In-silico Network Pharmacology and Computational Modelling of Bioactive Compounds From Allium Cepa Targeting Downstream Protein Effectors in Diabetes

Network pharmacology is an emerging, cost-effective drug-development approach that uses systems biology and network theory to integrate data and reveal interactions between compounds and their biological targets. Diabetes mellitus is a widespread metabolic disease affecting millions worldwide, while traditional medicine represents knowledge of healing practices inherited across generations and indigenous communities. Allium cepa contains various nutraceutical compounds that give it notable antioxidant, antitumor, antidiabetic, and anti-inflammatory properties. Bioactive compounds of Allium cepa were identified using a phytochemical interactive database. Both the diabetic and bioactive compound target proteins were determined and screened for oral drug bioavailability potential with favorable pharmacokinetic properties. The target proteins underwent protein-protein interaction network analysis, and analyzed using molecular docking analysis. The interaction of kaempferol with PPARG, PPARA and GSK3B possesses − 8.5 kcal/mol, -8.1 kcal/mol, and − 8.0 kcal/mol, respectively. The results obtained showed that kaempferol identified with strong binding affinity with the selected diabetic target proteins and confirmed as the best bioactive compound with an overall interaction profile, antidiabetic property, and good oral drug likeness.