Based on UHPLC-QE-MS, network pharmacology, and molecular dynamics simulation to explore the mechanism of Panax notoginseng in treating osteoarthritis

doi:10.12307/2025.330

Abstract

Abstract: BACKGROUND: Our previous research found that Panax notoginseng can repair the morphological structure of bone cells, which has a good application prospect in the treatment of osteoarthritis, but the specific mechanism of Panax notoginseng is still unclear.
OBJECTIVE: To identify the main components of Panax notoginseng using ultra-high performance liquid chromatography-Q exactive-mass spectrometry (UHPLC-QE-MS), and to explore the mechanism of Panax notoginseng in the treatment of osteoarthritis by combining network pharmacology, molecular docking and molecular dynamics simulation.
METHODS: After identifying the main components of Panax notoginseng by UHPLC-QE-MS technology, the active components were screened by TCMSP database, and the targets of active components were found by TCMSP and Uniprot database. Osteoarthritis targets were screened out through disease databases. After the intersection of drug targets and disease targets, the protein-protein interaction network was constructed by importing STRING database and Cytoscape software, and the “active ingredient-action target” network was constructed to screen key active ingredients. Then the key targets were enriched and analyzed, and the key active components and key targets were verified by molecular docking. Finally, the results with the lowest binding energy were selected for molecular dynamics simulation.
RESULTS AND CONCLUSION: A total of 57 active components were identified in the solution of Panax Notoginseng, including 50 intersection targets of components and disease targets, 5 key active components (quercetin, ursodeoxycholic acid, kaempferol, naringenin and erythrocyanine), and 5 key targets (interleukin 6, matrix metalloproteinase 9, interleukin 1β, albumin and recombinant chemokine c-motif ligand 2). Gene ontology enriched 642 entries, among which 620 entries represent biological processes, 21 entries represent molecular functions, and 1 entry represents cellular components. Kyoto encyclopedia of genes and genomes analysis indicated 63 pathways, mainly including estrogen signaling pathway, interleukin 17 signaling pathway and hyperglycosylation end product-hyperglycosylation end product receptor signaling pathway. Molecular docking showed good binding activity of key active components and key targets. Molecular dynamics simulation indicated that the stable interaction between quercetin and matrix metalloproteinase 9. The composition of Panax notoginseng was comprehensively studied, and the material basis of its efficacy was preliminarily clarified. It was predicted that Panax notoginseng could play an anti-inflammatory, cartilage-protective, and immunomodulatory role in treating osteoarthritis through multiple components, targets, approaches and pathways.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: Panax notoginseng, osteoarthritis, molecular dynamics simulation, mass spectrometry, molecular docking, network pharmacology

CLC Number:

Chen Yueping, Chen Feng, Peng Qinglin, Chen Huiyi, Dong Panfeng . Based on UHPLC-QE-MS, network pharmacology, and molecular dynamics simulation to explore the mechanism of Panax notoginseng in treating osteoarthritis[J]. Chinese Journal of Tissue Engineering Research, 2025, 29(8): 1751-1760.

