{"id":13507,"date":"2024-07-19T18:14:47","date_gmt":"2024-07-19T18:14:47","guid":{"rendered":"https:\/\/dailyai.com\/?p=13507"},"modified":"2024-07-20T12:17:50","modified_gmt":"2024-07-20T12:17:50","slug":"ai-model-simulates-500-million-years-of-evolution-to-create-a-novel-fluorescent-protein","status":"publish","type":"post","link":"https:\/\/dailyai.com\/sv\/2024\/07\/ai-model-simulates-500-million-years-of-evolution-to-create-a-novel-fluorescent-protein\/","title":{"rendered":"AI-modell simulerar 500 miljoner \u00e5r av evolution f\u00f6r att skapa ett nytt fluorescerande protein"},"content":{"rendered":"

Forskare har utvecklat ett AI-system som kan simulera hundratals miljoner \u00e5r av proteinevolution och skapa ett nytt fluorescerande protein som inte liknar n\u00e5got som finns i naturen.<\/b><\/p>\n

Forskargruppen, som leds av Alexander Rives p\u00e5 EvolutionaryScale, skapade en stor spr\u00e5kmodell (LLM) kallad ESM3 f\u00f6r att bearbeta och generera information om proteinsekvenser, strukturer och funktioner.\u00a0<\/span><\/p>\n

Genom att tr\u00e4na p\u00e5 data fr\u00e5n miljarder naturliga proteiner l\u00e4rde sig ESM3 att f\u00f6ruts\u00e4ga hur proteiner kan utvecklas och f\u00f6r\u00e4ndras \u00f6ver tid.<\/span><\/p>\n

Forskarna menar att ESM3 inte bara h\u00e4mtar eller rekombinerar befintlig proteininformation.\u00a0<\/span><\/p>\n

Ist\u00e4llet verkar den ha utvecklat en f\u00f6rst\u00e5else f\u00f6r de grundl\u00e4ggande principer som styr proteinernas struktur och funktion, vilket g\u00f6r det m\u00f6jligt f\u00f6r den att skapa helt nya konstruktioner.<\/span><\/p>\n

\"ESM3 \u00e4r en framv\u00e4xande simulator som har l\u00e4rt sig genom att l\u00f6sa en uppgift f\u00f6r att f\u00f6ruts\u00e4ga symboler p\u00e5 data som genererats av evolutionen\", f\u00f6rklarar forskarna i <\/span>studie<\/span><\/a>.<\/span><\/p>\n

\"Det finns en teori om att neurala n\u00e4tverk uppt\u00e4cker den underliggande strukturen i de data som de \u00e4r tr\u00e4nade att f\u00f6ruts\u00e4ga. F\u00f6r att l\u00f6sa uppgiften att f\u00f6ruts\u00e4ga token skulle modellen p\u00e5 s\u00e5 s\u00e4tt beh\u00f6va l\u00e4ra sig den djupa struktur som avg\u00f6r vilka steg evolutionen kan ta, dvs. proteinernas grundl\u00e4ggande biologi.\"<\/span><\/p>\n

F\u00f6r att testa modellen uppmanade teamet ESM3 att designa ett helt nytt gr\u00f6nt fluorescerande protein (GFP) - en typ av protein som \u00e4r ansvarigt f\u00f6r bioluminescens hos vissa marina djur och som ofta anv\u00e4nds inom bioteknisk forskning.<\/span><\/p>\n

Det AI-genererade proteinet, som kallas esmGFP, delar endast 58% av sin sekvens med de mest liknande k\u00e4nda fluorescerande proteinerna.<\/span><\/p>\n

Anm\u00e4rkningsv\u00e4rt \u00e4r att esmGFP uppvisar en ljusstyrka som \u00e4r j\u00e4mf\u00f6rbar med naturligt f\u00f6rekommande GFP:er och bibeh\u00e5ller den karakteristiska tunnformade struktur som \u00e4r n\u00f6dv\u00e4ndig f\u00f6r fluorescens.\u00a0<\/span><\/p>\n

