文献类型：期刊文献

英文题名：Insights into the mechanism of Arnebia euchroma on leukemia via network pharmacology approach

作者：Wang, Biting[1];Wu, Zengrui[1];Wang, Jiye[1];Li, Weihua[1];Liu, Guixia[1];Zhang, Bo[2];Tang, Yun[1]

机构：[1]East China Univ Sci & Technol, Sch Pharm, Shanghai Key Lab New Drug Design, Shanghai 200237, Peoples R China;[2]Shihezi Univ, Sch Pharm, Key Lab Xinjiang Phytomed Resource & Utilizat, Minist Educ, Shihezi 832002, Peoples R China

年份：2020

卷号：20

期号：1

外文期刊名：BMC COMPLEMENTARY MEDICINE AND THERAPIES

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000588487200001)】；

基金：This work was supported by the National Natural Science Foundation of China (Grants U1603122 and 81673356) and the 111 Project (Grant BP0719034).

语种：英文

外文关键词：Arnebia euchroma; Concentration; Leukemia; Traditional Chinese medicine; Network pharmacology; Weighted network

摘要：Background 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. Methods 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. Results 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. Conclusions 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.