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中国精品科技期刊2020
聂丽媛,范三红,曹林旭,等. 基于UPLC-Q-TOF-MS技术以及网络药理学分析山西陈醋的小分子肽类成分及潜在作用机制[J]. 食品工业科技,2024,45(18):31−41. doi: 10.13386/j.issn1002-0306.2023100274.
引用本文: 聂丽媛,范三红,曹林旭,等. 基于UPLC-Q-TOF-MS技术以及网络药理学分析山西陈醋的小分子肽类成分及潜在作用机制[J]. 食品工业科技,2024,45(18):31−41. doi: 10.13386/j.issn1002-0306.2023100274.
NIE Liyuan, FAN Sanhong, CAO Linxu, et al. Small Molecule Peptide and the Potential Mechanism of Shanxi Vinegar Based on UPLC-Q-TOF-MS Technology and Network Pharmacology[J]. Science and Technology of Food Industry, 2024, 45(18): 31−41. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023100274.
Citation: NIE Liyuan, FAN Sanhong, CAO Linxu, et al. Small Molecule Peptide and the Potential Mechanism of Shanxi Vinegar Based on UPLC-Q-TOF-MS Technology and Network Pharmacology[J]. Science and Technology of Food Industry, 2024, 45(18): 31−41. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023100274.

基于UPLC-Q-TOF-MS技术以及网络药理学分析山西陈醋的小分子肽类成分及潜在作用机制

Small Molecule Peptide and the Potential Mechanism of Shanxi Vinegar Based on UPLC-Q-TOF-MS Technology and Network Pharmacology

  • 摘要: 目的:明确山西陈醋中的小分子肽类化学成分,并进一步探讨其针对心血管等疾病的潜在作用机制。方法:采用超高效液相色谱-四极杆-飞行时间串联质谱(UPLC-Q-TOF-MS)技术结合GNPS分子网络技术分析山西陈醋中的小分子肽类成分。运用Genecards、Drugbank 5.0、DAVID等数据库对小分子肽类化合物靶点及通路进行分析,并通过Cytoscape软件构建“成分-靶点-信号通路-疾病”网络。使用Autodock Dock 1.5.6和PyMol 2.5.5进行山西陈醋核心靶点与关键成分的分子对接。结果:共鉴定出41个小分子肽类化合物,其中包括27个环二肽、10个直链二肽和4个三肽类化合物。其发挥心血管和肥胖等保健作用的“成分-靶点-信号通路-疾病”网络包含14个活性成分和109个药物靶点。通路富集分析得到59条信号通路。分子对接结果表明Cyclo(Leu-Pro)、Val-Val、Pro-Phe、Cyclo(His-Pro)等成分可能与核心靶点F2、MAPK1,MMP9、VCAM1等具有较好的结合能力,初步验证了网络药理学预测结果的准确性。结论:山西陈醋可能通过多成分、多靶点、多通路协同发挥预防调节心血管疾病和肥胖等疾病的保健作用。

     

    Abstract: Objective: To elucidate the small molecule peptides in Shanxi vinegar and further explore their potential mechanism of action against cardiovascular and other related diseases. Methods: The small molecule peptides of Shanxi vinegar were analyzed using ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS/MS). The targets and pathways of small molecule peptides were predicted via Genecards, Drugbank 5.0, DAVID, and other databases. The "component-target-signaling pathway-disease" network was constructed using Cytoscape software. Autodock Dock 1.5.6 and Pymol 2.2.0 were used to perform molecular docking between the core targets of Shanxi vinegar and the components. Results: A total of 41 small molecule peptide compounds were identified by UPLC-Q-TOF-MS/MS, which including 27 cyclic dipeptides, 10 linear dipeptides, and 4 tripeptides. The "component-target-signaling pathway-disease" network, contributing to the health-promoting effects on cardiovascular and obesity, encompasses 14 active components and 109 drug targets. A total of 59 pathways were identified by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Molecular docking results demonstrated favorable binding interactions between the core targets (F2, MAPK1, MMP9, VCAM1) and the corresponding active components Cyclo (Leu-Pro), Val-Val, Pro-Phe, Cyclo (His-Pro) in Shanxi vinegar, which preliminarily confirming the accuracy of the network pharmacology prediction. Conclusion: Shanxi vinegar might prevent and regulate cardiovascular diseases and obesity through multiple components, targets and pathways.

     

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