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10.3390/molecules25215172

http://scihub22266oqcxt.onion/10.3390/molecules25215172
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33172092!7664330!33172092
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suck abstract from ncbi

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  • Drugs Repurposing Using QSAR, Docking and Molecular Dynamics for Possible Inhibitors of the SARS-CoV-2 M(pro) Protease #MMPMID33172092
  • Tejera E; Munteanu CR; Lopez-Cortes A; Cabrera-Andrade A; Perez-Castillo Y
  • Molecules 2020[Nov]; 25 (21): ä PMID33172092show ga
  • Wuhan, China was the epicenter of the first zoonotic transmission of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) in December 2019 and it is the causative agent of the novel human coronavirus disease 2019 (COVID-19). Almost from the beginning of the COVID-19 outbreak several attempts were made to predict possible drugs capable of inhibiting the virus replication. In the present work a drug repurposing study is performed to identify potential SARS-CoV-2 protease inhibitors. We created a Quantitative Structure-Activity Relationship (QSAR) model based on a machine learning strategy using hundreds of inhibitor molecules of the main protease (M(pro)) of the SARS-CoV coronavirus. The QSAR model was used for virtual screening of a large list of drugs from the DrugBank database. The best 20 candidates were then evaluated in-silico against the M(pro) of SARS-CoV-2 by using docking and molecular dynamics analyses. Docking was done by using the Gold software, and the free energies of binding were predicted with the MM-PBSA method as implemented in AMBER. Our results indicate that levothyroxine, amobarbital and ABP-700 are the best potential inhibitors of the SARS-CoV-2 virus through their binding to the M(pro) enzyme. Five other compounds showed also a negative but small free energy of binding: nikethamide, nifurtimox, rebimastat, apomine and rebastinib.
  • |Amobarbital/pharmacology[MESH]
  • |Antiviral Agents/chemistry/*pharmacology[MESH]
  • |Binding Sites[MESH]
  • |COVID-19/*drug therapy[MESH]
  • |Computer Simulation[MESH]
  • |Coronavirus 3C Proteases/*antagonists & inhibitors[MESH]
  • |Drug Discovery/*methods[MESH]
  • |Drug Repositioning/*methods[MESH]
  • |Humans[MESH]
  • |Machine Learning[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Molecular Dynamics Simulation[MESH]
  • |Pandemics[MESH]
  • |Protease Inhibitors/chemistry/*pharmacology[MESH]
  • |Protein Binding[MESH]
  • |Quantitative Structure-Activity Relationship[MESH]
  • |SARS-CoV-2/drug effects/*enzymology[MESH]
  • |Small Molecule Libraries/chemistry[MESH]
  • |Software[MESH]
  • |Thermodynamics[MESH]
  • |Thyroxine/pharmacology[MESH]


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  • suck abstract from ncbi

    ä 21.25 2020