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采用 UPLC-Orbitrap Fusion MS 和网络药理学系统表征紫金牛属植物的有效成分及分子机制。

Systematic characterization of the effective constituents and molecular mechanisms of Ardisiae Japonicae Herba using UPLC-Orbitrap Fusion MS and network pharmacology.

机构信息

Academy of Chinese Medicine Sciences, Henan University of Chinese Medicine, Zhengzhou, Henan, China.

Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases co-constructed by Henan province & Education Ministry of P. R. China, Zhengzhou, Henan, China.

出版信息

PLoS One. 2022 Jun 15;17(6):e0269087. doi: 10.1371/journal.pone.0269087. eCollection 2022.

DOI:10.1371/journal.pone.0269087
PMID:35704651
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9200335/
Abstract

OBJECTIVE

Ardisiae Japonicae Herba (AJH), the dried whole herb of Ardisia japonica (Thunb.) Blume [Primulaceae], has been used in treating chronic obstructive pulmonary disease (COPD) in China. However, the material basis and molecular mechanisms of AJH against COPD remain unclear. Therefore, in this study, we attempt to establish a systematic approach to elucidate the material basis and molecular mechanisms through compound identification, network analysis, molecular docking, and experimental validation.

METHODS

Ultra-high performance liquid chromatography-Orbitrap Fusion mass spectrometry (UPLC-Orbitrap Fusion MS) was used to characterize the chemical compounds of AJH. The SwissTargetPrediction, String and Metascape databases were selected for network pharmacology analysis, including target prediction, protein-protein interaction (PPI) network analysis, GO and KEGG pathway enrichment analysis. Cytoscape 3.7.2 software was used to construct a component-target-pathway network to screen out the main active compounds. Autodock Vina software was used to verify the affinity between the key compounds and targets. TNF-α-stimulated A549 cell inflammation model was built to further verify the anti-inflammatory effects of active compounds.

RESULTS

Altogether, 236 compounds were identified in AJH, including 33 flavonoids, 21 Phenylpropanoids, 46 terpenes, 7 quinones, 27 steroids, 71 carboxylic acids and 31 other compounds. Among them, 41 compounds were selected as the key active constituents, which might exhibit therapeutic effects against COPD by modulating 65 corresponding targets primarily involved in inflammation/metabolism/immune-related pathways. The results of molecular docking showed that the key compounds could spontaneously bind to the receptor proteins with a strong binding ability. Finally, the anti-inflammatory effects of the three active compounds were validated with the decreased levels of Interleukin-6 (IL-6) and Matrix Metalloproteinase 9 (MMP9) in TNF-α-induced A549 cells model.

CONCLUSION

This study clarified that AJH may exert therapeutic actions for COPD via regulating inflammation/immune/metabolism-related pathways using UPLC-Orbitrap Fusion MS technology combined with network pharmacology for the first time. This study had a deeper exploration of the chemical components and pharmacological activities in AJH, which provided a reference for the further study and clinical application of AJH in the treatment of COPD.

摘要

目的

紫金牛(AJH)是紫金牛科紫金牛属植物紫金牛(Thunb.)Blume 的干燥全草,在中国用于治疗慢性阻塞性肺疾病(COPD)。然而,AJH 治疗 COPD 的物质基础和分子机制尚不清楚。因此,本研究试图通过化合物鉴定、网络分析、分子对接和实验验证,建立一种系统的方法来阐明其物质基础和分子机制。

方法

采用超高效液相色谱-轨道阱融合质谱(UPLC-Orbitrap Fusion MS)对 AJH 的化学成分进行表征。选择 SwissTargetPrediction、String 和 Metascape 数据库进行网络药理学分析,包括靶标预测、蛋白质-蛋白质相互作用(PPI)网络分析、GO 和 KEGG 通路富集分析。使用 Cytoscape 3.7.2 软件构建成分-靶标-通路网络,筛选出主要的活性化合物。使用 Autodock Vina 软件验证关键化合物与靶标的亲和力。建立 TNF-α 刺激的 A549 细胞炎症模型,进一步验证活性化合物的抗炎作用。

结果

共鉴定出 AJH 中的 236 种化合物,包括 33 种黄酮类化合物、21 种苯丙素类化合物、46 种萜类化合物、7 种醌类化合物、27 种甾体类化合物、71 种羧酸类化合物和 31 种其他化合物。其中,选择 41 种化合物作为关键活性成分,可能通过调节 65 个主要涉及炎症/代谢/免疫相关途径的对应靶标,对 COPD 发挥治疗作用。分子对接结果表明,关键化合物能够与受体蛋白自发结合,具有较强的结合能力。最后,通过降低 TNF-α 诱导的 A549 细胞模型中白细胞介素-6(IL-6)和基质金属蛋白酶 9(MMP9)的水平,验证了三种活性化合物的抗炎作用。

结论

本研究首次采用 UPLC-Orbitrap Fusion MS 技术结合网络药理学,阐明了 AJH 可能通过调节炎症/免疫/代谢相关途径对 COPD 发挥治疗作用。本研究对 AJH 的化学成分和药理活性进行了更深入的探讨,为 AJH 治疗 COPD 的进一步研究和临床应用提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/9845b7a03497/pone.0269087.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/ddf3f0128513/pone.0269087.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/f38c7753aa17/pone.0269087.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/1ab0a31a8285/pone.0269087.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/7efa1ba26ad4/pone.0269087.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/f51588b3d277/pone.0269087.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/1cf16f1791a5/pone.0269087.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/9845b7a03497/pone.0269087.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/ddf3f0128513/pone.0269087.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/f38c7753aa17/pone.0269087.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/1ab0a31a8285/pone.0269087.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/7efa1ba26ad4/pone.0269087.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/f51588b3d277/pone.0269087.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/1cf16f1791a5/pone.0269087.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0466/9200335/9845b7a03497/pone.0269087.g007.jpg

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