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- Serena Dotolo
- University of Salerno
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- Anna Marabotti
- University of Salerno
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- Angelo Facchiano
- Institute of Food Sciences, CNR Italy
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- Roberto Tagliaferri
- Artificial Intelligence, Statistical Pattern Recognition, Clustering, Biomedical imaging and Bioinformatics
説明
<jats:title>Abstract</jats:title><jats:p>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.</jats:p>
収録刊行物
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- Briefings in Bioinformatics
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Briefings in Bioinformatics 22 (2), 726-741, 2020-11-05
Oxford University Press (OUP)