In Silico Identification of the Potential Natural Inhibitors of SARS-CoV-2 Guanine-N7 Methyltransferase.

The outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 has triggered intense scientific research into the possible therapeutic strategies that can combat the ravaging disease. One of such strategies is the inhibition of an important enzyme that affects an important physiological process of the virus. The enzyme, Guanine 7 Methyltransferase is responsible for the capping of the SARS-CoV-2 mRNA to conceal it from the host’s cellular defense. The study aims at computationally identifying the potential natural inhibitors of the SARS-CoV-2 GuanineN7 methyltransferase binding at the active site (Pocket 41). A library of small molecules was obtained from edible African plants and were molecularly docked against the SARS-CoV-2 Guanine-N7 methyltransferase (QHD43415_13. pdb) using the Pyrx software. Sinefungin, an approved antiviral drug which had a binding score of -7.6 kcal/ mol with the target was chosen as a standard. Using the molecular descriptors of the compounds, a virtual screening for oral availability was performed using the Pubchem and SWISSADME web tools. The online servers PKCSM and Molinspiration were used for further screening for pharmacokinetic properties and bioactivity respectively. The molecular dynamic simulation and analyses of the Apo and Holo proteins was performed using the GROMACS software on the Galaxy webserver. The lead compounds are Crinamidine, Marmesin and Sinensetin which are obtained from waterleaf, mango, and orange plants respectively. All the lead compounds performed better than the standard. Crinamidine is predicted to show the greatest inhibitory activity. Further tests are required to further investigate the inhibitory activities of the lead compounds.