A structural biology community assessment of AlphaFold 2 applications
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Abstract Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods have led to protein structure predictions that have reached the accuracy of experimentally determined models. While this has been independently verified, the implementation of these methods across structural biology applications remains to be tested. Here, we evaluate the use of AlphaFold 2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modelling of interactions; and modelling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modelled when compared to homology modelling, identifying structural features rarely seen in the PDB. AF2-based predictions of protein disorder and protein complexes surpass state-of-the-art tools and AF2 models can be used across diverse applications equally well compared to experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life science research.
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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 Akdel et al., 2021
AlphaFold and RoseTTAfold have demonstrated unprecedented accuracy in predicting structures of monomeric proteins.
“However, AlphaFold and RoseTTAfold have recently demonstrated unprecedented accuracy in predicting structures of monomeric proteins (27,28,(61)(62)(63)(64)(65)(66) and complexes (35,62,67,68).”
From AI-based structure prediction empowers integrative structural analysis of human nuclear pores (2022) · cites this paper as [61]
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- Authors
- Akdel, M., Pires, D. E. V., Porta Pardo, E., Jänes, J., Zalevsky, A. O., Mészáros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., Shenoy, A., Zhu, W., Kundrotas, P., Ruiz Serra, V., Rodrigues, C. H. M., Dunham, A. S., Burke, D., Borkakoti, N., Velankar, S., Frost, A., Lindorff-Larsen, K., Valencia, A., Ovchinnikov, S., Durairaj, J., Ascher, D. B., Thornton, J. M., Davey, N. E., Stein, A., Elofsson, A., Croll, T. I., & Beltrao, P.
- Affiliations
- Wageningen University & Research (NL)
- The University of Melbourne (AU)
- European Bioinformatics Institute (GB)
- Russian Academy of Sciences (RU)
- European Molecular Biology Laboratory (DE)
- Science for Life Laboratory (SE)
- University of Copenhagen (DK)
- University of California, San Francisco (US)
- Barcelona Supercomputing Center (ES)
- Harvard University (US)
- University of Basel (CH)
- Institute of Cancer Research (GB)
- University of Cambridge (GB)
- Corresponding author
- Valencia, Alfonso
- Ovchinnikov, Sergey
- Durairaj, Janani
- Ascher, David B
- Thornton, Janet M
- Davey, Norman E
- Stein, Amelie
- Elofsson, Arne
- Croll, Tristan I
- ORCID
- Akdel, Mehmet
- Pires, Douglas E V
- Porta Pardo, Eduard
- Jänes, Jürgen
- Zalevsky, Arthur O
- Mészáros, Bálint
- Bryant, Patrick
- Good, Lydia L.
- Laskowski, Roman A
- Pozzati, Gabriele
- Shenoy, Aditi
- Zhu, Wensi
- Kundrotas, Petras
- Ruiz Serra, Victoria
- Rodrigues, Carlos H M
- Dunham, Alistair S
- Burke, David
- Borkakoti, Neera
- Velankar, Sameer
- Frost, Adam
- Lindorff-Larsen, Kresten
- Valencia, Alfonso
- Ovchinnikov, Sergey
- Durairaj, Janani
- Ascher, David B
- Thornton, Janet M
- Davey, Norman E
- Stein, Amelie
- Elofsson, Arne
- Croll, Tristan I
- Beltrao, Pedro
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2021-09-26
- OpenAlex
- W3204490060
- Cited by
- 122
- References
- 63
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 9 · 2023: 34 · 2022: 68 · 2021: 4
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- en
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- cc-by
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- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Apollo
- ETH Zürich Research Collection (cc-by)
- ETH Zürich Research Collection
- Funders
- National Science Foundation (2032259)
- Simons Foundation (735929LPI)
- Wellcome Trust
- Swedish e-Science Research Centre
- European Commission (HORIZON2020, 842490)
- Eidgenössische Technische Hochschule Zürich
- Lundbeckfonden (R272-2017-4528)
- Novo Nordisk
- Vetenskapsrådet (2016-06301, Berzelius-2021-29)
- State Government of Victoria
- Russian Science Foundation (20-14-00121)
- Novo Nordisk Fonden (NNF18OC0033950)
- ETH Zürich Foundation
- H. Lundbeck A/S
- Helmut Horten Stiftung
- National Institutes of Health (DP5OD026389)
- Medical Research Council
- National Health and Medical Research Council (1174405)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- AlphaFold2, protein structure prediction, protein disorder prediction, ligand binding site prediction, confidence measures, proteome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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