Strengthening nucleic acid biosecurity screening against generative protein design tools

IF 45.8 1区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Science Pub Date : 2025-10-02 DOI:10.1126/science.adu8578

Bruce J. Wittmann, Tessa Alexanian, Craig Bartling, Jacob Beal, Adam Clore, James Diggans, Kevin Flyangolts, Bryan T. Gemler, Tom Mitchell, Steven T. Murphy, Nicole E. Wheeler, Eric Horvitz

{"title":"Strengthening nucleic acid biosecurity screening against generative protein design tools","authors":"Bruce J. Wittmann, Tessa Alexanian, Craig Bartling, Jacob Beal, Adam Clore, James Diggans, Kevin Flyangolts, Bryan T. Gemler, Tom Mitchell, Steven T. Murphy, Nicole E. Wheeler, Eric Horvitz","doi":"10.1126/science.adu8578","DOIUrl":null,"url":null,"abstract":"<div >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.</div>","PeriodicalId":21678,"journal":{"name":"Science","volume":"390 6768","pages":""},"PeriodicalIF":45.8000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science","FirstCategoryId":"103","ListUrlMain":"https://www.science.org/doi/10.1126/science.adu8578","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

加强对生成蛋白设计工具的核酸生物安全筛选

人工智能（AI）辅助蛋白质工程的进步正在使生命科学取得突破，但也带来了新的生物安全挑战。核酸合成是人工智能辅助蛋白质工程管道的瓶颈。因此，鉴于人工智能能力，加强生物安全的一个重要重点是加强核酸合成提供者筛选订单的方法。我们评估了开源人工智能驱动的蛋白质设计软件的能力，以创建可能逃避核酸合成提供商使用的生物安全筛选工具检测的关注蛋白质变体，识别出人工智能重新设计的序列无法被当前工具可靠检测的漏洞。作为回应，我们开发并部署了补丁，大大提高了合成同源物的检出率，更有可能保留野生型样功能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Science 综合性期刊-综合性期刊

CiteScore

61.10

自引率

0.90%

发文量

审稿时长

2.1 months

期刊介绍： Science is a leading outlet for scientific news, commentary, and cutting-edge research. Through its print and online incarnations, Science reaches an estimated worldwide readership of more than one million. Science’s authorship is global too, and its articles consistently rank among the world's most cited research. Science serves as a forum for discussion of important issues related to the advancement of science by publishing material on which a consensus has been reached as well as including the presentation of minority or conflicting points of view. Accordingly, all articles published in Science—including editorials, news and comment, and book reviews—are signed and reflect the individual views of the authors and not official points of view adopted by AAAS or the institutions with which the authors are affiliated. Science seeks to publish those papers that are most influential in their fields or across fields and that will significantly advance scientific understanding. Selected papers should present novel and broadly important data, syntheses, or concepts. They should merit recognition by the wider scientific community and general public provided by publication in Science, beyond that provided by specialty journals. Science welcomes submissions from all fields of science and from any source. The editors are committed to the prompt evaluation and publication of submitted papers while upholding high standards that support reproducibility of published research. Science is published weekly; selected papers are published online ahead of print.