![]() To evade immune memory, influenza spike, hemagglutinin (HA), rapidly acquires mutations from one year to the next. A major pandemic event occurred in 2009 when the H1N1 influenza A virus performed a zoonotic shift from swine to humans. Ab escape is common in other RNA viruses such as the influenza virus, which causes seasonal epidemics and occasional pandemics. Others, such as N501Y and E484K are associated with escape from Ab response. One mutation at the spike (D614G) is now widespread and is thought to support a high viral growth rate. Since its zoonotic shift, SARS-CoV-2 acquired several key mutations. These therapeutic approaches have been successful in eliciting strong Ab and T cell response against the virus and in particular, Abs against the receptor-binding domain (RBD) of the spike, which have been shown to have neutralization and protective capabilities. The spike, a class I fusion glycoprotein, mediates entry to the host cell by binding to the angiotensin-converting enzyme 2 (ACE2) receptor and is the main target of Ab response. Almost all vaccination approaches aimed to use the glycoproteins or spike protein (S) of the virus in its trimeric form or vaccinate with the full (inactivated) virus. In response to the SARS-CoV-2 pandemic, many approaches for antibody (Ab) therapies, and vaccines have been explored. One result of such proofreading activity is that CoVs genomes are less mutable compared to other RNA viruses, and thus the sequence diversity of SARS-CoV-2 is quite low. Nonstructural protein 14 (nsp14), a subunit of the replicase polyprotein encoded by CoVs is thought to provide a form of proofreading activity, which could support the expansion of large CoVs genomes to their current size. Ĭoronaviruses (CoVs) have the largest genomes among RNA viruses. ![]() It is a member of the betacoronaviruses family, related to coronaviruses found in bats, and to SARS CoV which causes severe respiratory syndrome. The virus emerged as a result of a zoonotic shift. The COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, is one of the most challenging global health crises of the century. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. įunding: A.A was supported by the National Institutes of Health, grant number 2U19AI057229-16. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and its Supporting Information files. Received: DecemAccepted: NovemPublished: December 13, 2021Ĭopyright: © 2021 Assaf Amitai. PLoS Comput Biol 17(12):Įditor: Becca Asquith, Imperial College London, UNITED KINGDOM Therefore, it can inform of the likely functional role of observed mutations and predict at which residues antibody-escaping mutation might arise.Ĭitation: Amitai A (2021) Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure. Our model further allowed us to identify key residues of the SARS-CoV-2 spike at which antibody escape mutations have now occurred. For the 2009 H1N1 and SARS-CoV-2 pandemics, a mutability gradient along the main axis of the spike was not observed. This identifies the role of viral surface geometry in shaping the evolution of circulating viruses. ![]() In particular, we identified an antibody-targeting gradient, which matches a mutability gradient along the main axis of the spike. 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. We used coarse-grained MD simulations to estimate the on-rate (targeting) of an antibody model to surface residues of the spike protein. 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. Because of the high density of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies. The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the viral spike.
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