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An effective method for the selection of active compounds from cranberry based on counter-current fractionation and bioassay-guided separation was established. Cranberry extract showed potential α-glucosidase inhibitory activity. The active compounds were extracted by different solvents and enriched in water. The water extract was divided into eight fractions via high-speed counter-current chromatography to further track the active compounds. Results indicated that the α-glucosidase inhibitory activity of F7 was remarkable higher than the other fractions. Four compounds, including delphinidin-3-glucoside (D3G), cyanidin-3-glucoside, cyanidin-3-rutinoside, and pelargonidin-3-glucoside, were separated from F7 through column chromatography, and their structures were identified by high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry, 1H nuclear magnetic resonance (NMR), and 13C NMR. D3G showed the strongest α-glucosidase inhibitory activity among the compounds. Moreover, the interaction mechanism between α-glucosidase and D3G was clearly characterized and described by spectroscopic analyses and molecular docking. D3G could spontaneously bind with α-glucosidase to form complexes through hydrophobic interaction. The secondary structure of α-glucosidase changed in varying degrees after complexation with D3G. The α-helix and β-turn contents of α-glucosidase markedly decreased, whereas the irregular coil increased. These findings provide a new insight into the interaction between α-glucosidase and D3G. • Counter-current fractionation assisted bioassay-guided separation. • Four compoundswere separated from cranberry. • Delphinidin-3-glucoside (D3G) showed the strongest α-glucosidase inhibitory activity. • Interaction between α-glucosidase and D3G was studied. • Spectroscopy and molecular docking explored the interaction mechanism. [ABSTRACT FROM AUTHOR]

Ultrasound assisted aqueous two-phase extraction of polysaccharides from Lilium lancifolium Thunb was modeled by response surface methodology (RSM) and artificial neural network (ANN), and optimized using genetic algorithm coupled with ANN (GA-ANN). Statistical analysis showed that the models obtained by RSM and ANN could accurately predict the Lilium lancifolium Thunb polysaccharides (LLPs) yield. However, ANN prediction was more accurate than RSM. The optimum extraction parameters to achieve the highest LLPs yield (15.17 ± 0.21)% was obtained at the ultrasound power of 250 W, extraction temperature of 63 °C, liquid-to-solid ratio of 21 mL/g, and extraction time of 32 min. Subsequently, the crude LLPs were further purified via DEAE-52 and Sephadex G-100 chromatography to obtain a homogenous fraction (LLPs-2-SG, 421.41 kDa) that contained mannose, glucose, and galactose in a molar ratio of 10.52:23.06:7.19. The structure of LLPs-2-SG was characterized with UV–vis, FT–IR, AFM, and SEM. The findings provide a critical method for the extraction, separation and purification of polysaccharides from natural resources. • Ultrasound assisted aqueous two-phase extraction was proposed to extract LLT polysaccharides. • RSM and ANN were modeled to predict the LLPs yield. • GA-ANN was used to optimize extraction process for obtaining the maximum LLPs yield. • LLPs-2-SG contains three monosaccharides and does not contain a triple helix structure. [ABSTRACT FROM AUTHOR]