Screening of Therapeutic Agents for COVID-19 using Machine Learning and Ensemble Docking Simulations

Understand

The world has witnessed unprecedented human and economic loss from the COVID-19 disease, caused by the novel coronavirus SARS-CoV-2.

• Extensive research is being conducted across the globe to identify therapeutic agents against the SARS-CoV-2.
• Here, we use a powerful and efficient computational strategy by combining machine learning (ML) based models and high-fidelity ensemble docking simulations to enable rapid screening of possible therapeutic molecules (or ligands).
• Our screening is based on the binding affinity to either the isolated SARS-CoV-2 S-protein at its host receptor region or to the Sprotein-human ACE2 interface complex, thereby potentially limiting and/or disrupting the host-virus interactions.