Deciphering the Anti-Diabetic Potential of Gymnema Sylvestre Using Integrated Computer-Aided Drug Design and Network Pharmacology
Deciphering the Anti-Diabetic Potential of Gymnema Sylvestre Using Integrated Computer-Aided Drug Design and Network Pharmacology
This study explores novel therapeutic avenues for diabetes, a global health concern marked by elevated blood glucose levels. We investigated the anti-diabetic potential of Gymnema Sylvestre's bioactive compounds, including Gymnemic acid I, Stigmasterol, Deacylgymnemic acid, Beta-Amyrin acetate, Longispinogenin, Gymnemic acid II, Gymnemic acid, Gymnemic acid X, Gymnemaside VI, Phytic acid and Gymnemic acid X. Employing network pharmacology, molecular docking and molecular dynamics (MD), we elucidated the potential mechanism of action. SwissTargetPrediction identified targets for bioactive constituents, while DisGeNET provided diabetes-related targets. A GeneVenn diagram revealed 397 common potential targets for diabetes management. The protein–protein interaction network, constructed via the STRING database, underwent topological analysis in Cytoscape, identifying AKT1, SRC, TNF, PPARG and IL1B as top targets. Gene ontology analysis using FunRich identified crucial roles of screened targets in integrin family cell surface interactions and glypican pathways for diabetes management. Molecular interactions and binding affinities with the top target, AKT1, were assessed, with Gymnemic acid I displaying the least binding energy (−9.813) with H- and non-H-bond interactions. Molecular dynamics simulations provided insights into the distinct behaviours of Gymnemic acid I within the protein complex. In conclusion, our study elucidates the potential anti-diabetic mechanism of Gymnemic acid I, underscoring the need for further in vitro, in vivo and clinical studies to validate our findings.
This study explores novel therapeutic avenues for diabetes, a global health concern marked by elevated blood glucose levels.
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