Modeling the impact of drug interactions on therapeutic selectivity
Weinstein, Zohar B. and Kuru, Nurdan and Kiriakov, Szilvia and Palmer, Adam C. and Khalil, Ahmad S. and Clemons, Paul A. and Zaman, Muhammad H. and Roth, Frederick P. and Çokol, Murat (2018) Modeling the impact of drug interactions on therapeutic selectivity. Nature Communications, 9 . ISSN 2041-1723
Official URL: http://dx.doi.org/10.1038/s41467-018-05954-3
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 nontarget 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.
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