A review on drug repurposing applicable to COVID-19. Issue 2 (5th November 2020)

• Record Type: Journal Article
• Authors: Dotolo, Serena; Marabotti, Anna; Facchiano, Angelo; Tagliaferri, Roberto
• Is Part Of: Briefings in bioinformatics. Volume 22:Issue 2(2021)
• Page Start: 726
• Page End: 741
• Publication Date: 2020-11-05
• Subjects: COVID-19 -- network-based approaches -- molecular docking -- AI -- new therapies -- drug repurposing; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbaa288
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.