Computational investigation of potent inhibitors against SARS-CoV-2 2'-O-methyltransferase (nsp16): Structure-based pharmacophore modeling, molecular docking, molecular dynamics simulations and binding free energy calculations.

The Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, has created unprecedented public health and economic crises around the world. SARS-CoV-2 2'-O-methyltransferase (nsp16) adds a "cap" to viral RNA to maintain the stability of viral RNA, and inhibition of nsp16 activity may reduce viral proliferation, making this protein an attractive drug target. Here, we report the identification of several small molecule inhibitors of nsp16 by virtual screening. First, the nsp16-sinefungin complex (PDB ID: 6WKQ) was selected from the protein data bank. Asp6912, Cys6913, Asp6897 and Asp6928 were determined to be the key amino acids for sinefungin binding in the crystal structure of nsp16-sinefungin complex by molecular dynamics simulation. The complex structures in the stable binding trajectory of nsp16-sinefungin were than clustered through molecular dynamics RMSD analysis. Six clusters were generated, and six representative structures were selected to construct the pharmacophore based on the structure. These six pharmacophores were superimposed on the binding pocket to simplify and pick the common characteristics. The compounds obtained by the pharmacophore screening from Bionet and Chembiv databases were docked into the nsp16 active pocket. The candidate compounds were selected according to the molecular docking score and then screened by MM/GBSA. Finally, four candidate compounds were obtained. Four sets of 150ns molecular dynamics simulations were performed to determine whether candidate compounds could maintain stable interactions with key amino acids. The results of MD and MM/PBSA energy decomposition indicated that C1 and C2 could form a stable complex system with nsp16, and could form strong hydrogen bonds and salt bridges with the key amino acid Asp6897 and Asp6928. This study thus identifies and attempts to validate for the first time the potential inhibitory activities of C1 and C2 against nsp16, allowing the development of potent anti-COVID-19 drugs and unique treatment strategies.