Bold breakthrough in blocking viruses: a single protein interaction could stop herpes from invading cells. Washington State University researchers have uncovered a method to tune a common viral fusion protein, effectively preventing the virus from entering host cells and potentially opening doors to new antiviral therapies.
In this foundational study, published in Nanoscale, teams from the School of Mechanical and Materials Engineering and the Department of Veterinary Microbiology and Pathology zeroed in on a crucial molecular interaction that herpes viruses rely on to fuse with and breach cell membranes. As Jin Liu, the paper’s corresponding author and a professor in the engineering school, explains, viruses are exceptionally clever. The cell-entry process is a web of interactions, and only a subset are truly critical; much of what occurs may be background noise, but a few key contacts drive infection.
The researchers focused on a fusion protein used by herpes viruses to merge with cells, a step required for infection and a driver of many illnesses. Our understanding of how this complex protein unfolds and initiates entry has remained limited, contributing to the lack of vaccines for these widespread viruses.
Leveraging artificial intelligence and molecular-scale simulations, professors Prashanta Dutta and Jin Liu screened thousands of potential interactions within the protein. They developed an algorithm to analyze the myriad amino-acid contacts and a machine-learning approach to distinguish the most consequential interactions.
Under Anthony Nicola’s leadership in the veterinary microbiology and pathology department, the team introduced a mutation in one of the identified amino acids. This alteration markedly disrupted the virus’s fusion capability, preventing herpes from entering cells.
The study highlights the pivotal role of simulations and ML in guiding experimental work. Liu notes that testing a single interaction through traditional lab trials could take years; combining computation with experiments accelerates discovery of vital biological interactions.
Despite confirming the importance of the targeted interaction, the researchers acknowledge that they do not yet have a complete map of how the overall protein structure adapts when this amino acid is altered. They plan to expand their use of simulations and machine learning to gain a broader view of the protein’s behavior.
There remains a gap between what bench scientists observe and what simulations reveal. The next challenge is to link the small, critical interaction to larger-scale structural changes—a difficult but essential step.
Beyond Liu, Dutta, and Nicola, the project included PhD students Ryan Odstrcil, Albina Makio, and McKenna Hull. The National Institutes of Health funded the work.
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