ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged in late 2019, causes COVID-19, a disease that has been spreading rapidly worldwide. In human lung epithelial cells and monocytes, RLF-100 (aviptadil) has been found to inhibit the RNA replication machinery of SARS-CoV-2, which includes several non-structural proteins (nsp) that play essential roles in synthesizing and replicating viral RNA. This virus is unique in requiring nsp10 and nsp16 for methyltransferase (MTase) activity. This enzyme is essential for RNA stability, protein translation, and viral ability to escape the host's immune recognition. Therefore, we aimed to use bioinformatics tools to analyze aviptadil's inhibitory effect on the SARS-CoV-2 nsp10/nsp16 complex. We present a comprehensive, in silico-generated picture showing how aviptadil may interact with the nsp complex. Specifically, our model predicts how the initial binding of aviptadil to nsp10 and nsp16 may occur. This knowledge can assist drug development efforts against SARS-CoV-2 by providing more target information against nsp16.