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Liquid–liquid equilibrium (LLE) data for the ternary systems 1-propanol + water + n-alcohols (1-pentanol, 1-hexanol, 1-octanol, 1-nonanol, 1-decanol, or 1-dodecanol) were determined at 298.15 K and atmospheric pressure. The n-alcohols from 1-pentanol up to 1-dodecanol can be used as extraction solvents for the separation of 1-propanol from aqueous solutions. The miscibility curves, the conode lines, and the plait points were obtained. The phase diagrams for all of these systems are of type I in according to Trayball classification. The Othmer–Tobias and Hand equations, used to verify the quality of the experimental data, give similar and generally good results for all of the systems. The experimental ternary LLE data were correlated with the universal quasichemical activity coefficient (UNIQUAC) model which represents satisfactorily the obtained experimental data. Distribution coefficients (D i) and separation factors (S) were calculated from tie-line data to evaluate the extracting capability of the solvents, which increases with increasing alcohol chain length.

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A prototype of a family of at least nine members, cellular Src tyrosine kinase is a therapeutically interesting target because its inhibition might be of interest not only in a number of malignancies, but also in a diverse array of conditions, from neurodegenerative pathologies to certain viral infections. Computational methods in drug discovery are considerably cheaper than conventional methods and offer opportunities of screening very large numbers of compounds in conditions that would be simply impossible within the wet lab experimental settings. We explored the use of global quantitative structure-activity relationship (QSAR) models and molecular ligand docking in the discovery of new c-src tyrosine kinase inhibitors. Using a dataset of 1038 compounds from ChEMBL database, we developed over 350 QSAR classification models. A total of 49 models with reasonably good performance were selected and the models were assembled by stacking with a simple majority vote and used for the virtual screening of over 100,000 compounds. A total of 744 compounds were predicted by at least 50% of the QSAR models as active, 147 compounds were within the applicability domain and predicted by at least 75% of the models to be active. The latter 147 compounds were submitted to molecular ligand docking using AutoDock Vina and LeDock, and 89 were predicted to be active based on the energy of binding.