Electrochemical oxidation of flavonoids: PM6 and DFT for elucidating electronic changes and modelling oxidation potential (part II)

Application of Changes in Atomic Charges Resulting from Different Electrochemical Oxidation Mechanisms for the Estimation of the First Oxidation Potential of Flavonoids

“…As previously stated [1][2][3][4], an improvement of all of the models was obtained by adding the number of OH groups (NOH) on a flavonoid skeleton as a variable to quadratic regressions. The statistics for all of the models mentioned were significantly improved, but again, the model using ring were taken into account, which enabled us to obtain much better statistics for all of the models.…”

“…= 0.031 and S.E.cv = 0.037 (N = 29). The introduction of pH as a variable[1][2][3][4] allowed the estimation of Ep1 values at pHs of both 3 and 7 (N = 58), and the statistics obtained by mean variable was of similar quality; R 2 = 0.982, S.E. = 0.039 and S.E.cv = 0.043 (Fig.4).…”

“…Earlier [2][3][4] we developed a model based on the sum of atomic orbital spin populations over the carbon atoms in the skeleton of a flavonoid radical molecule, s(C)  AOSPRad. A comparison of our models with the model using hydrogen bond dissociation energy (BDE), which is one of the most important variables for antioxidant activity modeling [5,6], showed inferiority of the BDE model for estimating Ep1 values [1][2][3][4]. In this study, I used the same set of 29 flavonoids as in Ref.…”

Hybrid Classification/Regression Approach to QSAR Modeling of Stoichiometric Antiradical Capacity Assays’ Endpoints

“…The classification of the OH-groups of interest (phenolic, enolic in curcuminoids, and chromanol OH-groups of flavan-3-ols) as active or inactive in radical scavenging reactions was based on the calculated electronic parameters determining radical stability. The BDE and the spin delocalization were used for this purpose [ 25 , 26 , 27 , 28 , 29 ]. Having in mind the substantial structural diversity of the dataset used, we chose the maximal SD localized on any of the heavy atoms of oxygen-centered radicals (maxSD) as a measure of the spin delocalization on radical structures (lower maxSD indicates more spin delocalization) instead of using SD sums/normalized sums over the oxygen or aromatic atoms in the compounds’ radicals [ 27 , 28 , 29 , 49 ].…”

“…The explicit classification of (poly)phenol OH-groups could be based on easily interpretable calculated electronic parameters, as illustrated by [ 17 , 18 ], where the lowest BDE was used as a descriptor assisting in the classification of simple phenolics or flavonoid compound performance in antiradical capacity assays, but implicitly on the level of whole molecules only. Reasonable candidates for classification descriptors regarding the participation of OH-groups in the radical scavenging are the electronic parameters determining the phenoxyl radical stability, e.g., BDE (predominantly for monophenols [ 25 ]) or some spin-densities-related parameters describing spin delocalization on the phenoxyl radicals (predominantly for polyphenols [ 26 , 27 , 28 , 29 ]). However, such explicit classification of OH-groups, and its use in QSAR models, has some limitations and requires some important assumptions: (a) it cannot account for some molecular features important in radical stabilization [ 13 , 30 , 31 , 32 ] unless they are reflected in the electronic descriptors used; (b) it cannot account for the structural changes in (poly)phenol molecules upon its participation in a number of sequential radical scavenging reactions [ 33 , 34 ]; and thus, (c) it assumes that ranking of the individual OH-groups remains unchanged during the radical scavenging assay, both within a single polyphenol molecule and across the all molecules tested in the assay.…”