Li Jie, Wang Yi, Wang Rui, Wu Meng-Yu, Shan Jing, Zhang Ying-Chi, Xu Hai-Ming
School of Public Health and Management, Ningxia Medical University, Yinchuan, 750004, Ningxia, China.
The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, No. 1160, Shengli Street, Xingqing District, Yinchuan, Ningxia, China.
Heliyon. 2022 Aug 13;8(8):e10201. doi: 10.1016/j.heliyon.2022.e10201. eCollection 2022 Aug.
This study aims to screen the potential targets of tetrandrine (Tet) against pulmonary fibrosis (PF) based on network pharmacological analysis, molecular docking and experimental verification.
The network pharmacology methods were employed to predict targets, construct Tet-PF-intersection target-pathway networks, and screen the candidate targets. The molecular docking was performed using AutoDockTools1.5.6. TGF-β1-induced human lung adenocarcinoma A549 cells were used as an experimental verification model, taking dexamethasone (Dex) as the positive control, to verify the effects of Tet on the mRNA expression of the candidate targets.
Six candidate targets were predicted based on network pharmacology and molecular docking, namely , and . The experimental verification results showed that Dex and Tet presented quite different pharmacological effects. Specifically, compared with the model group, both Dex and Tet (5 μΜ) significantly increased the mRNA expression of and ( < 0.001). Dex up-regulated the mRNA expression of and , while Tet (1.25 μΜ) down-regulated ( < 0.001). Dex up-regulated the mRNA expression of , but Tet had no effect. Dex down-regulated mRNA expression, while Tet (5 μΜ) up-regulated ( < 0.01).
Combined with the results of theoretical calculation and experimental verification, and considering the roles of these targets in the pathogenesis of PF, Tet might antagonize PF by acting on and . The results of this study will provide scientific reference for the prevention and clinical diagnosis and treatment of PF.
本研究旨在基于网络药理学分析、分子对接和实验验证,筛选粉防己碱(Tet)抗肺纤维化(PF)的潜在靶点。
采用网络药理学方法预测靶点,构建Tet-PF交集靶点-通路网络,并筛选候选靶点。使用AutoDockTools1.5.6进行分子对接。以转化生长因子-β1(TGF-β1)诱导的人肺腺癌A549细胞作为实验验证模型,以地塞米松(Dex)作为阳性对照,验证Tet对候选靶点mRNA表达的影响。
基于网络药理学和分子对接预测出6个候选靶点,即 、 、 、 、 和 。实验验证结果表明,Dex和Tet呈现出截然不同的药理作用。具体而言,与模型组相比,Dex和Tet(5 μΜ)均显著增加了 和 的mRNA表达( < 0.001)。Dex上调了 和 的mRNA表达,而Tet(1.25 μΜ)下调了其表达( < 0.001)。Dex上调了 的mRNA表达,但Tet无此作用。Dex下调了 的mRNA表达,而Tet(5 μΜ)上调了其表达( < 0.01)。
结合理论计算和实验验证结果,并考虑这些靶点在PF发病机制中的作用,Tet可能通过作用于 和 来拮抗PF。本研究结果将为PF的预防及临床诊断和治疗提供科学参考。