Network pharmacology research integrating LC-MS/MS, machine learning, molecular docking, and dynamics simulation: key biomarkers and potential mechanisms of against prostate cancer.
[UNLABELLED] To explore the key biomarkers and molecular mechanisms of Phellinus igniarius (Sanghuang, SH) in the prevention and treatment of prostate cancer (PCa).
APA
Ren Z, Liu X, et al. (2026). Network pharmacology research integrating LC-MS/MS, machine learning, molecular docking, and dynamics simulation: key biomarkers and potential mechanisms of against prostate cancer.. In silico pharmacology, 14(1), 65. https://doi.org/10.1007/s40203-025-00511-5
MLA
Ren Z, et al.. "Network pharmacology research integrating LC-MS/MS, machine learning, molecular docking, and dynamics simulation: key biomarkers and potential mechanisms of against prostate cancer.." In silico pharmacology, vol. 14, no. 1, 2026, pp. 65.
PMID
41717432
Abstract
[UNLABELLED] To explore the key biomarkers and molecular mechanisms of Phellinus igniarius (Sanghuang, SH) in the prevention and treatment of prostate cancer (PCa). LC-MS/MS was used to identify 118 bioactive SH blood components, followed by target prediction. PCa-related genes were screened through differential expression analysis (DEGs) and weighted gene co-expression network analysis (WGCNA) by integrating disease databases and TCGA-PRAD data. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were then performed to reveal pathways. Machine learning algorithms were then used to screen core targets. Mendelian randomisation (MR) analysis was then used to identify key SH biomarkers against PCa. Molecular docking and dynamics simulations were then used to assess the binding characteristics between the key biomarkers and their corresponding active SH components. Finally, we examined the relationship between the key biomarkers and immune cell infiltration levels in the tumour microenvironment. KEGG enrichment analysis revealed a strong enrichment of these targets in the Rap1, Ras and MAPK signalling pathways. Five key SH targets against PCa were identified: FGFR2, GSTP1, FOLH1, TERT and CXCR2. Dataset validation confirmed significant differences in the expression of core targets in PCa tissues. Further MR analysis indicated that GSTP1 and CXCR2 may be key biomarkers for SH against PCa. Molecular dynamics simulations provided preliminary support for the binding stability between SH components and their targets. Meanwhile, immune infiltration analysis revealed correlations between these targets and immune cell populations. Together, these results offer insights into the potential roles of SH components in PCa treatment. SH may exert its anti-PCa effects by regulating key biomarkers such as GSTP1 and CXCR2, interfering with oncogenic signalling pathways including Rap1, Ras and MAPK, and modulating the infiltration levels of immune cells such as M0/M1 macrophages simultaneously.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s40203-025-00511-5.
[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1007/s40203-025-00511-5.
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