This study employed network pharmacology, bioinformatics, and molecular dynamics (MD) simulations methods to elucidate the anti-Prostate cancer mechanism of 20(S)-Rg3. By integrating four databases, 451 potential drug targets were identified and cross-analyzed with 14,886 Prostate cancer related genes (GeneCards), 2,906 Weighted Correlation Network Analysis (WGCNA) module genes, and 4,515 DepMap essential genes, ultimately yielding 22 common targets. Functional enrichment analysis indicated that these genes were mainly involved in cell-cycle regulation. Transcriptomic analysis of the TCGA-PRAD cohort confirmed that the core targets AURKA and CDK1 were significantly overexpressed in Prostate cancer. Survival analysis demonstrated that high expression of AURKA and CDK1 was associated with shorter Progression-Free Survival (PFS) and reduced Disease-Free Survival (DFS). In Prostate cancer cell lines, CRISPR dependency scores below -1 suggested their essential roles. Analysis of 400 ns molecular dynamics simulations showed that 20(S)-Rg3 binds to the core targets with binding energies of -33.47 kcal/mol (AURKA) and -33.51 kcal/mol (CDK1), comparable to co-crystal inhibitors, and exhibits stable Root Mean Square Deviation (RMSD ≈ 2 - 3 Å) with persistent hydrogen-bond interactions (6 - 9 per frame). These quantitative findings indicate that 20(S)-Rg3 may exert anticancer effects in prostate cancer by selectively targeting AURKA and CDK1 to inhibit cell-cycle progression, thereby providing a numerical and mechanistic basis for its antitumor activity.
Yu et al. (Fri,) studied this question.