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SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets.

Alsulami, AF; Thomas, SE; Jamasb, AR; Beaudoin, CA; Moghul, I; Bannerman, B; Copoiu, L; ... Blundell, TL; + view all (2021) SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets. Briefings in Bioinformatics , 22 (2) pp. 769-780. 10.1093/bib/bbaa404. Green open access

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Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly growing infectious disease, widely spread with high mortality rates. Since the release of the SARS-CoV-2 genome sequence in March 2020, there has been an international focus on developing target-based drug discovery, which also requires knowledge of the 3D structure of the proteome. Where there are no experimentally solved structures, our group has created 3D models with coverage of 97.5% and characterized them using state-of-the-art computational approaches. Models of protomers and oligomers, together with predictions of substrate and allosteric binding sites, protein-ligand docking, SARS-CoV-2 protein interactions with human proteins, impacts of mutations, and mapped solved experimental structures are freely available for download. These are implemented in SARS CoV-2 3D, a comprehensive and user-friendly database, available at https://sars3d.com/. This provides essential information for drug discovery, both to evaluate targets and design new potential therapeutics.

Type: Article
Title: SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets.
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bib/bbaa404
Publisher version: https://doi.org/10.1093/bib/bbaa404
Language: English
Additional information: © The Author(s) 2021. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: SARS-CoV-2 3D database, SARS-CoV-2 drug targets, SARS-CoV-2 proteome modelling, drug discovery, proteome analysis
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Cancer Institute > Research Department of Cancer Bio
URI: https://discovery.ucl.ac.uk/id/eprint/10126311
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