Cambridge scientists have identified 200 approved drugs predicted to work against COVID-19—of which only 40 are currently being tested in COVID-19 clinical trials.
In a study published today in Science Advances, a team led by researchers at the University of Cambridge’s Milner Therapeutics Institute and Gurdon Institute used a combination of computational biology and machine learning to create a comprehensive map of proteins that are involved in SARS-CoV-2 infection—from proteins that help the virus break into the host cell to those generated as a consequence of infection. By examining this network using artificial intelligence (AI) approaches, they were able to identify key proteins involved in infection as well as biological pathways that might be targeted by drugs.
To date, the majority of small molecule and antibody approaches for treating COVID-19 are drugs that are either currently the subject of clinical trials or have already been through clinical trials and been approved. Much of the focus has been on several key virus or host targets, or on pathways—such as inflammation—where a drug treatment could be used as an intervention.
The team used computer modelling to carry out a ‘virtual screen’ of almost 2,000 approved drugs and identified 200 approved drugs that could be effective against COVID-19. Forty of these drugs have already entered clinical trials, which the researchers argue supports the approach they have taken.
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Science Advances. Study Paper:
