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_27
Snippet: These 20 antibody designs are now being expressed and experimentally tested for binding to SARS-CoV-2 spike protein, which will provide invaluable feedback to further improve the machine learning-driven designs. We are also continually improving our platform and performing additional in silico calculations, which will be included in future updates to this document. In addition, we are currently (1) performing higher fidelity molecular dynamics ca.....
Document: These 20 antibody designs are now being expressed and experimentally tested for binding to SARS-CoV-2 spike protein, which will provide invaluable feedback to further improve the machine learning-driven designs. We are also continually improving our platform and performing additional in silico calculations, which will be included in future updates to this document. In addition, we are currently (1) performing higher fidelity molecular dynamics calculations to increase the accuracy of predictions using [26, 27] , (2) investigating binding "hotspots" via single point mutation computational analysis, and (3) exploring any potential impacts from glycosylation at the RBD site.
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