A review on drug repurposing applicable to COVID-19

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.

Automated summary

Drug repurposing involves finding new uses for existing drugs at a lower cost and in a shorter time period. Different computational drug-repurposing strategies, including network-based models, structure-based approaches, and artificial intelligence (AI) approaches, have been applied to COVID-19. Network-based clustering and propagation approaches have been used to identify proteins associated with COVID-19, while structure-based approaches have focused on discovering new applications for existing drugs through interactions with biological targets. AI-based networks, however, require more data before becoming relevant in this context.