Gudasi_2025_Sci.Rep_15_32747

This study explores the potential of Ailanthus excelsa Roxb. for managing obesity by evaluating its effects on key metabolic enzymes. We evaluated a hydroalcoholic extract and its fractions for their ability to modulate important metabolic enzymes, porcine pancreatic lipase, HMG-CoA reductase, alpha-glucosidase, and alpha-amylase activities. Our methodology integrated in vitro enzymatic assays with cluster analysis (MCODE, ClueGO, and Cluepedia) and network pharmacology to elucidate interactions between metabolites and target enzymes. Protein-protein interaction (PPI) analysis, consisting of a network with 51 nodes and 264 edges, was performed using the CytoNCA plugin to calculate topological parameters. Key targets were identified based on degree centrality, including ADIPOQ, PPARA, PPARG, IL6, TNF, and AKT1. Cluster analysis of the PPI networks, conducted using the MCODE plugin, highlighted a top cluster with a high score of 22.82. Network pharmacology has identified key targets associated with obesity, including HK1, HK2, PIK3CA, AKT1, MTOR, CD36, ACACB, SLC2A4, CPTIA, INSR, ACACA, FASN, and ADIPOQ. These targets are linked to highly modulated metabolic pathways. Isoquercetin shows significant binding affinities: - 7.11 for HMG-CoA Reductase (PDB ID: 1HW9), -9.96 for lipase (PDB ID: 1LPB), - 8.96 for alpha-amylase, and - 10.41 for alpha-Glucosidase (PDB ID: 3A47). The ethyl acetate fractions exhibit notable inhibition of Porcine Pancreatic lipase (IC(50): 56.25 +/- 4.85 microg/mL) and HMG-CoA reductase (IC(50): 108.27 +/- 3.38 microg/mL), alpha-glucosidase (IC(50): 117.08 +/- 3.28 microg/mL), and alpha-amylase (IC(50): 125.93 +/- 2.29 microg/mL). Moreover, metabolites showed stronger binding affinities to all four enzymes than reference molecules. By integrating in vitro assays with molecular modeling, this study highlights the promising potential of A. excelsa and its fractions in obesity management, offering valuable insights into its therapeutic applications.