Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction
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Abstract
Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCS IM ). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCS IM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.
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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
The coming of age of de novo protein design
Huang, P.-S., Boyken, S. E., & Baker, D. (2016) · Nature · doi:10.1038/nature19946 · Cited by 1,478 · see citing works
Advances in protein structure prediction and design
Kuhlman, B., & Bradley, P. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0163-x · Cited by 806 · see citing works
Native mass spectrometry: a bridge between interactomics and structural biology
Heck, A. J. R. (2008) · Nature Methods · doi:10.1038/nmeth.1265 · Cited by 766 · see citing works
Native Mass Spectrometry: What is in the Name?
Leney, A. C., & Heck, A. J. R. (2017) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-016-1545-3 · Cited by 602 · cited 2× · see citing works
“The templates and weights associated with all proteins for CM are provided in Supplementary Data 11 and Supplementary Data 12 for the ideal and experimental dataset respectively.”
BackgroundAllison, T. M., Barran, P., Cianférani, S., Degiacomi, M. T., Gabelica, V., Grandori, R., Marklund, E. G., Menneteau, T., Migas, L. G., Politis, A., et al. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.9b05791 · Cited by 38 · see citing works
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- Authors
- Turzo, S. B. A., Seffernick, J. T., Rolland, A. D., Donor, M. T., Heinze, S., Prell, J. S., Wysocki, V. H., & Lindert, S.
- Affiliations
- The Ohio State University (US)
- University of Oregon (US)
- Corresponding author
- Lindert, Steffen
- ORCID
- Venue
- Nature Communications
- Published
- 2022-07-28
- Volume
- 13
- Issue
- 1
- Pages
- 4377-4377
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC9334640
- OpenAlex
- W4288096022
- Cited by
- 47
- References
- 6
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 9 · 2023: 10 · 2022: 5 · 2021: 1
- FWCI
- 2.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (R21 A125804, P41 GM128577)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- ion mobility mass spectrometry, collision cross sections, protein structure prediction, integrative modeling, Rosetta, monomeric protein, confidence measures, protein shape
- MeSH terms
- Ion Mobility Spectrometry, Algorithms, Proteins, Mass Spectrometry
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