PropertyValue
?:abstract
  • 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
is ?:annotates of
?:creator
?:license
  • unk
?:publication_isRelatedTo_Disease
?:source
  • WHO
?:title
  • Rapid Prediction of Possible Inhibitors for SARS-CoV-2 Main Protease using Docking and FPL Simulations
?:type
?:who_covidence_id
  • #400
?:year
  • 2020

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