that the predicted protein pairs more frequently have a negative genetic interaction than random proteins from the same complex. Furthermore, we apply our model to human protein complexes to predict novel cancer drug targets, and identify 20 candidate targets with empirical support and 10 novel targets amenable to further experimental validation. Our study illustrates that negative genetic interactions can be predicted by systematically exploring genome evolution, and that this is useful to identify novel anti-cancer drug targets.

Suggested Citation

  • Xiaowen Lu & Philip R. Kensche & Martijn A. Huynen & Richard A. Notebaart, 2013. "Genome evolution predicts genetic interactions in protein complexes and reveals cancer drug targets," Nature Communications, Nature, vol. 4(1), pages 1-10, October.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3124
    DOI: 10.1038/ncomms3124
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