A team led by an Indian-origin scientist has used artificial intelligence (AI) to identify hundreds of new potential drugs that could help treat COVID-19, the disease caused by the novel coronavirus, or SARS-CoV-2.<br />”<br />”There is an urgent need to identify effective drugs that treat or prevent COVID-19, said Anandasankar Ray, a professor at the University of California, Riverside in the US.<br />”<br />”We have developed a drug discovery pipeline that identified several candidates, said Ray, who led the research published in the journal Heliyon.<br />”<br />”The drug discovery pipeline is a type of computational strategy linked to AI — a computer algorithm that learns to predict activity through trial and error, improving over time.<br />”<br />”Existing FDA-approved drugs that target one or more human proteins important for viral entry and replication are currently high priority for repurposing as new COVID-19 drugs, he said.<br />”<br />”Joel Kowalewski, a graduate student in Ray's lab, used small numbers of previously known ligands for 65 human proteins that are known to interact with SARS-CoV-2 proteins.<br />”<br />”The researchers were thus able to create a database of chemicals whose structures were predicted as interactors of the 65 protein targets. They also evaluated the chemicals for safety. Ray and Kowalewski used their machine learning models to screen more than 10 million commercially available small molecules from a database of 200 million chemicals.<br />”<br />”They identified the best-in-class hits for the 65 human proteins that interact with SARS-CoV-2 proteins.<br />”<br />”The method allowed the researchers to not only identify the highest scoring candidates with significant activity against a single human protein target, but also find a few chemicals that were predicted to inhibit two or more human protein targets.<br />