In silico identification of the potential natural inhibitors of SARS-CoV-2 Guanine-N7 methyltransferase

Background: The outbreak of the COVID-19 pandemic caused by SARS-CoV-2 has triggered intense scientific research into possible therapeutic strategies that can combat ravaging disease. One such is inhibition an important enzyme affects physiological process virus. enzyme, Guanine-N7 Methyltransferase responsible for capping mRNA to conceal it from host’s cellular defense. aim study: This study aims at computationally identifying potential natural inhibitors methyltransferase binding active site (Pocket 41). Materials and methods: A library small molecules was obtained edible African plants molecularly docked against (QHD43415_13. pdb) using Pyrx software. Sinefungin, approved antiviral drug had a score -7.6 kcal/ mol with target chosen as standard. Using molecular descriptors compounds, virtual screening oral availability performed Pubchem SWISSADME web tools. online servers pkCSM Molinspiration were used further pharmacokinetic properties bioactivity respectively. dynamic simulation analyses Apo Holo proteins GROMACS software on Galaxy webserver. Results: With total RMSD 77.78, average 3.704, regional (active site) RMSF 30.61, 1.91, gyration 6.9986, B factor 696.14, Crinamidine showed greatest distortion target. Conclusion: All lead compounds better than standard while predicted show inhibitory activity. Further tests are required investigate activities compounds.