University of Cambridge researchers identify 200 existing drugs with potential to fight Covid-19
Researchers have identified 200 already approved drugs that have potential to be repurposed for the fight against Covid-19, only 40 of which are currently being tested against the virus in clinical trials.
The work, led by scientists at the University of Cambridge’s Milner Therapeutics Institute and Gurdon Institute used computational biology and machine learning to predict which existing medicines might be effective against SARS-CoV-2.
They created a comprehensive map of proteins involved in the infection, from those that help the virus break into the host cell to those generated as a result.
Using artificial intelligence approaches to probe this network, they then identified key proteins involved in infection as well as biological pathways that could be targeted by drugs.
Prof Tony Kouzarides, director of the Milner Therapeutics Institute, who led the study, said: “By looking across the board at the thousands of proteins that play some role in SARS-CoV-2 infection – whether actively or as a consequence of infections – we’ve been able to create a network uncovering the relationship between these proteins.
“We then used the latest machine learning and computer modelling techniques to identify 200 approved drugs that might help us treat Covid-19. Of these, 160 had not been linked to this infection before. This could give us many more weapons in our armoury to fight back against the virus.”
Most of the small molecule and antibody drugs in use for treating Covid-19 are either in clinical trials currently or already approved.
The focus for intervention has typically been on several key virus or host targets, or on pathways – such as inflammation.
A ‘virtual screen’ of almost 2,000 approved drugs was carried out with computer modelling, with one in 10 showing promise.
And the researchers were buoyed by the fact that 40 of these drugs have already entered clinical trials, as it offers some validation of the data-driven approach.
Further hope came after a subset of the drugs was tested the lab.
The team used artificial neural network analysis to classify the drugs based on the key role of their targets in SARS-CoV-2 infection - namely those that targeted viral replication and those that targeted the immune response.
A subset of drugs with targets implicated in viral replication was tested using cell lines derived from humans and non-human primates, and two showed particular promise.
Sulfasalazine, a drugs used to treat conditions such as rheumatoid arthritis and Crohn’s disease, and anti-malarial drug proguanil were shown to reduce SARS-CoV-2 viral replication in cells, which offers hope that could be used to prevent infection or to treat Covid-19.
Dr Namshik Han, head of computational research and AI at the Milner Therapeutics Institute, added: “Our study has provided us with unexpected information about the mechanisms underlying Covid-19 and has provided us with some promising drugs that might be repurposed for either treating or preventing infection.
“While we took a data-driven approach – essentially allowing artificially intelligent algorithms to interrogate datasets – we then validated our findings in the laboratory, confirming the power of our approach.
“We hope this resource of potential drugs will accelerate the development of new drugs against Covid-19. We believe our approach will be useful for responding rapidly to new variants of SARS-CoV2 and other new pathogens that could drive future pandemics.”
The research was funded by LifeArc, the LOEWE Center DRUID, the Bundesministerium für Bildung und Forschung, the European Union’s Horizon 2020 programme, Wellcome and Cancer Research UK.
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