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DOI: 10.18413/2658-6533-2022-8-3-0-6

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 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-N7 Methyltransferase is responsible for the capping of the SARS-CoV-2 mRNA to conceal it from the host’s cellular defense. The aim of the study: This study aims at computationally identifying the potential natural inhibitors of the SARS-CoV-2 Guanine-N7 methyltransferase binding at the active site (Pocket 41). Materials and methods: A library of small molecules was obtained from edible African plants and was molecularly docked against the SARS-CoV-2 Guanine-N7 methyltransferase (QHD43415_13. pdb) using the Pyrx software. Sinefungin, an approved antiviral drug had a binding score of -7.6 kcal/ mol with the target was chosen as a standard. Using the molecular descriptors of the compounds, 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 the pharmacokinetic properties and bioactivity respectively. The molecular dynamic simulation and analyses of the Apo and Holo proteins were performed using the GROMACS software on the Galaxy webserver. Results: With a total RMSD of 77.78, average RMSD of 3.704, total regional (active site) RMSF of 30.61, average regional RMSF of 1.91, gyration of 6.9986, and B factor of 696.14, Crinamidine showed the greatest distortion of the target. Conclusion: All the lead compounds performed better than the standard while Crinamidine is predicted to show the greatest inhibitory activity. Further tests are required to further investigate the inhibitory activities of the lead compounds.

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