Computational Analysis of Plumbagin in Prostate Cancer Using Network Pharmacology and Molecular Dynamics Simulations

Prostate cancer is a major contributor to cancer-related mortality among men. Because many patients are diagnosed only after the disease has progressed to a locally advanced or metastatic stage, curative treatment is often no longer possible. In the present study, we applied an integrated computational approach combining network pharmacology, molecular docking, and molecular dynamics simulations to explore the potential molecular mechanisms underlying the therapeutic effects of plumbagin in prostate cancer. Potential therapeutic targets were identified through integrated database analysis, followed by protein-protein interaction network construction, functional enrichment analysis, molecular docking, and molecular dynamics simulations to evaluate the stability of protein-ligand interactions. Our computational analyses identified that plumbagin may form stable interactions with multiple hub targets, including AKT serine/threonine kinase 1 (AKT1), estrogen receptor 1 (ESR1), BCL2 apoptosis regulator (BCL2), epidermal growth factor receptor (EGFR), tumor necrosis factor (TNF), mitogen-activated protein kinase 3 (MAPK3), heat shock protein 90 alpha family class A member 1 (HSP90AA1), SRC proto-oncogene, non-receptor tyrosine kinase (SRC), and peroxisome proliferator activated receptor gamma (PPARG), suggesting its potential to modulate key pathways involved in prostate cancer progression. These in silico findings provide new insights into the possible molecular mechanisms of plumbagin and offer a rationale for future experimental validation. However, further in vitro and in vivo studies are warranted to confirm its functional activity and therapeutic efficacy.