Figures/Tables 13

2.1 三七主要成分的获取根据质谱检测结果，获得三七溶液在正离子(图1A)和负离子(图1B)全扫描模式下的总离子色谱图。通过质谱碎片检测得到大量的质谱峰，将其理论值与实测值进行比对，计算相对误差后共鉴别出2 042个主要成分。 2.2 三七活性成分靶点和骨关节炎靶点的预测将2 042个主要成分导入TCMSP数据库，剔除1 985个不符合条件的成分后，共筛选出57个活性成分，见表1。整合57个活性成分对应的靶标蛋白后，运用Uniprot数据库查询靶蛋白对应的基因名，共得到329个活性成分靶点。合并GeneCard、OMIM、TTD和PharmGKB数据库中获得的靶点，去重得到306个骨关节炎相关靶基因(图2A)。再通过构建Venn图预测“三七-骨关节炎”共有靶点，结果显示三七对应的329个靶基因与骨关节炎相关的306个靶基因相互映射，得到共有靶点50个(图2B)。 2.3 蛋白互作网络分析及 “活性成分-作用靶点”网络构建将获得的50个共有靶点导入STRING数据库，得到蛋白互作网络，再利用 Cytoscape软件对蛋白互作网络进行可视化分析(图3)。图中共涉及49个节点、687条边，根据度值筛选出排名前5的蛋白基因为白细胞介素6、基质金属蛋白酶9、白细胞介素1β、白蛋白和趋化因子配体2，这些蛋白基因在整个网络中发挥着关键的作用，可能是三七治疗骨关节炎的关键靶点，其基本信息见表2。将活性成分与共有靶点间的作用关系导入Cytoscape软件，构建三七治疗骨关节炎的“活性成分-作用靶点”网络(图4)，该网络中度值排名前5的活性成分分别是槲皮素、熊脱氧胆酸、山奈酚、柚皮素和红藻氨酸，为该网络的关键活性成分，对治疗骨关节炎具有重要的意义。 2.4 富集分析在GO富集分析关键靶点的功能过程中，共确定642个条目，其中620个条目代表生物过程，主要涉及神经炎症反应的调节、细胞对白细胞介素1的反应、CD4阳性α-βT细胞细胞因子产生和细胞对脂多糖的反应等方面；1个条目代表细胞成分，涉及内质网腔；21个条目代表分子功能，主要涉及细胞因子活性、细胞因子受体结合、受体配体活性和生长因子受体结合。GO分析结果得出的"

模拟，根据对接结果绘制结合能热图，见图6，若结合能≤-21 kJ/mol说明两者有较好结合活性[13]。研究所得结果均<-21 kJ/mol，说明关键活性成分和关键靶点具有较好的结合活性。选取结合能最低的槲皮素和基质金属蛋白酶9进行分子对接展示，见图7。 2.6 分子动力学模拟使用分子动力学技术模拟槲皮素和基质金属蛋白酶9复合物的稳定性和灵活性，评估二者的相互作用。均方根偏差是评估蛋白质结构变化的指标，此次模拟计算了槲皮素和基质金属蛋白酶9之间的均方根偏差值(图8A)，在时间为100 ns的模拟过程中，槲皮素和基质金属蛋白酶9之间的均方根偏差值较大，之后逐渐趋于平稳，整体来看均方根偏差值维持在一个较小的范围内(< 0.6)，说明槲皮素和基质金属蛋白酶9的结合比较稳定。均方根波动是评估蛋白质动态性的指标，此次模拟计算了槲皮素和基质金属蛋白酶9之间的均方根波动值(图8B)，基质金属蛋白酶9的均方根波动值在结合部分较小，而在非结合部分较大，说明槲皮素能够使基质金属蛋白酶9的结构域柔性更大、更容易产生构象的改变。旋转半径是评估蛋白质整体紧凑程度的指标，此次模拟计算了槲皮素和基质金属蛋白酶9之间的旋转半径(图8C)，结果显示槲皮素和基质金属蛋白酶9结合后的旋转半径相较于未结合前有所下降，说明槲皮素的结合使基质金属蛋白酶9更加紧凑。溶剂可及表面积是评估蛋白质表面积的指标，此次模拟计算了槲皮素和基质金属蛋白酶9之间的溶剂可及表面积(图8D)，结果显示在槲皮素和基质金属蛋白酶9结合之前，基质金属蛋白酶9的溶剂可及表面积较大，而在结合后则有所下降，说明槲皮素的结合使得基质金属蛋白酶9表面积减小。此次模拟计算了槲皮素和基质金属蛋白酶9之间的氢键(图8E)，结果显示，"

