Integrated , microarray, and network pharmacology analysis reveals the multi-target anti-diabetic potential of .

Introduction: Diabetes mellitus (DM), particularly type 2 DM (T2DM), is a chronic metabolic disorder requiring novel therapeutic approaches as the available therapies are not meeting the current challenges. This study investigates the anti-diabetic potential of Vigna unguiculata using a network pharmacology approach, supported by and analyses.

Methods: The plant was collected from Khyber Pakhtunkhwa, Pakistan, and subjected to hydroalcoholic extraction and fractionation. assays included α-amylase, α-glucosidase, and aldose reductase. Target prediction using STITCH and SwissTargetPrediction identified 88 common genes linked to T2DM. Protein-protein interaction (PPI) network analysis highlighted key genes like EGFR, PTGS2, and TLR4 as central nodes in diabetes-related pathways. Molecular docking was used to study the binding affinities of compounds.

Results: IC50 values were determined using IBM SPSS Statistics 21 software. The data underwent analysis using one-way ANOVA followed by Dunnett's multiple comparison test. Significance value was determined at *p   0.05, **p   0.01 and ***p   0.001. In-vitro assays demonstrated significant α-amylase, α-glucosidase, and aldose reductase inhibitory activities. Phytochemical screening identified several bioactive compounds. Functional annotation and KEGG pathway analysis confirmed these genes' roles in crucial metabolic pathways. Virtual screening revealed strong binding affinities of compounds like Stigmasterol, Luteoline, and Quercetin with GSK3B, PTGS2, and TLR4. The Molecular Dynamics (MD) simulation, binding free energy calculations (MM-PBSA and MM-GBSA), confirmed the results of Virtual screening.

Conclusion: In short, these findings underscore as a promising source for anti-diabetic agents, supporting further clinical trials for T2DM management.