丹参治疗口腔黏膜下纤维化的多靶点药理学机制：网络药理学方法。
Multi-target pharmacological mechanisms of Salvia miltiorrhiza against oral submucous fibrosis: A network pharmacology approach.
机构信息
Department of Oral Pathology, Peking University School and Hospital of Stomatology, National Center of Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health, NMPA Key Laboratory for Dental Materials, Beijing, 100081, People's Republic of China; Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, 100081, People's Republic of China.
Research Unit of Precision Pathologic Diagnosis in Tumors of the Oral and Maxillofacial Regions, Chinese Academy of Medical Sciences (2019RU034), Beijing, 100081, People's Republic of China; Central Laboratory, Peking University School and Hospital of Stomatology, Beijing, 100081, People's Republic of China.
出版信息
Arch Oral Biol. 2021 Jun;126:105131. doi: 10.1016/j.archoralbio.2021.105131. Epub 2021 Apr 19.
OBJECTIVES
The herb Salvia miltiorrhiza is used to treat oral submucous fibrosis (OSF); however, the mechanism underlying its efficacy has not been elucidated. As such, a network pharmacology-based approach was applied to investigate the potential mechanisms of Salvia miltiorrhiza against OSF.
MATERIALS AND METHODS
Potential targets of Salvia miltiorrhiza were collected by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine, and Swiss Target Prediction. Potential targets of OSF were collected from DisGeNET, GeneCards, and National Center for Biotechnology Information Gene database. Salvia miltiorrhiza against OSF targets protein-protein interaction and enrichment analyses network were constructed by Cytoscape and Metascape.
RESULTS
Twelve active ingredients from Salvia miltiorrhiza and 57 potential OSF-related targets were identified. The constructed network predicted seven potential key targets of Salvia miltiorrhiza for the treatment of OSF. Functional enrichment analysis showed that biological processes such as cellular response to drugs and pathways such as bladder cancer were mainly regulated by the Salvia miltiorrhiza active ingredient targets. Furthermore, the protein-protein interaction network demonstrated that the molecular complex detection components were mainly related to the ErbB signaling pathway, cancer pathways and IL-17 signaling.
CONCLUSIONS
A network approach was employed to document how Salvia miltiorrhiza active ingredients change various pathways against OSF. Salvia miltiorrhiza active ingredient targets against OSF involved CYP19A1, EGFR, PTPN11, ACHE, TERT, MAPK8 and PGR and were enriched in several signaling pathways.
目的
丹参被用于治疗口腔黏膜下纤维化（OSF）；然而，其疗效的机制尚未阐明。因此，应用网络药理学方法研究丹参治疗 OSF 的潜在机制。
材料与方法
通过中药系统药理学数据库与分析平台、中药分子机制生物信息学分析工具和瑞士靶向预测收集丹参的潜在靶点。通过 DisGeNET、GeneCards 和美国国立生物技术信息中心基因数据库收集 OSF 的潜在靶点。通过 Cytoscape 和 Metascape 构建丹参治疗 OSF 靶点蛋白-蛋白相互作用和富集分析网络。
结果
从丹参中鉴定出 12 种活性成分和 57 个潜在的 OSF 相关靶点。构建的网络预测了丹参治疗 OSF 的 7 个潜在关键靶点。功能富集分析表明，丹参活性成分靶点主要调节细胞对药物的反应等生物学过程和膀胱癌等途径。此外，蛋白质-蛋白质相互作用网络表明，分子复合物检测成分主要与 ErbB 信号通路、癌症途径和 IL-17 信号有关。
结论
采用网络方法记录丹参活性成分如何改变各种途径对 OSF 的作用。丹参治疗 OSF 的活性成分靶点涉及 CYP19A1、EGFR、PTPN11、ACHE、TERT、MAPK8 和 PGR，并富集在几个信号通路中。
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