Bioinformatics-Guided Multi-Target Antidiabetic Lead Discovery from Ficus altissima: From In Vitro Enzyme Inhibition to Network Pharmacology and Molecular Docking

The management of postprandial hyperglycemia in diabetes mellitus often involves inhibition of carbohydrate-digesting enzymes, yet synthetic inhibitors such as acarbose are associated with gastrointestinal side effects. Natural compounds offer safer alternatives with multi-target therapeutic potential compared to synthetic ones. This study investigates the antidiabetic potential and molecular mechanisms of Ficus altissima (FA) leaves extract using a combined in vitro and in silico approach. In vitro enzyme inhibition assays were performed to evaluate the effect of FA on α-amylase and α-glucosidase, followed by IC₅₀ determination and statistical validation. Metabolite profiling was conducted using UPLC-HRMS, and virtual ADME screening was applied to identify drug-like candidates. Network pharmacology approaches, including protein-protein interaction analysis, compound-target-pathway network construction and analysis, gene ontology, and hierarchical network study, were employed to predict targets and underlying pathways for antidiabetic effectiveness. The protein targets were further corroborated through molecular docking. FA extract demonstrated significant inhibition of α-amylase (IC₅₀ = 10.58 mg/mL) and α-glucosidase (IC₅₀ = 13.74 mg/mL), showing comparable or superior efficacy to acarbose at specific concentrations. UPLC-HRMS identified 15 metabolites, of which seven satisfied ADME criteria. Network pharmacology revealed several intersecting protein targets, enriched in PI3K-Akt, AGE-RAGE, AMPK, JAK-STAT, and insulin resistance pathways. Hub genes PIK3CA, MMP2, IL2, and EP300 emerged as central nodes. Molecular docking confirmed strong binding affinities, particularly FA6 with MMP2 (-11.6 kcal/mol) and FA4 with PIK3CA (-9.1 kcal/mol), suggesting stable interactions at active sites. Molecular dynamics simulations (200 ns) coupled with MMPBSA binding free energy calculations further corroborated the stability of the top-ranked protein-ligand complexes, confirming persistent interactions and favorable binding energetics throughout the simulation period. This integrative study demonstrates that FA extract exerts antidiabetic potential through dual enzyme inhibition. The identified compounds from the FA extract represent candidate scaffolds for the development of safer, naturally derived antidiabetic therapeutics and the modulation of critical signalling pathways.