Research to stop viral infections receives $1.2 million grant

Graduate student Albina Makio, left, and Anthony Nicola, right, a professor of Virology in the Department of Veterinary Microbiology and Pathology in the College of Veterinary Medicine at WSU, pose for a photo in their lab ( photo by College of Veterinary Medicine/Ted S. Warren).

A four-year $1.2 million grant funded by the National Institutes of Health is aimed at helping Washington State University researchers stop viruses before they cause infections in their hosts.

Co-led by professors Jin Liu and Prashanta Dutta at the Voiland College of Engineering and Architecture and professor Anthony Nicola at the College of Veterinary Medicine, the interdisciplinary research project uses biology, machine learning, and multiscale modeling to study virus-cell interactions at the moment a virus merges with a cell to initiate an infection – a process known as virus fusion.

“Virus fusion is a highly complex, multistage and multiscale process. The associated protein interactions and structural changes are extremely complicated and high-dimensional,” said Liu, associate professor in the School of Mechanical and Materials Engineering and the lead investigator on the project. “A combination of knowledge from different disciplines, and expertise from both state-of-the-art numerical modeling and biological experiments, is the key to tackle down the problem.”

By examining these interactions and proteins central to virus entry, researchers at WSU are looking for a way to thwart infection by blocking the virus from ever merging with a cell.

“For viruses, this is such an important process, and although we’ve been studying it for many, many years, it’s something that’s not well understood. There are really important molecular details that still escape us,” said Nicola, a professor in WSU’s Veterinary Microbiology and Pathology department.

The physics-based machine learning method and multiscale model will be developed to simulate cell-virus interactions and expedite the research.

“This is not data-driven machine learning as used by most scientists and engineers. Rather, our novel machine learning algorithm captures important biological phenomena from fundamental physics and chemistry,” said Prashanta Dutta, professor in the School of Mechanical and Materials Engineering.

In the collaborative project, Ryan Odstrcil and Amir Birjandi, both PhD students in the School of Mechanical and Materials Engineering, will lead the modeling and simulation research, while PhD student Albina Makio, a member of WSU’s Immunology and Infectious Disease graduate student program, is leading the experimental research by staging and observing these cell-virus interactions in the laboratory.

The experimentally validated computational models developed by the team may provide critical, new insights and guidance to new experiments.

“Results from the research will improve our understanding of the fundamental mechanisms of virus fusion and facilitate the development of antiviral vaccines and treatments,” said Liu. “The experiments are done using herpes simplex virus type 1, but the knowledge and strategies will be applicable to many other viruses that infect cells a similar way, such as HIV and SARS-CoV-2.”

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