LC–MS/MS Metabolite Profiling Combined with Network Pharmacology and Molecular Simulation Uncovers the Antidiabetic Mechanisms of Litsea angulata

Litsea angulata is a medicinal plant with promising bioactive metabolites, yet its antidiabetic mechanism remains insufficiently understood. This study investigated the antidiabetic potential of Litsea angulata leaf metabolites using an integrated approach combining LC–MS/MS profiling, network pharmacology, molecular docking, molecular dynamics (MD), and MM-PBSA analyses. Dried leaves were extracted by maceration with ۷۰% ethanol and subjected to LC–MS/MS for metabolite annotation. Predicted compound targets were intersected with Type ۲ Diabetes Mellitus (T۲DM)–related genes to identify shared targets, followed by protein–protein interaction network construction, hub gene screening using maximal clique centrality (MCC), and GO/KEGG enrichment analysis. Molecular docking was conducted against PIK۳R۱ (PDB ID: ۵XGJ), and the best-scoring complexes were evaluated by ۵۰ ns MD simulations using GROMACS ۲۰۱۶.۳. Structural stability was assessed through RMSD, RMSF, Rg, SASA, RDF, and hydrogen bond analyses, while binding free energies were estimated using MM-PBSA. A total of ۴۳۲ shared targets were identified, forming a densely connected network, with PIK۳R۱ ranked among the top hub proteins (MCC ۹۷۲,۲۰۳). Sitosterol (Mol۱۰) exhibited strong docking affinity toward PIK۳R۱ with a binding energy of −۹.۳۹ kcal/mol and an inhibition constant of ۱۳۱.۴۶ nM, approaching the affinity of the native ligand (−۹.۱۸ kcal/mol; Ki ۱۸۶.۷۸ nM). MM-PBSA calculations supported these findings, yielding comparable binding free energies for the native ligand (−۱۱۸.۸۵۲ ± ۱۴.۲۰۸ kJ/mol) and sitosterol (−۱۱۷.۹۳۱ ± ۱۷.۹۵۵ kJ/mol). These results suggest that Litsea angulata, particularly sitosterol, may modulate PI۳K-related signaling pathways through stable interactions with PIK۳R۱.

کلیدواژه ها:

Litsea angulate ، Type ۲ diabetes mellitus ، LC-MS/MS metabolite profiling ، network pharmacology ، Molecular Dynamics Simulation