Abstract: OBJECTIVE To investigate the effect and molecular mechanism of Rabdosia rubescens in regulating energy metabolism in breast cancer based on the combination of network pharmacology, bioinformatics and molecular docking. METHODS The active ingredients of Rabdosia rubescens were found through multiple databases and literature, and screened the reported ingredients with the antitumor effects and in accordance with the Lipinski rules. By using the PubChem database and PharmMapper database, the structures of the active ingredients with the antitumor activities from Rabdosia rubescens and their potential targets were collected. In addition, the transcriptome data of breast cancer samples were obtained from TCGA and GEO databases, and the targets related to breast cancer were identified by differentially expressed genes analysis and WGCNA. After mapping with predicted targets of the active ingredients of Rabdosia rubescens, intersecting targets were identified and then analyzed by GO enrichment and KEGG analysis. The PPI network was constructed by using the STRING database for the intersecting targets. Network visualization was performed by Cytoscape software, and the top 10 targets of the PPI network were acquired by using two algorithms, DEGREE and MCC respectively. Key targets related to energy metabolism were obtained after eliminating duplicate targets obtained by both algorithms and intersecting with the top-ranked targets from the enrichment analysis regarding pathways and energy metabolism-related biological processes. Subsequently, the expression of energy metabolism-related key targets was analyzed by the UALCAN database, and the relationship between these targets and immune infiltration was analyzed by the TIMER database. Lastly, molecular docking was utilized between these targets and active ingredients that had predicted interactions. RESULTS Seven active ingredients of Rabdosia rubescens, including Oridonin, Ponicidin, Lushanrubescinsin C, Beta-Pinene, D-Limonene, Taibairubescensin A, Xindongnin J, and 368 potential targets were selected, 34 common targets were identified by mapping breast cancer-related targets. GO and KEGG enrichment analysis revealed that most of the top-ranked functions/pathways were involved with glucose and lipid metabolism. Seven energy metabolism-related key targets, PCK1, ADH1C, AKR1C3, HSD11B1, MAOA, ALDH2, and RBP4, were obtained from these functions/pathways. Meantime, the expression of these targets at the mRNA and protein levels in breast cancer was lower than those in normal tissues, and all of them were negatively correlated with tumor purity. Furthermore, the degree of immune cell infiltration such as CD4⁺ T cells and CD8⁺ T cells affected the prognosis of patients with breast cancer. The results of molecular docking showed that the above 7 active ingredients had great binding potential with the predicted targets. CONCLUSION Rabdosia rubescens exhibits anti-breast cancer effects through multi-component, multi-target, and multi-pathway, which may be achieved by regulating the energy metabolism of breast cancer to clear heat and detoxify.