{"id":"doi:10.1038/s41586-026-10965-y","kind":"article","title":"Function-preserving watermarking of AI-generated proteins","authors":["Stutz D","Cowen-Rivers AI","Ortiz-Jimenez G","Ratcliff J","Zambaldi V","Willmore L","Abramson J","Patani H","Kouridi C","Stimberg F","Vecerik M","Chu A","Singh S","Dathathri S","Papa E","De Bortoli V","Doucet A","Hassabis D","Wang J","Gowal S","Kohli P"],"author_count":21,"year":2026,"published":"2026-09-30","venue":"Nature","cited_by":0,"doi":"10.1038/s41586-026-10965-y","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/s41586-026-10965-y","archive_url":"https://space-kitty.com/papers/doi:10.1038/s41586-026-10965-y","updated":null,"pmid":"42816606","pmcid":null,"openalex_id":null,"pdf_url":null,"abstract":"Generative artificial intelligence (AI) models are revolutionizing biology, with tools such as AlphaFold 3 and protein design models accelerating breakthroughs in protein structure prediction and the creation of new functional proteins 1 . Tracking and establishing the provenance of AI-generated protein sequences and structures is becoming increasingly important to tackle a range of emerging challenges, including biosecurity and concerns about information veracity 2-4 . Here we introduce SynthIDBio, a family of methods for watermarking protein sequences and structures to establish the provenance of those generated with AI. SynthIDBio-sequence actively embeds a watermark into protein sequences while preserving function. We demonstrate this by creating watermarked, functional designed protein binders with binding affinity comparable with non-watermarked counterparts and near-perfect watermark detection accuracy. Furthermore, SynthIDBio-structure, a fine-tuned AlphaFold3 model, embeds an imperceptible watermark into biomolecular structures. Our work is a proof-of-concept that function-preserving biological watermarking is feasible, introducing a potential tool for provenance in the rapidly expanding era of AI-driven biological engineering.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"Function-preserving watermarking of AI-generated proteins\" by Stutz D, Cowen-Rivers AI, Ortiz-Jimenez G et al., https://doi.org/10.1038/s41586-026-10965-y, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"protein-design","name":"AI Protein Design & Structure Prediction","domain_slug":"biotech"}],"cited_in_dossiers":[]}