Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure

The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the viral spike. Because of the high density of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies. We offer here a geometry-based approach to predict an...

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Bibliographic Details
Main Author: Amitai, Assaf (Author)
Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor)
Format: Article
Language:English
Published: Public Library of Science (PLoS), 2022-01-12T14:11:20Z.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Amitai, Assaf  |e author 
100 1 0 |a Massachusetts Institute of Technology. Institute for Medical Engineering & Science  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Department of Chemical Engineering  |e contributor 
245 0 0 |a Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure 
260 |b Public Library of Science (PLoS),   |c 2022-01-12T14:11:20Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/138891.2 
520 |a The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the viral spike. Because of the high density of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies. We offer here a geometry-based approach to predict and rank the probability of surface residues of SARS spike (S protein) and influenza H1N1 spike (hemagglutinin) to acquire antibody-escaping mutations utilizing in-silico models of viral structure. We used coarse-grained MD simulations to estimate the on-rate (targeting) of an antibody model to surface residues of the spike protein. Analyzing publicly available sequences, we found that spike surface sequence diversity of the pre-pandemic seasonal influenza H1N1 and the sarbecovirus subgenus highly correlates with our model prediction of antibody targeting. In particular, we identified an antibody-targeting gradient, which matches a mutability gradient along the main axis of the spike. This identifies the role of viral surface geometry in shaping the evolution of circulating viruses. For the 2009 H1N1 and SARS-CoV-2 pandemics, a mutability gradient along the main axis of the spike was not observed. Our model further allowed us to identify key residues of the SARS-CoV-2 spike at which antibody escape mutations have now occurred. Therefore, it can inform of the likely functional role of observed mutations and predict at which residues antibody-escaping mutation might arise. 
520 |a National Institutes of Health (Grant 2U19AI057229-16) 
546 |a en 
655 7 |a Article 
773 |t 10.1371/journal.pcbi.1009664 
773 |t PLOS Computational Biology