Jason Yang, Francesca-Zhoufan Li, Yueming Long, Frances H Arnold
{"title":"Illuminating the universe of enzyme catalysis in the era of artificial intelligence.","authors":"Jason Yang, Francesca-Zhoufan Li, Yueming Long, Frances H Arnold","doi":"10.1016/j.cels.2025.101372","DOIUrl":null,"url":null,"abstract":"<p><p>Scientific research has revealed only a minuscule fraction of the enzymes that evolution has generated to power life's essential chemical reactions-and an even tinier fraction of the vast universe of possible enzymes. Beyond the enzymes already annotated lie an astronomical number of biocatalysts that could enable sustainable chemical production, degrade toxic pollutants, and advance disease diagnosis and treatment. For the past few decades, directed evolution has been a powerful strategy for reshaping enzymes to access new chemical transformations: by harnessing nature's existing diversity as a starting point and taking inspiration from nature's most powerful design process, evolution, to modify enzymes incrementally. Recently, artificial intelligence (AI) methods have started revolutionizing how we understand and compose the language of life. In this perspective, we discuss a vision for AI-driven enzyme discovery to unveil a world of enzymes that transcends biological evolution and perhaps offers a route to genetically encoding almost any chemistry.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101372"},"PeriodicalIF":7.7000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.cels.2025.101372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Scientific research has revealed only a minuscule fraction of the enzymes that evolution has generated to power life's essential chemical reactions-and an even tinier fraction of the vast universe of possible enzymes. Beyond the enzymes already annotated lie an astronomical number of biocatalysts that could enable sustainable chemical production, degrade toxic pollutants, and advance disease diagnosis and treatment. For the past few decades, directed evolution has been a powerful strategy for reshaping enzymes to access new chemical transformations: by harnessing nature's existing diversity as a starting point and taking inspiration from nature's most powerful design process, evolution, to modify enzymes incrementally. Recently, artificial intelligence (AI) methods have started revolutionizing how we understand and compose the language of life. In this perspective, we discuss a vision for AI-driven enzyme discovery to unveil a world of enzymes that transcends biological evolution and perhaps offers a route to genetically encoding almost any chemistry.