Forskarna uppskattar att det skulle ha tagit \u00f6ver 500 miljoner \u00e5r av naturlig evolution att producera ett protein som ligger s\u00e5 l\u00e5ngt fr\u00e5n k\u00e4nda GFP:er.<\/span><\/p>\n

Mer om studien<\/h2>\n

Processen f\u00f6r att generera esmGFP omfattade flera viktiga steg:<\/span><\/p>\n

    \n
  1. Uppgifter<\/strong>: Forskarna tr\u00e4nade ESM3 p\u00e5 cirka 2,78 miljarder naturliga proteiner som samlats in fr\u00e5n sekvens- och strukturdatabaser. Detta inkluderade data fr\u00e5n UniRef, MGnify, JGI och andra k\u00e4llor.<\/li>\n
  2. Arkitektur<\/strong>: ESM3 anv\u00e4nder en transformatorbaserad arkitektur med vissa modifieringar, inklusive en mekanism f\u00f6r \"geometrisk uppm\u00e4rksamhet\" f\u00f6r att bearbeta 3D-proteinstrukturer.<\/li>\n
  3. Prompting<\/b>: Forskarna f\u00f6rs\u00e5g ESM3 med minimal strukturell information fr\u00e5n en mall GFP (det fluorescerande proteinet).<\/span><\/li>\n
  4. Generation<\/b>: ESM3 anv\u00e4nde denna uppmaning f\u00f6r att generera nya proteinsekvenser och strukturer genom en iterativ process.<\/span><\/li>\n
  5. Filtrering<\/b>: Tusentals kandidatdesigner utv\u00e4rderades och filtrerades f\u00f6r att hitta de starkaste kandidaterna.<\/span><\/li>\n
  6. Experimentell testning<\/b>: De mest lovande konstruktionerna syntetiserades och testades i labbet f\u00f6r fluorescensaktivitet.<\/span><\/li>\n
  7. F\u00f6r\u00e4dling<\/b>: Efter att ha identifierat en svag men avl\u00e4gsen GFP-variant anv\u00e4nde forskarna ESM3 f\u00f6r att ytterligare optimera designen och slutligen producera ett ljusare fluorescerande protein.<\/span><\/li>\n<\/ol>\n

    Konsekvenserna av denna forskning str\u00e4cker sig l\u00e4ngre \u00e4n till skapandet av ett enda nytt protein.\u00a0<\/span><\/p>\n

    ESM3 visar en f\u00f6rm\u00e5ga att utforska proteiners designutrymmen l\u00e5ngt ifr\u00e5n vad den naturliga evolutionen har producerat, vilket \u00f6ppnar nya v\u00e4gar f\u00f6r att skapa proteiner med \u00f6nskade funktioner eller egenskaper.<\/span><\/p>\n

    Dr. Tiffany Taylor, professor i mikrobiell ekologi och evolution vid University of Bath, som inte var involverad i studien, <\/span>ber\u00e4ttade f\u00f6r LiveScience<\/span><\/a>: \"Just nu saknar vi fortfarande den grundl\u00e4ggande f\u00f6rst\u00e5elsen f\u00f6r hur proteiner, s\u00e4rskilt de som \u00e4r \"nya f\u00f6r vetenskapen\", beter sig n\u00e4r de introduceras i ett levande system, men detta \u00e4r ett h\u00e4ftigt nytt steg som g\u00f6r att vi kan n\u00e4rma oss syntetisk biologi p\u00e5 ett nytt s\u00e4tt.\"<\/span><\/p>\n

    \"AI-modellering som ESM3 kommer att g\u00f6ra det m\u00f6jligt att uppt\u00e4cka nya proteiner som det naturliga urvalet aldrig skulle till\u00e5ta, vilket skapar innovationer inom proteinteknik som evolutionen inte kan\", tillade Dr. Taylor.<\/span><\/p>\n

