蛋白质组学
化学基因学
背景(考古学)
化学生物学
药物发现
计算机科学
瓶颈
工作流程
自动化
计算生物学
化学
小分子
生物信息学
生物
工程类
生物化学
机械工程
古生物学
数据库
基因
嵌入式系统
作者
Zongtao Lin,Juan Pablo Gongora,Xingyu Liu,Yixuan Xie,Chengxiang Zhao,Dongwen Lv,Benjamin A. García
标识
DOI:10.1021/acs.jproteome.3c00467
摘要
Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.
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