Author: Thomas Desautels; Adam Zemla; Edmond Lau; Magdalena Franco; Daniel Faissol
Title: Rapid in silico design of antibodies targeting SARS-CoV-2 using machine learning and supercomputing Document date: 2020_4_10
ID: kg2j0dqy_28
Snippet: The Supplementary Materials to this document include (1) the 10 homology-based structural models we developed of SARS-CoV-2 in complex with SARS-CoV-1 neutralizing antibodies and (2) all antibody mutant sequences and in silico free energy calculations performed for 89,263 mutant antibodies derived from the M396 SARS-CoV-1 neutralizing antibody, which we used to select a first round of 20 candidate antibodies for experimental evaluation......
Document: The Supplementary Materials to this document include (1) the 10 homology-based structural models we developed of SARS-CoV-2 in complex with SARS-CoV-1 neutralizing antibodies and (2) all antibody mutant sequences and in silico free energy calculations performed for 89,263 mutant antibodies derived from the M396 SARS-CoV-1 neutralizing antibody, which we used to select a first round of 20 candidate antibodies for experimental evaluation.
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