New tool predicts changes that could make COVID variants more infectious

University Park, PA — As SARS-CoV-2 continues to evolve, it is expected that new variants will emerge that may infect the host and increase its ability to evade the host’s immune system. The first important step in infection is when the viral spike protein binds to the ACE2 receptor in human cells. Researchers at Pennsylvania State University have created a new framework that can predict amino acid changes in viral peplomer with reasonable accuracy. This improves binding to human cells and increases virus infectivity.

This tool allows computational monitoring of SARS-CoV-2 and may provide advance warning of potentially dangerous mutants with the potential for even higher binding affinities. This may help early implementation of public health measures to prevent the spread of the virus, and may even inform vaccine booster formulations.

Suresh Kuchipudi, clinical professor and deputy director of veterinary science and biomedicine at Penn State University’s Institute for Animal Diagnosis, said: “Therefore, it is important to proactively assess which amino acid changes may increase the infectivity of the virus. Our framework is that amino acid changes in the SARS-CoV-2 peplomer are human and It is a powerful tool for determining the effects that affect the ability of multiple animal species to bind to ACE2 receptors. “

Using a new two-step computational procedure, the team used a new two-step computational procedure in which amino acid throat changes (molecules linked together to form proteins) in the receptor binding domain (RBD) of SARS-CoV-2 peplomer proteins. I created a model that predicts what might happen. It affects its ability to bind to ACE2 receptors in human and other animal cells.

According to Kuchipudi, the variants currently in circulation contain one or more mutations that result in amino acid changes in the RBD of the peplomer.

“Changes in these amino acids may have led to fitness benefits and increased infectivity through a variety of mechanisms,” he said. “Increased binding affinity between the peplomer RBD and the human ACE2 receptor is one such mechanism.”

Kuchipudi explained that the peplomer that binds to the ACE2 receptor is the first important step in viral entry into cells.

“The binding strength between RBD and ACE2 has a direct impact on the dynamics of infection and potentially disease progression,” he said. “The ability to reliably predict the effects of viral amino acid changes on the ability of RBD to interact more strongly with the ACE2 receptor assesses its impact on public health and its potential for spillover and adaptation to humans and other animals. Helps to do. “

Costas D. Maranas, Professor Donald B. Broughton of the Faculty of Chemical Engineering, Pennsylvania State University, led the development of a new two-step procedure for the team. First, researchers tested the predictive power of a technique called molecular mechanics-generalized surface area (MM-GBSA) analysis to quantify the binding affinity of RBD for ACE2. MM-GBSA analysis summarizes multiple types of energy contributions associated with the viral RBD “attaching” to the human ACE2 receptor. Using data from existing variants, the team found that this approach could only partially predict the binding affinity of SARS-CoV-2’s RBD for ACE2.

Therefore, Maranas and the team considered using the energy term of the MM-GBSA analysis as a feature of a neural network regression model (a type of deep learning algorithm) and are ly available for coupling in a single variant. I trained the model using the data. Amino acids change. They found that changes in a particular amino acid could predict with greater than 80% accuracy whether changes in the studyed dataset improved or worsened the binding affinity.

“This combination of MM-GBSA and neural network model approach seems to be very effective in predicting the effects of amino acid changes that were not used during model training,” Maranas said. ..

The model was also able to predict the binding strength of various already observed changes in the SARS-CoV-2 amino acids found in the alpha, beta, gamma, and delta variants. This may provide a computational tool for predicting such affinities in variants that have not yet been discovered. Nonetheless, our computational tools can find amino acid changes that further enhance binding affinity, but have not yet been observed in circulating mutants. This may mean that such changes may interfere with other requirements for productive viral infections. Recall that binding to the ACE2 receptor is not a complete story.

NS Survey results announced today (September 29) Bulletin of the National Academy of Sciences.

“Our method sets up a framework for screening for changes in binding affinity due to changes in unknown single and multiple amino acids. Therefore, in terms of improving affinity and infectivity for ACE2. Provides a valuable tool for assessing currently circulating and future viral variants, “says Maranas.

Kuchipudi said: “SARS-CoV-2 can switch hosts as a result of increased contact between the virus and potential new hosts. This tool understands the vast amount of virus sequence data generated by genome monitoring. In particular, it can help determine if the virus can adapt and spread to agricultural animals, thereby notifying targeted mitigation measures. “

The co-lead authors of this treatise are Chen Chen, a postdoctoral fellow at Penn State University, and Veda Sheersh Boorla, a graduate student in chemical engineering. Other authors include Deepro Banerjee, a graduate research assistant at Pennsylvania State University. Ratur Choudhry, Ph.D. successor at Harvard University. Victoria S. Cavener, a researcher at the Hack Institute for Life Sciences, Pennsylvania State University. Ruth H. Nissly, Research Engineer, Veterinary Sciences and Biomedical Sciences, Pennsylvania State University. Abhinay Gontu, a graduate student in Veterinary and Biomedical Sciences, Pennsylvania State University. Nina R. Boyle, a graduate student in integrated and biomedical physiology at Pennsylvania State University. Kurt Vandegrift, Associate Professor of Biology, Pennsylvania State University. Meera Surendran Nair, an assistant clinical professor of veterinary and biomedical sciences at Pennsylvania State University.

The United States Department of Agriculture, the United States Department of Energy, and the Pennsylvania State University Hack Life Science Institute supported this study.