Abstract: Objective To study the anti-inflammatory mechanism of Nigella glandulifera seeds with the tools of network pharmacology. Method Component targets were predicted using literature searching and the Swiss Target Prediction database. The disease targets were collected using OMIM, DrugBank, Genecard databases. The common targets were analyzed using Venny 2. 1. 0 and STRING software. According to the average degree value, important targets were taken out. A common component-target interaction network was created using the Cytoscape software. The biological function enrichment and signaling pathway enrichment analysis of the important targets were performed through Metascape. Result Fifty-seven components were collected, and 101 important interaction targets of drugs and diseases were predicted. Enrichment of biological functions illustrated 111 cell components, 139 molecular functions, 2 104 biological processes, and 165 signaling pathways. Cell components were mainly membrane components, and the principal molecular functions were focused on the G protein-coupled receptors. Biological processes involved kinases, positive regulation of transferase activity, and regulation of the MAPK cascade. Pathway enrichment predicted that the Th17 cell differentiation pathway referred to IL-6 and STAT3 as key genes were closely related to the anti-inflammatory effects of Nigella glandulifera seeds. Conclusion Given the characteristics of multi-component, multi-target, and multi-pathway of the traditional Chinese medicine, the potential anti-inflammatory mechanism of Nigella glandulifera seeds was analyzed using network pharmacology approach so as to provide the basis for further study. However, the key target and the specific regulatory mechanism need to be further verified.

Key words: Nigella glandulifera seeds, anti-inflammatory mechanism, network pharmacology, rheumatoid arthritis, chronic obstructive pulmonary disease

摘要： 目的 运用网络药理学技术研究瘤果黑种草子抗炎作用机制。 方法 通过文献检索及 Swiss Target Prediction 数据库进行成分靶标预测;采用 OMIM、DrugBank、Genecard 数据库进行疾病靶标搜集,使用 Venny2. 1. 0分析共同靶标;构建蛋白互作网络,按照平均 degree 值筛选重要靶标;构建成分-共同靶标网络;对重要靶标进行基因本体和生物通路富集分析。 结果 收集到化合物 57 个,预测到药物和疾病的重要交互靶标 101 个。 生物功能富集得到细胞组分 111 条、分子功能 139 条,生物过程 2 104 条,信号通路 165 条。 细胞组分以膜成分为主,分子功能排名靠前的多为 G 蛋白偶联受体,生物过程涉及激酶、转移酶活性调控、MAPK 级联调控等。 通路富集到以 IL-6、STAT3 等为关键基因的 Th17 细胞分化通路,与瘤果黑种草子的抗炎机制密切相关。 结论 运用网络药理学分析技术,针对中药多组分、多靶标、多通路的特点,分析了瘤果黑种草子抗炎的潜在机制,为瘤果黑种草子的深入研究提供参考,然其核心靶标和具体的调控机制尚待进一步的实验验证。

关键词: 瘤果黑种草子, 抗炎机制, 网络药理学, 类风湿关节炎, 慢性阻塞性肺病