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suck abstract from ncbi


10.1002/ddr.21757

http://scihub22266oqcxt.onion/10.1002/ddr.21757
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33170521!?!33170521

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suck abstract from ncbi

pmid33170521      Drug+Dev+Res 2021 ; 82 (3): 374-392
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  • Step toward repurposing drug discovery for COVID-19 therapeutics through in silico approach #MMPMID33170521
  • Marak BN; Dowarah J; Khiangte L; Singh VP
  • Drug Dev Res 2021[May]; 82 (3): 374-392 PMID33170521show ga
  • The outbreak of SARS-CoV-2 has become a threat to global health and has led to a global economic crisis. Although the researchers worldwide are putting tremendous effort toward gaining more insights into this zoonotic virus and developing vaccines and therapeutic drugs, no vaccine or drug is yet available to combat COVID-19 effectively. Drug discovery is often a laborious, time-consuming, and expensive task. In this time of crisis, employing computational methods could provide a feasible alternative approach that can potentially be used for drug discovery. Therefore, a library of several antiparasitic and anti-inflammatory drugs was virtually screened against SARS-CoV-2 proteases to identify potential inhibitors. The identified inhibitory drugs were further analyzed to confirm their activities against SARS-CoV-2. Our results could prove to be helpful in repurposing the drug discovery approach, which could substantially reduce the expenses, time, and resources required.
  • |*COVID-19 Drug Treatment[MESH]
  • |Anti-Inflammatory Agents/therapeutic use[MESH]
  • |Antiparasitic Agents/therapeutic use[MESH]
  • |Antiviral Agents/pharmacology[MESH]
  • |Computational Biology[MESH]
  • |Computer Simulation[MESH]
  • |Drug Discovery/*trends[MESH]
  • |Drug Repositioning/*trends[MESH]
  • |Humans[MESH]
  • |Models, Molecular[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Protease Inhibitors[MESH]
  • |Receptors, Virus/chemistry/drug effects/genetics[MESH]
  • |SARS-CoV-2/drug effects/genetics[MESH]
  • |Spike Glycoprotein, Coronavirus/antagonists & inhibitors[MESH]


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