Estimation of lipophilicity and design of new 17β-carboxamide glucocorticoids using RP-HPLC and quantitative structure-retention relationships analysis

Eight 17β-carboxamide glucocorticoids with local anti-inflammatory activity were selected and their retention behavior tested in six RP-HPLC systems (I–VI). logkw, a, and φ0 parameters were calculated and correlation with previously determined logPo/w values was examined. RP-HPLC system IV, which consisted of cyano column and methanol–water mobile phases (50:50, 60:40, 70:30, and 80:20, v/v), was selected as the most reliable for lipophilicity prediction and used for the analysis of chromatographic behavior of remaining fourteen 17β-carboxamide glucocorticoids. Quantitative structure-retention relationships analysis was performed and PLS(logkw) model was selected as the most statistically significant. On the basis of selected model and interpretation of corresponding descriptors, new derivatives with higher logkw values and higher expected lipophilicity were designed.

Conformational preferences of fluorine-containing agrochemicals and their implications for lipophilicity prediction

Molecular polarity governs lipophilicity, which in turn determines important agrochemical and environmental properties, such as soil sorption and bioconcentration of organic compounds. Since the C–F bond is the most polar in organic chemistry, the orientation of fluorine substituents originating from the rotation around C–C(F) bonds should affect the polarity and, consequently, the physicochemical and biological properties of fluorine-containing agrochemicals. Accordingly, this study aims to determine the most likely conformers of some fluorine-containing agrochemicals and to correlate their molecular dipole moments with the respective n-octanol/water partition coefficients (log P), in order to investigate the dependence of the lipophilicity with the molecular conformation.

Conformational Preferences of Fluorine-Containing Agrochemicals and their Implications for Lipophilicity Prediction

Molecular polarity governs lipophilicity, which in turn determines important agrochemical and environmental properties, such as soil sorption and bioconcentration of organic compounds. Since the C–F bond is the most polar in organic chemistry, the orientation of fluorine substituents originated from the rotation around C–C(F) bonds should affect the polarity and, consequently, the physicochemical and biological properties of fluorine-containing agrochemicals. Accordingly, this study aims to determine the most-likely conformers of some fluorine-containing agrochemicals and correlate their molecular dipole moments with the respective n-octanol/water partition coefficients (log P), in order to investigate the dependence of the lipophilicity with the molecular conformation.

Lipophilicity prediction of peptides and peptide derivatives by consensus machine learning

Lipophilicity prediction is routinely applied to small molecules. For compounds outside the domain of classical medicinal chemistry these predictions lack accuracy, advocating the development of bespoke in silico approaches.

The validation of quantum chemical lipophilicity prediction of alcohols

The validation of octanol-water partition coefficients (logP) quantum chemical calculations is presented for 27 alkane alcohols. The chemical accuracy of predicted logPvalues was estimated for six DFT functionals (B3LYP, PBE0, M06-2X, ωB97X-D, B97-D3, M11) and three implicit solvent models. Triple-zeta basis set 6-311++G(d,p) was employed. The best linear correlation with the experimental logPvalues was achieved for the B3LYP and B97-D3 functionals combined with the SMD model. On the other hand, no linearity was found when IEF-PCM or C-PCM implicit models were employed.