A computer simulation of the H1N1 influenza virus at 160 million atomic resolution. Credit: Lorenzo Casalino / Amaro Lab / UC San Diego
The dynamic movements of H1N1 proteins reveal previously unknown vulnerabilities.
The World Health Organization reports that there are approximately 1 billion cases of influenza each year, with 3-5 million severe cases and as many as 650,000 influenza-related respiratory deaths worldwide. To be effective, seasonal influenza vaccines must be updated annually with circulating virus strains. If the vaccine matches the circulating strain, it offers substantial protection. However, vaccine protection may be limited if the vaccine and virus strain do not match.
Hemagglutinin (HA) and neuraminidase (NA) glycoproteins are major targets of influenza vaccines. The HA protein facilitates viral attachment to the host cell, while the NA protein acts as a pincer to detach HA from the cell membrane, allowing viral replication. Despite previous studies on the properties of these glycoproteins, a complete understanding of their movements does not exist.
Researchers at the University of California, San Diego have created the first atomic-level computer model of the H1N1 virus. This model reveals new vulnerabilities through glycoprotein ‘breathing’ and ’tilting’ movements. This work, published in ACS Central Sciencesuggesting possible strategies for the design of future vaccines and antiviral agents against influenza.
“When I first saw how dynamic these glycoproteins were, how much respiration and tilt they had, I really thought there was something wrong with the simulation,” said the project’s principal investigator. said Rommie Amaro, Distinguished Professor of Chemistry and Biochemistry. “Once we knew our model was correct, we realized the great potential of this discovery. can be used for
Traditionally, influenza vaccines have targeted the head of the HA protein and, based on static images, showed a tight conformation in which the protein hardly moves. and revealed respiratory motility that exposes unknown sites of immune response known as epitopes.
Computer model of the H1N1 influenza virus – 160 million atoms detail.Credit: University of California, San Diego
The findings complemented previous work by one of the paper’s co-authors, Ian A. Wilson, Hansen Professor of Structural Biology at the Scripps Research Institute. Binds to parts of the protein that do not appear to be exposed. This suggests that the glycoprotein is more dynamic than previously thought, giving the antibody the opportunity to attach. I was.
The NA protein also showed atomic-level movements with head-tilting movements. This provided important insight to co-authors Julia Lederhofer and her Kanekiyo Masaru at the National Institute of Allergy and Infectious Diseases.when they saw recovery[{” attribute=””>plasma — that is, plasma from patients recovering from the flu — they found antibodies specifically targeting what is called the “dark side” of NA underneath the head. Without seeing the movement of NA proteins, it wasn’t clear how the antibodies were accessing the epitope. The simulations Amaro’s lab created showed an incredible range of motion that gave insight into how the epitope was exposed for antibody binding.
The H1N1 simulation Amaro’s team created contains an enormous amount of detail — 160 million atoms worth. A simulation of this size and complexity can only run on a few select machines in the world. For this work, the Amaro lab used Titan at Oak Ridge National Lab, formerly one of the largest and fastest computers in the world.
Amaro is making the data available to other researchers who can uncover even more about how the influenza virus moves, grows, and evolves. “We’re mainly interested in HA and NA, but there are other proteins, the M2 ion channel, membrane interactions, glycans, and so many other possibilities,” Amaro stated. “This also paves the way for other groups to apply similar methods to other viruses. We’ve modeled SARS-CoV-2 in the past and now H1N1, but there are other flu variants, MERS, RSV, HIV — this is just the beginning.”
Reference: “Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities” by Lorenzo Casalino, Christian Seitz, Julia Lederhofer, Yaroslav Tsybovsky, Ian A. Wilson, Masaru Kanekiyo and Rommie E. Amaro, 8 December 2022, ACS Central Science.
DOI: 10.1021/acscentsci.2c00981
The study was funded by the National Institutes of Health, the National Science Foundation, the US Department of Energy, and the National Science Foundation.
