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Computer-Based Modeling Can Predict Mutation “Hotspots” and Antibody Escapers in SARS-CoV-2 Spike Protein
Study Identifies Structural Basis of Spike Protein Mutations with Stronger Binding and Antibody Resistance, Which May Explain Transmissibility of New COVID-19 Variants
Computational modeling shows that mutations on SARS-CoV-2’s spike protein that enhance the virus’ ability to bind to the ACE2 receptor occur in two clusters or mutation “hotspots.” Image courtesy of Hin Hark Gan and Kristin Gunsalus, NYU’s Department of Biology
SARS-CoV-2 has evolved to acquire mutations on the spike protein-the part of the virus that protrudes from its surface and latches onto cells to infect them-that enhance the coronavirus’ ability to bind to human cells or evade antibodies. A new study from the Centers for Genomics and Systems Biology at New York University and NYU Abu Dhabi uses computational modeling to assess the biological significance of spike protein mutations, uncovering versions of the virus that bind more tightly or resist antibodies and offering a promising public health surveillance tool.