The Supporting Information is available free of charge on the ACS Publications website at DOI: Detailed description of the computational strategy, Tables and figures showing complementary information about the SolvL and ProtL scales, and their application to several test systems.
Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (P) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log P values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (P). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.
In a previous study, the detailed low-molecular weight polyphenolic profile of the different plant parts (leaves, stem, bark and wood) of Uncaria tomentosa was reported, the leaves being the plant part with the highest phenolic content and presenting the most heterogenous proanthocyanidin composition. Further, cytotoxicity of leaves extracts in two cancer cell lines was also found to be higher than in the remaining parts of the plant. In the present study, fractioning of U. tomentosa leaves polyphenolic extracts was performed using Diaion® HP-20 resin and a detailed characterization and quantification of fractions (n = 5) was achieved using advanced analytical techniques such as Ultra-Performance Liquid Chromatography coupled with Electrospray Ionization and Triple Quadrupole (TQD) Tandem Mass Spectrometry (UPLC/TQ-ESI-MS) and 13C-NMR. Oxygen Radical Absorbance Capacity (ORAC) and cytotoxicity on gastric adenocarcinoma AGS and colon adenocarcinoma SW20 cell lines were also determined in the different fractions. Results showed selective distribution of 32 non-flavonoid and flavonoid phenolics among the different fractions. ORAC varied between 3.2 and 11.8 μmol TE/mg in the different fractions, whereas IC50 of cytotoxicity on gastric adenocarcinoma AGS and colon adenocarcinoma SW20 cell lines best values were between 71.4 and 75.6 µg/mL. Fractions rich in proanthocyanidins also showed the highest bioactivity. In fact, significant positive correlation was found between total proanthocyanidins (TP) quantified by UPLC-DAD and ORAC (R2 = 0.970), whereas significant negative correlation was found between TP and cytotoxicity towards AGS (R2 = 0.820) and SW620 (R2 = 0.843) adenocarcinoma cell lines. Among proanthocyanidins, propelargonidin dimers were of particular interest, showing significant correlation with cytotoxic selectivity on both gastric AGS (R2 = 0.848) and colon SW620 (R2 = 0.883) adenocarcinoma cell lines. These results show further evidence of the bioactivity of U. tomentosa proanthocyanidin extracts and their potential health effects.
The IEFPCM/MST continuum solvation model is used for the blind prediction of noctanol/water partition of a set of 11 fragment-like small molecules within the SAMPL6 Part II Partition Coefficient Challenge. The partition coefficient of the neutral species (log P) was determined using an extended parametrization of the B3LYP/6-31G(d) version of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol. Comparison with the experimental data provided for partition coefficients yielded a root-mean square error (rmse) of 0.78 (log P units), which agrees with the accuracy reported for our method (rmse = 0.80) for nitrogencontaining heterocyclic compounds. Out of the 91 sets of log P values submitted by the participants, our submission is within those with an rmse < 1 and among the four best ranked physical methods. The largest errors involve three compounds: two with the largest positive deviations (SM13 and SM08), and one with the largest negative deviations (SM15). Here we report the potentiometric determination of the log P for SM13, leading to a value of 3.62 ± 0.02, which is in better agreement with most empirical predictions than the experimental value reported in SAMPL6. In addition, further inclusion of several conformations for SM08 significantly improved our results. Inclusion of these refinements led to an overall error of 0.51 (log P units), which supports the reliability of the IEFPCM/MST model for predicting the partitioning of neutral compounds.
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