Xiaoyue Shen, Yanbin Li
Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China.
Biofactors. 2022 Jan;48(1):228-238. doi: 10.1002/biof.1812. Epub 2021 Dec 18.
We aimed to investigate the target and signal pathway of Smilacis Glabrae Rhixoma (SGR) in the treatment of myasthenia gravis (MG) based on network pharmacology, and to explore its potential molecular mechanism. The main active components of SGR were searched in the pharmacology database of traditional Chinese medicine systems, and analysis platform. The related targets of SGR were obtained by Genecards, connective tissue disease, therapeutic target database, Drugbank, and Online Mendelian Inheritance in Man database. Moreover, the target information was corrected through UniProtKB and also, this data integrated to draw the "Ingredients-targets" network of SGR. Protein interaction analysis was performed in data platform, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways as well as enrichment analysis on disease-drug target was carried out through metascape online platform. A total of 15 active components were collected from SGR, which correspond to 159 targets; There were 1758 MG-related targets; there are 81 targets related to both drug components and diseases, including 12 key targets. In GO bioaccumulation analysis, 1933 GO items were gathered, which were mainly related to the metabolism of active oxygen species and the active factors of postsynaptic neurotransmitter receptor. According to KEGG analysis, SGR may play a role in the treatment of MG through phosphatidylinositol-3-kinase-protein kinase B signaling pathway, T-cell receptor, cAMP, tumor necrosis factor (TNF), and interleukin-17 (IL-17) signaling pathway, Th17 cell differentiation, endocrine resistance, hepatitis, and some cancer pathways. This study shows that SGR mainly treat myasthenia gravis through the regulation of TNF, MAPK1, JUN, TP53 and other targets, T-cell receptor, TNF, and IL-17 signaling pathway, Th17 cell differentiation and other pathways, which reflects the characteristics of multicomponent, multitarget, and multichannel of traditional Chinese medicine, and providing a certain pharmacological basis for the follow-up study.
我们旨在基于网络药理学研究土茯苓治疗重症肌无力（MG）的靶点和信号通路，并探索其潜在分子机制。在中药系统药理学数据库及分析平台中检索土茯苓的主要活性成分。通过Genecards、结缔组织病、治疗靶点数据库、Drugbank及人类孟德尔遗传在线数据库获取土茯苓的相关靶点。此外，通过UniProtKB对靶点信息进行校正，并整合这些数据绘制土茯苓的“成分-靶点”网络。在数据平台进行蛋白质相互作用分析、基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析，并通过metascape在线平台对疾病-药物靶点进行富集分析。共从土茯苓中收集到15种活性成分，对应159个靶点；有1758个MG相关靶点；有81个靶点与药物成分和疾病均相关，其中包括12个关键靶点。在GO生物富集分析中，共收集到1933个GO条目，主要与活性氧代谢及突触后神经递质受体的活性因子相关。根据KEGG分析，土茯苓可能通过磷脂酰肌醇-3-激酶-蛋白激酶B信号通路、T细胞受体、环磷酸腺苷（cAMP）、肿瘤坏死因子（TNF）和白细胞介素-17（IL-17）信号通路、Th17细胞分化、内分泌抵抗、肝炎及一些癌症通路在MG治疗中发挥作用。本研究表明，土茯苓主要通过调节TNF、丝裂原活化蛋白激酶1（MAPK1）、原癌基因蛋白（JUN）、肿瘤蛋白p53（TP53）等靶点、T细胞受体、TNF和IL-17信号通路、Th17细胞分化等通路治疗重症肌无力，体现了中药多成分、多靶点、多途径的特点，为后续研究提供了一定的药理学依据。
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