References

[1] MOTTA F, BARONE E, SICA A, et al. Inflammaging and Osteoarthritis. Clin Rev Allergy Immunol. 2023;64(2):222-238.
[2] ROEMER FW, WIRTH W, DEMEHRI S, et al. Imaging Biomarkers of Osteoarthritis. Semin Musculoskelet Radiol. 2024;28(1):14-25.
[3] WEN C, XIAO G. Advances in osteoarthritis research in 2021 and beyond. J Orthop Translat. 2022;32:A1-A2.
[4] 李辉,谢兴文,赵永利,等.中药有效成分防治骨关节炎的作用机制研究进展[J].中草药,2022,53(23):7543-7552.
[5] GUO D, YU M, GUO H, et al. Panax notoginseng saponins inhibits oxidative stress- induced human nucleus pulposus cell apoptosis and delays disc degeneration in vivo and in vitro. J Ethnopharmacol. 2024; 319(Pt 1):117166.
[6] JU L, HU P, CHEN P, et al. Huoxuezhitong capsule ameliorates MIA-induced osteoarthritis of rats through suppressing PI3K/ Akt/ NF-κB pathway. Biomed Pharmacother. 2020;129:110471.
[7] 韩杰,陈跃平,莫坚,等.三七总皂苷干预激素性股骨头缺血坏死模型兔的超微结构评价[J].中国组织工程研究,2019, 23(7):1035-1039.
[8] ZHANG Y, CAI W, HAN G, et al. Panax notoginseng saponins prevent senescence and inhibit apoptosis by regulating the PI3K‑AKT‑mTOR pathway in osteoarthritic chondrocytes. Int J Mol Med. 2020;45(4):1225-1236.
[9] FANG C, GUO JW, WANG YJ, et al. Diterbutyl phthalate attenuates osteoarthritis in ACLT mice via suppressing ERK/c-fos/NFATc1 pathway, and subsequently inhibiting subchondral osteoclast fusion. Acta Pharmacol Sin. 2022;43(5):1299-1310.
[10] MEIMEI C, FENGZHEN W, HUANGWEI L, et al. Discovery of Taxus chinensis fruit wine as potentially functional food against Alzheimer’s disease by UHPLC-QE-MS/MS, network pharmacology and molecular docking. J Food Biochem. 2022; 46(12):e14502.
[11] 牛明,张斯琴,张博,等.《网络药理学评价方法指南》解读[J].中草药,2021, 52(14):4119-4129.
[12] HU X, ZENG Z, ZHANG J, et al. Molecular dynamics simulation of the interaction of food proteins with small molecules. Food Chem. 2023;405(Pt A):134824.
[13] WANG Y, TAO X, GAO Y, et al. Study on the mechanism of Shujin Tongluo granules in treating cervical spondylosis based on network pharmacology and molecular docking. Medicine (Baltimore). 2023;102(29):e34030.
[14] TSAI CF, CHEN GW, CHEN YC, et al. Regulatory Effects of Quercetin on M1/M2 Macrophage Polarization and Oxidative/Antioxidative Balance. Nutrients. 2021;14(1):67.
[15] WANG L, HE C. Nrf2-mediated anti-inflammatory polarization of macrophages as therapeutic targets for osteoarthritis. Front Immunol. 2022;13:967193.
[16] SUL OJ, RA SW. Quercetin Prevents LPS-Induced Oxidative Stress and Inflammation by Modulating NOX2/ROS/NF-kB in Lung Epithelial Cells. Molecules. 2021;26(22):6949.
[17] CHEN Y, XUE Y, WANG X, et al. Molecular mechanisms of the Guizhi decoction on osteoarthritis based on an integrated network pharmacology and RNA sequencing approach with experimental validation. Front Genet. 2023;14:1079631.
[18] MOON SJ, JEONG JH, JHUN JY, et al. Ursodeoxycholic Acid ameliorates pain severity and cartilage degeneration in monosodium iodoacetate-induced osteoarthritis in rats. Immune Netw. 2014; 14(1):45-53.
