基诺美
可药性
药物重新定位
药物发现
重新调整用途
计算生物学
激酶
药品
医学
生物
卡波扎尼布
生物信息学
药理学
药物开发
癌症研究
细胞生物学
血管内皮生长因子受体
基因
生物化学
生态学
作者
Susan Klaeger,Stephanie Heinzlmeir,Mathias Wilhelm,Harald Polzer,Binje Vick,Paul-Albert Koenig,Maria Reinecke,Benjamin Ruprecht,Svenja Wiechmann,Chen Meng,Jana Zecha,Katrin Reiter,Huichao Qiao,Dominic Helm,Heiner Koch,Melanie Schoof,Giulia Canevari,Elena Casale,Stefania Re Depaolini,Annette Feuchtinger
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2017-11-30
卷期号:358 (6367)
被引量:767
标识
DOI:10.1126/science.aan4368
摘要
Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making.
科研通智能强力驱动
Strongly Powered by AbleSci AI