Xiaobei Lu,1 Yapeng Sun,2 Man Gong,1 Zhigang Sun,1 Xueru Fan,1 Na Huang,1 Liping Dai,1 Erping Xu1 

1Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, 450046, People’s Republic of China; 2Third Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, 450008, People’s Republic of China

Correspondence: Erping Xu, Henan Key Laboratory for Modern Research on Zhongjing’s Herbal Formulae, Academy of Chinese Medical Sciences, Henan University of Chinese Medicine, 156 East Jinshui Road, Zhengzhou, 450046, People’s Republic of China, Email xuerping@hactcm.edu.cn Liping Dai, Henan Key Laboratory for Modern Research on Zhongjing’s Herbal Formulae, Academy of Chinese Medical Sciences, Henan University of Chinese Medicine, 156 East Jinshui Road, Zhengzhou, 450046, People’s Republic of China, Email liping_dai@hactcm.edu.cn

Background: Ulcerative colitis (UC) is a chronic inflammatory bowel disease. A modified traditional Chinese medicine (TCM) formula, “Jiawei Jianpi Huoyu Formula (JJHF)”, has been reported to be effective in relieving UC symptoms, but its potential pharmacological components and targets remain unclear.
Methods: This study employs an integrative approach combining network pharmacology, machine learning, molecular docking, Mendelian randomization (MR), and experimental validation to investigate the therapeutic mechanisms of JJHF in UC.
Results: We identified 199 intersecting targets that were considered potential JJHF targets for treating UC. Network analysis revealed quercetin, luteolin, and kaempferol as key components modulating inflammatory pathways such as TNF and IL-6. Machine learning identified four core targets associated with UC progression, including glycogen synthase kinase 3 beta (GSK3B), vascular cell adhesion protein 1 (VCAM1), caspase-1 (CASP1), and heat shock protein family A member 5 (HSPA5). Molecular docking confirmed strong binding affinities between these targets and JJHF components, particularly β-sitosterol and HSPA5. In vitro experiments demonstrated that JJHF’s efficacy in reducing LPS-induced inflammatory cytokines (IL-1β, TNF-α, MCP-1) and downregulating the expression of HSPA5, GSK3B, VCAM1, and CASP1 mRNA expression in RAW264.7 macrophages. In vivo, sixty mice were utilized to assess the efficacy of JJHF in DSS-induced colitis, where the JJHF alleviated colitis, improved colon length, disease activity index (DAI), and histopathology while suppressing pro-inflammatory cytokines. Notably, MR analysis established a causal link between elevated HSPA5 expression and UC risk (OR=5.639, p=0.040).
Conclusion: These findings highlight the innovative application of MR in JJHF research and underscore its multi-component, multi-target mechanisms in UC treatment, particularly through anti-inflammatory pathways and modulation of HSPA5 signaling. This study lays a scientific foundation for the clinical application and mechanistic exploration of JJHF in managing UC, offering potential advantages over standard therapies like mesalazine.

Keywords: Jiawei Jianpi Huoyu Formula, ulcerative colitis, network pharmacology, machine learning, Mendelian randomization analysis