柏青曼抗痛风性关节炎机制的网络药理学研究及体内验证。

IF 1.6 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Qing-Xin Kong, Wei-Ping Xu, Cheng Fan, Bi-Lin Liu, Li-Ping Reng, Qiao Ruan
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引用次数: 0

摘要

目的:从茯苓中提取的茯苓多糖用于治疗痛风性关节炎(GA)已有数千年的历史,尽管其确切的作用和机制尚不清楚。在此,我们研究pachyman对GA的治疗作用并探讨其潜在机制。方法:采用网络药理学和实验方法,探讨茯苓多糖抗GA的作用机制。构建了痛风与肿痛风共享靶点的蛋白-蛋白相互作用网络。进一步阐明了pachyman对GA的作用和机制。随后,我们通过大鼠实验验证了预测的机制。结果:球髓球蛋白治疗GA主要与肿瘤坏死因子(TNF)、基质金属蛋白酶(MMP)、松弛因子信号通路有关。在实验验证中,发现球髓多糖可调节高尿酸血症大鼠IL-1β、TNF-α、TGF-β、超氧化物歧化酶和谷胱甘肽过氧化物酶的表达。结论:这些共同的发现表明,pachyman有望作为GA的替代治疗方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of the Mechanism of Pachyman against Gout Arthritis with Network Pharmacology Analysis and Verification In Vivo.

Purpose: Pachyman, derived from Poria cocos, has been used to treat gouty arthritis (GA) for thousands of years, although its precise role and mechanisms remain unclear. Herein, we investigate the therapeutic effects of pachyman on GA and explore their underlying mechanisms.

Methods: Network pharmacology and experimental methods were employed to investigate the therapeutic mechanisms of pachyman against GA. The protein-protein interaction network of shared targets between pachyman and gout was constructed. Furthermore, we elucidated the functions and mechanisms of pachyman against GA. Subsequently, we validated the predicted mechanisms from an experiment on rats.

Results: The treatment of GA with pachyman primarily related to tumor necrosis factor (TNF), matrix metalloproteinases (MMP), and relaxation factor signaling pathways. In the experimental validation, pachyman were found to regulate the expression of IL-1β, TNF-α, TGF-β, superoxide dismutase, and glutathione peroxidase of hyperuricemic rats.

Conclusion: These collective findings suggest that pachyman holds promise as an alternative treatment for GA.

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来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
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