As artificial intelligence begins to profoundly impact structural biology, one of the next challenges is to predict protein structures from individual sequences alone. A deep learning model addresses this challenge by representing single sequences with protein language models and distilling knowledge from multi-sequence structure predictors.
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References
Anfinsen, C. B. Science 181, 223–230 (1973).
Göbel, U., Sander, C., Schneider, R. & Valencia, A. Proteins: Struct. Funct. Genet. 18, 309–317 (1994).
Wang, S., Sun, S., Li, Z., Zhang, R. & Xu, J. PLOS Comput. Biol. 13, e1005324 (2017).
Jumper, J. et al. Nature 596, 583–589 (2021).
Baek, M. et al. Science 373, 871–876 (2021).
Wang, W., Peng, Z. & Yang, J. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00373-3 (2022).
Rives, A. et al. Proc. Natl Acad. Sci. 118, e2016239118 (2021).
Akdel, M. et al. Nat. Struct. Mol. Biol. 29, 1056–1067 (2022).
Weissenow, K., Heinzinger, M. & Rost, B. Structure 30, 1169–1177e4 (2022).
Chowdhury, R. et al. Nat. Biotechnol. 40, 1617–1623 (2022).
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Shen, Y. Predicting protein structure from single sequences. Nat Comput Sci 2, 775–776 (2022). https://doi.org/10.1038/s43588-022-00378-y
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DOI: https://doi.org/10.1038/s43588-022-00378-y