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Google DeepMind embeds watermarks in AI-generated proteins to enhance biosecurity.

Scientists at Google DeepMind have developed a method to embed hidden "watermarks" in AI-generated proteins to improve traceability and prevent bioweapon creation. While the technique shows promise iโ€ฆ

Scientists can now 'watermark' AI-generated proteins to deter bioweapon creation. But will it really work?
Live Science โ€” 23 October 2026
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Scientists at Google DeepMind have unveiled a method to embed hidden โ€œwatermarksโ€ in proteins designed by artificialโ€‘intelligence tools, aiming to make it easier to trace the origin of AIโ€‘generated sequences and to deter their use in bioweapons. The technique, called SynthIDBioโ€‘sequence, modifies the aminoโ€‘acid choices made by the proteinโ€‘design program ProteinMPNN so that a secret key can later reveal whether a sequence was created with the watermark. In tests, the watermarked proteins performed as well as ordinary designs, binding to their targets without loss of function.

The breakthrough comes as AIโ€‘driven protein engineering has moved from prediction to creation. Since AlphaFoldโ€™s 2020 release, researchers can predict a proteinโ€™s threeโ€‘dimensional shape from its sequence, and newer tools can suggest entirely new sequences that fold into desired structures. That power promises novel medicines but also raises biosecurity fears, because AI can generate proteins that look unlike any known toxin or virus component, slipping past existing screening systems that rely on similarity to known threats. Experts say the ability to flag engineered proteins for extra checks could help keep databases clean and prevent malicious actors from hiding dangerous designs.

While the watermark offers a promising safeguard, some scientists warn it may be a doubleโ€‘edged sword. The same AI algorithms that insert the hidden code can also be trained to erase it, potentially leaving a loophole for adversaries. Royโ€ฏSleator, a biology professor in Ireland, said the method could improve provenance tracking and reduce false claims about how a protein was made, but emphasized that broader adoption and robust verification standards will be needed. Georgeโ€ฏRose, a biophysics emeritus at Johns Hopkins, cautioned that any technology useful for good can be repurposed for harm. The DeepMind team plans to refine the keyโ€‘generation process and work with international biosecurity bodies to embed the watermark into public proteinโ€‘design pipelines, hoping the added traceability will become a standard part of future AIโ€‘driven biotechnology.

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