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Predicting the Shapes of Protein Complexes Through Collision Cross Section Measurements and Database Searches

preprint
submitted on 08.05.2020, 18:29 and posted on 12.05.2020, 05:20 by Michael Landreh, Cagla Sahin, Joseph Gault, Samira Sadeghi, Chester Lee Drum, povilas uzdavinys, David Drew, Timothy Allison, Matteo Degiacomi, Erik Marklund
In structural biology, collision cross sections (CCS) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures, we find that we can distinguish oblate- and prolate-shaped protein complexes. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and an eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.

Funding

Uppsala-Durham Seedcorn Fund

Novo Nordisk Foundation Postdoctoral Fellowship (NNF19OC0055700)

Swedish Foundation for Strategic Research (SSF)

KI-StratNeuro starting grant

Swedish Research Council (VR) Starting Grant

Cancerfonden

Swedish Research Council (VR) Grant 2013_08807

History

Email Address of Submitting Author

erik.marklund@kemi.uu.se

Institution

Uppsala University

Country

Sweden

ORCID For Submitting Author

0000-0002-9804-5009

Declaration of Conflict of Interest

No conflict of interest

Version Notes

Submitted manuscript with journal-specific information and grant details removed.

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