Analysis of Multi-Target Synergistic Mechanism of Coix Seed Therapy for Herpes Zoster Based on Machine Learning and Network Pharmacology
文献类型： 外文期刊
作者： Song, Zhiqin 1 ; Yang, Lin 1 ; He, Jing 2 ; Li, Yuchao 2 ; Yang, Ningxian 3 ; Yang, Min 4 ; Wu, Mingkai 1 ;
作者机构： 1.Guizhou Acad Agr Sci, Inst Crop Germplasm Resources, Inst Modern Chinese Herbal Med, Guiyang 550006, Peoples R China
2.Guizhou Univ, Inst Agro Bioengn, Coll Life Sci, Key Lab Plant Resource Conservat & Germplasm Innov, Guiyang 550025, Guizhou, Peoples R China
3.Guizhou Med Univ, Guizhou Prov Engn Res Ctr Ecol Food Innovat, Key Lab Environm Pollut Monitoring & Dis Control, Sch Publ Hlth,Minist Educ, Guiyang 561113, Peoples R China
4.Rural Revitalizat Serv Ctr Guiyang City, Guiyang 550004, Peoples R China
关键词： network pharmacology; machine learning; molecular dynamics simulation; herpes zoster; molecular docking
期刊名称：GENES （ 影响因子：2.8； 五年影响因子：3.2 ）
ISSN：
年卷期： 2025 年 16 卷 5 期
页码：
收录情况： SCI
摘要： Objective: To explore the efficacy and mechanism of Coix seeds in treating herpes zoster (HZ) using an integrated computational approach. Methods: Network pharmacology, molecular docking, and machine learning were employed. Disease-related targets were collected from multiple databases, and intersection targets with Coix seed were analyzed via PPI, GO, and KEGG enrichment. A "TCM-Ingredient-Target" network was constructed using Cytoscape. Molecular docking and dynamics simulations were performed for validation. Results: Fifty-five overlapping targets were identified, with core targets including TNF, EGF, and GAPDH. Enrichment analysis revealed key pathways such as inflammation and immune regulation. Molecular docking confirmed strong binding affinity between active compounds and targets. Conclusions: This study demonstrates that Coix seed exerts anti-HZ effects through multi-target mechanisms, providing a theoretical basis for developing novel multi-pathway treatment strategies.
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