Objective: Recent pandemic caused by the SARS-CoV-2, first described in Wuhan city of
China in December 2019, spread widely in almost all the countries of the world. Coronavirus
(COVID-19) led to the unexpected death of many people and caused a severe economic loss in a
number of countries. Virtual screening based on molecular docking, drug-likeness prediction, and in
silico ADMET studies are some of the effective tools for the identification of small molecules as novel
antiviral drugs to treat diseases.
Methods: In the current study, virtual screening was performed through molecular docking for identifying
potent inhibitors against Mpro enzyme from the ZINC library for the possible treatment of the
COVID-19 pandemic. Interestingly, some compounds have been identified as possible anti-covid-19
agents for future research. A total of 350 compounds were screened based on their similarity score
with reference compound X77 from ZINC data bank and were subjected to docking with crystal structure
available of Mpro enzyme. These compounds were then filtered by their in silico ADME-Tox and
drug-likeness prediction values.
Results: Out of these 350 screened compounds, 10 compounds were selected based on their docking
score and best-docked pose in comparison to the reference compound X77. In silico ADME-Tox and
drug likeliness predictions of the top compounds were performed and showed excellent results. All the
10 screened compounds showed a significant binding pose with the target main protease (Mpro) enzyme
and satisfactory pharmacokinetic and toxicological properties.
Conclusion: Based on these results, it is suggested that the identified compounds may be considered
for therapeutic development against the COVID-19 virus and can further be evaluated for in vitro activity,
preclinical, clinical studies, and formulated in a suitable dosage form to maximize their bioavailability.