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Modeling the impact of drug interactions on therapeutic selectivity

Author

Listed:
  • Zohar B. Weinstein

    (Boston University School of Medicine)

  • Nurdan Kuru

    (Sabanci University)

  • Szilvia Kiriakov

    (Boston University
    Boston University)

  • Adam C. Palmer

    (Harvard Medical School)

  • Ahmad S. Khalil

    (Boston University
    Harvard University
    Boston University)

  • Paul A. Clemons

    (Broad Institute of Harvard and MIT)

  • Muhammad H. Zaman

    (Boston University
    Boston University)

  • Frederick P. Roth

    (University of Toronto
    Lunenfeld-Tanenbaum Research Institute
    Canadian Institute for Advanced Research)

  • Murat Cokol

    (Sabanci University
    Harvard Medical School)

Abstract

Combination therapies that produce synergistic growth inhibition are widely sought after for the pharmacotherapy of many pathological conditions. Therapeutic selectivity, however, depends on the difference between potency on disease-causing cells and potency on non-target cell types that cause toxic side effects. Here, we examine a model system of antimicrobial compound combinations applied to two highly diverged yeast species. We find that even though the drug interactions correlate between the two species, cell-type-specific differences in drug interactions are common and can dramatically alter the selectivity of compounds when applied in combination vs. single-drug activity—enhancing, diminishing, or inverting therapeutic windows. This study identifies drug combinations with enhanced cell-type-selectivity with a range of interaction types, which we experimentally validate using multiplexed drug-interaction assays for heterogeneous cell cultures. This analysis presents a model framework for evaluating drug combinations with increased efficacy and selectivity against pathogens or tumors.

Suggested Citation

  • Zohar B. Weinstein & Nurdan Kuru & Szilvia Kiriakov & Adam C. Palmer & Ahmad S. Khalil & Paul A. Clemons & Muhammad H. Zaman & Frederick P. Roth & Murat Cokol, 2018. "Modeling the impact of drug interactions on therapeutic selectivity," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05954-3
    DOI: 10.1038/s41467-018-05954-3
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