{"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\/es\/blog\/news\/deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov","title":{"rendered":"DeepMind ha hecho p\u00fablico el c\u00f3digo de AlphaFold 3, un sistema de IA para la modelaci\u00f3n de estructuras de prote\u00ednas.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

La compa\u00f1\u00eda Google DeepMind ha publicado los textos fuente del sistema de aprendizaje autom\u00e1tico AlphaFold 3, dise\u00f1ado para predecir la estructura tridimensional de las prote\u00ednas y modelar la interacci\u00f3n de las prote\u00ednas con otros tipos de mol\u00e9culas. Este a\u00f1o, se otorg\u00f3 el Premio Nobel de Qu\u00edmica por la creaci\u00f3n de los algoritmos de aprendizaje autom\u00e1tico implementados en la segunda versi\u00f3n de AlphaFold. El conjunto de herramientas relacionado con AlphaFold 3 est\u00e1 escrito en Python y C++, y se distribuye bajo la licencia CC BY-NC-SA 4.0. Los modelos entrenados se proporcionan bajo un acuerdo de usuario. Separadamente, se lanz\u00f3 servidor<\/a>, que permite experimentar con AlphaFold 3 en modo online. <\/p>\n

El modelo, que ha sido entrenado en una colecci\u00f3n con descripciones de la estructura de todas las prote\u00ednas conocidas y secuencias de amino\u00e1cidos, aborda el problema del plegamiento de prote\u00ednas y permite predecir la estructura tridimensional de nuevas prote\u00ednas con una precisi\u00f3n que al menos no es inferior al an\u00e1lisis de laboratorio, y al evaluar la interacci\u00f3n de prote\u00ednas con otros tipos de mol\u00e9culas, supera significativamente los m\u00e9todos de predicci\u00f3n existentes. La tercera versi\u00f3n del modelo AlphaFold se diferencia por el uso de una nueva arquitectura llamada \"Pairformer\", que desarrolla la idea de la arquitectura \"transformer\". <\/p>\n

A diferencia de AlphaFold 2, la nueva versi\u00f3n no se limita a prote\u00ednas compuestas de una sola cadena polipept\u00eddica, y puede aplicarse para predecir complejos proteicos con ADN y ARN, as\u00ed como para modelar variantes modificadas de estas mol\u00e9culas. A AlphaFold se le presenta una lista de mol\u00e9culas y, como salida, se genera una estructura 3D conjunta que determina la interacci\u00f3n m\u00e1s probable de las mol\u00e9culas especificadas. <\/p>\n

Desde un punto de vista pr\u00e1ctico, AlphaFold 3 puede utilizarse para el desarrollo de medicamentos y m\u00e9todos de tratamiento, as\u00ed como para la creaci\u00f3n de nuevas prote\u00ednas. Por ejemplo, se ha dise\u00f1ado una prote\u00edna con AlphaFold capaz de unirse a ciertas c\u00e9lulas cancerosas, lo que puede ser utilizado en la terapia contra el c\u00e1ncer de nueva generaci\u00f3n. AlphaFold tambi\u00e9n se usa activamente en el estudio de la interacci\u00f3n de anticuerpos con prote\u00ednas para comprender la respuesta inmunitaria humana y en la creaci\u00f3n de nuevos anticuerpos.
\n
Fuente: 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 ha abierto el c\u00f3digo de AlphaFold 3, un sistema de IA para modelar la estructura de prote\u00ednas | ProHoster","description":"La compa\u00f1\u00eda Google DeepMind ha publicado los textos fuente del sistema de aprendizaje autom\u00e1tico AlphaFold 3, dise\u00f1ado para predecir la estructura tridimensional de las 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