Calculating the Aqueous pKa of Phenols: Predictions for Antioxidants and Cannabinoids - Max Walton-Raaby; Tyler Floen; Guillermo García-Díez; Nelaine Mora-Diez (MDPI AG, 2023)
We aim to develop a theoretical methodology for the accurate aqueous pKa prediction of structurally complex phenolic antioxidants and cannabinoids. In this study, five functionals (M06-2X, B3LYP, BHandHLYP, PBE0, and TPSS) and two solvent models (SMD and PCM) were combined with the 6-311++G(d,p) basis set to predict pKa values for twenty structurally simple phenols. None of the direct calculations produced good results. However, the correlations between the calculated Gibbs energy difference of each acid and its conjugate base, <semantics><msubsup>ΔGaq(BA)°</msubsup>=<msubsup>ΔGaq<mfenced separators="|">A−</mfenced>°</msubsup>−<msubsup>ΔGaq(HA)°</msubsup></semantics>, and the experimental aqueous pKa values had superior predictive accuracy, which was also tested relative to an independent set of ten molecules of which six were structurally complex phenols. New correlations were built with twenty-seven phenols (including the phenols with experimental pKa values from the test set), which were used to make predictions. The best correlation equations used the PCM method and produced mean absolute errors of 0.26-0.27 pKa units and R2 values of 0.957-0.960. The average range of predictions for the potential antioxidants (cannabinoids) was 0.15 (0.25) pKa units, which indicates good agreement between our methodologies. The new correlation equations could be used to make pKa predictions for other phenols in water and potentially in other solvents where they might be more soluble.