Integrating in vitro, network pharmacology, and molecular docking approaches to uncover the antidiabetic potential of Tylophora hirsuta.

Tylophora hirsuta is traditionally employed in folk medicine for the treatment of various conditions including diabetes. Recently, the therapeutic potential of T. hirsuta in the management of diabetes has gained interest due to its bioactive compounds. In this study, we employed in vitro antidiabetic potential and detailed network pharmacology (NP)-based methodology for the investigation of the active ingredients of T. hirsuta. Results revealed that among all tested samples, crude extract exhibited significant effects at various concentration with IC value of 0.257 mg/ml against α-amylase, IC value of 0.104 mg/ml against α-glucosidase and aldose reductase with IC 14.533 µg/ml. Similarly, the virtual screening of the active ingredients was performed against the diabetes targets such as Glucosidase (8IBK), Amylase (1B2Y), and GLP1 (7S15) to obtain the top hits. Deoxytubulosine showed highest binding energies against the Glucosidase, and GLP1, while the Stigmasterol showed the highest binding energy against the Amylase. The virtual screening was followed by the molecular dynamic simulation studies and binding free energy calculations to validate the results of the virtual screening. The MD simulation results showed that complexes remain stable during the course of 50 ns simulation using RMSD (Root Mean Square Deviation), RMSF (Root Mean Square Fluctuation), and Rg (Radius of Gyration) post-MD analysis. The MM-PBSA/GBSA (Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized-Born Surface Area) analysis revealed favorable binding interaction and stability of the complexes in term of binding free energy. In short, the network pharmacology analysis, virtual screening, simulation, binding free energy calculations and in vitro data point to T. hirsuta as a possible option for antidiabetic medication development.