It should also help in mRNA-based therapeutics, says Huang, who is now a computational biologist at Oregon State University in Corvallis. But the technique should prove useful when designing mRNA vaccines against any disease, says Liang Huang, a former Baidu scientist who spearheaded the tool’s creation. So far, Zhang and his colleagues have tested LinearDesign-enhanced vaccines against only COVID-19 and shingles in mice. “It’s a tremendous improvement,” says Yujian Zhang, former head of mRNA technology at StemiRNA Therapeutics in Shanghai, China, who led the experimental-validation studies. The algorithm also helped to extend the shelf stability of vaccine designs up to sixfold in standard test-tube assays performed at body temperature. In validation tests, it has yielded vaccines that, when evaluated in mice, triggered antibody responses up to 128 times greater than those mounted after immunization with more conventional, codon-optimized vaccines.
Known as LinearDesign, the tool takes just minutes to run on a desktop computer. The Baidu tool takes this a step further, ensuring that the mRNA - usually a single-stranded molecule - loops back on itself to create double-stranded segments that are more rigid (see ‘Design optimization’). This process, known as codon optimization, leads to more-efficient protein production. Vaccine developers already commonly adjust mRNA sequences to align with cells’ preferences for certain genetic instructions over others. “The computational efficiency is really impressive and more sophisticated than anything that has come before.” Linear thinking The new methodology is “remarkable”, says Dave Mauger, a computational RNA biologist who previously worked at Moderna in Cambridge, Massachusetts, a maker of mRNA vaccines. A more resilient product, optimized by AI, could eliminate the need for cold-chain equipment to handle such jabs. This limited their distribution in resource-poor regions of the world that lack access to ultracold storage facilities. During the COVID-19 pandemic, mRNA-based shots against the coronavirus SARS-CoV-2 famously had to be transported and kept at temperatures below –15 ☌ to maintain their stability. What’s more, the enhanced structural complexity of the mRNA offers improved protection against vaccine degradation. This, in turn, leads to a rise in protective antibodies, theoretically leaving immunized individuals better equipped to fend off infectious diseases. The more stable the mRNA that’s delivered to a person’s cells, the more antigens are produced by the protein-making machinery in that person’s body. This enables the genetic material to persist for longer than usual.
Naturewall ndesign software#
Credit: Jean-Francois Monier/AFP via GettyĪn artificial intelligence (AI) tool that optimizes the gene sequences found in mRNA vaccines could help to create jabs with greater potency and stability that could be deployed across the globe.ĭeveloped by scientists at the California division of Baidu Research, an AI company based in Beijing, the software borrows techniques from computational linguistics to design mRNA sequences with shapes and structures more intricate than those used in current vaccines. A new AI tool could improve that characteristic.
During the COVID-19 pandemic, mRNA vaccines against the coronavirus SARS-CoV-2 had to be kept at temperatures below –15 ☌ to maintain their stability.
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