AlphaFold2 examples from CASP 14

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===ORF8 is not a novel fold===
===ORF8 is not a novel fold===
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Less than 2% of new [[empirically-determined structures]] have novel folds; that is, folds not aready represented in the [[PDB]]<ref name="cath2011">PMID: 21097779</ref>. When chain A of [[7jx6]] was submitted to Dali<ref name="dali2020">PMID: 31606894</ref> (February, 2021), the top hit was one of the two domains in [[5a2f]], the CD166 human cell surface receptor involved in activation of T lymphocytes. The Z-score was 7.1, and 88 alpha carbons aligned with RMSD 3.2 Å. Dali reported the sequence identity as 6%.
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Less than 2% of new [[empirically-determined structures]] have novel folds; that is, folds not aready represented in the [[PDB]]<ref name="cath2011">PMID: 21097779</ref>. When chain A of [[7jx6]] was submitted to Dali<ref name="dali2020">PMID: 31606894</ref> (February, 2021), the top hit was the N-terminal domain of two domains in [[5a2f]], the CD166 human cell surface receptor involved in activation of T lymphocytes. The Z-score was 7.1, and 88 alpha carbons aligned with RMSD 3.2 Å. Dali reported the identity as 6% in a structure-based sequence alignment. Sequence alignment by MAFFT<ref name="mafft">PMID: 23329690</ref> obtained 18% sequence identity using more and larger gaps.
===AlphaFold2 Prediction for ORF8===
===AlphaFold2 Prediction for ORF8===

Revision as of 22:09, 28 February 2021

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, documented 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. 4.0 4.1 Summary and Classifications of Domains for CASP 14.
  5. 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
  6. 6.0 6.1 6.2 Alignment by Swiss-PdbViewer's iterative magic fit. This starts with a sequence alignment-guided structural alignment, and then selects subsets of the structures to minimize the RMSD. Eight intermediate structures were generated by the Theis Morph Server by linear interpolation.
  7. Cuff AL, Sillitoe I, Lewis T, Clegg AB, Rentzsch R, Furnham N, Pellegrini-Calace M, Jones D, Thornton J, Orengo CA. Extending CATH: increasing coverage of the protein structure universe and linking structure with function. Nucleic Acids Res. 2011 Jan;39(Database issue):D420-6. doi: 10.1093/nar/gkq1001. , Epub 2010 Nov 19. PMID:21097779 doi:http://dx.doi.org/10.1093/nar/gkq1001
  8. Holm L. DALI and the persistence of protein shape. Protein Sci. 2020 Jan;29(1):128-140. doi: 10.1002/pro.3749. Epub 2019 Nov 5. PMID:31606894 doi:http://dx.doi.org/10.1002/pro.3749
  9. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013 Apr;30(4):772-80. doi: 10.1093/molbev/mst010. Epub 2013 Jan, 16. PMID:23329690 doi:http://dx.doi.org/10.1093/molbev/mst010
  10. Download AlphaFold2's predicted structure for ORF8 from T1064TS427_1-D1.pdb.
  11. Alignment by Swiss-PdbViewer's magic fit. This is a sequence alignment-guided structural alignment. Eight intermediate structures were generated by the Theis Morph Server by linear interpolation.
  12. For all targets in CASP 14, the top two servers were QUARK and Zhang-server (which were not significantly different at a Z-score sum of 62.9), followed by Zhang-CEthreader (55.9) and BAKER-ROSETTASERVER (55.3).

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