Due to various unpleasant side effects and general ineffectiveness of current treatments for prostate cancer (PCa), more and more people with PCa try to look for complementary and alternative medicine such as herbal medicine. However, since herbal medicine has multi-components, multi-targets and multi-pathways features, its underlying molecular mechanism of action is not yet known and still needs to be systematically explored. Presently, a comprehensive approach consisting of bibliometric analysis, pharmacokinetic assessment, target prediction and network construction is firstly performed to obtain PCa-related herbal medicines and their corresponding candidate compounds and potential targets. Subsequently, a total of 20 overlapping genes between DEGs in PCa patients and the target genes of the PCa-related herbs, as well as five hub genes, i.e., CCNA2, CDK2, CTH, DPP4 and SRC were determined employing bioinformatics analysis. Further, the roles of these hub genes in PCa were also investigated through survival analysis and tumour immunity analysis. Moreover, to validate the reliability of the C-T interactions and to further explore the binding modes between ingredients and their targets, the molecular dynamics (MD) simulations were carried out. Finally, based on the modularization of the biological network, four signaling pathways, i.e., PI3K-Akt, MAPK, p53 and cell cycle were integrated to further analyze the therapeutic mechanism of PCa-related herbal medicine. All the results show the mechanism of action of herbal medicines on treating PCa from the molecular to systematic levels, providing a reference for the treatment of complex diseases using TCM.
Keywords: MD simulations; bioinformatics analysis; herbal medicines; mechanism of action; prostate cancer.