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An informatic framework for decoding protein complexes by top-down mass spectrometry

Reputable Mentor II
Reputable Mentor II

Owen S Skinner1,8, Pierre C Havugimana2,3,8, Nicole A Haverland1, Luca Fornelli1–3, Bryan P Early3, Joseph B Greer3, Ryan T Fellers3, Kenneth R Durbin4, Luis H F Do Vale3,5, Rafael D Melani1,Henrique S Seckler1, Micah T Nelp6, Mikhail E Belov7, Stevan R Horning7, Alexander A Makarov7, Richard D LeDuc2, Vahe Bandarian6, Philip D Compton1,3 & Neil L Kelleher1–4
Nature Methods (2016) doi:10.1038/nmeth.3731
Efforts to map the human protein interactome have resulted in information about thousands of multi-protein assemblies housed in public repositories, but the molecular characterization and stoichiometry of their protein subunits remains largely unknown. Here, we report a computational search strategy that supports hierarchical top-down analysis for precise identification and scoring of multi-proteoform complexes by native mass spectrometry.
1. Department of Chemistry, Northwestern University, Evanston, Illinois, USA. 2. Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois, USA. 3. Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, USA. 4. Department of Molecular Biosciences, Northwestern University, Evanston, Illinois, USA. 5. Brazilian Center for Protein Research, University of Brasilia, Brasilia, Federal District, Brazil. 6. Department of Chemistry and Biochemistry, University of Arizona, Tucson, Arizona, USA. 7. Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany. 8. These authors contributed equally to this work.

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