The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed, but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral proteins and pathological host pathways are undergoing clinical trials. Here, we review this work, highlight drugs with high predicted efficacy and classify their mechanisms of action. We discuss the strengths and limitations of the published methodologies and outline possible future directions. Finally, we curate a list of COVID-19 data portals and other repositories that could be used to accelerate future research.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8323501PMC
http://dx.doi.org/10.1016/j.drudis.2021.07.026DOI Listing

Publication Analysis

Top Keywords

advances computational
4
computational landscape
4
landscape repurposed
4
repurposed drugs
4
drugs covid-19
4
covid-19 covid-19
4
covid-19 pandemic
4
pandemic caused
4
caused millions
4
millions deaths
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!