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Strengthening nucleic acid biosecurity screening against generative protein design tools.

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Title: Strengthening nucleic acid biosecurity screening against generative protein design tools.
Authors: Wittmann, Bruce J., Alexanian, Tessa, Bartling, Craig, Beal, Jacob, Clore, Adam, Diggans, James, Flyangolts, Kevin, Gemler, Bryan T., Mitchell, Tom, Murphy, Steven T., Wheeler, Nicole E., Horvitz, Eric
Source: Science. 10/2/2025, Vol. 390 Issue 6768, p82-87. 6p.
Subjects: Protein engineering, Nucleic acid synthesis, Biosecurity, Artificial intelligence, Biological research
Abstract: Advances in artificial intelligence (AI)–assisted protein engineering are enabling breakthroughs in the life sciences but also introduce new biosecurity challenges. Synthesis of nucleic acids is a choke point in AI-assisted protein engineering pipelines. Thus, an important focus for efforts to enhance biosecurity given AI-enabled capabilities is bolstering methods used by nucleic acid synthesis providers to screen orders. We evaluated the ability of open-source AI-powered protein design software to create variants of proteins of concern that could evade detection by the biosecurity screening tools used by nucleic acid synthesis providers, identifying a vulnerability where AI-redesigned sequences could not be detected reliably by current tools. In response, we developed and deployed patches, greatly improving detection rates of synthetic homologs more likely to retain wild type–like function. Editor's summary: One way in which companies and governments can limit potentially harmful biological research is by restricting the commercial synthesis of DNA that encodes particular proteins or is from select pathogens. However, screening methods are not necessarily designed to detect engineered sequences. Wittmann et al. worked with four commercial DNA synthesis companies to stress test and develop patches for screening methods to greatly improve their ability to identify sequences that should be restricted. Their results demonstrate that proteins of concern can be flagged by updated software even if their sequences have been altered using protein design methods. —Michael A Funk [ABSTRACT FROM AUTHOR]
Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Strengthening nucleic acid biosecurity screening against generative protein design tools.
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  Data: <searchLink fieldCode="AR" term="%22Wittmann%2C+Bruce+J%2E%22">Wittmann, Bruce J.</searchLink><br /><searchLink fieldCode="AR" term="%22Alexanian%2C+Tessa%22">Alexanian, Tessa</searchLink><br /><searchLink fieldCode="AR" term="%22Bartling%2C+Craig%22">Bartling, Craig</searchLink><br /><searchLink fieldCode="AR" term="%22Beal%2C+Jacob%22">Beal, Jacob</searchLink><br /><searchLink fieldCode="AR" term="%22Clore%2C+Adam%22">Clore, Adam</searchLink><br /><searchLink fieldCode="AR" term="%22Diggans%2C+James%22">Diggans, James</searchLink><br /><searchLink fieldCode="AR" term="%22Flyangolts%2C+Kevin%22">Flyangolts, Kevin</searchLink><br /><searchLink fieldCode="AR" term="%22Gemler%2C+Bryan+T%2E%22">Gemler, Bryan T.</searchLink><br /><searchLink fieldCode="AR" term="%22Mitchell%2C+Tom%22">Mitchell, Tom</searchLink><br /><searchLink fieldCode="AR" term="%22Murphy%2C+Steven+T%2E%22">Murphy, Steven T.</searchLink><br /><searchLink fieldCode="AR" term="%22Wheeler%2C+Nicole+E%2E%22">Wheeler, Nicole E.</searchLink><br /><searchLink fieldCode="AR" term="%22Horvitz%2C+Eric%22">Horvitz, Eric</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Science%22">Science</searchLink>. 10/2/2025, Vol. 390 Issue 6768, p82-87. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Protein+engineering%22">Protein engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Nucleic+acid+synthesis%22">Nucleic acid synthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Biosecurity%22">Biosecurity</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+research%22">Biological research</searchLink>
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  Data: Advances in artificial intelligence (AI)–assisted protein engineering are enabling breakthroughs in the life sciences but also introduce new biosecurity challenges. Synthesis of nucleic acids is a choke point in AI-assisted protein engineering pipelines. Thus, an important focus for efforts to enhance biosecurity given AI-enabled capabilities is bolstering methods used by nucleic acid synthesis providers to screen orders. We evaluated the ability of open-source AI-powered protein design software to create variants of proteins of concern that could evade detection by the biosecurity screening tools used by nucleic acid synthesis providers, identifying a vulnerability where AI-redesigned sequences could not be detected reliably by current tools. In response, we developed and deployed patches, greatly improving detection rates of synthetic homologs more likely to retain wild type–like function. Editor's summary: One way in which companies and governments can limit potentially harmful biological research is by restricting the commercial synthesis of DNA that encodes particular proteins or is from select pathogens. However, screening methods are not necessarily designed to detect engineered sequences. Wittmann et al. worked with four commercial DNA synthesis companies to stress test and develop patches for screening methods to greatly improve their ability to identify sequences that should be restricted. Their results demonstrate that proteins of concern can be flagged by updated software even if their sequences have been altered using protein design methods. —Michael A Funk [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 10/2/2025
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