A computational study shows that dozens of mutations help the virus’ spike protein evade antibodies that target SARS-CoV-2
Massachusetts Institute of Technology
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.ength.
