Unal_2026_Chem.Biodivers_23_e02875

Natural products rich in natural ingredients play a supporting role in the treatment of many diseases. This study evaluated the biological activities of Citrus limon (L.) Osbeck extracts obtained under optimized conditions using two techniques: response surface methodology (RSM) and artificial neural network-genetic algorithm (ANN-GA). Optimization focused on temperature, extraction time, and ethanol-water ratio. The ANN-GA model predicted optimal conditions as 51.629 degreesC, 6.502 h, and 41.585% ethanol, while RSM suggested 53.219 degreesC, 13.461 h, and 41.535% ethanol. Antioxidant properties were assessed via DPPH, FRAP, and TAS/TOS assays. Anticholinesterase activity was measured through AChE and BChE inhibition, and antiproliferative effects were tested on A549 lung cancer cells. LC-MS/MS analysis identified major phenolic compounds, including gallic acid, caffeic acid, quercetin, naringenin, and kaempferol. ANN-GA extracts exhibited higher antioxidant, anticholinesterase, and antiproliferative activities than those obtained by RSM. These effects may be linked to the higher phenolic content detected in ANN-GA extracts. The findings highlight C. limon as a promising source of natural antioxidants and bioactives with potential therapeutic applications, particularly in neurodegenerative diseases and cancer. Further studies, including in vivo tests, are recommended to explore the full therapeutic potential of these extracts.