Du Xiao, Zhao Chunhui, Xi Yujie, Lin Pengfei, Liu Huihui, Wang Shuling, Guo Feifei
State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
College of Pharmacy, School of Medicine, Hangzhou Normal University, Hangzhou, China.
Front Pharmacol. 2024 Sep 17;15:1440542. doi: 10.3389/fphar.2024.1440542. eCollection 2024.
Having multiple pharmacological effects is a characteristic of Traditional Chinese Medicine (TCM). Currently, there is a lack of suitable methods to explore and discover modern diseases suitable for TCM treatment using this characteristic. Unsupervised machine learning technology is an efficient strategy to predict the pharmacological activity of drugs. This study takes Yuxuebi Tablet (YXB) as the research object. Using the unsupervised machine learning technology of drug cell functional fingerprint similarity research, the potential pharmacological effects of YXB were discovered and verified.
LC-MS combined with the intestinal absorption method was used to identify components of YXB that could be absorbed by the intestinal tract of rats. Unsupervised learning hierarchical clustering was used to calculate the degree of similarity of cellular functional fingerprints between these components and 121 marketed Western drugs whose indications are diseases and symptoms that YXB is commonly used to treat. Then, based on the Library of Integrated Network-based Cellular Signatures database, pathway analysis was performed for selected Western drugs with high similarity in cellular functional fingerprints with the components of YXB to discover the potential pharmacological effects of YXB, which were validated by animal experiments.
We identified 40 intestinally absorbed components of YXB. Through predictive studies, we found that they have pharmacological effects very similar to non-steroidal anti-inflammatory drugs (NSAIDs) and corticosteroids. In addition, we found that they have very similar pharmacological effects to anti-neuropathic pain medications (such as gabapentin, duloxetine, and pethidine) and may inhibit the NF-κB signaling pathway and biological processes related to pain perception. Therefore, YXB may have an antinociceptive effect on neuropathic pain. Finally, we demonstrated that YXB significantly reduced neuropathic pain in a rat model of sciatic nerve chronic constriction injury (CCI). Transcriptome analysis further revealed that YXB regulates the expression of multiple genes involved in nerve injury repair, signal transduction, ion channels, and inflammatory response, with key regulatory targets including Sgk1, Sst, Isl1, and Shh.
This study successfully identified and confirmed the previously unknown pharmacological activity of YXB against neuropathic pain through unsupervised learning prediction and experimental verification.
具有多种药理作用是中药的一个特点。目前,缺乏利用这一特点探索和发现适合中药治疗的现代疾病的合适方法。无监督机器学习技术是预测药物药理活性的一种有效策略。本研究以瘀血痹片(YXB)为研究对象。利用药物细胞功能指纹相似性研究的无监督机器学习技术,发现并验证了YXB的潜在药理作用。
采用液相色谱-质谱联用结合肠道吸收法,鉴定YXB中可被大鼠肠道吸收的成分。采用无监督学习层次聚类法,计算这些成分与121种已上市西药的细胞功能指纹相似度,这些西药的适应症是YXB常用治疗的疾病和症状。然后,基于基于综合网络的细胞特征库数据库,对与YXB成分在细胞功能指纹上具有高度相似性的选定西药进行通路分析,以发现YXB的潜在药理作用,并通过动物实验进行验证。
我们鉴定出YXB的40种肠道吸收成分。通过预测研究,我们发现它们具有与非甾体抗炎药(NSAIDs)和皮质类固醇非常相似的药理作用。此外,我们发现它们与抗神经性疼痛药物(如加巴喷丁、度洛西汀和哌替啶)具有非常相似的药理作用,并且可能抑制NF-κB信号通路和与疼痛感知相关的生物学过程。因此,YXB可能对神经性疼痛具有镇痛作用。最后,我们证明YXB在坐骨神经慢性压迫损伤(CCI)大鼠模型中显著减轻了神经性疼痛。转录组分析进一步揭示,YXB调节多个参与神经损伤修复?信号转导?离子通道和炎症反应的基因的表达,关键调控靶点包括Sgk1?Sst?Isl1和Shh。
本研究通过无监督学习预测和实验验证,成功鉴定并证实了YXB对神经性疼痛具有此前未知的药理活性。