AI Discovered a Method to Block a Virus Before it can Enter Cells

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Antiviral Virus Destruction
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Washington State University researchers found a way to block a key viral protein, stopping viruses from entering cells.. This breakthrough suggests a promising new avenue for developing future antiviral treatments.

Published in Nanoscale, the study explored blocking a key molecular interaction herpes viruses use to invade cells, in a collaboration between the School of Mechanical and Materials Engineering and the Department of Veterinary Microbiology and Pathology.

The Complexity of Viral Cell Entry

Viruses are incredibly clever,” said Jin Liu, the study’s corresponding author and a professor in the School of Mechanical and Materials Engineering. “The process of entering cells is highly complex, involving numerous interactions. While many of these may be insignificant, some are essential.”

The researchers studied a viral “fusion” protein herpes viruses use to enter cells, a process not well understood and a challenge for vaccine development.

To address this, the team used artificial intelligence alongside detailed molecular simulations. Professors Dutta and Liu used AI to pinpoint a single amino acid critical for viral entry.

Laboratory Experiments Confirm Key Viral Weak Point

After identifying the key amino acid, the team, led by Anthony Nicola, mutated it in the lab, stopping the virus from entering cells.

Liu emphasized that simulations and machine learning were crucial because testing even a single interaction experimentally can take months. Identifying the most important interaction beforehand made the lab work much more efficient.

Out of thousands of interactions, it was just one that mattered. Without simulations, relying on trial and error could have taken years,” Liu said. “Combining computational modeling with experimental work is highly efficient and can significantly speed up the discovery of key biological interactions.”

Although the interaction’s importance was confirmed, questions remain about how the mutation affects the full protein, and researchers will use simulations and AI to investigate.

There’s a gap between what experimentalists observe and what simulations reveal,” Liu said. “The next challenge is understanding how this single interaction influences structural changes on a larger scale, which is very complex.”

The study, led by Liu, Dutta, and Nicola with PhD students Ryan Odstrcil, Albina Makio, and McKenna Hull, was funded by the National Institutes of Health.


Read the original article on: Sciencedaily

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