AI revolutions in biology: The joys and perils of AlphaFold
Open accessAbstract
AlphaFold is the most ground-breaking application of AI in science so far; it will revolutionize structural biology, but caution is warranted.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AlphaFold2 can predict three-dimensional protein structures accurately from sequence alone, which may solve the long-standing structure prediction problem.
“enables accurate prediction of three-dimensional protein structures from only the target amino acid sequence”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [3]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808 · see citing works
Announcing the worldwide Protein Data Bank
Berman, H., Henrick, K., & Nakamura, H. (2003) · Nature Structural & Molecular Biology · doi:10.1038/nsb1203-980 · Cited by 3,093 · see citing works
Highly accurate protein structure prediction for the human proteome
Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025 · see citing works
Assessing the utility of <scp>CASP14</scp> models for molecular replacement
Millán, C., Keegan, R. M., Pereira, J., Sammito, M. D., Simpkin, A. J., McCoy, A. J., Lupas, A. N., Hartmann, M. D., Rigden, D. J., & Read, R. J. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26214 · Cited by 62 · see citing works
Flagged first, then by citations
Research works printed but not linked: 11
- Baek M, DiMaio F, Anishchenko I, Dauparas J, Ovchinnikov S, Lee GR, Wang J, Cong Q, Kinch LN, Schaeffer RD et al (2021) Accurate prediction of protein structures and interactions using a three‐track neural network. Science 8754: eabj8754 PMC7612213 34282049
- Bouatta N, Sorger P, AlQuraishi M (2021) Protein structure prediction by AlphaFold 2: are attention and symmetries all you need? Acta Crystallogr Sect D Struct Biol 77: 982– 991 34342271 PMC8329862
- Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, Christie C, Duarte JM, Dutta S, Feng Z et al (2019) Protein Data Bank: the single global archive for 3D macromolecular structure data. Nucleic Acids Res 47: D520– D528 30357364 PMC6324056
- Fernandez‐Leiro R, Bhairosing‐Kok D, Kunetsky V, Laffeber C, Winterwerp HH, Groothuizen F, Fish A, Lebbink JHG, Friedhoff P, Sixma TK et al (2021) The selection process of licensing a DNA mismatch for repair. Nat Struct Mol Biol 28: 373– 381 33820992
- Kim RQ, van Dijk WJ, Sixma TK (2016) Structure of USP7 catalytic domain and three Ubl‐domains reveals a connector α‐helix with regulatory role. J Struct Biol 195: 11– 18 27183903
- Levinthal (1969) Levinthal’s Paradox. In Mossbauer spectroscopy in biological systems: proceedings of a meeting held at allerton house, DeBrunner J T P ME (ed), pp 22– 24. Monticello, IL: University of Illinois
- McNicholas S, Potterton E, Wilson KS, Noble MEM (2011) Presenting your structures: the CCP4mg molecular‐graphics software. Acta Crystallogr Sect D Biol Crystallogr 67: 386– 394 21460457 PMC3069754
- Moult J, Pedersen JT, Judson R, Fidelis K (1995) A large‐scale experiment to assess protein structure prediction methods. Proteins Struct Funct Genet 23: ii– iv 8710822
- Sironi L, Mapelli M, Knapp S, De Antoni A, Jeang KT, Musacchio A (2002) Crystal structure of the tetrameric Mad1‐Mad2 core complex: implications of a “safety belt” binding mechanism for the spindle checkpoint. EMBO J 21: 2496– 2506 12006501 PMC126000
- Stein PE, Leslie AGW, Finch JT, Turnell WG, McLaughlin PJ, Carrell RW (1990) Crystal structure of ovalbumin as a model for the reactive centre of serpins. Nature 347: 99– 102 2395463
- Vitre B, Gudimchuk N, Borda R, Kim Y, Heuser JE, Cleveland DW, Grishchuk EL (2014) Kinetochore‐microtubule attachment throughout mitosis potentiated by the elongated stalk of the kinetochore kinesin CENP‐E. Mol Biol Cell 25: 2272– 2281 24920822 PMC4116301
Cited by
Sorted by citations
Ren, F., Ding, X., Zheng, M., Korzinkin, M., Cai, X., Zhu, W., Mantsyzov, A., Aliper, A., Aladinskiy, V., Cao, Z., et al. (2023) · Chemical Science · doi:10.1039/d2sc05709c · Cited by 365 · see citing works
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190 · see citing works
The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins
Agarwal, V., & McShan, A. C. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01638-w · Cited by 155 · see citing works
Novel machine learning approaches revolutionize protein knowledge
Bordin, N., Dallago, C., Heinzinger, M., Kim, S., Littmann, M., Rauer, C., Steinegger, M., Rost, B., & Orengo, C. (2023) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2022.11.001 · Cited by 72 · see citing works
Accelerating crystal structure determination with iterative <i>AlphaFold</i> prediction
Terwilliger, T. C., Afonine, P. V., Liebschner, D., Croll, T. I., McCoy, A. J., Oeffner, R. D., Williams, C. J., Poon, B. K., Richardson, J. S., Read, R. J., et al. (2023) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s205979832300102x · Cited by 62 · see citing works
Sahu, P. K., Benjamin, L. A., Singh Aswal, G., & Williams-Persad, A. (2023) · Postgraduate Medical Journal · doi:10.1093/postmj/qgad090 · Cited by 52 · see citing works
Barbarin-Bocahu, I., & Graille, M. (2022) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798322002157 · Cited by 52 · see citing works
Matzko, R., & Konur, S. (2024) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-024-00455-4 · Cited by 28 · see citing works
Karlin, D. G. (2024) · Journal of General Virology · doi:10.1099/jgv.0.001948 · Cited by 8 · see citing works
Structural Insights into the Dimeric Form of Bacillus subtilis RNase Y Using NMR and AlphaFold
Morellet, N., Hardouin, P., Assrir, N., van Heijenoort, C., & Golinelli-Pimpaneau, B. (2022) · Biomolecules · doi:10.3390/biom12121798 · Cited by 7 · see citing works
- Authors
- Perrakis, A., & Sixma, T. K.
- Affiliations
- The Netherlands Cancer Institute (NL)
- Corresponding author
- Sixma, Titia K
- Venue
- The EMBO Reports
- Published
- 2021-10-20
- Volume
- 22
- Issue
- 11
- Pages
- e54046-e54046
- ISSN
- 1469-221X (ISSN-L)
- 1469-3178
- PMC
- PMC8567224
- OpenAlex
- W3205208140
- Cited by
- 190
- References
- 5
- Citations by year
- 2026: 18 · 2025: 25 · 2024: 52 · 2023: 57 · 2022: 35 · 2021: 3
- FWCI
- 11.53
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- EMBO Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- European Commission (EC), iNEXT-Discovery (871037)
- 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, artificial intelligence in biology, protein structure prediction, structural biology, artificial intelligence in science
- MeSH terms
- Artificial Intelligence, Biology
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 ›
Are you an author, or do you see a problem with this page? Request a review
