{"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\/it\/blog\/news\/deepmind-otkryl-kod-alphafold-3-ai-sistemy-modelirovaniya-struktury-belkov","title":{"rendered":"DeepMind ha reso pubblico il codice di AlphaFold 3, un sistema AI per la modellazione della struttura delle proteine","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

La compagnia Google DeepMind ha pubblicato i codici sorgente del sistema di apprendimento automatico AlphaFold 3, progettato per prevedere la struttura tridimensionale delle proteine e modellare l'interazione delle proteine con altri tipi di molecole. Per la creazione degli algoritmi di apprendimento automatico realizzati nella seconda versione di AlphaFold, quest'anno \u00e8 stato assegnato il premio Nobel per la chimica. Gli strumenti associati a AlphaFold 3 sono scritti in Python e C++, e sono distribuiti con licenza CC BY-NC-SA 4.0. I modelli addestrati sono forniti sulla base di un accordo d'uso. Separatamente \u00e8 stato avviato server<\/a>, che consente di sperimentare con AlphaFold 3 in modalit\u00e0 online. <\/p>\n

Il modello, addestrato su una collezione che descrive le strutture di tutte le proteine e le sequenze di amminoacidi conosciute, affronta il problema del ripiegamento delle proteine e consente di prevedere la struttura tridimensionale di nuove proteine con una precisione almeno equivalente a quella dell'analisi di laboratorio, e nella valutazione delle interazioni delle proteine con altri tipi di molecole supera di gran lunga i metodi di previsione esistenti. La terza versione del modello AlphaFold si distingue per l'uso di una nuova architettura \"Pairformer\", che sviluppa l'idea dell'architettura \"trasformatore\". <\/p>\n

A differenza di AlphaFold 2, la nuova versione non \u00e8 limitata alle proteine costituite da una sola catena polipeptidica e pu\u00f2 essere applicata per prevedere complessi proteici con DNA e RNA, nonch\u00e9 per modellare varianti modificate di queste molecole. Ad AlphaFold viene fornito un elenco di molecole e in uscita viene generata una struttura 3D congiunta che determina l'interazione pi\u00f9 probabile tra le molecole specificate. <\/p>\n

Dal punto di vista pratico, AlphaFold 3 pu\u00f2 essere utilizzato per lo sviluppo di farmaci e trattamenti, oltre che per la creazione di nuove proteine. Ad esempio, utilizzando AlphaFold, \u00e8 stata progettata una proteina capace di legarsi a determinate cellule tumorali, il che pu\u00f2 essere utilizzato nella terapia oncologica di nuova generazione. AlphaFold \u00e8 anche utilizzato attivamente nello studio delle interazioni tra anticorpi e proteine per comprendere la risposta immunitaria dell'uomo e per creare nuovi anticorpi.
\n
Fonte: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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\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 aperto il codice di AlphaFold 3, un sistema AI per la modellazione della struttura delle proteine | ProHoster","description":"L'azienda Google DeepMind ha pubblicato i codici sorgente del sistema di apprendimento automatico AlphaFold 3, progettato per prevedere la struttura tridimensionale delle proteine e modellare le 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