Author: Xiaoqiang Huang; Robin Pearce; Yang Zhang
Title: Computational Design of Peptides to Block Binding of the SARS-CoV-2 Spike Protein to Human ACE2 Document date: 2020_3_31
ID: imkeghfd_25
Snippet: . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.28.013607 doi: bioRxiv preprint ( Figure 2C ), which was much higher than the sequence recapitulation rate obtained for the protein surface residues during the benchmarking of EvoEF2 18 . Although the peptide residues were considered to be highly exposed, .....
Document: . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.28.013607 doi: bioRxiv preprint ( Figure 2C ), which was much higher than the sequence recapitulation rate obtained for the protein surface residues during the benchmarking of EvoEF2 18 . Although the peptide residues were considered to be highly exposed, the high sequence identity revealed that a large number of critical binding residues should be correctly predicted, indicating that the designed peptides are reasonable.
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