��������

KALAMAZOO, Mich.—Researchers in �������� Michigan University’s College of Engineering and Applied Sciences have conducted preliminary research studies using new methods that could help scientists create more effective vaccines for viral infections such as SARS-CoV-2, the cause of the COVID-19 pandemic.

In an as-yet unpublished paper titled “Structural Motifs, Disorder, and the Efficacy of Viral Vaccines” recently uploaded to the open access website , Dr. Robert Makin and Dr. Steve Durbin explain how they drew from nearly a decade of experience launched with a National Science Foundation grant to study semiconductor crystals used for electronics such as solar cells. For that original study, researchers grew crystals whose material properties can be varied predictably depending on how atoms exchanged places with one another. The amount of this “disorder” in the material, they found, can be structurally tailored with a high degree of accuracy. 

Durbin, a professor in the Department of Electrical and Computer Engineering, and Makin, a recent doctoral graduate and the latest paper’s lead author, hypothesized the original research project could be used to inform vaccine development.

“After that paper was published last year, we extended the range of experimental techniques that allow us to quantify disorder to include electron microscopy,” or high definition images at the most minute levels, says Durbin. “Enter COVID-19.”

The pair surmised that the concept of “structural motifs” they used in their study of disordered semiconductor crystals could be applied to viral vaccine development in pretrial studies and during the manufacturing process. The premise is that since viruses are by nature highly complicated in physical arrangement and behavior, there is some commonality with complex semiconductor crystals. Traditionally, scientists examine the entire set of protein structures of the virus to develop a vaccine. ��������’s research shows that a more detailed consideration of outer layer virus protein features, such as COVID-19’s characteristic stalks sprouting from a sphere, is warranted.

When examining the numbers, the structural motif method “turns out to be more important, maybe even critical,” to vaccine effectiveness predictability, Durbin says. “We were totally amazed by what we saw.” The evidence points to the need for matching what Durbin and Makin refer to as the “order parameter” of the vaccine to the corresponding virus.

Makin and Durbin are going even further with their findings. They’re also using a concept called an Ising model from applied physics to help them predict the deadliness of different viruses.

“When we apply the Ising model to different viruses within the same family, such as influenza, it shows a path to predicting how deadly an infection might be from a population perspective, as there’s a clear relationship between case fatality rate and order parameter,” Durbin says. “It’s classic Ising model behavior but applied to biology.”

The two have been “pretty astounded” by the results of their study, basically all of it conducted most recently “while holed up at home during the pandemic,” says Markin. They chose to post their work immediately so that others can use it to further refine and apply their research as it goes through the peer-review publication process.

This material is based upon work partially supported by the National Science Foundation under Grant No. 1410915. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

The paper on semiconductor crystals that led to the current work .

For more �������� news, arts and events, visit �������� News online.