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Review
. 2018 Nov 2;17(11):3614-3627.
doi: 10.1021/acs.jproteome.8b00341. Epub 2018 Oct 8.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Affiliations
Review

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Upneet Kaur et al. J Proteome Res. .

Abstract

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

Keywords: mass spectrometry; protein folding; proteomics; thermodynamics.

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Figures

Figure 1.
Figure 1.
Schematic representation of experimental workflows utilized in native state approaches highlighted here including the XL-MS, HRF, DARTS, and LiP techniques.
Figure 2.
Figure 2.
Schematic representation of experimental workflows utilized in the SPROX, PP, and TPP techniques that utilize denaturant to probe the more global unfolding/refolding properties of proteins.
Figure 3.
Figure 3.
PIR structure. (A) Conceptual design of cross protein interaction reporters (PIRs). (B) Examples of fragmentation patterns of PIR-labeled peptides. Adapted with permission from Tang and Bruce, A new cross-linking strategy: protein interaction reporter (PIR) technology for protein-protein interaction studies, Mol Biosyst, 6(6), pages 939–947. Copyright 2010 the Royal Society of Chemistry.
Figure 4.
Figure 4.
IC-FPOP flow cell schematic. Optimal conditions were observed with a 10:1 sheath buffer to cellular analyte ratio capillary in dark blue, window for laser light in light blue. Single cell flow after exit from the cross is depicted in the inset. Adapted with permission from Rinas et al., Development of a Microflow System for In-Cell Footprinting Coupled with Mass Spectrometry, Anal. Chem., 88(20), pages 10052–10058. Copyright 2016 American Chemical Society.
Figure 5.
Figure 5.
Schematic representation of the experimental workflow employed in several recent applications of the SPROX methodology to the characterization of biological states including those associated with a mouse model of aging and cell culture models of cancer.,
Figure 6.
Figure 6.
Experimental workflow for in-cell XL-MS. Cells are cultured in isotopically light/heavy SILAC media followed by addition of PIR crosslinker to the cells in 1:1 mixture of light/heavy cells. The cells are lysed and the crosslinked peptides are enriched via strong cation exchange (SCX). LC/MS analysis by ReACt is used to identify cross-linked peptide pairs followed by MS based quantification of light/heavycrosslinked peptides. The selected crosslinked peptides are analyzed by targeted PRM. The resulting data is used to map the crosslinked peptides and further map the proteins that have been crosslinked. The crosslinked data is then complied into a protein interaction network and the crosslinks are analyzed in the context of existing structural information of the proteins.

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