Quantitative structural proteomics in living cells by covalent protein painting.
Quantitative structural proteomics in living cells by covalent protein painting.
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DOI：
10.1016/bs.mie.2022.08.046
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发表时间：
2023
影响因子：
--
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蛋白质的折叠和构象是成功的细胞功能的关键，但所有用于蛋白质结构测定的技术都是在具有高度纯化蛋白质的人工环境中进行的。虽然蛋白质构象已经被解决到原子分辨率，并且现代蛋白质结构预测工具快速生成接近准确的蛋白质模型，但仍然需要揭示活细胞中蛋白质的构象。在这里，我们描述了共价蛋白质绘画（CPP），一个简单而快速的方法来推断蛋白质构象的结构信息，在细胞中的定量蛋白质足迹技术。CPP以高灵敏度和高通量监测细胞中3D蛋白质组的构象景观。CPP的一个关键优势是它能够定量比较不同实验条件下的3D蛋白质组，并发现蛋白质构象的显着变化。我们详细介绍了如何进行一个成功的CPP实验，在进行实验之前要考虑的因素，以及如何解释结果。
The fold and conformation of proteins are key to successful cellular function, but all techniques for protein structure determination are performed in an artificial environment with highly purified proteins. While protein conformations have been solved to atomic resolution and modern protein structure prediction tools rapidly generate near accurate models of proteins, there is an unmet need to uncover the conformations of proteins in living cells. Here, we describe Covalent Protein Painting (CPP), a simple and fast method to infer structural information on protein conformation in cells with a quantitative protein footprinting technology. CPP monitors the conformational landscape of the 3D proteome in cells with high sensitivity and throughput. A key advantage of CPP is its’ ability to quantitatively compare the 3D proteomes between different experimental conditions and to discover significant changes in the protein conformations. We detail how to perform a successful CPP experiment, the factors to consider before performing the experiment, and how to interpret the results.
影响因子：
3
作者：
Pascal BD;Chalmers MJ;Busby SA;Mader CC;Southern MR;Tsinoremas NF;Griffin PR
通讯作者：
Griffin PR