The Oxford research team used an advanced computational approach using machine learning methods and arrived at a map of proteins related to COVID-19 infection. This included potential host and viral therapeutic targets.

They then virtually screened around 2,000 drugs. Of these, 200 showed high efficacy against COVID-19. Forty drugs in this list have entered clinical trials to date.

Based on the mechanism of action, the drugs were classified into two groups using artificial neural network analysis:

• Drugs that targeted SARS-CoV-2 replication

• Drugs that targeted host’s immune response

The first set of drugs were tested for their efficacy in cell lines derived from humans and some other mammals. This analysis revealed that two drugs, sulfasalazine (an anti-rheumatic drug) and proguanil (an antimalarial drug), arrested the multiplication of the virus, suggesting their potential use to treat COVID-19.

“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,” highlighted Kouzarides.

Source: Medindia