Scientists’ Side Hustle? Using AI and Quantum Computing to Generate New Peptides
Researchers at the Technical University of Denmark successfully used a hybrid quantum-classical computing model to generate novel peptides for vaccine development. The study demonstrates that quantum-enhanced AI can outperform traditional models, particularly when training data is limited.
Why it matters
This breakthrough suggests that quantum computing could significantly accelerate drug discovery and the development of personalized immunotherapies, potentially overcoming current limitations in biological data.
The Technical University of Denmark team ran their generative AI model for predicting proteins in conjunction with a printer-sized quantum computer built by British startup ORCA Computing, which sped up AI by linking quantum machines with traditional processors. The researchers used the hybrid technique to generate novel peptides—short chains of amino acids—capable of binding to specific proteins in the body. Doing so is a crucial step in vaccine development.
The team of researchers worked weekends and pooled unspent money from other projects because "most innovative science is too scary for foundations,” according to DTU professor Timothy Patrick Jenkins, who led the project.
Making the peptides in the laboratory and testing whether these would bind to the particular proteins showed the model produced more successful peptides than its classical counterpart, with the strongest improvements where training data was rare.
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