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

  • Owen S. Skinner
  • , Pierre C. Havugimana
  • , Nicole A. Haverland
  • , Luca Fornelli
  • , Bryan P. Early
  • , Joseph B. Greer
  • , Ryan T. Fellers
  • , Kenneth R. Durbin
  • , Luis H.F. Do Vale
  • , Rafael D. Melani
  • , Henrique S. Seckler
  • , Micah T. Nelp
  • , Mikhail E. Belov
  • , Stevan R. Horning
  • , Alexander A. Makarov
  • , Richard D. LeDuc
  • , Vahe Bandarian
  • , Philip D. Compton
  • , Neil L. Kelleher

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)237-240
Number of pages4
JournalNature Methods
Volume13
Issue number3
DOIs
StatePublished - Feb 25 2016

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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