PLoS ONE · 2015 · 16 citations · 35 references
PharmacyPharmacologyCancer PharmacologyDrug DesignDrug DiscoveryDrug Interaction ModelingDrug-receptor InteractionsGene - Drug InteractionsReceptor ModelingSelectivity DesignDose - Response Interaction ModelingGene OverexpressionGene Overexpression StrategiesPopulation Drug Interaction ModelingPopulation-based Dose OptimizationReceptor Binding ModelsSynergistic ImpactsSynergistic Interaction Modeling
The design of selective drugs and combinatorial drug treatments are two of the main focuses in modern pharmacology. In this study we use a mathematical model of chimeric ligand-receptor interaction to show that the combination of selective drugs is synergistic in nature, providing a way to gain optimal selective potential at reduced doses compared to the same drugs when applied individually. We use a cell population model of proliferating cells expressing two different amounts of a target protein to show that both selectivity and synergism are robust against variability and heritability in the cell population. The reduction in the total drug administered due to the synergistic performance of the selective drugs can potentially result in reduced toxicity and off-target interactions, providing a mechanism to improve the treatment of cell-based diseases caused by aberrant gene overexpression, such as cancer and diabetes.
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