Wang Biting, Wu Zengrui, Wang Jiye, Li Weihua, Liu Guixia, Zhang Bo, Tang Yun
Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
Key Laboratory of Xinjiang Phytomedicine Resource and Utilization, Ministry of Education, School of Pharmacy, Shihezi University, Shihezi, 832002, China.
BMC Complement Med Ther. 2020 Oct 27;20(1):322. doi: 10.1186/s12906-020-03106-z.
Arnebia euchroma (A. euchroma) is a traditional Chinese medicine (TCM) used for the treatment of blood diseases including leukemia. In recent years, many studies have been conducted on the anti-tumor effect of shikonin and its derivatives, the major active components of A. euchroma. However, the underlying mechanism of action (MoA) for all the components of A. euchroma on leukemia has not been explored systematically.
In this study, we analyzed the MoA of A. euchroma on leukemia via network pharmacology approach. Firstly, the chemical components and their concentrations in A. euchroma as well as leukemia-related targets were collected. Next, we predicted compound-target interactions (CTIs) with our balanced substructure-drug-target network-based inference (bSDTNBI) method. The known and predicted targets of A. euchroma and leukemia-related targets were merged together to construct A. euchroma-leukemia protein-protein interactions (PPIs) network. Then, weighted compound-target bipartite network was constructed according to combination of eight central attributes with concentration information through Cytoscape. Additionally, molecular docking simulation was performed to calculate whether the components and predicted targets have interactions or not.
A total of 65 components of A. euchroma were obtained and 27 of them with concentration information, which were involved in 157 targets and 779 compound-target interactions (CTIs). Following the calculation of eight central attributes of targets in A. euchroma-leukemia PPI network, 37 targets with all central attributes greater than the median values were selected to construct the weighted compound-target bipartite network and do the KEGG pathway analysis. We found that A. euchroma candidate targets were significantly associated with several apoptosis and inflammation-related biological pathways, such as MAPK signaling, PI3K-Akt signaling, IL-17 signaling, and T cell receptor signaling pathways. Moreover, molecular docking simulation demonstrated that there were eight pairs of predicted CTIs had the strong binding free energy.
This study deciphered that the efficacy of A. euchroma in the treatment of leukemia might be attributed to 10 targets and 14 components, which were associated with inhibiting leukemia cell survival and inducing apoptosis, relieving inflammatory environment and inhibiting angiogenesis.
新疆紫草是一种用于治疗包括白血病在内的血液疾病的传统中药。近年来,针对新疆紫草的主要活性成分紫草素及其衍生物的抗肿瘤作用开展了许多研究。然而,新疆紫草所有成分对白血病的潜在作用机制尚未得到系统探究。
在本研究中,我们通过网络药理学方法分析新疆紫草对白血病的作用机制。首先,收集新疆紫草中的化学成分及其浓度以及白血病相关靶点。接下来,我们使用基于平衡子结构 - 药物 - 靶点网络的推断(bSDTNBI)方法预测化合物 - 靶点相互作用(CTIs)。将新疆紫草已知和预测的靶点与白血病相关靶点合并,构建新疆紫草 - 白血病蛋白质 - 蛋白质相互作用(PPIs)网络。然后,通过Cytoscape根据八个中心属性与浓度信息的组合构建加权化合物 - 靶点二分网络。此外,进行分子对接模拟以计算成分与预测靶点之间是否存在相互作用。
共获得65种新疆紫草成分,其中27种具有浓度信息,它们涉及157个靶点和779个化合物 - 靶点相互作用(CTIs)。计算新疆紫草 - 白血病PPI网络中靶点的八个中心属性后,选择所有中心属性大于中位数的37个靶点构建加权化合物 - 靶点二分网络并进行KEGG通路分析。我们发现新疆紫草候选靶点与几个凋亡和炎症相关的生物学途径显著相关,如MAPK信号通路、PI3K - Akt信号通路、IL - 17信号通路和T细胞受体信号通路。此外,分子对接模拟表明有八对预测的CTIs具有较强的结合自由能。
本研究表明,新疆紫草治疗白血病的疗效可能归因于10个靶点和14种成分,它们与抑制白血病细胞存活和诱导凋亡、缓解炎症环境以及抑制血管生成有关。