Advancing Mass Spectrometry Analyses of Proteins, Assemblies, and Proteoforms

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PROJECT SUMMARY/ABSTRACT Understanding cellular processes and pathways in depth requires methods that not only investigate the composition and arrangement of various protein assemblies, but that also elucidate their dynamics and functional regulation. Experimental strategies delivering structural information beyond primary sequence; i.e., higher-order structure and protein modifications, connect proteomics to structural biology in ways yielding potential insights into complex disease mechanisms. New techniques based on mass spectrometry (MS), native MS (i.e., measuring biomolecules in their native solution environment preserving ligand- and other molecular interactions), and top-down MS/proteomics will be advanced and applied to facilitate the characterization of proteins and protein assemblies. Coupling sensitive ionization, solution- and gas-phase separations, new electron-based dissociation methods (e.g., electron capture dissociation, ECD; electron ionization dissociation, EID) and other activation/dissociation techniques to ultra-high resolution mass spectrometry will provide an experimental platform for complete sequence and proteoform coverage. These advanced tools will be employed to characterize important biological complexes for which high-resolution structures have been difficult to obtain, including G-coupled protein receptors (GPCRs) and other membrane proteins. The exploration of links between post-translational modifications (PTMs) and proteoforms to the aggregation and toxicity of neurodegenerative diseases such as Alzheimer's disease (AD) will be furthered by our advanced MS methods. Our experimental strategies apply broadly and integrate with numerous biophysical techniques to enable the detailed structural study of large and complex molecular machines and to provide insights into their dynamics. Native top-down MS promises to advance structural biology and to hasten drug discovery and development. Improvements in MS-based technologies can advance our understanding of how proteins and protein machines drive biology.