基于网络药理学-分子对接技术探讨泽泻 抗炎作用的分子机制

摘要：目的：应用网络药理学方法及分子对接技术,探讨泽泻发挥抗炎作用的活性成分及其对应靶点和相关通路。方法：通过TCMSP筛选出泽泻的活性成分,运用SwissTarget Prediction 数据库预测活性成分相关靶标,同时采用GeneCards数据库得到炎症相关靶点,再将获得的活性成分靶点和炎症靶点导入VENNY2.1得到药物治疗疾病的潜在靶点;再运用STRING数据库、Cytoscape3.7.1软件构建简化后的药物治疗疾病的靶蛋白互作图（PPI）并筛选关键靶点。利用DAVID数据库对关键靶点进行GO功能富集分析和KEGG信号通路分析,再用Cytoscape3.7.1软件构建“化合物-靶点-通路”图并筛选核心成分与核心靶点。最后运用AutoDock Vina和Pymol将核心成分与核心靶点进行分子对接。结果：获得10个药物活性成分,得到相关潜在靶点284个,疾病潜在靶点11414个,药物治疗疾病的相关靶点260个,有SRC、HSP90AA1、PIK3CA、MAPK1、AKT1、LCK、FYN、JAK1、PLCG1、JAK1等关键靶点58个;涉及PI3K-Akt信号通路、ErbB信号通路、FoxO信号通路等133条通路。结论：泽泻发挥抗炎的作用机制可能是一方面通过调控PIK3、AKT、m-TOR等相关蛋白,激活PI3K-Akt信号通路,从而抑制细胞凋亡;另一方面可能通过调控EGFR相关蛋白,介导ErbB信号通路,从而干预炎症细胞生长。本研究基于网络药理学方法和分子对接技术,阐释了泽泻通过多种成分、多靶点、多信号通路发挥抗炎作用与机制,为该药的进一步研究提供了有益参考和科学依据。

Study the Molecular Mechanism of Anti-Inflammatory Effects of Rhizoma Alismatis Based on Network Pharmacology-Molecular Docking

Abstract: Objective: Network pharmacology and molecular docking techniques were used to investigate the active components and their corresponding targets and related pathways. Method: The main active components of rhizoma alismatis were screened from the pharmacology database of traditional Chinese medicine system ( TCMSP ). The targets prediction of active components was made by SwissTarget Prediction database, and the inflammatory related targets were obtained by GeneCards database. Then the active ingredient targets and inflammatory targets were imported into VENNY2.1 to obtain the targets of drug therapy.Moreover, STRING database and Cytoscape3.7.1 software were used to construct a simplified target protein interaction map (PPI) for drug therapy and screen key targets. DAVID database was used to conduct GO functional enrichment analysis and KEGG signaling pathway analysis for key targets. Then Cytoscape3.7.1 software was used to construct the "compounds - targets - pathways" diagram and screen core components and core targets. Finally, AutoDock Vina and Pymol were used to conduct molecular docking between core components and core targets. Results: 10 active ingredients were collected, 284 related potential targets and 11414 disease potential targets were obtained, and 260 intersection targets were obtained through Venn diagram. The anti-inflammatory effect of purpura purpura mainly acts on 58 targets such as SRC, HSP90AA1, PIK3CA, MAPK1, AKT1, LCK, FYN, JAK1, PLCG1, JAK1, and 133 pathways including T cell receptor signaling pathway, PI3K-Akt signaling pathway, and FoxO signaling pathway. Conclusion: The anti-inflammatory mechanism of senna may be that on the one hand, it activates the PI3K-Akt signaling pathway by regulating PIK3, AKT, m-TOR and other related proteins, thus inhibiting cell apoptosis. On the other hand, ErbB-related proteins may mediate the ErbB signaling pathway to interfere with the growth of inflammatory cells. Based on the network pharmacology and molecular docking technology, the possible targets and signaling pathways of rhizoma alismatis in the treatment of inflammation were discussed, which provided a scientific basis for the study of the anti-inflammatory mechanism of rhizoma alismatis.