{"id":120556,"date":"2024-11-12T19:09:07","date_gmt":"2024-11-12T17:09:07","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov"},"modified":"2024-11-12T19:09:07","modified_gmt":"2024-11-12T17:09:07","slug":"deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sv\/blog\/news\/deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov","title":{"rendered":"DeepMind har \u00f6ppnat koden f\u00f6r AlphaFold 3, AI-systemet f\u00f6r modellering av proteinstruktur.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

F\u00f6retaget Google DeepMind har publicerat k\u00e4llkoden f\u00f6r maskininl\u00e4rningssystemet AlphaFold 3, som \u00e4r avsett f\u00f6r att f\u00f6ruts\u00e4ga tredimensionell struktur av proteiner och modellera interaktionen mellan proteiner och andra typer av molekyler. F\u00f6r utvecklingen av maskininl\u00e4rningsalgoritmerna, som implementerades i den andra versionen av AlphaFold, tilldelades i \u00e5r Nobelpriset i kemi. Verktygen kopplade till AlphaFold 3 \u00e4r skrivna i Python och C++ och distribueras under licensen CC BY-NC-SA 4.0. De tr\u00e4nade modellerna g\u00f6rs tillg\u00e4ngliga baserat p\u00e5 anv\u00e4ndarvillkoren. Separat har lanserats server<\/a>, som m\u00f6jligg\u00f6r experimentering med AlphaFold 3 i online-l\u00e4ge. <\/p>\n

Modellen, som har tr\u00e4nats p\u00e5 en samling av beskrivningar av strukturer f\u00f6r alla k\u00e4nda proteiner och aminosyrasekvenser, l\u00f6ser problemet med proteinveckning och g\u00f6r det m\u00f6jligt att f\u00f6ruts\u00e4ga den tredimensionella strukturen av nya proteiner med en noggrannhet som minst inte \u00e4r s\u00e4mre \u00e4n laboratorieanalys, och vid bed\u00f6mning av interaktioner mellan proteiner och andra typer av molekyler \u00f6vertr\u00e4ffar den betydligt befintliga f\u00f6ruts\u00e4gningsmetoder. Den tredje versionen av AlphaFold-modellen k\u00e4nnetecknas av anv\u00e4ndningen av en ny arkitektur kallad \"Pairformer\", som vidareutvecklar id\u00e9n bakom arkitekturen \"transformer\". <\/p>\n

Till skillnad fr\u00e5n AlphaFold 2 \u00e4r den nya versionen inte begr\u00e4nsad till proteiner som best\u00e5r av en enda polypeptidkedja och kan till\u00e4mpas f\u00f6r att f\u00f6ruts\u00e4ga protein-komplex med DNA och RNA, samt modellera modifierade versioner av dessa molekyler. En lista \u00f6ver molekyler matas in i AlphaFold, och en gemensam 3D-struktur skapas som definierar den mest troliga interaktionen mellan de angivna molekylerna. <\/p>\n

Praktiskt sett kan AlphaFold 3 anv\u00e4ndas f\u00f6r l\u00e4kemedelsutveckling och behandlingsmetoder, samt f\u00f6r att skapa nya proteiner. Till exempel har AlphaFold designat ett protein som kan f\u00e4sta sig vid specifika cancerceller, vilket kan anv\u00e4ndas i n\u00e4sta generations cancerterapi. AlphaFold anv\u00e4nds ocks\u00e5 aktivt f\u00f6r att studera interaktionen mellan antikroppar och proteiner f\u00f6r att f\u00f6rst\u00e5 den m\u00e4nskliga immunresponsen och skapa nya antikroppar.
\n
K\u00e4lla: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google DeepMind \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b\u0430 \u0438\u0441\u0445\u043e\u0434\u043d\u044b\u0435 \u0442\u0435\u043a\u0441\u0442\u044b \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f AlphaFold 3, \u043f\u0440\u0435\u0434\u043d\u0430\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u043e\u0439 \u0434\u043b\u044f \u043f\u0440\u0435\u0434\u0441\u043a\u0430\u0437\u0430\u043d\u0438\u044f \u0442\u0440\u0451\u0445\u043c\u0435\u0440\u043d\u043e\u0439 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u0431\u0435\u043b\u043a\u043e\u0432 \u0438 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0432\u0437\u0430\u0438\u043c\u043e\u0434\u0435\u0439\u0441\u0442\u0432\u0438\u044f \u0431\u0435\u043b\u043a\u043e\u0432 \u0441 \u0434\u0440\u0443\u0433\u0438\u043c\u0438 \u0442\u0438\u043f\u0430\u043c\u0438 \u043c\u043e\u043b\u0435\u043a\u0443\u043b. \u0417\u0430 \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u0435 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f, \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0432\u043e \u0432\u0442\u043e\u0440\u043e\u0439 \u0432\u0435\u0440\u0441\u0438\u0438 AlphaFold, \u0432 \u044d\u0442\u043e\u043c \u0433\u043e\u0434\u0443 \u043f\u0440\u0438\u0441\u0443\u0436\u0434\u0435\u043d\u0430 \u041d\u043e\u0431\u0435\u043b\u0435\u0432\u0441\u043a\u0430\u044f \u043f\u0440\u0435\u043c\u0438\u044f \u043f\u043e \u0445\u0438\u043c\u0438\u0438. \u0421\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0439 \u0441 AlphaFold 3 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 Python \u0438 C++, \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-120556","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47DeepMind har \u00f6ppnat koden f\u00f6r AlphaFold 3, AI-systemet f\u00f6r modellering av proteinstruktur | ProHoster","description":"F\u00f6retaget Google DeepMind har publicerat k\u00e4llkoden f\u00f6r maskininl\u00e4rningssystemet AlphaFold 3, som \u00e4r avsett f\u00f6r att f\u00f6ruts\u00e4ga tredimensionell struktur av 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