UPLC‐MS/MS and Box–Behnken Design Optimization of Ultrasound‐Assisted Extraction of Ailanthus excelsa with Pharmacophore Modeling and Molecular Docking Studies Targeting HMG‐CoA Reductase

Abstract Ailanthus excelsa is a medicinal plant known for its diverse pharmacological properties. Optimizing extraction methods is crucial for enhancing the yield of bioactive compounds, ensuring efficiency and sustainability. This study investigates the optimal extraction conditions of A. excelsa , along with UPLC‐MS/MS analysis, and in silico evaluation against HMG‐CoA reductase. Ultrasound‐assisted extraction parameters were optimized using Box–Behnken design, yielding optimal conditions at 60 °C for 30 min and a solid‐to‐solvent ratio of 1:15. Under these conditions, the extract showed a pancreatic lipase inhibition IC 50 value of 110.7 µg/mL, total phenolic content of 23.4 mg GAE/g, and total flavonoid content of 32.6 mg QE/g. The optimized extract (Batch 14) exhibited notable in vitro inhibitory activity against HMG‐CoA reductase (IC 50 = 50.21 µg/mL). UPLC‐MS/MS analysis identified 35 phytoconstituents. Receptor‐based e‐pharmacophore modeling, based on simvastatin (HMG‐CoA reductase) interactions, facilitated virtual screening, identifying S9, S12, and S19 as top candidates. Molecular docking studies against HMG‐CoA reductase (PDB ID: 1HW9) revealed that S13, S12, and S9 exhibited superior binding affinities (−5.08, −5.03, and − 4.07, respectively) compared to simvastatin (−1.98), forming key interactions with GLU559, SER565, and ARG568. These findings highlight A. excelsa as a promising source of HMG‐CoA reductase inhibitors with potential application in metabolic disorder management.