284 - Quantifying synergy for hormetic compounds using the dose-equivalence/zero-interaction (DE/ZI) method: Nrf2/antioxidant response element pathway activation

Abstract

Small molecule Nrf2/ARE pathway activators show promise to preventchronic disease conditions, given their role in mitigating oxidative and electrophilic stress. We find that the efficacy and potency of the clinically-studied electrophilic Nrf2/ARE activator sulforaphane are enhanced by 12.5 µM 2,5-di-tert-butyl hydroquinone (dtBHQ), a reactive oxygen species-generating diphenol. Because the maximum efficacy of sulforaphane is increased, the compounds are acting in a synergistic manner. The issue that arises is how to quantitate the extent of the synergistic interaction. Synergy is defined by a response greater than the predicted additive response. We investigated whether the commonly used dose-effect models, including Highest Single Agent, Response Additivity, and Bliss Independence, as well as the curve-based models, e.g. Loewe Additivity and the Chou-Talalay method, could be applied to sulforaphane and dtBHQ data sets to predict the additive response. Nrf2-targeted activators, including sulforaphane, do not exhibit a traditional Hill-slope dose-response curve, but rather a hormetic dose-response, with a U-shape. We show that, given the sulforaphane curve shape, published methods of determining the predictive additive effect are not appropriate. Therefore, we propose a model to assess synergistic interactions that can be applied to any curve shape. This method, termed dose-equivalence/zero-interaction (DE/ZI), is based on the principles of Loewe Additivity, in which additivity is determined not by adding the effects of doses of drug A and drug B, but by adding the dose of A and the equivalent dose of B and calculating the predicted effect. DE/ZI differs from Loewe Additivy in that DE/ZI releases the constraint that interpolation off curve A and curve B must give the same predicted additive result. DE/ZI generates a FoldSynergy value with error, based on a Monte Carlo simulation. DE/ZI allows drug combinations to be assessed for synergy or antagonism, even for compounds that do not fit to a traditional Hill-slope model.