Massive Virtual screening and evaluation of small molecule inhibitors of
the Papain-like protease of SARS-CoV-2
In the face of the rapid emergence and spread of new variants of the
type 2 coronavirus causing acute respiratory syndrome, it is necessary
to seek new pharmacological treatments for the disease, especially for
patients infected by the new and more aggressive variants of the virus.
In the present work, we selected ~18,000 compounds with
similar structure to GRL0617 (Tanimoto index greater than 80 %) from
the PubChem database with ~109 million compounds.
Molecular docking was used to assess the affinity of the selected
compounds, in which GRL0617 was included as an internal control. Then,
based on the ligand efficacy index obtained as molecular docking, 500
compounds with higher affinity than GRL0617 for papain-like protease
were considered. Finally, based on ADME parameters within the acceptable
range for a drug, the seven best compounds were selected. Next, 200 ns
molecular dynamics simulation studies, ∆G calculations using generalized
Born and surface continuous solvation molecular dynamics, and quantum
mechanical calculations were performed with the selected candidates.
Using this In Silico protocol, seven papain-like protease inhibitors are
proposed: three compounds with binding free energy like GRL0617 (D28,
D04 and D59), three compounds with higher binding free energy than
GRL0617 (D60, D99 and D06) and one compound (D24) that binds to a region
of the enzyme that could block inhibition by the host immune system. The
compounds proposed in this study could be used for invitro testing or
smart drug design, accelerating the development of an effective
treatment for this disease.