Protein complex prediction using Rosetta, AlphaFold, and mass spectrometry covalent labeling
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Abstract
Covalent labeling (CL) in combination with mass spectrometry can be used as an analytical tool to study and determine structural properties of protein-protein complexes. However, data from these experiments is sparse and does not unambiguously elucidate protein structure. Thus, computational algorithms are needed to deduce structure from the CL data. In this work, we present a hybrid method that combines models of protein complex subunits generated with AlphaFold with differential CL data via a CL-guided protein-protein docking in Rosetta. In a benchmark set, the RMSD (root-mean-square deviation) of the best-scoring models was below 3.6 Å for 5/5 complexes with inclusion of CL data, whereas the same quality was only achieved for 1/5 complexes without CL data. This study suggests that our integrated approach can successfully use data obtained from CL experiments to distinguish between nativelike and non-nativelike models.
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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
Protein complex prediction with AlphaFold-Multimer
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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
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DockQ: A Quality Measure for Protein-Protein Docking Models
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High‐accuracy protein structure prediction in <scp>CASP14</scp>
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“…sequence coevolution datawhichhasshownremarkablesuccessandhasoutperformedother prediction methods during the 13th and 14th (with AF2) Critical Assessment of Techniques for Protein Structure Prediction (CASP) 22,23 , a series of blind tests to gauge the current state of protein structure prediction.”
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- Authors
- Drake, Z. C., Seffernick, J. T., & Lindert, S.
- Affiliations
- The Ohio State University (US)
- Corresponding author
- Lindert, Steffen
- Venue
- Nature Communications
- Published
- 2022-12-21
- Volume
- 13
- Issue
- 1
- Pages
- 7846-7846
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC9772387
- OpenAlex
- W4313339743
- Cited by
- 85
- References
- 8
- Citations by year
- 2026: 10 · 2025: 25 · 2024: 36 · 2023: 11 · 2022: 2 · 2012: 1
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- 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 (GM128577)
- Alfred P. Sloan Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Keywords
- protein-protein complex prediction, covalent labeling, protein-protein docking, AlphaFold, Rosetta, mass spectrometry
- MeSH terms
- Algorithms, Protein Conformation, Proteins, Mass Spectrometry
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