    Generativ design av proteiner<\/h2>\n

    AI-driven proteinforskning och design har n\u00e5tt en feberniv\u00e5, med <\/span>DeepMind<\/span><\/span><\/span><\/span>'s AlphaFold 3<\/span><\/a> f\u00f6ruts\u00e4ga hur proteiner viks med otrolig precision.\u00a0<\/span><\/p>\n

    AI-designade proteiner har ocks\u00e5 visat <\/span>utm\u00e4rkt bindningsstyrka<\/span><\/a>och visar att de har praktiska anv\u00e4ndningsomr\u00e5den.\u00a0<\/span><\/p>\n

    Men som med all teknik som utvecklas snabbt och som p\u00e5 n\u00e5got s\u00e4tt interagerar med biologi finns det risker.\u00a0<\/span><\/p>\n

    F\u00f6r det f\u00f6rsta, om AI-designade proteiner skulle komma ut i milj\u00f6n skulle de potentiellt kunna interagera med naturliga ekosystem och till och med konkurrera ut naturliga proteiner eller st\u00f6ra befintliga biologiska processer.\u00a0<\/span><\/p>\n

    F\u00f6r det andra kan de utl\u00f6sa ov\u00e4ntade interaktioner inom levande organismer och eventuellt till och med skapa skadliga biologiska agens eller toxiner.\u00a0<\/span><\/p>\n

    Forskare efterlyste nyligen <\/span>etiska skyddsvallar<\/span><\/a> f\u00f6r AI-proteindesign f\u00f6r att f\u00f6rhindra riskfyllda resultat inom detta sp\u00e4nnande, om \u00e4n of\u00f6ruts\u00e4gbara, omr\u00e5de.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Forskare har utvecklat ett AI-system som kan simulera hundratals miljoner \u00e5r av proteinevolution, vilket skapar ett nytt fluorescerande protein som inte liknar n\u00e5got som finns i naturen. Forskargruppen, som leds av Alexander Rives vid EvolutionaryScale, skapade en stor spr\u00e5kmodell (LLM) kallad ESM3 f\u00f6r att bearbeta och generera information om proteinsekvenser, strukturer och funktioner. Genom att tr\u00e4na p\u00e5 data fr\u00e5n miljarder naturliga proteiner l\u00e4rde sig ESM3 att f\u00f6ruts\u00e4ga hur proteiner kan utvecklas och f\u00f6r\u00e4ndras \u00f6ver tid. Forskarna menar att ESM3 inte bara h\u00e4mtar eller rekombinerar befintlig proteininformation. Ist\u00e4llet verkar den ha utvecklat en f\u00f6rst\u00e5else f\u00f6r<\/p>","protected":false},"author":2,"featured_media":13508,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[353,105,178],"class_list":["post-13507","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biology","tag-machine-learning","tag-medicine"],"yoast_head":"\nAI model simulates 500 million years of evolution to create a novel fluorescent protein | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/sv\/2024\/07\/ai-model-simulates-500-million-years-of-evolution-to-create-a-novel-fluorescent-protein\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI model simulates 500 million years of evolution to create a novel fluorescent protein | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Scientists have developed an AI system capable of simulating hundreds of millions of years of protein evolution, creating a novel fluorescent protein unlike any found in nature. The research team, led by Alexander Rives at EvolutionaryScale, created a large language model (LLM) called ESM3 to process and generate information about protein sequences, structures, and functions.\u00a0 By training on data from billions of natural proteins, ESM3 learned to predict how proteins might evolve and change over time. The researchers argue that ESM3 is not simply retrieving or recombining existing protein information.\u00a0 Instead, it appears to have developed an understanding of the\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/sv\/2024\/07\/ai-model-simulates-500-million-years-of-evolution-to-create-a-novel-fluorescent-protein\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-19T18:14:47+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-20T12:17:50+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/DALL\u00b7E-2024-07-19-19.13.56-A-high-quality-landscape-image-featuring-a-large-glowing-and-intricate-fluorescent-protein-structure-in-a-futuristic-lab.-The-protein-should-have-v.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta 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