A computational prediction of SARS-CoV-2 structural protein inhibitors from (Neem).

The rapid global spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has created an unprecedented healthcare crisis. The treatment for the severe respiratory illness caused by this virus is primarily symptomatic at this point, although the usage of a broad antiviral drug Remdesivir has been allowed on emergency basis by the Food and Drug Administration (FDA). The ever-increasing death toll highlights an urgent need for development of specific antivirals. In this work, we have utilized docking and simulation methods to identify small molecule inhibitors of SARS-CoV-2 Membrane (M) and Envelope (E) proteins, which are essential for virus assembly and budding. A total of 70 compounds from an Indian medicinal plant source ( or Neem) were virtually screened against these two proteins and further analyzed with molecular dynamics simulations, which resulted in the identification of a few common compounds with strong binding to both structural proteins. The compounds bind to biologically critical regions of M and E, indicating their potential to inhibit the functionality of these components. We hope that our computational approach may result in the identification of effective inhibitors of SARS-CoV-2 assembly.Communicated by Ramaswamy H. Sarma.