Modeling SARS‐CoV2 proteins in the CASP ‐commons experiment

Kryshtafovych, A. ORCID: https://orcid.org/0000-0001-5066-7178, Moult, J. ORCID: https://orcid.org/0000-0002-3012-2282, Billings, W. M., Della Corte, D. ORCID: https://orcid.org/0000-0002-8884-9724, Fidelis, K. ORCID: https://orcid.org/0000-0002-8061-412X, Kwon, S., Olechnovič, K. ORCID: https://orcid.org/0000-0003-4918-9505, Seok, C. ORCID: https://orcid.org/0000-0002-1419-9888, Venclovas, Č., Won, J., Adiyaman, R. and McGuffin, L. ORCID: https://orcid.org/0000-0003-4501-4767 (2021) Modeling SARS‐CoV2 proteins in the CASP ‐commons experiment. Proteins: Structure, Function, and Bioinformatics, 89 (12). pp. 1987-1996. ISSN 0887-3585 doi: 10.1002/prot.26231

Abstract/Summary

CASP (Critical Assessment of Structure Prediction) is an organization aimed at advancing the state of the art in computing protein structure from sequence. In the spring of 2020, CASP launched a community project to compute the structures of the most structurally challenging proteins coded for in the SARS-CoV2 genome. Forty-seven research groups submitted over 3000 three-dimensional models and 700 sets of accuracy estimates on ten proteins. The resulting models were released to the public. CASP community members also worked together to provide estimates of local and global accuracy and identify structure-based domain boundaries for some proteins. Subsequently, two of these structures (ORF3a and ORF8) have been solved experimentally, allowing assessment of both model quality and the accuracy estimates. Models from the AlphaFold2 group were found to have good agreement with the experimental structures, with main chain GDT_TS accuracy scores ranging from 63 (a correct topology) to 87 (competitive with experiment).

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/100066
Identification Number/DOI	10.1002/prot.26231
Refereed	Yes
Divisions	Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR) Interdisciplinary centres and themes > Reading Systems Biology Network (RSBN) Life Sciences > School of Biological Sciences > Biomedical Sciences
Publisher	Wiley
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