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10.1002/minf.202060080

http://scihub22266oqcxt.onion/10.1002/minf.202060080
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33904240!8206717!33904240
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suck abstract from ncbi


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pmid33904240      Mol+Inform 2021 ; 40 (6): e2060080
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  • Targeting SARS-CoV-2 Spike Protein/ACE2 Protein-Protein Interactions: a Computational Study #MMPMID33904240
  • Pirolli D; Righino B; De Rosa MC
  • Mol Inform 2021[Jun]; 40 (6): e2060080 PMID33904240show ga
  • The spike glycoprotein (S) of the SARS-CoV-2 virus surface plays a key role in receptor binding and virus entry. The S protein uses the angiotensin converting enzyme (ACE2) for entry into the host cell and binding to ACE2 occurs at the receptor binding domain (RBD) of the S protein. Therefore, the protein-protein interactions (PPIs) between the SARS-CoV-2 RBD and human ACE2, could be attractive therapeutic targets for drug discovery approaches designed to inhibit the entry of SARS-CoV-2 into the host cells. Herein, with the support of machine learning approaches, we report structure-based virtual screening as an effective strategy to discover PPIs inhibitors from ZINC database. The proposed computational protocol led to the identification of a promising scaffold which was selected for subsequent binding mode analysis and that can represent a useful starting point for the development of new treatments of the SARS-CoV-2 infection.
  • |*COVID-19 Drug Treatment[MESH]
  • |Angiotensin-Converting Enzyme 2/*metabolism[MESH]
  • |Antiviral Agents/chemistry/*pharmacology[MESH]
  • |COVID-19/metabolism[MESH]
  • |Drug Delivery Systems[MESH]
  • |Drug Discovery[MESH]
  • |Host-Pathogen Interactions/drug effects[MESH]
  • |Humans[MESH]
  • |Machine Learning[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Protein Interaction Maps/*drug effects[MESH]
  • |SARS-CoV-2/*drug effects/physiology[MESH]
  • |Spike Glycoprotein, Coronavirus/*metabolism[MESH]


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