How Omicron escapes from antibodies
A computational study shows that dozens of mutations help the virus'
spike protein evade antibodies that target SARS-CoV-2

Date:
February 1, 2022
Source:
Massachusetts Institute of Technology
Summary:
Dozens of mutations in the spike protein of the Omicron variant help
it to evade all four of the classes of antibodies that can target
SARS-CoV- 2, according to a new study. This includes antibodies
generated by the immune systems of vaccinated or previously infected
people, as well as most of the monoclonal antibody treatments that
have been developed.



FULL STORY ==========================================================================
A new study from MIT suggests that the dozens of mutations in the spike
protein of the Omicron variant help it to evade all four of the classes
of antibodies that can target the SARS-CoV-2 virus that causes Covid-19.


==========================================================================
This includes antibodies generated by vaccinated or previously infected
people, as well as most of the monoclonal antibody treatments that have
been developed, says Ram Sasisekharan, the Alfred H. Caspary Professor
of Biological Engineering and Health Sciences and Technology (HST) at MIT.

Using a computational approach that allowed them to determine how mutated
amino acids of the viral spike protein influence nearby amino acids,
the researchers were able to get a multidimensional view of how the
virus evades antibodies.

According to Sasisekharan, the traditional approach of only examining
changes in the virus' genetic sequence reduces the complexity of the
spike protein's three-dimensional surface and doesn't describe the multidimensional complexity of the protein surfaces that antibodies are attempting to bind to.

"It is important to get a more comprehensive picture of the many mutations
seen in Omicron, especially in the context of the spike protein,
given that the spike protein is vital for the virus's function, and
all the major vaccines are based on that protein," he says. "There is
a need for tools or approaches that can rapidly determine the impact of mutations in new virus variants of concern, especially for SARS-CoV-2." Sasisekharan is the senior author of the study, which appears this week in
Cell Reports Medicine. The lead author of the paper is MIT HST graduate
student Nathaniel Miller. Technical associate Thomas Clark and research scientist Rahul Raman are also authors of the paper.

Even though Omicron is able to evade most antibodies to some degree,
vaccines still offer protection, Sasisekharan says.



========================================================================== "What's good about vaccines is they don't just generate B cells, which
produce the monoclonal [antibody] response, but also T cells, which
provide additional forms of protection," he says.

Antibody escape After the Omicron variant emerged last November,
Sasisekharan and his colleagues began to analyze its trimeric spike
protein using a network-based computational modeling method they had
originally developed several years ago to study the hemagglutinin spike
protein on flu viruses. Their technique allows them to determine how
mutations in the genetic sequence are related in the three-dimensional
space through a network of inter-amino-acid interactions that critically
impact the structure and function of the viral protein.

The researchers' approach, known as amino acid interaction network
analysis, evaluates how one mutated amino acid can influence nearby
amino acids depending on how "networked" they are -- a measure of how
much a given amino acid interacts with its neighbors. This yields
richer information than simply examining individual changes in the one-dimensional amino acid sequence space, Sasisekharan says.

"With the network approach, you're looking at that amino acid
residue in the context of its neighborhood and environment," he
says. "When we started to move away from the one-dimensional sequence
space toward multidimensional network space, it became evident that
critical information about the interaction of an amino acid in its three-dimensional environment in the protein structure is lost when you
look at just the one-dimensional sequence space." Sasisekharan's lab
has previously used this technique to determine how mutations in the hemagglutinin protein of an avian flu virus could help it to infect
people. In that study, he and his laboratory identified mutations that
could change the structure of hemagglutinin so that it could bind to
receptors in the human respiratory tract.



==========================================================================
When Omicron emerged, with about three dozen mutations on the spike
protein, the researchers decided to rapidly use their method to study
the variant's ability to evade human antibodies. They focused their
analysis on the receptor binding domain (RBD), which is the part of
the spike protein targeted by antibodies. The RBD is also the part of
the viral protein that attaches to human ACE2 receptors and allows the
virus to enter cells.

Using their network modeling approach, the researchers studied how each
of the mutations on the RBD changes the protein's shape and affect
its interactions with four classes of human antibodies that target
SARS-CoV-2. Class 1 and 2 antibodies target the RBD site that binds to
the ACE2 receptor, while class 3 and 4 antibodies bind to other parts
of the RBD.

The researchers compared the Omicron variant to the original SARS-CoV-2
virus, as well as the Beta and Delta variants. The Beta and Delta
variants have mutations that help them evade class 1 and 2 antibodies,
but not class 3 and 4.

Omicron, on the other hand, has mutations that affect the binding of
all four classes of antibodies.

"With Omicron you can see a significant number of sites being perturbed compared to Beta and Delta," Sasisekharan says. "From the original strain
to the Beta strain, and then the Delta strain, there is a general trend
towards a greater ability to escape." Those perturbations allow the
virus to evade not only antibodies generated by vaccination or previous SARS-CoV-2 infection, but also many of the monoclonal antibody treatments
that pharmaceutical companies have developed.

As patients began to appear with Omicron infections, researchers and pharmaceutical companies sought to guide treatment by predicting which antibodies were most likely to retain their efficacy against the new
variant.

Based on their one-dimensional sequence and single point mutation
analyses, pharmaceutical companies believed that their monoclonal
antibodies were likely to bind Omicron and not lose any potency. However,
when experimental data became available, the Omicron variant was found to substantially escape from monoclonal antibodies known as ADG20, AZD8895,
and AZD1061, as predicted by the network analyses in this study, while
the activity of monoclonal antibody S309 was also reduced by threefold.

Additionally, the study revealed that some of the mutations in the Omicron variant make it more likely that the RBD will exist in a configuration
that makes it easier to grab onto the ACE2 receptor, which may contribute
to its enhanced transmissibility.

The researchers plan to use the tools described in this paper to analyze
future variants of concern that may emerge.

Vaccine targets The findings from the new study could help to identify
regions of the RBD that could be targeted with future vaccines and
therapeutic antibodies. The Sasisekharan lab has previously engineered
a therapeutic antibody that potently and specifically neutralized the
Zika virus by targeting a highly networked envelope surface protein of
the Zika virus. Sasisekharan hopes to identify RBD sites where mutations
would be harmful to the SARS-CoV-2 virus, making it harder for the virus
to escape antibodies that target those regions.

"Our hope is that as we understand the viral evolution, we're able to
hone in on regions where we think that any perturbation would cause
instability to the virus, so that they would be the Achilles heels,
and more effective sites to target," he says.

To create more effective antibody treatments, Sasisekharan believes
it may be necessary to develop cocktails of antibodies that target
different parts of the spike protein. Those combinations would likely
need to include class 3 and 4 antibodies, which appear to offer fewer
escape routes for the virus to evade them, he says.

The research was funded by the National Institutes of Health and the
Singapore- MIT Alliance for Research and Technology.

========================================================================== Story Source: Materials provided by
Massachusetts_Institute_of_Technology. Original written by Anne
Trafton. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Nathaniel L. Miller, Thomas Clark, Rahul Raman, Ram Sasisekharan.

Insights on the mutational landscape of the SARS-CoV-2 Omicron
variant receptor binding domain. Cell Reports Medicine, 2022;
100527 DOI: 10.1016/j.xcrm.2022.100527 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220201143956.htm

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