Researchers from the ELLIS Unit Linz have recently used a neural network called ChemAI to screen for new drugs against Covid-19. In a large effort, they have searched a database of a billion molecules for favorable properties and now provide the resulting list of 30,000 potential drugs to the public. They also computationally tested existing drugs for the for their potential use as a therapeutic for Covid-19.
Due to the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there is an urgent need for novel therapies and drugs. The ELLIS unit Linz conducted a large-scale virtual screening for small molecules that are potential CoV-2 inhibitors. To this end, the researchers utilized ChemAI, a deep neural network trained on more than 220M data points across 3.6M molecules from three public drug-discovery databases. With ChemAI, the ELLIS unit Linz screened and ranked one billion molecules from the ZINC database for favourable effects against CoV-2. The result was then reduced to the 30,000 top-ranked compounds, which are readily accessible and purchasable via the ZINC database. Additionally, 10,000 drugs from DrugBank were tested and ranked for their potential to be repurposed as treatment for SARS-Cov-2.