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other·ophthalmology, ocular immunology, traditional chinese medicine, network pharmacology·PMC10470687

Identification of the key mechanisms of action of Si-Ni-San in uveitis using bioinformatics and network pharmacology

Medicine · 7 authors, 5 centres

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TL;DR

This study used network pharmacology and molecular docking to identify that Si-Ni-San (SNS) may treat uveitis through anti-inflammatory and immune-regulatory mechanisms involving key targets JUN, RELA, and MAPK1 and active compounds like kaempferol, luteolin, quercetin, and naringin. The findings suggest SNS acts via multiple pathways, including MAPK, Toll-like receptor, TNF, and NOD-like receptor signaling. These results provide a scientific basis for further research and clinical application of SNS in uveitis.

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**Background:** Uveitis is a common autoimmune eye disease that can lead to blindness. Current treatments with hormones and immunosuppressants have limitations due to dependency, toxicity, and side effects. Si-Ni-San (SNS), a traditional Chinese medicine composed of Radix Bupleuri, Fructus Aurantii, paeony, and licorice, has shown clinical efficacy in treating uveitis, but its mechanisms are poorly understood. This study aimed to explore the potential mechanisms of SNS in uveitis using network pharmacology and bioinformatics.

**Methods:** Active components of SNS were screened from the TCMSP database using criteria of oral bioavailability ≥ 30% and drug-like activity ≥ 0.18, yielding 144 active ingredients (92 from licorice, 22 from Fructus Aurantii, 13 from paeony, 17 from Radix Bupleuri). A total of 2549 targets were obtained, and after removing duplicates, 236 targets related to active ingredients were identified. Uveitis disease targets were retrieved from the Therapeutic Target, DrugBank, GeneCards, and GEO databases (using datasets GSE66936 and GSE18781). After batch correction and filtering (|LogFC| ≥ 1.5, P < .05), 89 differentially expressed genes were obtained (31 upregulated, 58 downregulated). Combining all databases, 580 disease-related targets were identified. Venn analysis revealed 56 intersection targets between SNS and uveitis. A protein-protein interaction (PPI) network was constructed using the String database (highest confidence 0.9) and analyzed with Cytoscape's CytoNCA plug-in. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed using R packages. Molecular docking of key targets (JUN, RELA, MAPK1) with core compounds (quercetin, kaempferol, luteolin, naringin) was conducted using AutoDock Vina.

**Key Results:** The PPI network identified 12 core genes: CCL2, RELA, FOS, JUN, IL1A, IL4, CXCL10, IL1B, CXCL8, STAT1, MAPK1, and IFNG. The top three key targets by degree were JUN, RELA, and MAPK1. GO enrichment yielded 1478 functions (1339 biological processes, 11 cellular components, 126 molecular functions), with top biological processes including response to lipopolysaccharides, bacterial molecules, reactive oxygen species, and regulation of steroid metabolism. KEGG analysis identified 122 pathways, with key pathways including Toll-like receptor, IL-17, MAPK, TNF, and NOD-like receptor signaling pathways. Molecular docking showed strong binding affinities: JUN with quercetin (−8.6 kcal/mol), luteolin (−8.8 kcal/mol), and kaempferol (−8.7 kcal/mol); MAPK1 with quercetin (−8.4 kcal/mol), luteolin (−8.6 kcal/mol), and naringin (−8.4 kcal/mol); and NFKB3 (RELA) with luteolin (−7.7 kcal/mol), quercetin (−7.7 kcal/mol), and naringin (−7.4 kcal/mol).

**Clinical Implications:** This study provides a scientific basis for the multi-component, multi-target, and multi-pathway mechanism of SNS in treating uveitis, primarily through anti-inflammatory and immune-regulatory effects. The identified key targets (JUN, RELA, MAPK1) and pathways (MAPK, Toll-like receptor, TNF, NOD-like receptor) offer potential therapeutic targets for uveitis. The active compounds (kaempferol, luteolin, quercetin, naringin) demonstrate good binding to these targets, supporting their role in SNS efficacy. These findings justify further biological experiments and clinical trials to validate SNS as a complementary therapy for uveitis, potentially reducing reliance on conventional immunosuppressants with their associated side effects.

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other

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ophthalmology

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ORIGINAL PAPER

PMC10470687

Identification of the key mechanisms of action of Si-Ni-San in uveitis using bioinformatics and network pharmacology

Medicine

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ABSTRACT

Background: Uveitis is an eye disease with a high rate of blindness, whose pathogenesis is not completely understood. Si-Ni-San (SNS) has been used as a traditional medicine to treat uveitis in China. However, its mechanism of action remains unclear. This study explored the potential mechanisms of SNS in the treatment of uveitis through network pharmacology and bioinformatics. Methods: Using R language and Perl software, the active components and predicted targets of SNS, as well as the related gene targets of uveitis, were mined through the Traditional Chinese Medicine Systems Pharmacology, Therapeutic Target, Gene Expression Omnibus, GeneCards, and DrugBank databases. The network diagram of active components and intersection targets was constructed using Cytoscape software and the String database. The CytoNCA plug-in was used to conduct topological analysis on the network diagram and screen out the core compounds and key targets. The genes were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Chemoffice, Pymol, AutoDock, and Vina were used to analyze the molecular docking of key targets and core compounds of diseases through the PubChem database. Results: JUN, RELA, and MAPK may play important roles in the treatment of uveitis by SNS. Kyoto encyclopedia of genes and genomes pathway enrichment analysis showed that core genes were mainly concentrated in MAPK, toll-like receptor, tumor necrosis factor, and nucleotide oligomerization domain-like receptor signaling pathways. In addition, molecular docking results showed that the bioactive compounds (kaempferol, luteolin, naringin, and quercetin) exhibited good binding ability to JUN, RELA, and MAPK. Conclusion: Based on these findings, SNS exhibits multi-component and multi-target synergistic action in the treatment of uveitis, and its mechanism may be related to anti-inflammatory and immune regulation.

CITATION EXPORT

Dandan Zhang, Liu Hong, Rui Su Zhang et al.. Identification of the key mechanisms of action of Si-Ni-San in uveitis using bioinformatics and network pharmacology. Medicine. (2023). https://doi.org/10.1097/MD.0000000000034615

AUTHORS

7 · 5 CENTRES

Dandan Zhang, Liu Hong, Rui Su Zhang, Qian Zhang, Jing Yao, Jiadi Wang, Ning Zhang

a Dalian Women and Children’s Medical Group, Dalian, China
b The Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Ha Er Bin Shi, China
c Heilongjiang University of Chinese Medicine, Harbin, China
d The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
e Banan Hospital of Chongqing Medical University, Chongqing, China.