Averrhoa bilimbi L. has long been utilized in traditional medicine and is increasingly investigated for its metabolic benefits, particularly in diabetes management. However, the molecular mechanisms underlying its antidiabetic activity and the influence of formulation strategies on its efficacy remain insufficiently understood. This study aimed to elucidate the antidiabetic potential of Averrhoa bilimbi L. leaf metabolites through an integrated approach combining LC–MS/MS profiling, network pharmacology analysis, and formulation into a self-nanoemulsifying drug delivery system (SNEDDS). Metabolites were identified using LC–MS/MS and subjected to in silico target prediction, followed by the collection of Type 2 Diabetes Mellitus-related genes to determine overlapping targets. Protein–protein interaction (PPI) analysis and maximal clique centrality (MCC) were employed to identify key hub proteins. Network pharmacology analysis revealed 434 shared targets, highlighting the involvement of the PI3K–AKT signaling pathway as a central mechanism. The optimized SNEDDS formulation demonstrated high transmittance (81.5%), nanoscale droplet size (157.7 ± 4.90 nm), rapid emulsification time (57 s), and satisfactory stability. In vitro α-amylase inhibition assays showed a significant reduction in IC₅₀ values from 440.92 ± 10.96 µg/mL in the crude extract to 3.75 ± 0.09 µg/mL in the SNEDDS formulation. Nevertheless, the observed enhancement should be interpreted cautiously due to the inherent inhibitory activity of the blank SNEDDS system. Overall, Averrhoa bilimbi L. exhibits promising antidiabetic activity through multitarget modulation, although further experimental validation is necessary to confirm these findings.
Aryani et al. (2026) studied this question.