SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets. Issue 2 (8th January 2021)

• Record Type: Journal Article
• Authors: Alsulami, Ali F; Thomas, Sherine E; Jamasb, Arian R; Beaudoin, Christopher A; Moghul, Ismail; Bannerman, Bridget; Copoiu, Liviu; Vedithi, Sundeep Chaitanya; Torres, Pedro; Blundell, Tom L
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 2(2021)
• Page Start: 769
• Page End: 780
• Publication Date: 2021-01-08
• Subjects: SARS-CoV-2 proteome modelling -- SARS-CoV-2 3D database -- SARS-CoV-2 drug targets -- proteome analysis -- drug discovery; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa404
• Languages: English
• ISSNs: 1467-5463

Abstract

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.