COVID-19 was first reported in China on December 31, 2019 but quickly spread around the world to gain the designation of a pandemic by March 11, 2020. Thus, a viable treatment option is vital to ensure public safety. COVID-19 is caused by the novel coronavirus, SARS-CoV-2. The functional polypeptides of the virus are activated by a main protease that has no similar homologs in humans, making it a desired target for potential drugs. The structure of the main protease of the virus was solved by Jin, et al., in March 2020. The goal of the present research is to find a suitable inhibitor for the main protease using a known drug database. In the present study, three of the most promising inhibitors from the Jin study (ebselen, cinanserin, and N3) were docked to the protease structure (PDB code 6LU7) and used as controls. To test for novel inhibitors, 5180 known protease inhibitors identified as “purchasable” by the ZINC15 online molecular database were screened in this study using Autodock QuickVina02. The 38 molecules that resulted in the lowest docking scores have been further investigated using molecular dynamics. The structure and dynamics of the complexes during their simulations have been analyzed, and their average binding free energies have been calculated. The average binding free energies of the controls (N3, ebselen, and cinanserin) are -14.3, -17.0, and -16.2 kcal mol<sup>-1</sup>, respectively. The average binding free energies of the two inhibitors with the best scores were found to be -45.42 and -44.15 kcal mol<sup>-1</sup>. These results are promising since we want our complexes to be as stable as possible and much more stable than the positive controls. This work takes us closer to finding treatments for the novel coronavirus. Currently, we are employing the structures of our most promising ligands, using those structures as base structures and making minor modifications to them, to work towards optimizing our own potential treatment.

Computational drug discovery for a protease inhibitor as a treatment for the coronavirus disease

ACS Spring Meeting 2021

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