{"id":21363,"date":"2026-10-21T13:19:01","date_gmt":"2026-10-21T13:19:01","guid":{"rendered":"https:\/\/www.sygnaturediscovery.com\/event\/les-sciences-des-proteines-dans-la-decouverte-de-medicaments\/"},"modified":"2026-10-22T14:32:31","modified_gmt":"2026-10-22T14:32:31","slug":"protein-sciences-in-drug-discovery","status":"publish","type":"event","link":"https:\/\/www.sygnaturediscovery.com\/fr\/event\/protein-sciences-in-drug-discovery\/","title":{"rendered":"Protein Sciences in Drug Discovery 2026"},"content":{"rendered":"\n

Rejoignez-nous \u00e0 la conf\u00e9rence \u00ab Protein Sciences in Drug Discovery 2026 \u00bb organis\u00e9e par l\u2019ELRIG<\/a> pour d\u00e9couvrir comment les avanc\u00e9es en sciences des prot\u00e9ines, la conception bas\u00e9e sur l\u2019IA et les nouvelles modalit\u00e9s th\u00e9rapeutiques permettent de relever les d\u00e9fis complexes de la d\u00e9couverte de m\u00e9dicaments, de la validation des cibles \u00e0 l\u2019optimisation des candidats-m\u00e9dicaments.<\/p>\n\n

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Vous ne pouvez pas assister \u00e0 la conf\u00e9rence \u00ab Protein Sciences in Drug Discovery \u00bb ?<\/p>\n\n

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Contactez directement notre \u00e9quipe<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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Solutions connexes<\/h2>\n\n\n\n

Nous r\u00e9unissons un m\u00e9lange dynamique de nouveaux talents et d\u2019experts chevronn\u00e9s de l\u2019industrie pharmaceutique du monde entier, garantissant l\u2019excellence \u00e0 chaque \u00e9tape de la d\u00e9couverte.<\/p>\n<\/div>\n\n<\/div>\n\t\t\n\t <\/section>\n<\/div>\n\n\n\n

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\n \n \"Protein<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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Science des Prot\u00e9ines et Biologie Structurale<\/a><\/h3>\n\n\n\n

Page d\u2019accueil du d\u00e9partement de prot\u00e9omique et de biologie structurale. Nous prenons le temps de comprendre votre objectif et les finalit\u00e9s de votre projet afin d\u2019adapter notre approche en cons\u00e9quence. <\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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\n \n \"Generative<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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Intelligence artificielle g\u00e9n\u00e9rative et apprentissage automatique<\/a><\/h3>\n\n\n\n

En combinant la conception pilot\u00e9e par l\u2019IA, des mod\u00e8les d\u2019apprentissage automatique sur mesure et la bioinformatique bas\u00e9e sur le LLM avec une collaboration pratique, nous vous aidons \u00e0 d\u00e9couvrir plus rapidement des candidats m\u00e9dicaments optimis\u00e9s.<\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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\n \n \"Protein<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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Pr\u00e9diction de la structure des prot\u00e9ines<\/a><\/h3>\n\n\n\n

L\u2019utilisation d\u2019une IA avanc\u00e9e et de techniques de mod\u00e9lisation \u00e9prouv\u00e9es permet de pr\u00e9dire avec pr\u00e9cision les structures prot\u00e9iques, acc\u00e9l\u00e9rant ainsi la conception de m\u00e9dicaments bas\u00e9e sur la structure et la d\u00e9couverte de nouvelles th\u00e9rapies.
possibilit\u00e9s.<\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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\n \n \"Membrane<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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Prot\u00e9ines membranaires<\/a><\/h3>\n\n\n\n

Cette classe de prot\u00e9ines complexe et diversifi\u00e9e compte parmi les plus pr\u00e9cieuses pour la d\u00e9couverte de m\u00e9dicaments. Chez Sygnature, nous disposons d\u2019une \u00e9quipe de sp\u00e9cialistes d\u00e9di\u00e9e \u00e0 la production de ces cibles difficiles \u00e0 ma\u00eetriser. <\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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\n \n \"Protein<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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Caract\u00e9risation des prot\u00e9ines<\/a><\/h3>\n\n\n\n

Nous proposons des techniques biophysiques de pointe pour l\u2019identification, la qualit\u00e9 et la stabilit\u00e9 des prot\u00e9ines, notamment la spectrom\u00e9trie de masse, la FIDA et la RMN, adapt\u00e9es \u00e0 vos besoins de recherche.<\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n
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\n \n \"Antibody<\/source><\/picture>\n\n \n <\/section><\/div>\n\n\n\n
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conjugu\u00e9s anticorps-m\u00e9dicament<\/a><\/h3>\n\n\n\n

D\u00e9couvrez plus en d\u00e9tail notre large \u00e9ventail de capacit\u00e9s pour soutenir les projets ADC.<\/p>\n\n\n\n

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Apprendre encore plus<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n<\/div>\n\t\t\n\t <\/section>\n","protected":false},"excerpt":{"rendered":"","protected":false},"featured_media":21365,"template":"post-template-4268","category":[1409,1410,819,933,815,1415],"events_category":[],"class_list":["post-21363","event","type-event","status-publish","has-post-thumbnail","hentry","category-adcs-conjugues-anticorps-medicament","category-caracterisation-des-proteines","category-decouverte-integree-de-medicaments","category-intelligence-artificielle-generative-et-apprentissage-automatique","category-proteines-et-structure","category-proteines-membranaires"],"acf":[],"yoast_head":"\nLes sciences des prot\u00e9ines au service de la d\u00e9couverte de m\u00e9dicaments | D\u00e9couvrez Sygnature<\/title>\n<meta name=\"description\" content=\"Le colloque \u00ab Protein Sciences in Drug Discovery 2026 \u00bb organis\u00e9 par ELRIG aborde la conception de prot\u00e9ines 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