Computational network pharmacology and molecular simulations to explore the potential mechanisms of Pyrrosia piloselloides compounds against prostate cancer

Background Prostate cancer is major cause of cancer-related morbidity and mortality in men worldwide. Emerging evidence highlights the dragon scale fern ( Pyrrosia piloselloides or P. piloselloides ) has demonstrated anticancer potential, but its molecular mechanisms against prostate cancer remain unclear. The study aimed to investigate its potential anticancer compounds and underlying molecular mechanisms using an integrated in silico approach. Methods A structured computational workflow integrating network pharmacology, molecular simulations, and MM/GBSA analysis was employed to explore the potential mechanism of bioactive compounds of P. piloselloides against prostate cancer-related targets. Additionally, the pharmacokinetic and toxicity profiles were evaluated using ADMET prediction. Results Eight bioactive compounds of the plants were identified as potentially interacting with 32 prostate cancer-related proteins, including nine key targets: ESR1, MYC, CTNNB1, PPARG, AKT1, STAT3, BCL2, AR, and ERBB2. Clustering analysis identified 20 proteins within the major cluster, that subsequently dianalisis enrichment idapati bahwa mereka were associated with 235 molecular functions, 142 cellular components, and more than 1,000 biological processes, including epithelial cell proliferation dan identified terlibat dalam 161 enriched pathways, including the PI3K–Akt and ERBB signaling pathways. Docking analysis revealed variable predicted binding affinities, particularly for 7-dehydrodiosgenin 3-acetate against ERBB2 (− 11.85 kcal/mol), AKT1 (− 9.49 kcal/mol), and BCL2 (− 9.38 kcal/mol), stigmasterol against PPARG (− 9.63 kcal/mol), ERBB2 (− 9.94 kcal/mol), and AR (− 9.31 kcal/mol), and 6-hydroxymethaqualone against ESR1 (− 9.34 kcal/mol). Molecular dynamics simulations indicated overall structural stability with localized flexibility, while MM/GBSA analysis yielded favorable predicted binding free energies for ERBB2 with 6-hydroxymethaqualone (− 45.57 kcal/mol), PPARG with stigmasterol (− 41.52 kcal/mol), and BCL2 with 7-dehydrodiosgenin 3-acetate (− 23.35 kcal/mol). The compounds also showed generally favorable predicted ADMET profiles, providing basis for further experimental evaluation. Conclusion The integrated computational analysis identified 6-hydroxymethaqualone, stigmasterol, and 7-dehydrodiosgenin 3-acetate as compounds with promising predicted interactions across prostate cancer-related targets. These findings provide a basis for further investigation and experimental validation.