One signal

Update

What changed

Google DeepMind says wet-lab tests of SynthID Bio-marked protein binders across three targets matched unwatermarked designs on hit rate, binding affinity and natural sequence diversity. The company identifies the targets as VEGF-A, the SARS-CoV-2 spike protein receptor-binding domain and PD-L1.

The company also describes a separate method that builds a detectable watermark into AlphaFold 3’s model weights, so predicted protein structures carry a signal regardless of who runs the model. Google DeepMind says it preserved prediction accuracy and remained detectable despite digital noise or minor coordinate changes.

Google DeepMind says it is publishing a methods paper, code and in-vitro data, and releasing model weights to researchers. It calls this an early step, noting that making watermarks robust against deliberate tampering remains a challenge.

Sources and evidence

• SynthID Bio: Watermarking methods for synthetic biology – Google DeepMind: Google DeepMind says SynthID Bio-marked protein binders matched unwatermarked designs on three reported measures across three targets; it also reports a watermarking method for AlphaFold 3 structures and says it is releasing code, data, a methods paper and model weights.

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