基于网络药理学的益髓颗粒治疗骨髓增生异常综合征的机制研究

Objective To explore the mechanism of Yisui Granule in treating myelodysplastic syndromes (MDS) based on network pharmacology. Methods Potential active components of Yisui Granule were predicted using databases such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The SwissTargetPrediction platform was employed to predict targets of the active components. Disease-related targets of MDS were retrieved from the GeneCards database. Common targets between Yisui Granule and MDS were identified using the Venny website. A protein-protein interaction (PPI) network and a drug-disease-target network were constructed using the STRING database and Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the common targets were performed using the DAVID database. Results A total of 93 potential active components of Yisui Granule were screened from TCMSP and other databases. After prediction and filtering via SwissTargetPrediction, 874 drug targets were identified. GeneCards yielded 1,567 potential disease targets related to MDS. Venny analysis revealed 242 common targets between Yisui Granule and MDS. KEGG enrichment analysis highlighted pathways such as PI3K-Akt, JAK-STAT, and NF-κB signaling. Conclusion Yisui Granule may treat MDS through a "multi-component, multi-target, multi-pathway" mechanism, potentially involving the regulation of PI3K-Akt, JAK-STAT, and NF-κB pathways to inhibit malignant clone proliferation, ameliorate differentiation blockades in hematopoietic stem/progenitor cells, and modulate the bone marrow microenvironment.