FunctionalDeep Eutectic Solvents to Boost AntioxidantSynergism in Edible Fats

This work leverages the complexity of hydrogen-bond interactions to develop <i>functional</i> deep eutectic solvents, defined as those formed by molecules with specific functionality (antioxidants, in this case). Specifically, the proposed strategy utilizes established machine learning models to sequentially predict which antioxidants are likely to form synergistic mixtures and then predict which mixtures would also form stable deep eutectic solvents (DES). As a proof of concept, we herein present results obtained with mixtures of BHA (<i>tert</i>-butyl-4-hydroxyanisole) and BHT (3,5-di-<i>tert</i>-butyl-4-hydroxytoluene), which are not only known to form synergistic mixtures but also identified by our model as top candidates for the proposed strategy. To investigate the structure and interaction energy between the selected compounds, a computational analysis using density functional theory was also implemented. The antioxidant capacity of the formulated DES was then assessed (by the thiobarbituric acid reactive substances assay) using oleic acid as well as commercial samples of olive oil, pork lard, and duck fat. To the best of our knowledge, this represents the first report of the use of a DES formed using only antioxidants (as hydrogen bond donors/acceptors), leading to mixtures that feature a total antioxidant capacity that is superior to both the individual components and the non-DES forms of the same antioxidants. These differences, attributed to significant decreases in the bond dissociation enthalpy of the antioxidants involved in the DES, highlight the importance of promoting (and preserving) the formation of intermolecular hydrogen bonds between antioxidants to boost their efficiency.