AlphaFold2 examples from CASP 14

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===Third Best Prediction for ORF8===
===Third Best Prediction for ORF8===
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The third best prediction was by the Perez Lab, with GDT_TS 33 (see TABLE above). It correctly predicted the anti-parallel beta sheet formed by the amino and carboxy terminal ends of the chain. <scene name='87/875686/3rd_best_orf8/1'>When the 2-stranded parallel beta strands formed by the ends of the chains are aligned, the remainder aligns poorly</scene>. This prediction '''failed to include any of the three disulfide bonds''' found in the [[empirical models]], or in the best and 2nd best predictions (not shown).
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The third best prediction was by the Perez Lab, with GDT_TS 33 (see TABLE above). It '''correctly predicted the parallel beta strands formed by the amino and carboxy terminal ends of the chain'''. <scene name='87/875686/3rd_best_orf8/1'>When the 2-stranded parallel beta strands formed by the ends of the chains are aligned, the remainder aligns poorly</scene>. This prediction has '''no disulfide bonds'''.
===Baker Rosetta Server Prediction for ORF8===
===Baker Rosetta Server Prediction for ORF8===

Revision as of 20:58, 25 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 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. Download AlphaFold2's predicted structure for ORF8 from T1064TS427_1-D1.pdb.
  8. 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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Eric Martz

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