解庚肝草汤改善溃疡性结肠炎：网络药理学和蛋白质组学相结合的综合方法，通过计算机和体内研究

IF 6.7 1区医学 Q1 CHEMISTRY, MEDICINAL

Phytomedicine Pub Date : 2025-06-11 DOI:10.1016/j.phymed.2025.156972

Ruipeng Shi , Sio I Chan , Haochun Jin , Wei Li , Lili Zhang , Jinglin Yang , Ruichen Wang , Xiaoting Zheng , Guozhen Cui , Zhangfeng Zhong

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引用次数: 0

摘要

背景溃疡性结肠炎（UC）是一种慢性结肠炎症，严重影响患者的生活质量。虽然目前的治疗方法可以缓解一些症状，但它们往往伴随着副作用和有限的长期疗效。解梗肝草汤是一种由桔梗和甘草组成的中药经典方剂，是一种副作用很小的潜在替代疗法。目的本研究旨在建立一种新的草药研究策略，以JGD为例，提高网络药理学的预测效率和准确性，利用大数据加速草药研究和开发。鉴于目前UC治疗的临床需求尚未得到满足，而JGD具有广阔的应用前景，本研究结合化学谱分析、网络药理学预测、蛋白质组学分析建立模型，探讨JGD治疗UC的作用机制。方法采用suhplc - q - exactive Orbitrap/MS法对黄芪皂苷及其血清代谢物进行化学成分分析。利用大数据和网络药理学预测靶点和通路。建立小鼠dss性结肠炎模型，每日口服1.85 mg/kg JGD。通过结肠长度检测、体重监测、疾病活动指数（DAI）评分和组织病理学评估来评估治疗结果。采用酶联免疫吸附试验（ELISA）、蛋白质组学、流式细胞术、western blotting等方法探讨JGD抗结肠炎作用的机制。结果采用UHPLC-Q-Exactive Orbitrap/MS对JGD的化学成分进行分析，鉴定出关键的生物活性成分。这些化合物使用大数据和网络药理学进行评估，包括四个数据源。化合物来源：草本：102，血清：21，综述：117，数据库：99。该整合产生了与基因、基因本体（GO）和京都基因与基因组百科全书（KEGG）途径相关的72个组合和864个数据集。JGD治疗通过改善体重、结肠长度、炎症反应和肠道屏障，显著减轻dss诱导的小鼠结肠炎。此外，蛋白质组学和western blotting实验证实，JGD减轻了dss诱导的SLC6A14和RAGE的下调蛋白水平。通过与RAGE和SLC6A14对接筛选JGD的成分，确定了甘草酸3- o -葡糖苷、山奈酚3- o -rutinoside、Glyasperin A是JGD抗结肠炎作用的主要药理物质。结论中药提取物数据与文献资料相结合可显著提高预测效率和准确性。结果强调了JGD在UC中的治疗潜力，证明了其调节关键炎症和代谢途径的能力。这种综合方法促进了对JGD潜在作用的理解，并支持网络药理学与大数据在草药研究和开发中的更广泛应用。

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Jiegeng Gancao Decoction Ameliorates Ulcerative Colitis: An Integrative Approach Combining Network Pharmacology and Proteomics via in silico and in vivo studies

Background

Ulcerative colitis (UC) is a chronic inflammatory condition of the colon that significantly affects the quality of life of patients. Although current treatments offer some relief, they are often accompanied by side effects and limited long-term efficacy. Jiegeng Gancao Decoction (JGD), a Chinese classical prescription composed of Platycodon and Licorice, are potential alternative treatments with minimal side effects.

Purpose

This present study aimed to establish a novel strategy for herbal medicine research, using JGD as a case study to improve the prediction efficiency and accuracy of network pharmacology and leveraging big data to accelerate herbal medicine research and development.

Study design

Given the unmet clinical needs in the treatment of UC and the promising potential of JGD, this study integrated chemical profiling, network pharmacology predictions, and proteomic analysis to establish a model to explore the therapeutic mechanisms of JGD for the treatment of UC.

Methods

UHPLC-Q-Exactive Orbitrap/MS was used to analyze the chemical components of JGD and its serum metabolites. Big data and network pharmacology were used to predict targets and pathways. A mouse model of DSS-induced colitis was established and were administered by JGD orally at 1.85 mg/kg daily. Therapeutic outcomes were evaluated through colon length detection, body weight monitoring, Disease Activity Index (DAI) scoring, and histopathological assessments. Enzyme-linked immunosorbent assay (ELISA), proteomics, flow cytometry, and western blotting were used to explore the underlying mechanism of the anti-colitis effects of JGD.

Results

The chemical composition of JGD was analyzed to identify key bioactive compounds using UHPLC-Q-Exactive Orbitrap/MS. These compounds were evaluated using big data and network pharmacology, incorporating four data sources. Compounds were sourced from Herb: 102, Serum: 21, Review: 117, and Database: 99. This integration generated 72 combos and 864 datasets related to the Gene, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. JGD treatment significantly attenuated DSS-induced colitis in mice by improving body weight, colon length, inflammatory response, and intestinal barrier. Furthermore, proteomics and western blotting experiments confirmed that JGD attenuated DSS-induced down-regulated protein levels of SLC6A14 and RAGE. By screening the components of JGD via docking with RAGE and SLC6A14, Glycyrrhetic acid 3-O-glucuronide, Kaempferol-3-O-rutinoside, and Glyasperin A were identified as the main pharmacological substances that underlie the anti-colitis effects of JGD.

Conclusion

Combining data from herb extracts and sources from the literature significantly improved prediction efficiency and accuracy. The results highlight the therapeutic potential of JGD in UC, demonstrating its ability to modulate key inflammatory and metabolic pathways. This integrative approach advances the understanding of the potential effects of JGD and supports the broader application of network pharmacology with big data in research and development of herbal medicine.

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来源期刊

Phytomedicine 医学-药学

CiteScore

10.30

自引率

5.10%

发文量

670

审稿时长

91 days

期刊介绍： Phytomedicine is a therapy-oriented journal that publishes innovative studies on the efficacy, safety, quality, and mechanisms of action of specified plant extracts, phytopharmaceuticals, and their isolated constituents. This includes clinical, pharmacological, pharmacokinetic, and toxicological studies of herbal medicinal products, preparations, and purified compounds with defined and consistent quality, ensuring reproducible pharmacological activity. Founded in 1994, Phytomedicine aims to focus and stimulate research in this field and establish internationally accepted scientific standards for pharmacological studies, proof of clinical efficacy, and safety of phytomedicines.