Identification of active components and functional mechanisms of BAIMA oil against acute soft-tissue injury using network pharmacology

Fen He¹, Tingting Tang¹, Anping Yang², Hui Liu², Lixia Fan², Baobin Wang³, Yongqi Xie¹, Dongshan Yang⁴, Fanghao Zheng⁵

1. Orthopedics Department 13 (Rehabilitation Medicine Department), Foshan Traditional of Chinese Medicine Hospital, The Eighth Clinical School of Guangzhou University of Traditional Chinese Medicine, Foshan City, Guangdong Province, China
2. Department of Pharmacy, Medical College, Foshan University, Foshan City, Guangdong Province, China
3. Science and Education Department, Foshan Traditional of Chinese Medicine Hospital, The Eighth Clinical School of Guangzhou University of Traditional Chinese Medicine, Foshan City, Guangdong Province, China
4. Office of the Director, Tibetan Medicine Hospital of Mêdog County, Tibet, China
5. Preparation Center, Foshan Traditional of Chinese Medicine Hospital, The Eighth Clinical School of Guangzhou University of Traditional Chinese Medicine, Foshan City, Guangdong Province, China

• Corresponding Author: Fanghao Zheng E-mail: 914559936@qq.com

Abstract
Objective
Acute soft-tissue injury (STI), a common exercise-related clinical injury, significantly affects patients’ health and work capacity. This study aimed to analyze the main components and underlying therapeutic targets of BAIMA oil in the treatment of acute STI using network pharmacology.
Methods
The major components and potential targets of BAIMA oil were identified using the TCMSP, PubChem, and Swiss Target Prediction databases. Disease-related targets of acute STI were obtained from the GeneCards and OMIM databases and intersected with the predicted targets of BAIMA oil. Subsequently, a herb–component–target–disease network was constructed using Cytoscape to identify key active components. A protein–protein interaction (PPI) network of the shared targets was then established, and hub genes were identified based on topological and cluster analyses. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the selected disease–component targets.
Results
A total of 46 active components and 680 potential targets of BAIMA oil were identified. Overall, 261 disease–component targets were screened using a Venn diagram. In the herb–component–target–disease network, the top five active components were naringenin, Sennoside E_qt, 5-hydroxy-7-methoxy-2-(3,4,5-trimethoxyphenyl)chromone, acacetin, and quercetin. In the PPI network, TP53, EGFR, and STAT3 were identified as the top three core targets based on topological analysis. GO and KEGG enrichment analyses indicated that the disease–component target genes were mainly associated with ATP binding, protein kinase activity, regulation of cell proliferation and apoptosis, protein phosphorylation, and were involved in signaling pathways such as the PI3K/Akt and MAPK pathways.
Conclusion
This study systematically analyzed the active components and molecular targets of BAIMA oil in the treatment of acute soft-tissue injury, providing scientific evidence to support the potential application of BAIMA oil as an alternative therapeutic strategy for patients with acute STI.
Keywords: BAIMA oil, active components, acute soft-tissue injury, network pharmacology