AlphaFold2 examples from CASP 14

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This page is under construction. Eric Martz 01:03, 22 February 2021 (UTC)

Prediction of protein structures from amino acid sequences, theoretical modeling, has been extremely challenging. In 2020, breakthrough success was achieved by AlphaFold2[1], a project of DeepMind. For an overview of this breakthrough, verified by the bi-annual prediction competition CASP, please see 2020: CASP 14. Below are illustrated some examples of predictions from that competition.

Drag the structure with the mouse to rotate

References

  1. Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, Qin C, Zidek A, Nelson AWR, Bridgland A, Penedones H, Petersen S, Simonyan K, Crossan S, Kohli P, Jones DT, Silver D, Kavukcuoglu K, Hassabis D. Improved protein structure prediction using potentials from deep learning. Nature. 2020 Jan;577(7792):706-710. doi: 10.1038/s41586-019-1923-7. Epub 2020 Jan, 15. PMID:31942072 doi:http://dx.doi.org/10.1038/s41586-019-1923-7
  2. CASP14: what Google DeepMind’s AlphaFold 2 really achieved, and what it means for protein folding, biology and bioinformatics, a blog post by Carlos Outeir al Rubiera, December 3, 2020.
  3. Flower TG, Buffalo CZ, Hooy RM, Allaire M, Ren X, Hurley JH. Structure of SARS-CoV-2 ORF8, a rapidly evolving immune evasion protein. Proc Natl Acad Sci U S A. 2021 Jan 12;118(2). pii: 2021785118. doi:, 10.1073/pnas.2021785118. PMID:33361333 doi:http://dx.doi.org/10.1073/pnas.2021785118
  4. Summary and Classifications of Domains for CASP 14.

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