The greatly improved prediction of protein 3D structure from sequence achieved by the second version of AlphaFold in 2020 has already had a huge impact on biological research, but challenges remain; the protein folding problem cannot be considered solved. We expect fierce competition to improve the method even further and new applications of machine learning to help illuminate proteomes and their many interactions.
References
Pereira, J. et al. Proteins 89, 1687–1699 (2021).
Jumper, J. et al. Nature 596, 583–589 (2021).
Tunyasuvunakool, K. et al. Nature 596, 590–596 (2021).
Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R. & Wu, C. H. Bioinformatics 23, 1282–1288 (2007).
Vaswani, A. et al. in Advances in Neural Information Processing Systems 31 (NIPS 2017) Proceedings (ed. Guyon, I. et al.) 5998–6008 (Association for Computing Machinery, 2017).
Fuchs, F. B., Worrall, D. E., Fischer, V. & Welling, M. in Advances in Neural Information Processing Systems 1970–1981 (Curran Associates, 2020).
Taylor, W. R. & Orengo, C. A. J. Mol. Biol. 208, 1–22 (1989).
Mariani, V., Biasini, M., Barbato, A. & Schwede, T. Bioinformatics 29, 2722–2728 (2013).
Senior, A. W. et al. Nature 577, 706–710 (2020).
Laskowski, R. A., MacArthur, M. W., Moss, D. S. & Thornton, J. M. J. Appl. Crystallogr. 26, 283–291 (1993).
van der Lee, R. et al. Chem. Rev. 114, 6589–6631 (2014).
Outeiral, C., Nissley, D. A. & Deane, C. M. Preprint at bioRxiv https://doi.org/10.1101/2021.09.20.461137 (2021).
Akdel, M. et al. Preprint at bioRxiv https://doi.org/10.1101/2021.09.26.461876 (2021).
Diwan, G. D., Gonzalez-Sanchez, J. C., Apic, G. & Russell, R. B. J. Mol. Biol. 433, 167180 (2021).
Pak, M. A. et al. Preprint at bioRxiv https://doi.org/10.1101/2021.09.19.460937 (2021).
Moffat, L., Greener, J. G. & Jones, D. T. Preprint at bioRxiv https://doi.org/10.1101/2021.08.24.457549 (2021).
Jendrusch, M., Korbel, J. O. & Sadiq, S. K. Preprint at bioRxiv https://doi.org/10.1101/2021.10.11.463937 (2021).
Bryant, P., Pozzati, G. & Elofsson, A. Preprint at bioRxiv https://doi.org/10.1101/2021.09.15.460468 (2021).
Yin, R., Feng, B. Y., Varshney, A. & Pierce, B. G. Preprint at bioRxiv https://doi.org/10.1101/2021.10.23.465575 (2021).
Evans, R. et al. Preprint at bioRxiv https://doi.org/10.1101/2021.10.04.463034 (2021).
McCoy, A. J., Sammiti, M. D. & Read, R. J. Preprint at bioRxiv https://doi.org/10.1101/2021.05.18.444614 (2021).
Beckham, K. S. H. et al. Sci. Adv. https://doi.org/10.1126/sciadv.abg9923 (2021).
Leman, J. K. et al. Nat. Methods 17, 665–680 (2020).
Thornton, J. M., Laskowski, R. A. & Borkakoti, N. Nat. Medicine 27, 1666–1669 (2021).
Greener, J. G., Kandathil, S. M., Moffat, L. & Jones, D. T. Nat. Rev. Mol. Cell Biol. https://doi.org/10.1038/s41580-021-00407-0 (2021).
Orengo, C. A. et al. Structure 5, 1093–1108 (1997).
Murzin, A. G., Brenner, S. E., Hubbard, T. & Chothia, C. J. Mol. Biol. 247, 536–540 (1995).
Cheng, H. et al. PLOS Comput. Biol. 10, e1003926 (2014).
Baek, M. et al. Science 373, 871–876 (2021).
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The authors acknowledge help from R. Laskowski, who generated Fig. 3. J.M.T. acknowledges funding from EMBL.
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Jones, D.T., Thornton, J.M. The impact of AlphaFold2 one year on. Nat Methods 19, 15–20 (2022). https://doi.org/10.1038/s41592-021-01365-3
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DOI: https://doi.org/10.1038/s41592-021-01365-3
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