Abstract
This study aimed to determine the extraction conditions that maximize the biological activities of Morchella importuna and to demonstrate the pharmacological potential of the optimized extracts. Ultrasonic-assisted extraction was applied, and the effects of temperature, time, and solvent ratio were evaluated using Response Surface Methodology (RSM) and a hybrid Artificial Neural Network-Genetic Algorithm (ANN-GA) approach. ANN-GA optimization yielded higher levels of key phenolics, particularly quercetin, protocatechuic acid, and gallic acid, compared to RSM. The antioxidant capacities of the ANN-GA and RSM extracts were determined as TAS: 5.266 ± 0.015 and 5.101 ± 0.031 mmol/L, TOS: 8.144 ± 0.035 and 10.240 ± 0.054 µmol/L, OSI: 0.155 ± 0.001 and 0.201 ± 0.002, DPPH: 121.82 ± 1.30 and 113.26 ± 1.44 mg TE/g, and FRAP: 158.98 ± 0.91 and 141.87 ± 1.80 mg TE/g, respectively. ANN-GA extracts also showed stronger anticholinesterase activity with AChE inhibition values of 66.47 ± 0.85 µg/mL and BChE values of 119.16 ± 1.11 µg/mL. In antiproliferative assays, ANN-GA extracts exhibited higher cytotoxicity against A549, MCF-7, and DU-145 cell lines compared to RSM extracts. Overall, the ANN-GA-assisted optimization approach not only improved extraction efficiency but also enhanced the antioxidant, anticholinesterase, and antiproliferative properties of M. importuna. These findings highlight the potential of ANN-GA optimized extracts as promising natural candidates for functional food, nutraceutical, and future pharmaceutical applications.