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  • Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs #MMPMID33051297
  • Li Z; Li X; Huang YY; Wu Y; Liu R; Zhou L; Lin Y; Wu D; Zhang L; Liu H; Xu X; Yu K; Zhang Y; Cui J; Zhan CG; Wang X; Luo HB
  • Proc Natl Acad Sci U S A 2020[Nov]; 117 (44): 27381-27387 PMID33051297show ga
  • The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (M(pro)). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE-based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 M(pro) The most potent one is dipyridamole (inhibitory constant Ki = 0.04 microM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki = 0.36 microM) and chloroquine (Ki = 0.56 microM) were also found to potently inhibit SARS-CoV-2 M(pro) We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts.
  • |*Drug Repositioning[MESH]
  • |Antiviral Agents/*pharmacology[MESH]
  • |Betacoronavirus/*drug effects[MESH]
  • |COVID-19[MESH]
  • |Chloroquine/pharmacology[MESH]
  • |Coronavirus 3C Proteases[MESH]
  • |Coronavirus Infections/drug therapy[MESH]
  • |Cysteine Endopeptidases[MESH]
  • |Dipyridamole/pharmacology[MESH]
  • |Humans[MESH]
  • |Hydroxychloroquine/pharmacology[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Molecular Structure[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/drug therapy[MESH]
  • |Protease Inhibitors/*pharmacology[MESH]
  • |SARS-CoV-2[MESH]
  • |Viral Nonstructural Proteins/*antagonists & inhibitors[MESH]

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  • suck abstract from ncbi

    27381 44.117 2020