{"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\/fr\/blog\/news\/deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov","title":{"rendered":"DeepMind a ouvert le code d'AlphaFold 3, un syst\u00e8me d'IA pour la mod\u00e9lisation de la structure des prot\u00e9ines","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

La soci\u00e9t\u00e9 Google DeepMind a publi\u00e9 les codes sources du syst\u00e8me d'apprentissage machine AlphaFold 3, con\u00e7u pour pr\u00e9dire la structure tridimensionnelle des prot\u00e9ines et mod\u00e9liser les interactions entre les prot\u00e9ines et d'autres types de mol\u00e9cules. Pour la cr\u00e9ation des algorithmes d'apprentissage machine r\u00e9alis\u00e9s dans la deuxi\u00e8me version d'AlphaFold, le prix Nobel de chimie a \u00e9t\u00e9 d\u00e9cern\u00e9 cette ann\u00e9e. Les outils associ\u00e9s \u00e0 AlphaFold 3 sont \u00e9crits en Python et C++, et sont diffus\u00e9s sous la licence CC BY-NC-SA 4.0. Les mod\u00e8les entra\u00een\u00e9s sont fournis sur la base d'un accord utilisateur. Un environnement a \u00e9t\u00e9 lanc\u00e9 s\u00e9par\u00e9ment serveur<\/a>, permettant d'exp\u00e9rimenter avec AlphaFold 3 en mode en ligne. <\/p>\n

Le mod\u00e8le, qui a \u00e9t\u00e9 form\u00e9 sur une collection d\u00e9crivant les structures de toutes les prot\u00e9ines connues et les s\u00e9quences d'acides amin\u00e9s, r\u00e9sout le probl\u00e8me du repliement des prot\u00e9ines et permet de pr\u00e9dire la structure tridimensionnelle de nouvelles prot\u00e9ines avec une pr\u00e9cision au moins \u00e9gale \u00e0 celle de l'analyse en laboratoire, et dans l'\u00e9valuation des interactions des prot\u00e9ines avec d'autres types de mol\u00e9cules, il d\u00e9passe consid\u00e9rablement les m\u00e9thodes de pr\u00e9diction existantes. La troisi\u00e8me version du mod\u00e8le AlphaFold se distingue par l'utilisation d'une nouvelle architecture \u00ab Pairformer \u00bb, d\u00e9veloppant l'id\u00e9e de l'architecture \u00ab transformeur \u00bb. <\/p>\n

Contrairement \u00e0 AlphaFold 2, la nouvelle version ne se limite pas aux prot\u00e9ines compos\u00e9es d'une seule cha\u00eene polypeptidique et peut \u00eatre utilis\u00e9e pour pr\u00e9dire des complexes prot\u00e9iques avec l'ADN et l'ARN, ainsi que pour mod\u00e9liser les variantes modifi\u00e9es de ces mol\u00e9cules. Une liste de mol\u00e9cules est fournie en entr\u00e9e \u00e0 AlphaFold, et en sortie, une structure 3D conjointe est g\u00e9n\u00e9r\u00e9e, d\u00e9terminant l'interaction la plus probable des mol\u00e9cules indiqu\u00e9es. <\/p>\n

D'un point de vue pratique, AlphaFold 3 peut \u00eatre utilis\u00e9 pour le d\u00e9veloppement de m\u00e9dicaments et de m\u00e9thodes de traitement, ainsi que pour la cr\u00e9ation de nouvelles prot\u00e9ines. Par exemple, gr\u00e2ce \u00e0 AlphaFold, une prot\u00e9ine capable de se lier \u00e0 des cellules canc\u00e9reuses sp\u00e9cifiques a \u00e9t\u00e9 con\u00e7ue, ce qui peut \u00eatre utilis\u00e9 dans une th\u00e9rapie anticanc\u00e9reuse de nouvelle g\u00e9n\u00e9ration. AlphaFold est \u00e9galement largement utilis\u00e9 pour \u00e9tudier l'interaction entre les anticorps et les prot\u00e9ines afin de comprendre la r\u00e9ponse immunitaire humaine et de cr\u00e9er de nouveaux anticorps.
\n
Source : 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\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 a ouvert le code d'AlphaFold 3, un syst\u00e8me d'IA de mod\u00e9lisation de la structure des prot\u00e9ines | ProHoster","description":"La soci\u00e9t\u00e9 Google DeepMind a publi\u00e9 les codes sources du syst\u00e8me d'apprentissage machine AlphaFold 3, con\u00e7u pour pr\u00e9dire la structure tridimensionnelle des 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