ArticleBMC complementary medicine and therapies2024
Screening of the key response component groups and mechanism verification of Huangqi-Guizhi-Wuwu-Decoction in treating rheumatoid arthritis based on a novel computational pharmacological model.
Article in BMC complementary medicine and therapies, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 4 citations in OpenAlex.
- Molecular mechanisms of herbal medicines and bioactive compounds in rheumatoid arthritis: a comprehensive network pharmacology perspective.Molecular biology reports · 2026Review
- Using computational pharmacology and experimental verification to decode mechanism of Qing-Wei-San in treating periodontitis.BMC complementary medicine and therapies · 2025Article
- Emerging Therapeutic Targets in Rheumatoid Arthritis: Focusing on HIF-1α, Nrf2, STATs, and RORγt.Current drug targets · 2025Review
- Formulation A in the prevention of rheumatoid arthritis: a study protocol for a multicenter randomized controlled trial.Frontiers in medicine · 2025Article
- Exploring the potential anti-diabetic peripheral neuropathy mechanisms of Huangqi Guizhi Wuwu Decoction by network pharmacology and molecular docking.Metabolic brain disease · 2024Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundRheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the destruction of synovial tissue and articular cartilage. Huangqi-Guizhi-Wuwu-Decoction (HGWD), a formula of Traditional Chinese Medicine (TCM), has shown promising clinical efficacy in the treatment of RA. However, the synergistic effects of key response components group (KRCG) in the treatment of RA have not been well studied.
methodsThe components and potential targets of HGWD were extracted from published databases. A novel node influence calculation model that considers both the node control force and node bridging force was designed to construct the core response space (CRS) and obtain key effector proteins. An increasing coverage coefficient (ICC) model was employed to select the KRCG. The effectiveness and potential mechanism of action of KRCG were confirmed using CCK-8, qPCR, and western blotting.
resultsA total of 796 key effector proteins were identified in CRS. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses confirmed their effectiveness and reliability. In addition, 59 components were defined as KRCG, which contributed to 85.05% of the target coverage of effective proteins. Of these, 677 targets were considered key reaction proteins, and their enriched KEGG pathways accounted for 84.89% of the pathogenic genes and 87.94% of the target genes. Finally, four components (moupinamide, 6-Paradol, hydrocinnamic acid, and protocatechuic acid) were shown to inhibit the inflammatory response in RA by synergistically targeting the cAMP, PI3K-Akt, and HIF-1α pathways.
conclusionsWe have introduced a novel model that aims to optimize and analyze the mechanisms behind herbal formulas. The model revealed the KRCG of HGWD for the treatment of RA and proposed that KRCG inhibits the inflammatory response by synergistically targeting cAMP, PI3K-Akt, and HIF-1α pathways. Overall, the novel model is plausible and reliable, offering a valuable reference for the secondary development of herbal formulas.
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