Artificial intelligence (AI) is helping to redraw the virus family tree. Predicted protein structures generated by AlphaFold and chatbot-inspired ‘protein language models’ have uncovered some surprising connections in a family of viruses that includes pathogens that infect humans as well as emerging threats.
Much of scientists’ understanding of viral evolution is based on genome comparisons. But the lightning-quick evolution of viruses — particularly those with genomes written in RNA — and their tendency to acquire genetic material from other organisms mean that genetic sequences can hide deep and distant relationships between viruses, which can also vary depending on the gene examined.
By contrast, the shapes, or structures, of the proteins encoded by viral genes tend to change slowly, which makes it possible to suss out these hidden evolutionary connections. But until the dawn of tools such as AlphaFold, which can predict protein structures at scale, it was not possible to compare protein structures across an entire viral family, says Joe Grove, a molecular virologist at the University of Glasgow, UK.
In a paper published this month in Nature1, Grove and his team demonstrate the power of a structure-based approach in the flaviviruses — a group that includes the hepatitis C, dengue and Zika viruses, as well as some major animal pathogens and species that could be emerging threats to human health.
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