Rapid Prediction of Possible Inhibitors for SARS-CoV-2 Main Protease using Docking and FPL Simulations
2020
Appearance for the first time from Wuhan, China, the SARS-CoV-2
rapidly outbreaks worldwide and causes a serious global health issue. The
effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this
work, we have tried to rapidly predict a list of potential inhibitors for
SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and
fast pulling of ligand (FPL) simulations. The approaches were initially
validated over a set of eleven available inhibitors. Both Autodock Vina and FPL
calculations adopted good consistent results with the respective experiment
with correlation coefficients of R_Dock=0.72 ± 0.14 and R_W = -0.76 ± 0.10, respectively. The combined approaches were
then utilized to predict possible inhibitors, which were selected from a ZINC15
sub-database, for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able
to bind well to SARS-CoV-2 Mpro. The obtained results probably lead to enhance
COVID-19 therapy.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
0
References
0
Citations
NaN
KQI