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10.3390/molecules27030683

http://scihub22266oqcxt.onion/10.3390/molecules27030683
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35163948!8838031!35163948
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suck abstract from ncbi


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pmid35163948      Molecules 2022 ; 27 (3): ä
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  • DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design #MMPMID35163948
  • Liu Y; Gan J; Wang R; Yang X; Xiao Z; Cao Y
  • Molecules 2022[Jan]; 27 (3): ä PMID35163948show ga
  • Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target proteins from 181 CADD publications. We performed unified docking simulations and neck-to-neck comparison with the solved co-crystal structures. We computed their chemical features and classified these compounds, aiming to provide insights for subsequent drug design. Through detailed analyses, we recommended a batch of compounds that are worth further study. Moreover, we organized all the abundant data and constructed a freely available database, DrugDevCovid19, to facilitate the development of COVID-19 therapeutics.
  • |*COVID-19 Drug Treatment[MESH]
  • |*Drug Design[MESH]
  • |Antiviral Agents/*chemistry/therapeutic use[MESH]
  • |Databases, Pharmaceutical[MESH]
  • |Drug Development[MESH]
  • |Humans[MESH]
  • |Models, Molecular[MESH]


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