AlphaFold2 examples from CASP 14: Difference between revisions
From Proteopedia
Jump to navigationJump to search
Eric Martz (talk | contribs) No edit summary |
Eric Martz (talk | contribs) No edit summary |
||
| Line 13: | Line 13: | ||
The quality of predictions for the structure of ORF8 are judged by comparison with X-ray crystallographic [[empirical models]] which were not available to the groups making predictions. Shortly after the CASP 14 competition (summer 2020), two X-ray crystal structures were reported for ORF8: [[7jtl]] released August 26, 2020, and [[7jx6]], released September 23, 2020. The [[resolution|resolutions]] are 2.0 and 1.6 Å respectively, and both have worse than average [[Rfree]] values. | The quality of predictions for the structure of ORF8 are judged by comparison with X-ray crystallographic [[empirical models]] which were not available to the groups making predictions. Shortly after the CASP 14 competition (summer 2020), two X-ray crystal structures were reported for ORF8: [[7jtl]] released August 26, 2020, and [[7jx6]], released September 23, 2020. The [[resolution|resolutions]] are 2.0 and 1.6 Å respectively, and both have worse than average [[Rfree]] values. | ||
{{Template:Green links zoom}} | {{Template:Green links zoom}} | ||
<scene name='87/875686/Morf_lin_7jx6_imf_7jtl/ | <scene name='87/875686/Morf_lin_7jx6_imf_7jtl/3'>The two X-ray structures agree very well</scene>: 87 of the 102 residues/chain align with a [https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions root mean square deviation] '''(RMSD) of 0.66 Å'''<ref>Alignment and RMSD calculation was by ''iterative magic fit'' of Swiss PDB Viewer.</ref>. | ||
===AlphaFold2 Prediction for ORF8=== | ===AlphaFold2 Prediction for ORF8=== | ||
Revision as of 01:54, 23 February 2021
This page is under construction. Eric Martz 01:03, 22 February 2021 (UTC)
Prediction of protein structures from amino acid sequences, homology 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 empirical models, please see 7jtl. Below are illustrated some examples of predictions from that competition.
| |||||||||||
References
- ↑ 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:https://dx.doi.org/10.1038/s41586-019-1923-7
