蛋白质组
质谱法
全景望远镜
蛋白质组学
串联质量标签
熔化曲线分析
计算生物学
定量蛋白质组学
色谱法
生物信息学
化学
生物
组蛋白
组蛋白脱乙酰基酶
生物化学
DNA
基因
聚合酶链反应
作者
Holger Franken,Toby Mathieson,Dorothee Childs,Gavain M.A. Sweetman,Thilo Werner,Ina Tögel,Carola Doce,Stephan Gade,Marcus Bantscheff,Gerard Drewes,Friedrich Reinhard,Wolfgang Huber,Mikhail M. Savitski
出处
期刊:Nature Protocols
[Springer Nature]
日期:2015-09-17
卷期号:10 (10): 1567-1593
被引量:548
标识
DOI:10.1038/nprot.2015.101
摘要
The direct detection of drug-protein interactions in living cells is a major challenge in drug discovery research. Recently, we introduced an approach termed thermal proteome profiling (TPP), which enables the monitoring of changes in protein thermal stability across the proteome using quantitative mass spectrometry. We determined the intracellular thermal profiles for up to 7,000 proteins, and by comparing profiles derived from cultured mammalian cells in the presence or absence of a drug we showed that it was possible to identify direct and indirect targets of drugs in living cells in an unbiased manner. Here we demonstrate the complete workflow using the histone deacetylase inhibitor panobinostat. The key to this approach is the use of isobaric tandem mass tag 10-plex (TMT10) reagents to label digested protein samples corresponding to each temperature point in the melting curve so that the samples can be analyzed by multiplexed quantitative mass spectrometry. Important steps in the bioinformatic analysis include data normalization, melting curve fitting and statistical significance determination of compound concentration-dependent changes in protein stability. All analysis tools are made freely available as R and Python packages. The workflow can be completed in 2 weeks.
科研通智能强力驱动
Strongly Powered by AbleSci AI