Optimization of Ultrasonic-Assisted Extraction of α-Glucosidase Inhibitors from Using Artificial Neural Network and Response Surface Methodology.

Nakai is a plant with significant medicinal properties, such as anticancer, antioxidant, and anti-inflammatory activities, making it an attractive research target. Our study describes the isolation of major metabolites from , and their inhibitory activities on α-glucosidase were evaluated for the first time. The results revealed that nortrisflavaspidic acid ABB () is the most potent α-glucosidase inhibitor, with an IC of 34.0 ± 0.14 μM. In addition, artificial neural network (ANN) and response surface methodology (RSM) were used in this study to optimize the extraction conditions and evaluate the independent and interactive effects of ultrasonic-assisted extraction parameters. The optimal extraction conditions are extraction time of 103.03 min, sonication power of 342.69 W, and solvent-to-material ratio of 94.00 mL/g. The agreement between the predicted models of ANN and RSM and the experimental values was notably high, with a percentage of 97.51% and 97.15%, respectively, indicating that both models have the potential to be utilized for optimizing the industrial extraction process of active metabolites from . Our results could provide relevant information for producing high-quality extracts from for functional foods, nutraceuticals, and pharmaceutical industries.