Using AlphaFold to predict the impact of single mutations on protein stability and function
Open accessPreprint — published as 10.1371/journal.pone.0282689 · Paper page
Abstract
Abstract AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is “solved”. However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the AlphaFold predictions on the impact of a single mutation on structure with a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold cannot be immediately applied to other problems or applications in protein folding.
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AF2, despite its accuracy, likely does not learn the energy landscapes underpinning protein folding and function.
“Several preprints have provided evidence that AF2, despite its accuracy, likely does not learn the energy landscapes underpinning protein folding and function (Saldaño et al., 2021; Pak et al., 2021; Akdel et al., 2021).”
From Sampling alternative conformational states of transporters and receptors with AlphaFold2 (2022) · cites this paper as Pak et al., 2021
Some reports have indicated that AF2 does not appear to be well suited to predict the structures of mutated proteins.
“However, some reports have indicated that AF2 does not appear to be well suited to predict the structures of mutated proteins54,55.”
From A structural biology community assessment of AlphaFold2 applications (2022) · cites this paper as [54]
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References 32 · Cited by 322
- Authors
- Pak, M. A., Markhieva, K. A., Novikova, M. S., Petrov, D. S., Vorobyev, I. S., Maksimova, E. S., Kondrashov, F. A., & Ivankov, D. N.
- Affiliations
- Skolkovo Institute of Science and Technology (RU)
- Peoples' Friendship University of Russia (RU)
- University of New Mexico (US)
- Ural Federal University (RU)
- Institute of Science and Technology Austria (AT)
- Okinawa Institute of Science and Technology Graduate University (JP)
- Corresponding author
- Ivankov, Dmitry N.
- Venue
- PLoS ONE
- Publisher
- openRxiv
- Published
- 2021-09-20
- Volume
- 18
- Issue
- 3
- Pages
- e0282689-e0282689
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC10019719
- OpenAlex
- W4327566741
- Cited by
- 322
- References
- 32
- Citations by year
- 2026: 51 · 2025: 90 · 2024: 77 · 2023: 66 · 2022: 34 · 2021: 3
- FWCI
- 25.09
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PLoS ONE (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Electronic Archive of Ural Federal University (ELAR UrFU) (submittedVersion, cc-by)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- AlphaFold, single mutation, protein stability, protein folding, pLDDT, ΔΔG, protein function, green fluorescent protein, fluorescence, protein structure prediction, protein folding problem
- MeSH terms
- Amino Acid Sequence, Mutation, Proteins, Protein Folding, Protein Stability
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