Comprehensive chemico-pharmacological profiling of Ailanthus excelsa Roxb bark: An integrated GC-MS/MS and molecular dynamics approach with free energy landscape and PCA insights

• Reviewer concerns addressed with enhanced clarity. • FEL global and metastable energy values explicitly incorporated • Overgeneralization avoided through target filtering and docking validation • Methodological limitations are transparently discussed where applicable • English language and technical presentation has been improved Ailanthus excelsa Roxb. (Tree of Heaven), native to Central and Southern India, is traditionally recognized for diverse medicinal properties. However, its molecular mechanisms in metabolic disorder management remain largely unexplored. In the present study the hydroalcoholic bark extract of A. excelsa was analyzed by GC-MS/MS to identify bioactive phytoconstituents. Identified metabolites were subjected to network pharmacology, molecular docking, 100 ns MD simulations, FEL mapping, PCA, and DFT calculations. In vitro enzyme inhibition assays were performed against pancreatic lipase and HMG-CoA reductase to validate computational findings. The GC-MS/MS profiling revealed bioactive metabolites mapped to obesity-associated signaling pathways, including MAPK, PI3K-Akt, and Ras. Protein-protein interaction and target prediction highlighted key molecular nodes such as CCND1, INSR, PIK3CA, PIK3CG, RXRA, MTOR, and AKT1. Among the metabolites, AE4 exhibited better binding affinity towards the pancreatic lipase and HMG-CoA, with binding affinity superior to orlistat and simvastatin. MD simulations, FEL, and PCA confirmed stable enzyme-ligand complexes with persistent hydrogen bonding, hydrophobic, and water-bridge interactions. DCCM analysis indicated ligand-induced stabilization of intra-domain interactions. DFT results demonstrated that AE4 had the lowest HOMO-LUMO energy gap (0.144 eV) and highest softness, signifying enhanced chemical reactivity and stability. This integrated chemico-pharmacological investigation identifies AE4 as a promising lead metabolite from A. excelsa with potential therapeutic application in obesity and related metabolic disorders.