2 research outputs found

    A Novel, Extremely Bioavailable Cocrystal of Pterostilbene

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    New multicomponent solid forms of the nutraceutical pterostilbene have been discovered and characterized through experimental cocrystal screening. Among the coformers tested, picolinic acid formed a cocrystal with a 10-fold enhancement of oral bioavailability in rats, which converts the new cocrystal into a very promising candidate for new formulations of pterostilbene with improved performance

    Prediction of the n‑octanol/water partition coefficients in the SAMPL6 blind challenge from MST continuum solvation calculations

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    The IEFPCM/MST continuum solvation model is used for the blind prediction of n-octanol/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 nitrogen-containing 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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