Background CFF-1 is an effective treatment option for prostate cancer patients, but there is a lack of network pharmacology research on its molecular mechanism. Methods Based on bioavailability and drug-likeness, the main active ingredients of CFF-1 were obtained through the Traditional Chinese Medicine System Pharmacology (TCMSP) database. The GeneCard, OMIM, PharmGKB, Therapeutic Targets database, and DrugBank were used to construct prostate cancer target gene sets. Construct an

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... rget network and a protein-protein interaction network respectively, and GO and KEGG enrichment analysis were performed. After merging the two networks, important target genes were obtained in the merged network, and virtual screening of CFF-1 active ingredients was performed on these important target genes. Then the dynamic process of the binding of two small drug molecules to the target protein was simulated by molecular dynamics. Results 112 active ingredients of CFF-1 and 206 prostate cancer target genes were identified. The results of GO and KEGG enrichment analysis showed that the target genes regulated by CFF-1 were involved in prostate cancer-related signaling pathways. Two important target genes were obtained in the merge network, as well as the small molecules with the best binding among the active ingredients of CFF-1 were obtained through a virtual screening tool developed by us. Finally, simulate the dynamic process of two small molecules binding to the target protein. Conclusion In conclusion, this study predicted the potential molecular mechanism of CFF-1 in the treatment of prostate cancer through network pharmacology and found important target genes and their active ingredients in CFF-1. This provided a direction for future research on CFF-1 and promoted the reasonable application of CFF-1 in the clinical treatment of prostate cancer.