Modeling the impact of drug interactions on therapeutic selectivity

Nature Communications
Zohar B WeinsteinMurat Cokol

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.

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Citations

Jul 10, 2020·PloS One·Melike Cokol-CakmakMurat Cokol
Nov 25, 2020·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Ahmed Abdullah Ahmed, Stephen Neidle
Jun 14, 2021·Drug Discovery Today·Nathaniel R TwarogAnang A Shelat
Dec 3, 2021·Journal of Materials Chemistry. B, Materials for Biology and Medicine·Xin LiXianting Ding

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Methods Mentioned

BETA
flow cytometry
RAP
fluorescence imaging

Software Mentioned

FlowJo
ImageJ

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