AlphaFold2 examples from CASP 14: Difference between revisions
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<StructureSection load='' size='350' side='right' caption='' scene=''> | <StructureSection load='' size='350' side='right' caption='' scene=''> | ||
==SARS-CoV-2 ORF8 | ==SARS-CoV-2 ORF8== | ||
Following the discussion by Rubiera<ref name="rubiera">[https://www.blopig.com/blog/2020/12/casp14-what-google-deepminds-alphafold-2-really-achieved-and-what-it-means-for-protein-folding-biology-and-bioinformatics/ 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.</ref> | Following the discussion by Rubiera<ref name="rubiera">[https://www.blopig.com/blog/2020/12/casp14-what-google-deepminds-alphafold-2-really-achieved-and-what-it-means-for-protein-folding-biology-and-bioinformatics/ 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.</ref> | ||
our first example will be [[SARS-CoV-2 protein ORF8]], a protein that affects virulence in COVID-19. | our first example will be [[SARS-CoV-2 protein ORF8]], a protein that affects virulence in COVID-19. | ||
Revision as of 02:00, 23 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, verified by the bi-annual prediction competition CASP, please see 2020: CASP 14. Below are illustrated some examples of predictions from that competition.
SARS-CoV-2 ORF8Following the discussion by Rubiera[2] our first example will be SARS-CoV-2 protein ORF8, a protein that affects virulence in COVID-19.
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ReferencesReferences
- ↑ 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
- ↑ 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.