Quantitative structural proteomics in living cells by covalent protein painting

Abstract

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.

Keywords: Bottom-up proteomics; Dimethyl labeling; In vivo protein conformation; Isotope labeling; Protein footprinting; Protein misfolding; Quantitative mass spectrometry; Structural proteomics.

Figure 1:. The workflow of CPP in living cells.

The solvent-accessible lysine sites are initially modified with dimethylation (¹²CH₂D). After the initial labeling reaction in living cells, proteins are extracted, purified, and digested into peptides. The newly exposed lysine sites were modified with the different isotope dimethylation (¹³CD₃). Based on the results from proteomic analysis, the relative ratio of solvent-accessible to solvent-inaccessible lysine sites are quantified.

Figure 2:. Suggested design and use of the four 96 well plates for the simultaneous preparation of up to 12 CPP samples.

The dimethylation of the peptides and the desalting are performed sequentially but within one integrated workflow. The color of the wells indicates different solutions used during the procedure. Arrows indicate the workflow.