Coming to Grips with Ambiguity: Ion Mobility-Mass Spectrometry for Protein Quaternary Structure Assignment

  • Joseph D. Eschweiler
  • Aaron T. Frank
  • Brandon T. Ruotolo
Critical Insight


Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies.

Graphical Abstract


Native mass spectrometry Structural proteomics Bioinformatics Molecular dynamics simulations Protein network 



Protein topology modeling efforts in the Ruotolo lab are supported through the National Institute of General Medical Sciences, National Institutes of Health (R01 GM095832). Additionally, the authors gratefully acknowledge the support of Erik Marklund (Uppsala), Matteo Degiacomi (Oxford), and Justin Benesch (Oxford), who helped the authors to integrate IMPACT CCS calculations into their computational workflows.

Supplementary material

13361_2017_1757_MOESM1_ESM.docx (7 mb)
Supplemental Information All of the software used in this work for modeling and analysis will be made freely available at: Supplemental figures, discussion, and experimental methods can be found in the online Supporting Information document. (DOCX 7210 kb)


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Copyright information

© American Society for Mass Spectrometry 2017

Authors and Affiliations

  • Joseph D. Eschweiler
    • 1
  • Aaron T. Frank
    • 1
  • Brandon T. Ruotolo
    • 1
  1. 1.Department of ChemistryUniversity of MichiganAnn ArborUSA

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