{"id":25977,"date":"2025-06-18T20:15:44","date_gmt":"2025-06-18T20:15:44","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=25977"},"modified":"2025-06-18T20:15:46","modified_gmt":"2025-06-18T20:15:46","slug":"ai-could-speed-up-development-of-new-therapeutic-proteins","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/ai-could-speed-up-development-of-new-therapeutic-proteins\/","title":{"rendered":"AI Could Speed Up Development of New Therapeutic Proteins"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Scientists from the University of Sheffield and AstraZeneca have unveiled an AI approach, MapDiff, that significantly improves the design of new medicinal proteins. This development stands to revolutionize drug discovery, making treatments more effective and faster to develop.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p>University scientists and industry experts have collaborated to make a groundbreaking achievement in protein engineering. A team from the University of Sheffield and AstraZeneca has developed a new artificial intelligence approach that promises to revolutionize the field, potentially speeding up the development of new medicines.<\/p>\n\n\n\n<p>This innovative AI method, named MapDiff, significantly outperforms existing techniques in &#8220;inverse protein folding,&#8221; a complex but crucial aspect of protein design.<\/p>\n\n\n\n<p>Inverse protein folding involves determining the amino acid sequences that will fold into specific 3D shapes to perform designated functions. This process is vital because, for medicines to be effective, the proteins involved must fold into precise structures.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.nature.com\/articles\/s42256-025-01042-6\" target=\"_blank\" rel=\"noopener\" title=\"\">Published<\/a> in the journal Nature Machine Intelligence, the study builds on the use of machine learning models trained on vast datasets of known protein sequences and structures.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Breakthrough in Protein Folding<\/h2>\n\n\n\n<p>MapDiff has demonstrated superior predictive capabilities in simulated tests, offering a more accurate way to design amino acid sequences that will fold into stable, functional proteins. <\/p>\n\n\n\n<p>This development has the potential to speed up the creation of essential proteins for vaccines, gene therapies and other innovative treatments.<\/p>\n\n\n\n<p>\u201cThis work represents a significant step forward in using AI to design proteins with desired structures,&#8221; corresponding author Haiping Lu, a professor of machine learning at the University of Sheffield, said in a news release. &#8220;By learning how to generate amino acid sequences that are likely to fold into specific 3D structures, our method opens new possibilities for designing new therapeutic proteins, which can be used in various therapeutic applications. It\u2019s exciting to see AI helping us tackle such a fundamental challenge in biology.\u201d<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Pioneering Collaboration<\/h2>\n\n\n\n<p>The study is the result of a collaborative effort between academia and industry, building on previous successful partnerships between the University of Sheffield&#8217;s computer scientists and AstraZeneca. <\/p>\n\n\n\n<p>\u201cDuring my PhD, I was motivated by the potential of AI to accelerate biological discovery. I\u2019m proud that our method, MapDiff, helps design protein sequences that are more likely to fold into desired 3D structures \u2014 a key step towards advancing next-generation therapeutics,&#8221; added Peizhen Bai, a senior machine learning scientist at AstraZeneca, who developed the AI as a doctoral student at the University of Sheffield\u2019s School of Computer Science.<\/p>\n\n\n\n<p>The collaboration previously led to the development of <a href=\"https:\/\/www.sheffield.ac.uk\/news\/ai-could-speed-discovery-new-medicines\" target=\"_blank\" rel=\"noopener\" title=\"\">DrugBAN<\/a>, an AI that can predict drug-target binding efficiently, expediting the drug discovery process. That work has already made notable impacts and is among the most cited papers in Nature Machine Intelligence in 2023.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Future Implications<\/h2>\n\n\n\n<p>The successful implementation of MapDiff could herald a new era in medicinal protein design, complementing other recent advances such as AlphaFold, which predicts the 3D structure of proteins from amino acid sequences. By streamlining the design process, this AI-driven approach holds significant promise for accelerating the development of new therapies and improving treatment outcomes.\u00a0<\/p>\n\n\n\n<div style=\"height:11px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><strong>Source<\/strong>: <a href=\"https:\/\/www.sheffield.ac.uk\/news\/ai-could-accelerate-protein-engineering-key-developing-new-medicines\" target=\"_blank\" rel=\"noopener\" title=\"\">University of Sheffield<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>University scientists and industry experts have collaborated to make a groundbreaking achievement in protein engineering. A team from the University of Sheffield and AstraZeneca has developed a new artificial intelligence approach that promises to revolutionize the field, potentially speeding up the development of new medicines. This innovative AI method, named MapDiff, significantly outperforms existing techniques [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8],"tags":[397],"class_list":["post-25977","post","type-post","status-publish","format-standard","hentry","category-ai","tag-university-of-sheffield"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"University scientists and industry experts have collaborated to make a groundbreaking achievement in protein engineering. A team from the University of Sheffield and AstraZeneca has developed a new artificial intelligence approach that promises to revolutionize the field, potentially speeding up the development of new medicines. This innovative AI method, named MapDiff, significantly outperforms existing techniques&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/25977","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=25977"}],"version-history":[{"count":8,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/25977\/revisions"}],"predecessor-version":[{"id":26070,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/25977\/revisions\/26070"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=25977"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=25977"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=25977"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}