COMPUTATIONAL PRIORITIZATION OF A WITHANOLIDE-VEGFA INTERACTION IN DUCHENNE MUSCULAR DYSTROPHY USING NETWORK PHARMACOLOGY, MOLECULAR DOCKING, AND MOLECULAR DYNAMICS SIMULATIONS

Abstract

Duchenne Muscular Dystrophy (DMD) is a devastating X-linked recessive genetic neuromuscular disorder causes the progressive myopathy with few available therapeutic options. This study used an integrated network pharmacology, molecular docking, 200-ns molecular dynamics (MD) simulations, MM-GBSA and ADMET workflow computationally prioritize phytocompounds binding vascular endothelial growth factor A (VEGFA).An integrated Protein-Protein Interaction Network (PPIN) construct around VEGFA and predicted targets of screened compounds showed that VEGFA among the most central nodes by betweenness centrality, and computational knockout indicated it contributes disproportionality to network connectivity. Docking against VEGFA (PDB: 3QTK) showed withanolide, a steroidal lactone from Withania somnifera, achieved the most favorable binding score among all compounds (-9.3 kcal/mol), more favorable than the FDA-approved drug givinostat (-8.7 kcal/mol) under the same protocol. Through 200-ns molecular dynamic simulations, the VEGFA-withanolide complex remained structurally stable and MM-GBSA analysis represented a favorable binding free energy of 30.82 ± 3.04 kcal/mol. Withanolide also showed a favorable predicted ADMET profile relatives to givinostat. Ten common hub genes (MDM2, CASP3, ABL1, MTOR, AKT1, GSK3B, AR, SRC, PTGS2, CDK2) were identified within the network. These findings computationally prioritize withanolide as a candidate VEGFA-binding phytocompound and provides a strong rationale for further experimental validation and therapeutic target.