Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids
We aim to develop a theoretical methodology for the accurate aqueous pK<sub>a</sub> 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 wit...
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| Format: | Article |
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MDPI AG
2023-07-01
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| Series: | Antioxidants |
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| Online Access: | https://www.mdpi.com/2076-3921/12/7/1420 |
| _version_ | 1797590533652086784 |
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| author | Max Walton-Raaby Tyler Floen Guillermo García-Díez Nelaine Mora-Diez |
| author_facet | Max Walton-Raaby Tyler Floen Guillermo García-Díez Nelaine Mora-Diez |
| author_sort | Max Walton-Raaby |
| collection | DOAJ |
| description | We aim to develop a theoretical methodology for the accurate aqueous pK<sub>a</sub> 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 pK<sub>a</sub> 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, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mo>(</mo><mi>B</mi><mi>A</mi><mo>)</mo></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mfenced separators="|"><mrow><msup><mrow><mi>A</mi></mrow><mrow><mo>−</mo></mrow></msup></mrow></mfenced></mrow><mrow><mo>°</mo></mrow></msubsup><mo>−</mo><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mo>(</mo><mi>H</mi><mi>A</mi><mo>)</mo></mrow><mrow><mo>°</mo></mrow></msubsup></mrow></semantics></math></inline-formula>, and the experimental aqueous pK<sub>a</sub> 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 pK<sub>a</sub> 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 pK<sub>a</sub> units and R<sup>2</sup> values of 0.957–0.960. The average range of predictions for the potential antioxidants (cannabinoids) was 0.15 (0.25) pK<sub>a</sub> units, which indicates good agreement between our methodologies. The new correlation equations could be used to make pK<sub>a</sub> predictions for other phenols in water and potentially in other solvents where they might be more soluble. |
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| institution | Directory Open Access Journal |
| issn | 2076-3921 |
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| publishDate | 2023-07-01 |
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| series | Antioxidants |
| spelling | doaj.art-b07295c1119f40e982b47b3b34d877e62023-11-18T18:05:42ZengMDPI AGAntioxidants2076-39212023-07-01127142010.3390/antiox12071420Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and CannabinoidsMax Walton-Raaby0Tyler Floen1Guillermo García-Díez2Nelaine Mora-Diez3Department of Chemistry, Thompson Rivers University, Kamloops, BC V2C 0C8, CanadaDepartment of Chemistry, Thompson Rivers University, Kamloops, BC V2C 0C8, CanadaDepartment of Chemistry, Thompson Rivers University, Kamloops, BC V2C 0C8, CanadaDepartment of Chemistry, Thompson Rivers University, Kamloops, BC V2C 0C8, CanadaWe aim to develop a theoretical methodology for the accurate aqueous pK<sub>a</sub> 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 pK<sub>a</sub> 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, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mo>(</mo><mi>B</mi><mi>A</mi><mo>)</mo></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mfenced separators="|"><mrow><msup><mrow><mi>A</mi></mrow><mrow><mo>−</mo></mrow></msup></mrow></mfenced></mrow><mrow><mo>°</mo></mrow></msubsup><mo>−</mo><msubsup><mrow><mi mathvariant="sans-serif">Δ</mi><mi mathvariant="normal">G</mi></mrow><mrow><mi>a</mi><mi>q</mi><mo>(</mo><mi>H</mi><mi>A</mi><mo>)</mo></mrow><mrow><mo>°</mo></mrow></msubsup></mrow></semantics></math></inline-formula>, and the experimental aqueous pK<sub>a</sub> 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 pK<sub>a</sub> 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 pK<sub>a</sub> units and R<sup>2</sup> values of 0.957–0.960. The average range of predictions for the potential antioxidants (cannabinoids) was 0.15 (0.25) pK<sub>a</sub> units, which indicates good agreement between our methodologies. The new correlation equations could be used to make pK<sub>a</sub> predictions for other phenols in water and potentially in other solvents where they might be more soluble.https://www.mdpi.com/2076-3921/12/7/1420acid dissociation constantpK<sub>a</sub>phenolspredictionsantioxidantscannabinoids |
| spellingShingle | Max Walton-Raaby Tyler Floen Guillermo García-Díez Nelaine Mora-Diez Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids Antioxidants acid dissociation constant pK<sub>a</sub> phenols predictions antioxidants cannabinoids |
| title | Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids |
| title_full | Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids |
| title_fullStr | Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids |
| title_full_unstemmed | Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids |
| title_short | Calculating the Aqueous pK<sub>a</sub> of Phenols: Predictions for Antioxidants and Cannabinoids |
| title_sort | calculating the aqueous pk sub a sub of phenols predictions for antioxidants and cannabinoids |
| topic | acid dissociation constant pK<sub>a</sub> phenols predictions antioxidants cannabinoids |
| url | https://www.mdpi.com/2076-3921/12/7/1420 |
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