Modeling of human SARS-CoV-2 / ACE2 peak complex identifies high affinity mutants that result in higher transmissibility

The coronavirus disease (COVID-19) epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread around the world. The virus infects more than 165 million people worldwide, of which more than 3.43 million have died. SARS-CoV-2 is a severe acute respiratory syndrome-related coronavirus (SARSr-CoV) virus that appears to be derived from zoonotic diseases and has a strong genetic affinity with bats. Coronavirus..

As the pandemic continued, SARS-CoV-2 evolved, Advanced proteinThe part of the virus that locks onto the cell and infects the cell, increasing the virus’s ability to bind to human cells and escape antibodies. As a public health measure, efficient screening methods are needed to determine the functional effects of novel sequence variants.

New York University researchers have found that structural modeling of the SARS-CoV-2 peplomer, which binds to the human angiotensin converting enzyme 2 (ACE2) receptor, is the first host cell invasion step, with improved binding affinities. We have shown to predict the combination of new variants of. This means that the new computational method can identify high affinity mutations and efficiently assess peplomer and ACE2 mutations.

Studies published in Journal of Molecular Biology, Shows the potential to detect potential new variants that can cause COVID-19 to spread faster. The recent mutations and mutations detected have caused the infection to spread rapidly in many countries. The search for combinations of potential mutations can be a tool to predict future combinations and at the same time prevent them early.

SARS-CoV-2 mutation

In SARS-CoV-2, the peplomer functions as the key for the virus to bind and invade human cells. Several structural proteins are integrated into the viral envelope. The S protein contains the S1 and S2 subunits. Unit S1 has a receptor binding domain (RBD), and S2 anchors the peplomer to the viral envelope.

Most coronaviruses, including SARS-CoV-2, use RBD to bind to the human angiotensin converting enzyme 2 receptor (ACE2) and stimulate host cell fusion to invade the host cell. I go. It is also the peplomer which mutates.

Understanding viral mutations influences how scientists assess virus-host interactions and develop intervention strategies.

In viral epidemics, mutations occur that allow the virus to escape the immune system. Recent changes during the COVID-19 pandemic have led to an increase in cases. The UK, Brazil, South Africa and India have all seen an increase in cases due to the emergence of SARS-CoV-2 variants, which made it difficult for vaccination to be successful.

Analysis of the genomic sequence of SARS-CoV-2 suggests thousands of mutations, but their health effects remain uncertain. It is essential to develop a method capable of efficiently detecting the COVID-19 mutation, which is useful as a monitoring tool for newly emerged strains. It also helps in the development of new vaccines.

Advanced RBD High Affinity Mutations and Antibody Binding Sites. (A) Structure of WT SRBD in which three overlap Neutralizing antibody Structure (C121, 7K8X; C135, 7K8Z; STE90-C11, 7B3O). Residues that should contain high affinity mutants and rapidly spreading mutations are highlighted, indicating that mutations in the antibody binding site may reduce their effectiveness. The linked C135 and STE90-C11 antibody structures partially overlap. (B) Mutant antibody prolapse measured using the total prolapse fraction, i.e. the sum of all prolapse fractions across the antibodies tested using deep mutagenesis. (C) Summary of significant high affinity mutations in S and hACE2 proteins and their functional implications.

Screening for mutations

The researchers applied a structural modeling approach to more efficiently screen a large number of SARS-CoV-2 S-ACE2 mutant complexes to achieve their results. They calculated the binding affinity, which has been shown to be a reliable measure of the likelihood of a virus infecting a host cell. The new approach aims to bridge the gap between sequence-based analysis and laboratory confirmation of mutations.

The study also showed that structural modeling of the S protein that binds to the ACE2 receptor helps predict the combination of many new mutants with improved binding affinities.

By focusing on natural variants of the Spike-ACE2 interface and studying over 700 mutant complexes, researchers tend to collect high affinity Spike mutations near known human ACE2 recognition sites. I made it clear that there was. The team applied structural analysis to highly contagious mutants and found that circulation point mutations such as N501Y, E484K, and S477N form high affinity complexes.

The team also noted that when the predicted affinity and available data on antibody leaks were merged, rapidly spreading mutants would take advantage of combinatorial mutations with improved antibody affinity and resistance. They studied single, double and triple mutations in the important tip interface region. Model analysis shows tip variants S477N, N501Y and S477N + E484K and E484K + N501Y. It is a rapidly spreading double mutant found in the US, UK, Brazil and South Africa with enhanced binding to the ACE2 receptor.

The results showed that the E484K and E484Q mutations found in rapidly spreading mutants can bind more strongly to the ACE2 receptor.

“Interestingly, our model predicts that the K417T / E484K / N501Y triple mutations occurring in the ancestral strain E484K / N501Y have almost the same affinity as WT (wild type). The frequency is increasing all over the world, ”the researchers explain. This has been discussed.

Based on the research results, the team may be able to help predict the structural modeling of new emerging mutants to predict which mutations may pose the greatest threat in the current global health crisis. Suggested that there is.

Modeling of human SARS-CoV-2 / ACE2 peak complex identifies high affinity mutants that result in higher transmissibility

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About Gail Mena

Gail Mena

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