A Resource for Biomedical Mass Spectrometry

Washington University, Saint Louis MO

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Mass spectrometry has become the enabling tool for identification of lipids and proteins and for determination of their structures and properties. The Washington University Mass Spectrometry Resource (WUMSR) has played key roles in the elucidation of lipid structure and developing protein footprinting by mass spectrometry (MS) for more than a decade. Both research themes require improvements, particularity in their data pipelines. To advance this research, we propose two subprojects. The first, on lipids, aims at accelerating the development of lipid MS by developing and broadly disseminating software and databases (LipidQA) that have been created at WUMSR so that the national community can employ them in their own lipid research. This will be achieved by providing a web server housed at WUMSR, improving software with enhanced scoring, searching algorithms that accommodate multiple stage tandem MS data, and the addition of several classes of lipids to the database. The improved package will impact driving biomedical projects (DBPs) on understanding the virulence of parasitic diseases and the biology of lipid classes on obesity and diabetes. The protein biophysics project also aims at broader dissemination of techniques and software developed at WUMSR. Chemical footprinting strategies based on MS for detection including hydrogen deuterium exchange (HDX), fast photochemical oxidation of proteins (FPOP), and other covalent modifications can map the structure of proteins and their ligands down to the amino-acid level. Data analysis tools and workflows for these techniques (especially for FPOP) will be improved and made available to the scientific community. A new experiment in protein folding that involves two lasers will be further developed with the aid of a new laser system. Given that the footprinting experiments produce data that constrains protein and protein-complex structure, just as in NMR, new computational methods will be developed that can use these data to understand protein interactions, affinities, and folding, even in the absence of high resolution structural data. Progress in this area will impact a number of ongoing DBPs, particularly one that promises to improve pain management.