综合网络药理学、代谢组学和分子对接分析,揭示槲皮素治疗高脂血症的机制。

IF 3.1 3区 医学 Q2 CHEMISTRY, ANALYTICAL
Tao Chen , Tongtong Wang , Yuanxiang Shi , Jun Deng , Xiao Yan , Chenbin Zhang , Xin Yin , Wen Liu
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引用次数: 0

摘要

高脂血症(HLP)是心血管疾病的重要诱因。槲皮素(QUE)是一种天然黄酮类化合物,具有多种生物活性,因其潜在的治疗效果而备受关注。然而,槲皮素对 HLP 影响的确切机制仍不清楚。本研究采用了超高效液相色谱-四极杆/静电场 Orbitrap 高分辨率质谱(UPLC-Q-Exactive-MS)代谢组学策略来获得代谢物图谱,并在数据分析后确定了潜在的生物标志物。利用网络药理学和药物亲和力反应靶点稳定性(DARTS)测定来探索QUE治疗HLP的潜在靶点。然后综合代谢组学和网络药理学的结果,确定了 QUE 治疗 HLP 的关键靶点和代谢途径。分子对接和实验验证证实了这些关键靶点。通过全面的数据库搜索,确定了 138 个与 QUE-HLP 相关的靶点。使用 STRING 构建了一个蛋白-蛋白相互作用(PPI)网络,并使用 Cytoscape 过滤了共享靶点。其中,AKT1、TNF、VEGFA、mTOR、SREBP1 和 SCD 成为潜在的治疗靶点。体外细胞实验验证了这些发现。此外,通过将网络药理学与代谢组学相结合,评估了 QUE 对 HLP 的作用机制,确定了对 HLP 治疗至关重要的两条代谢组学通路。DARTS 实验证实了 QUE 与 FASN、p-mTOR、SREBP1 和 p-AKT 的稳定结合。在用棕榈酸(PA)处理的 HepG2 细胞中,QUE 显著降低了 ACLY、ACACA、FASN 和 SCD 的 mRNA 表达(p < 0.05)。Western 印迹分析显示,PA 能明显增加 p-mTOR、SREBP1、FASN 和 p-AKT 的蛋白表达(p < 0.05)。总之,我们的研究为QUE对HLP的保护机制提供了新的见解,并为其在临床治疗中的潜在益处提供了有价值的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated network pharmacology, metabolomics and molecular docking analysis to reveal the mechanisms of quercetin in the treatment of hyperlipidemia
Hyperlipidemia (HLP) is a significant contributor to cardiovascular diseases. Quercetin (QUE), a naturally occurring flavonoid with diverse bioactivities, has garnered attention due to its potential therapeutic effects. However, the precise mechanisms underlying the effects of QUE on HLP remain unclear. In this study, an ultra-high-performance liquid chromatography-quadrupole/electrostatic field Orbitrap high-resolution mass spectrometry (UPLC-Q-Exactive-MS) metabolomics strategy was employed to obtain metabolite profiles, and potential biomarkers were identified following data analysis. Network pharmacology and Drug Affinity Responsive Target Stability (DARTS) assays were utilized to explore the potential targets of QUE for HLP treatment. The results of metabolomics and network pharmacology were then integrated to identify the key targets and metabolic pathways involved in the therapeutic action of the QUE against HLP. Molecular docking and experimental validation were performed to confirm these key targets. A comprehensive database search identified 138 QUE-HLP-related targets. A protein-protein interaction (PPI) network was constructed using STRING, and the shared targets were filtered with Cytoscape. Among these, AKT1, TNF, VEGFA, mTOR, SREBP1, and SCD emerged as potential therapeutic targets. These findings were validated using in vitro cell experiments. Additionally, the mechanism of action of QUE against HLP was evaluated by integrating network pharmacology with metabolomics, identifying two metabolomic pathways crucial to HLP treatment. DARTS experiments confirmed the stable binding of QUE to FASN, p-mTOR, SREBP1, and p-AKT. In HepG2 cells treated with palmitic acid (PA), QUE significantly reduced the mRNA expression of ACLY, ACACA, FASN, and SCD (p < 0.05). Western blot analysis revealed that PA significantly increased protein expression of p-mTOR, SREBP1, FASN, and p-AKT (p < 0.05). In summary, our study provides novel insights into the protective mechanisms of QUE against HLP and offers valuable information regarding its potential benefits in clinical treatment.
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来源期刊
CiteScore
6.70
自引率
5.90%
发文量
588
审稿时长
37 days
期刊介绍: This journal is an international medium directed towards the needs of academic, clinical, government and industrial analysis by publishing original research reports and critical reviews on pharmaceutical and biomedical analysis. It covers the interdisciplinary aspects of analysis in the pharmaceutical, biomedical and clinical sciences, including developments in analytical methodology, instrumentation, computation and interpretation. Submissions on novel applications focusing on drug purity and stability studies, pharmacokinetics, therapeutic monitoring, metabolic profiling; drug-related aspects of analytical biochemistry and forensic toxicology; quality assurance in the pharmaceutical industry are also welcome. Studies from areas of well established and poorly selective methods, such as UV-VIS spectrophotometry (including derivative and multi-wavelength measurements), basic electroanalytical (potentiometric, polarographic and voltammetric) methods, fluorimetry, flow-injection analysis, etc. are accepted for publication in exceptional cases only, if a unique and substantial advantage over presently known systems is demonstrated. The same applies to the assay of simple drug formulations by any kind of methods and the determination of drugs in biological samples based merely on spiked samples. Drug purity/stability studies should contain information on the structure elucidation of the impurities/degradants.
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