目的 利用高效液相色谱-四极杆飞行时间串联质谱法（UPLC-Q-TOF-MS）分析丝穗金粟兰Chloranthus fortune水提物的主要成分，并结合网络药理学的方法对其抗炎镇痛药效物质及作用机制进行预测分析。方法 结合ChemSpider数据库、mzCloud平台及现有文献研究，对目标化合物二级质谱特征碎片离子进行比对确认，鉴定丝穗金粟兰水提物的化学成分；通过FAFDrug4数据库筛选丝穗金粟兰水提物的活性成分，运用Pharmmapper平台和Uniprot数据库预测丝穗金粟兰的成分靶点，GeneCards平台获得相关疾病靶点，利用Venny平台获得成分和疾病的交集靶点；通过String数据库和Cytoscape3.7.0软件构建蛋白质-蛋白质相互作用（protein-protein interaction，PPI）网络，并筛选核心靶点，利用David数据库对潜在的核心靶点进行基因本体（gene ontology，GO）功能和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）通路富集分析，并构建“活性成分-靶点-通路”网络。结果 从丝穗金粟兰水提物中共鉴定45个成分，包括有机酸类、黄酮类、香豆素类、倍半萜类、含氮类化合物；筛选出33种活性成分，活性成分与疾病交集靶点70个；通过PPI网络筛选出核心靶点13个；富集分析显示，丝穗金粟兰主要参与蛋白磷酸酶结合、胰岛素受体结合、蛋白激酶活性等功能，通过酪氨酸激酶受体信号通路、肿瘤坏死因子信号通路、酪氨酸激酶抑制剂耐药等通路抗炎镇痛。通过对“活性成分-靶点-通路”网络分析进一步得到5个关键靶点和8个关键活性成分。结论 通过结合UPLC-Q-TOF-MS和网络药理学的方法阐明了丝穗金粟兰是通过多成分、多靶点、多途径发挥抗炎镇痛的作用，为丝穗金粟兰的进一步质量评价及药理活性的研究提供参考。

Objective To analyze the main components of the aqueous extract of Chloranthus fortune by ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), and predict its anti-inflammatory and analgesic potent substances and mechanisms by combining network pharmacology methods. Methods Based on ChemSpider database, mzCloud platform and existing literature research, the secondary mass spectra of target compounds were compared and confirmed to identify the chemical composition of the aqueous extracts of C. fortune. The active ingredients of the aqueous extracts of C. fortune were screened by the FAFDrug4 database. The constituent targets of C. fortunewere predicted using the Pharmmapper platform and Uniprot database. The relevant disease targets were obtained using GeneCards platform, and the intersection targets of constituents and diseases were obtained using Venny platform. PPI network was constructed by using String database and Cytoscape 3.7.0 software, and the core targets were screened. Gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of potential core targets were performed by using David database, and “active ingredient-target-pathway” network was constructed.Results A total of 45 components, including organic acids, flavonoids, coumarins, sesquiterpenoids and nitrogen-containing compounds, were identified from the aqueous extracts of C. fortune. A total of 33 active components were screened and 70 active components and disease intersection targets were identified. A total of 13 core targets were screened through PPI network. Enrichment analysis showed that C. fortune mainly participated in protein phosphatase binding, insulin receptor binding, protein kinase activity and other functions, and presented the effects of resisting inflammation and pain through tyrosine kinase receptor signaling pathway, tumor necrosis factor signaling pathway, tyrosine kinase inhibitor resistance and other pathways. Five key targets and eight key active components were further obtained through the analysis of the “active ingredient-target-pathway” network. Conclusion By combining UPLC-Q-TOF-MS and network pharmacology, it is clarified that C. fortune plays an anti-inflammatory and analgesic role through multi-component, multi-target and multi-channel, which provides reference for further quality evaluation and pharmacological activity research of C. fortune.

R285.5

广西中医药大学“桂派杏林青年英才”培养项目（2022C032）；中药学广西一流学科（桂教科研[2018]12号）；壮瑶药协同创新中心（桂教科研[2013]20号）；广西壮瑶药重点实验室（桂科基字[2014]32号）；广西八桂学者中药创新理论与药效研究项目（J13162）；广西重点学科壮药学（桂教科研[2013]16号）；国家重点研发计划资助项目（2019YFC1712300）