{"id":204526,"date":"2025-01-25T14:30:32","date_gmt":"2025-01-25T20:30:32","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/01\/ai-accelerates-enzyme-engineering"},"modified":"2025-01-25T14:30:32","modified_gmt":"2025-01-25T20:30:32","slug":"ai-accelerates-enzyme-engineering","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/01\/ai-accelerates-enzyme-engineering","title":{"rendered":"AI Accelerates Enzyme Engineering"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/ai-accelerates-enzyme-engineering.jpg\"><\/a><\/p>\n<p>Engineered enzymes are poised to have transformative impacts across applications in energy, materials, biotechnology, and medicine. Recently, machine learning has emerged as a useful tool for enzyme engineering. Now, a team of bioengineers and synthetic biologists says they have developed a machine-learning guided platform that can design thousands of new enzymes, predict how they will behave in the real world, and test their performance across multiple chemical reactions.<\/p>\n<p>Their results are published in <em>Nature Communications<\/em> in an article titled, \u201c<a href=\"https:\/\/www.nature.com\/articles\/s41467-024-55399-0\">Accelerated enzyme engineering by machine-learning guided cell-free expression<\/a>,\u201d and led by researchers at Stanford University and Northwestern University.<\/p>\n<p>\u201cEnzyme engineering is limited by the challenge of rapidly generating and using large datasets of sequence-function relationships for predictive design,\u201d the researchers wrote. \u201cTo address this challenge, we develop a machine learning (ML)-guided platform that integrates cell-free DNA assembly, cell-free gene expression, and functional assays to rapidly map fitness landscapes across protein sequence space and optimize enzymes for multiple, distinct chemical reactions.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Engineered enzymes are poised to have transformative impacts across applications in energy, materials, biotechnology, and medicine. Recently, machine learning has emerged as a useful tool for enzyme engineering. Now, a team of bioengineers and synthetic biologists says they have developed a machine-learning guided platform that can design thousands of new enzymes, predict how they will [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1902,11,19,6],"tags":[],"class_list":["post-204526","post","type-post","status-publish","format-standard","hentry","category-bioengineering","category-biotech-medical","category-chemistry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/204526","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=204526"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/204526\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=204526"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=204526"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=204526"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}