[19] ORŠOLIĆ N, NEMRAVA J, JELEČ Ž, et al. Antioxidative and Anti-Inflammatory Activities of Chrysin and Naringenin in a Drug-Induced Bone Loss Model in Rats. Int J Mol Sci. 2022;23(5):2872.
[20] 谭丹妮,向琴,俞赟丰,等.白虎加人参汤治疗肥胖症合并2型糖尿病的潜在活性成分及作用机制分析[J].中国实验方剂学杂志,2024,30(13):1-10.
[21] DAINESE P, WYNGAERT KV, DE MITS S, et al. Association between knee inflammation and knee pain in patients with knee osteoarthritis: a systematic review. Osteoarthritis Cartilage. 2022;30(4):516-534.
[22] YU H, HUANG T, LU WW, et al. Osteoarthritis Pain. Int J Mol Sci. 2022;23(9):4642.
[23] HU X, NI S, ZHAO K, et al. Bioinformatics-Led Discovery of Osteoarthritis Biomarkers and Inflammatory Infiltrates. Front Immunol. 2022;13:871008.
[24] SHANG L, WANG Y, LI J, et al. Mechanism of Sijunzi Decoction in the treatment of colorectal cancer based on network pharmacology and experimental validation. J Ethnopharmacol. 2023;302(Pt A):115876.
[25] ZHANG J, FAN F, LIU A, et al. Icariin: A Potential Molecule for Treatment of Knee Osteoarthritis. Front Pharmacol. 2022;13: 811808.
[26] LI M, TIAN F, GUO J, et al. Therapeutic potential of Coptis chinensis for arthritis with underlying mechanisms. Front Pharmacol. 2023;14:1243820.
[27] WANG Y, PAN X, WANG J, et al. Exploration of Simiao-Yongan Decoction on knee osteoarthritis based on network pharmacology and molecular docking. Medicine (Baltimore). 2023; 102(40):e35193.
[28] TANG J, LIU T, WEN X, et al. Estrogen-related receptors: novel potential regulators of osteoarthritis pathogenesis. Mol Med. 2021;27(1):5.
[29] JIANG A, XU P, YANG Z, et al. Increased Sparc release from subchondral osteoblasts promotes articular chondrocyte degeneration under estrogen withdrawal. Osteoarthritis Cartilage. 2023;31(1):26-38.
[30] NI KN, YE L, ZHANG YJ, et al. Formononetin improves the inflammatory response and bone destruction in knee joint lesions by regulating the NF-kB and MAPK signaling pathways. Phytother Res. 2023;37(8):3363-3379.
[31] LIU Y, PENG H, MENG Z, et al. Correlation of IL-17 Level in Synovia and Severity of Knee Osteoarthritis. Med Sci Monit. 2015;21:1732-1736.
[32] ZHI X, WANG L, CHEN H, et al. l-tetrahydropalmatine suppresses osteoclastogenesis in vivo and in vitro via blocking RANK-TRAF6 interactions and inhibiting NF-κB and MAPK pathways. J Cell Mol Med. 2020;24(1):785-798.
[33] YANG S, XIE J, PAN Z, et al. Advanced glycation end products promote meniscal calcification by activating the mTOR-ATF4 positive feedback loop. Exp Mol Med. 2024; 56(3):630-645.
[34] YUAN Z, JIANG D, YANG M, et al. Emerging Roles of Macrophage Polarization in Osteoarthritis: Mechanisms and Therapeutic Strategies. Orthop Surg. 2024;16(3):532-550.
[35] WU X, XU LY, LI EM, et al. Application of molecular dynamics simulation in biomedicine. Chem Biol Drug Des. 2022; 99(5):789-800.
[36] LU C, PENG X, LU D. Molecular Dynamics Simulation of Protein Cages. Methods Mol Biol. 2023;2671:273-305.