{"id":2000117920,"date":"2026-07-02T18:30:00","date_gmt":"2026-07-02T16:30:00","guid":{"rendered":"https:\/\/new.igihe.com\/english\/?p=2000117920"},"modified":"2026-07-02T18:04:18","modified_gmt":"2026-07-02T16:04:18","slug":"researchers-develop-ai-system-translating-protein-sequences-into-natural-language","status":"publish","type":"post","link":"https:\/\/new.igihe.com\/english\/researchers-develop-ai-system-translating-protein-sequences-into-natural-language\/","title":{"rendered":"Researchers develop AI system translating protein sequences into natural language"},"content":{"rendered":"\n

This breakthrough, published in the U.S. scientific journal Proceedings of the National Academy of Sciences, is expected to significantly accelerate medical research and reduce costs in drug discovery and biotechnology, the researchers said.<\/p>\n\n\n\n

Proteins are essential to biological functions and underpin medical advances such as the diabetes drug Ozempic.<\/p>\n\n\n\n

However, despite the existence of billions of proteins in nature, scientists have identified the functions of only a small fraction, largely due to years of costly lab work.<\/p>\n\n\n\n

“BetaDescribe” works like a specialized translator, turning raw biological data into clear, detailed descriptions of a protein’s function, metabolic role, and medical potential, according to the researchers.<\/p>\n\n\n\n

The AI’s ability to rapidly generate evidence-based hypotheses about the functions of unknown proteins could significantly shorten the path from basic discovery to medical and industrial applications, the researchers concluded.<\/p>\n\n\n\n

\"\"
A researcher using a mass spectrometer to analyse proteins. Researchers have developed an AI system called “BetaDescribe” that translates complex protein sequences into readable natural-language descriptions, the Israel Institute of Technology said in a statement on Thursday.<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"

Researchers have developed an AI system called “BetaDescribe” that translates complex protein sequences into readable natural-language descriptions, the Israel Institute of Technology said in a statement on Thursday.<\/p>\n","protected":false},"author":131,"featured_media":2000117921,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[151],"byline":[235],"hashtag":[],"class_list":["post-2000117920","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science-technology","tag-editors-choice","byline-xinhua"],"bylines":[{"id":235,"name":"Xinhua","slug":"xinhua","description":"","image":{"id":0,"url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&f=y&r=g","alt":"Default avatar","title":"Default avatar","caption":"","mime_type":"image\/jpeg","sizes":[]},"user_id":80}],"contributors":[{"id":235,"name":"Xinhua","slug":"xinhua","description":"","image":{"id":0,"url":"https:\/\/secure.gravatar.com\/avatar\/?s=96&d=mm&f=y&r=g","alt":"Default avatar","title":"Default avatar","caption":"","mime_type":"image\/jpeg","sizes":[]},"user_id":80}],"featured_image":{"id":2000117921,"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","alt":"","caption":"Editorial use only \nMODEL RELEASED. Proteomics and mass spectrometry analysis. Researcher using a mass spectrometer to analyse proteins. This is part of a proteomics and mass spectrometry service provided both to researchers at the University of Dundee, Scotland, and to academic and industrial clients worldwide. The equipment being used here includes an ultra-high performance liquid chromatography (UHPLC) nanoflow system (left) and a linear trap quadropole (LTQ) ion-trap mass spectrometer (centre). Photographed in 2016, in Dundee, Scotland.","mime_type":"image\/jpeg","width":1216,"height":804,"sizes":{"thumbnail":{"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","width":1216,"height":804},"medium":{"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","width":1216,"height":804},"medium_large":{"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","width":1216,"height":804},"large":{"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","width":1216,"height":804},"full":{"url":"https:\/\/cdn.igihe.com\/en\/2026\/07\/20250331_on_aiproteomics.jpg","width":1216,"height":804}}},"_links":{"self":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000117920","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/users\/131"}],"replies":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/comments?post=2000117920"}],"version-history":[{"count":1,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000117920\/revisions"}],"predecessor-version":[{"id":2000117922,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/posts\/2000117920\/revisions\/2000117922"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/media\/2000117921"}],"wp:attachment":[{"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/media?parent=2000117920"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/categories?post=2000117920"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/tags?post=2000117920"},{"taxonomy":"byline","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/byline?post=2000117920"},{"taxonomy":"hashtag","embeddable":true,"href":"https:\/\/new.igihe.com\/english\/wp-json\/wp\/v2\/hashtag?post=2000117920"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}