GC-MS profiling and computational analysis of Balanites aegyptiaca phytoconstituents for antidiabetic activity: insights from network pharmacology and molecular docking.

This study investigates the antidiabetic potential of the extracts and subsequent phytochemicals of Balanites aegyptiaca (BA). The approaches used were GC-MS for phytochemical characterization, network pharmacology for target identification, in vitro studies, and computational techniques for the antidiabetic activity. Network pharmacology revealed genes-associated disease targets, i.e., IL-6, PPARα, GCG, and GCK, and their signaling pathways that were modulated by the identified phytocompounds. In vitro assays demonstrated substantial antioxidant activity of n-hexane and ethyl acetate extracts and were found to be comparable to ascorbic acid. The anti-inflammatory potential using the egg albumin method was found to be best for n-hexane extract in comparison to aspirin. The in vitro antidiabetic activity using α-amylase inhibition method was most pronounced in the methanol extract and was found to be comparable to acarbose. Molecular docking and molecular dynamics simulations (100 ns) identified stable interactions between BA-derived compounds and target proteins. In silico pharmacokinetic investigations revealed that the heptadecanoic acid and ragaglitazar exhibited the LD of 900 and 1600 mg/kg, vouching for the substantial safety. Molecular dynamics simulations confirmed the greater stability of protein-ligand complexes and also inferred about the possible ligand-protein interactions. The BA phytocompounds inherit huge potential in the management of diabetes, with promising antioxidant, anti-inflammatory, and antidiabetic effects.