Therapeutic Targets and Immune Mechanisms of Yinghuang Decoction in Sepsis: Integrating Network Pharmacology, Molecular Docking, and Pharmacokinetic Approaches.

BACKGROUND

Yinghuang Decoction is an herbal formula that is used for the treatment of sepsis. This study used network pharmacology and molecular docking methods to explore the potential mechanism of Yinghuang Decoction against sepsis.

METHODS

The active ingredients, target genes, and sepsis-related differentially expressed genes (DEGs) were acquired from the public database. The intersection genes were obtained, and the function enrichment analysis was performed. Next, the herbs-active ingredients-genes-disease and protein-protein interaction networks were constructed using Cytoscape v3.7.2. Subsequently, the hub genes were identified using the CytoHubba plugin. The immune cell levels were evaluated by the single-sample Gene Set Enrichment Analysis (ssGSEA). Furthermore, molecular docking was carried out. Finally, the pharmacokinetics and toxicity of active ingredients were predicted.

RESULTS

A total of 7 hub genes (ESR1, PTGS2, CACNB4, KCNMA1, GMPS, AHR, PRKCA) and 11 active ingredients were obtained. These hub genes were significantly correlated with immune cells that are significantly dysregulated in sepsis, such as immature B cells. Among them, three hub genes (CACNB4, GMPS, and PRKCA) exhibited relatively stable diagnostic performance for sepsis (AUC above 0.7). Four active ingredients, linoleic acid, palmitic acid, kaempferol, and afzelin, had good binding affinities with ESR1, PRKCA, and PTGS2, respectively. The four active ingredients met Lipinski's rule principles and were not hepatotoxic or carcinogenic. Real-time qPCR validated the expression of hub genes in sepsis patients, which could reverse after Yinghuang Decoction treatment.

CONCLUSION

This study exhibited the multiple active ingredients and hub genes of Yinghuang Decoction against sepsis and might offer new insight for advancing its research in sepsis treatment. Due to limited sample size, the expressions of hub genes should be validated in the larger cohorts.