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一种基于通用基因表达特征的高通量抗炎药物发现策略。

A universal gene expression signature-based strategy for the high-throughput discovery of anti-inflammatory drugs.

作者信息

Feng Juan, Dang Honglei, Zhang Xiaoling, Huang Wenting, Ma Chengmei, Zhang Aixiang, Hao Mimi, Xie Lan

机构信息

Medical Systems Biology Research Center, School of Medicine, Tsinghua University, Beijing, 100084, China.

College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, 518118, China.

出版信息

Inflamm Res. 2025 Jan 7;74(1):2. doi: 10.1007/s00011-024-01968-4.

Abstract

BACKGROUND

Traditional Chinese medicine (TCM) is a valuable resource for drug discovery and has demonstrated excellent efficacy in treating inflammatory diseases. This study aimed to develop a universal gene signature-based strategy for high-throughput discovery of anti-inflammatory drugs, especially Traditional Chinese medicine (TCM).

METHODS

The disease gene signature of liposaccharide-stimulated THP-1 cells and drug gene signatures of 655 drug candidates were established via sequencing. Anti-inflammatory drugs were screened based on similarities between drug gene signatures and the reversed disease gene signature.

RESULTS

Through screening, 83 potential anti-inflammatory drugs were identified. The efficacy of the TCM formula Biyun Powder, along with individual TCMs, Centipedea Herba, Kaempferiae Rhizoma, and Schizonepetae Spica Carbonisata, was verified in vitro or in vivo. Mechanistically, they exerted anti-inflammatory effects by inhibiting the nuclear factor-kappa B pathway. Kaempferol and luteolin were identified as bioactive IκB kinase-β inhibitors in Kaempferiae Rhizoma and Schizonepetae Spica Carbonisata, respectively.

CONCLUSION

We developed a universal gene signature-based approach for the high-throughput discovery of anti-inflammatory drugs that is applicable to compounds and to TCM herbs/formulae and established a workflow (screening, validation of efficacy, and identification of the mechanism of action and bioactive compounds) that can serve as a research template for high-throughput drug research.

摘要

背景

中药是药物发现的宝贵资源,在治疗炎症性疾病方面已显示出卓越疗效。本研究旨在开发一种基于通用基因特征的策略,用于高通量发现抗炎药物,尤其是中药。

方法

通过测序建立脂多糖刺激的THP-1细胞的疾病基因特征和655种候选药物的药物基因特征。基于药物基因特征与反向疾病基因特征之间的相似性筛选抗炎药物。

结果

通过筛选,鉴定出83种潜在的抗炎药物。中药方剂碧云散以及单味中药蜈蚣、高良姜和荆芥穗炭的疗效在体外或体内得到验证。机制上,它们通过抑制核因子-κB通路发挥抗炎作用。槲皮素和木犀草素分别被鉴定为高良姜和荆芥穗炭中的生物活性IκB激酶-β抑制剂。

结论

我们开发了一种基于通用基因特征的方法,用于高通量发现抗炎药物,该方法适用于化合物以及中药草药/方剂,并建立了一个工作流程(筛选、疗效验证、作用机制和生物活性化合物鉴定),可作为高通量药物研究的研究模板。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4941/11703948/f2e99f2ede21/11_2024_1968_Fig1_HTML.jpg

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