Discovery of potent Covid-19 main protease inhibitors using integrated drug-repurposing strategy

The emergence and rapid spreading of novel SARS-CoV-2 across the globe represent an imminent threat to public health. Novel antiviral therapies are urgently needed to overcome this pandemic. Given the significant role of the main protease of Covid-19 for virus replication, we performed a drug-repurposing study using the recently deposited main protease structure, 6LU7. For instance, pharmacophore- and e-pharmacophore-based hypotheses such as AARRH and AARR, respectively, were developed using available small molecule inhibitors and utilized in the screening of the DrugBank repository. Further, a hierarchical docking protocol was implemented with the support of the Glide algorithm. The resultant compounds were then examined for their binding free energy against the main protease of Covid-19 by means of the Prime-MM/GBSA algorithm. Most importantly, the machine learning-based AutoQSAR algorithm was used to predict the antiviral activities of resultant compounds. The hit molecules were also examined for their drug-likeness and toxicity parameters through the QikProp algorithm. Finally, the hit compounds activity against the main protease was validated using molecular dynamics simulation studies. Overall, the present analysis yielded two potential inhibitors (DB02986 and DB08573) that are predicted to bind with the main protease of Covid-19 better than currently used drug molecules such as N3 (cocrystallized native ligand), lopinavir, and ritonavir.

Automated summary

Through drug-repurposing study and machine learning-based algorithms, two potential inhibitors were identified in this research. These inhibitors are predicted to bind better with the main protease of Covid-19.