Target SARS-CoV-2: Machine Learning for the Prediction of Drug Suitability

Search for more suitable repurposed drugs will remove the dependence on limited drugs for the treatment of Covid-19 infection across the world. This improvised approach is predicated on the exploration of binding energy, interactions, and entropy sign with magnitude via molecular dynamics between SARS-CoV-2 main protease +2-DG/Molnupiravir drugs. The analysis emphasized the clinical suitability of Molnupiravir on top of 2-DG to deal with Covid-19 and the same is well supported by the clinical trial results. This study not only removes the scarcity of medicine that battle Covid-19 infection but also will pave the way for the essential information at the atomic level that would result in the planning and the development of more specific inhibitors for the treatment of Covid-19 infection. Funding Information: This study was not funded by any agency or Government. Declaration of Interests: The authors declare that they have no competing interests.