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In this work, the separation of 11 natural and synthetic steroids was studied using MEKC electrolytes modified by property-selected organic solvents: ethanol, ACN, and THF. The interplay between electrophoretic behavior and structural features was disclosed and the effects of organic modifiers to modulate retention and to alter selectivity were discussed in terms of system linear solvation energy relationships (LSER). The LSER indicated the total organic solvent percentage in the electrolyte as a major parameter to control retention and as a minor contribution, the hydrogen bond acidity. By evaluating the electropherograms obtained from mixture-designed electrolytes, a favorable separation condition for all solutes was achieved in ca. 25 min with an electrolyte composed of 20 mmol/L sodium tetraborate at pH 9.4, 20 mmol/L SDS and 20% EtOH (0.80% CV for migration time and 2.5% CV for peak area, n = five consecutive injections). The applicability of the proposed separation condition was demonstrated by the inspection of estrogens in urine sample (puberty stage).

A novel high-performance MEKC method developed for the analysis of butenolides 1 and 2 in leaf extracts of P. malacophyllum allowed their quantitative determined within an analysis time shorter than 5 min and the results indicated CE to be a feasible analytical technique for the quantitative determination of butenolides in Piper extracts.

The combination of computational methods and experimental data from Nuclear Magnetic Resonance (NMR) is a considerably valuable tool in the elucidation of new natural product structures and, also, in the structural revision of previously reported compounds. Until recently, only classical statistical parameters were used, for example, linear correlation coefficient (R 2 ), mean absolute error (MAE), or root mean square deviation (RMSD), as a way to statistically "validate" the structure pointed out by experimental NMR spectra. Regarding the resolution of the relative configuration of organic molecules, novel tools were available in the last few years to assist in the NMR elucidation process. The most relevant are DP4+, which is based on a Bayesian probabil-