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Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches
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Number of Authors: 102020 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 92, no 18, p. 12297-12303Article in journal (Refereed) Published
Abstract [en]

In structural biology, collision cross sections (CCSs) 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. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a 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.

Place, publisher, year, edition, pages
2020. Vol. 92, no 18, p. 12297-12303
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Chemical Sciences
Identifiers
URN: urn:nbn:se:su:diva-186381DOI: 10.1021/acs.analchem.0c01940ISI: 000572832900028PubMedID: 32660238OAI: oai:DiVA.org:su-186381DiVA, id: diva2:1502062
Available from: 2020-11-18 Created: 2020-11-18 Last updated: 2023-10-02Bibliographically approved

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Landreh, MichaelGault, JosephUzdavinys, PovilasDrew, DavidDegiacomi, Matteo T.

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