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10.1021/acs.jcim.0c00679

http://scihub22266oqcxt.onion/10.1021/acs.jcim.0c00679
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32786709!ä!32786709

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suck abstract from ncbi


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pmid32786709      J+Chem+Inf+Model 2020 ; 60 (12): 5794-5802
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  • Computational Prediction of Mutational Effects on SARS-CoV-2 Binding by Relative Free Energy Calculations #MMPMID32786709
  • Zou J; Yin J; Fang L; Yang M; Wang T; Wu W; Bellucci MA; Zhang P
  • J Chem Inf Model 2020[Dec]; 60 (12): 5794-5802 PMID32786709show ga
  • The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the "hotspot" residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis and also provide useful information for the design of antiviral drugs.
  • |Amino Acid Sequence[MESH]
  • |Angiotensin-Converting Enzyme 2/*metabolism[MESH]
  • |Binding Sites[MESH]
  • |COVID-19/*metabolism[MESH]
  • |Humans[MESH]
  • |Molecular Dynamics Simulation[MESH]
  • |Mutagenesis/genetics[MESH]
  • |Mutation[MESH]
  • |Protein Binding[MESH]
  • |Protein Conformation[MESH]
  • |SARS-CoV-2/*metabolism[MESH]
  • |Spike Glycoprotein, Coronavirus/*genetics/*metabolism[MESH]


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