Molecular Diversity ( IF 3.8 ) Pub Date : 2020-07-16 , DOI: 10.1007/s11030-020-10124-z Teng Wang 1 , Chun-Yi Lyu 1 , Yue-Hua Jiang 2 , Xue-Yan Dong 3 , Yan Wang 3 , Zong-Hong Li 1 , Jin-Xin Wang 1 , Rui-Rong Xu 3
Abstract
A poor prognosis, relapse and resistance are burning issues during adverse-risk acute myeloid leukaemia (AML) treatment. As a natural medicine, Scutellaria barbata D. Don (SBD) has shown impressive antitumour activity in various cancers. Thus, SBD may become a potential drug in adverse-risk AML treatment. This study aimed to screen the key targets of SBD in adverse-risk AML using the drug–biomarker interaction model through bioinformatics and network pharmacology methods. First, the adverse-risk AML-related critical biomarkers and targets of SBD active ingredient were obtained from The Cancer Genome Atlas database and several pharmacophore matching databases. Next, the protein–protein interaction network was constructed, and topological analysis and pathway enrichment were used to screen key targets and main pathways of intervention of SBD in adverse-risk AML. Finally, molecular docking was implemented for key target verification. The results suggest that luteolin and quercetin are the main active components of SBD against adverse-risk AML, and affected drug resistance, apoptosis, immune regulation and angiogenesis through the core targets AKT1, MAPK1, IL6, EGFR, SRC, VEGFA and TP53. We hope the proposed drug–biomarker interaction model provides an effective strategy for the research and development of antitumour drugs.
Graphic abstract
中文翻译:
预测黄芩 D. Don 在不良风险急性髓系白血病中关键靶点的药物-生物标志物相互作用模型。
摘要
不良风险的急性髓性白血病 (AML) 治疗期间,预后不良、复发和耐药性是紧迫的问题。作为一种天然药物,半枝莲D. Don (SBD) 在各种癌症中显示出令人印象深刻的抗肿瘤活性。因此,SBD 可能成为不良风险 AML 治疗的潜在药物。本研究旨在通过生物信息学和网络药理学方法,利用药物-生物标志物相互作用模型筛选不良风险 AML 中 SBD 的关键靶点。首先,从癌症基因组图谱数据库和几个药效团匹配数据库中获得与不良风险 AML 相关的关键生物标志物和 SBD 活性成分的靶标。其次,构建蛋白质-蛋白质相互作用网络,通过拓扑分析和通路富集筛选SBD干预不良风险AML的关键靶点和主要通路。最后,对关键靶点进行分子对接验证。结果表明,木犀草素和槲皮素是 SBD 对抗不良风险 AML 的主要活性成分,并通过核心靶点 AKT1、MAPK1、IL6、EGFR、SRC、VEGFA 和 TP53 影响耐药性、细胞凋亡、免疫调节和血管生成。我们希望所提出的药物-生物标志物相互作用模型为抗肿瘤药物的研发提供有效的策略。