The accuracy of protein structures in solution determined by AlphaFold and NMR
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Abstract
In the recent Critical Assessment of Structure Prediction (CASP) competition, AlphaFold2 performed outstandingly. Its worst predictions were for nuclear magnetic resonance (NMR) structures, which has two alternative explanations: either the NMR structures were poor, implying that Alpha-Fold may be more accurate than NMR, or there is a genuine difference between crystal and solution structures. Here, we use the program Accuracy of NMR Structures Using RCI and Rigidity (ANSURR), which measures the accuracy of solution structures, and show that one of the NMR structures was indeed poor. We then compare Alpha-Fold predictions to NMR structures and show that Alpha-Fold tends to be more accurate than NMR ensembles. There are, however, some cases where the NMR ensembles are more accurate. These tend to be dynamic structures, where Alpha-Fold had low confidence. We suggest that Alpha-Fold could be used as the model for NMR-structure refinements and that Alpha-Fold structures validated by ANSURR may require no further refinement.
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NMR structural ensembles provide a unique validation metric for AF2 because AF2's training PDB subset excluded NMR data.
“NMR structural ensembles offer a unique validation metric to assess the accuracy of predicted AlphaFold2 models since AlphaFold2 was trained on a subset of the PDB that excluded NMR data1,27–30”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [28]
Fowler et al found that for dynamic proteins, NMR ensembles can be more accurate than static AF2 models.
“Fowler et al revealed that NMR ensembles can be more accurate than static AF2 models for dynamic proteins28”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [28]
AF models are integrated with solution-state NMR data.
“Another burgeoning area where AF models are integrated with experimental data is solution-state NMR15,27,28,30,81–85.”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [28]
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- Authors
- Fowler, N. J., & Williamson, M. P.
- Affiliations
- University of Sheffield (GB)
- Corresponding author
- Fowler, Nicholas J.
- Venue
- Structure
- Publisher
- Elsevier BV
- Published
- 2022-07
- Volume
- 30
- Issue
- 7
- Pages
- 925-933.e2
- ISSN
- 0969-2126 (ISSN-L)
- PMC
- PMC9592556
- OpenAlex
- W4229373389
- Cited by
- 104
- References
- 38
- Citations by year
- 2026: 13 · 2025: 22 · 2024: 23 · 2023: 34 · 2022: 12
- FWCI
- 7.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Structure (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Biotechnology and Biological Sciences Research Council (BB/P020038/1)
- 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 › Advanced NMR Techniques and Applications
- Keywords
- AlphaFold2, protein structure prediction, solution structure, NMR ensembles, CASP, protein dynamics, NMR structure refinement
- MeSH terms
- Magnetic Resonance Spectroscopy, Protein Conformation, Proteins, Nuclear Magnetic Resonance, Biomolecular
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