Introducing SynthID Bio

Pushmeet Kohli, David Stutz, Ali Cowen-Rivers and Jeremy Ratcliff

Proof of concept for watermarking AI-generated proteins while preserving biological function.

Today, we’re introducing SynthID Bio to bring watermarking technology to synthetic biology. SynthID Bio embeds an imperceptible signature directly into the biological code, ensuring the watermark is verifiable not just on a digital model but on the synthesized, physical protein itself – all while preserving its biological function in laboratory testing.

Generative AI is helping scientists address critical biological challenges, from predicting the structure of proteins (AlphaFold) to designing entirely new proteins (AlphaProteo, and ProteinMPNN), and more recently, developing new bacteriophages, viruses that infect bacteria. Yet these tools also present new challenges: novel AI designs can bypass traditional DNA synthesis screening, while mislabeled synthetic 3D structures risk polluting public databases and misleading downstream research.

SynthID Bio is a family of watermarking methods developed specifically for synthetic biology to strengthen biosecurity and scientific integrity.

It adapts its approach depending on the type of data, subtly guiding the choice of amino acids for sequences and adjusting atomic coordinates for predicted 3D structures, creating a reliable signal for detection.

In experiments, these adjustments did not compromise the protein’s biological function, which is essential to effectively treat disease and advance scientific research.

Visualization of the predicted structure of our watermarked VEGF-A protein binder with watermark signal indicated by color for each amino acid.

We verified our approach for watermarking protein binders, i.e. molecules built to selectively latch onto other proteins, by using our binder design method AlphaProteo alongside a SynthID Bio-enabled version of ProteinMPNN, the commonly used protein sequence generation method.