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<dc:title xml:lang="fr">Cartographie chimique et modélisation de systèmes complexes</dc:title>
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<dc:subject xml:lang="fr">Criblage virtuel</dc:subject>
<dc:subject xml:lang="fr">Conception de chimiothèques</dc:subject>
<dc:subject xml:lang="fr">Visualisation de données</dc:subject>
<dc:subject xml:lang="fr">Bibliothèques combinatoires dynamiques</dc:subject>
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<dcterms:abstract xml:lang="fr">Cette thèse concerne l’utilisation de la Cartographie Topographique Générative (Generative Topographic Mapping – GTM) pour l’analyse et la visualisation de jeux de données, le criblage virtuel et la conception de chimiothèques. La performance en criblage virtuel de modèles GTM de classification multi-cibles (uGTM) a été étudiée et l’utilisation de plusieurs uGTM en consensus a été proposée. Un criblage virtuel utilisant une combinaison de la GTM avec d’autres techniques de chémoinformatique a permis de découvrir 29 nouveaux inhibiteurs de BRD4 dont l’activité a été prouvée expérimentalement. La GTM a été comparée à la méthode MaxMin comme outil de conception de chimiothèques. Il a été trouvé que malgré le fait que les chimiothèques obtenues avec MaxMin sont plus diverses que celles obtenues avec la GTM, cette dernière est plus rapide et peut être appliquée à des jeux de données plus larges. Un protocole de modélisation pour l’analyse de spéciation de bibliothèques combinatoires dynamiques basées sur la réaction de formation d’imines en absence et en présence d’une protéine a été proposé. Les modèles développés sont disponibles au public sur le site de Laboratoire de Chémoinformatique.</dcterms:abstract>
<dcterms:abstract xml:lang="en">This work concerns application of Generative Topographic Mapping method to different tasks including data analysis and visualization, virtual screening and library design. Performance of multi-target GTM-based classification models (uGTM) in virtual screening was investigated and consensus usage of several uGTMs has been suggested. Virtual screening involving a combination of GTM with some other chemoinformatics techniques allowed to discover 29 new BRD4 inhibitors, activities of which were experimentally confirmed. As a library design tool, GTM was compared to the MaxMin method. Although diversity of MaxMin libraries is systematically larger than those obtained with GTM, the latter is much faster and, therefore, can be recommended for large datasets. A modeling workflow for speciation analysis in imine-based Dynamic Combinatorial Libraries in absence and presence of a protein has been suggested. Developed models are publicly available at the site of the Laboratory of Chemoinformatics.</dcterms:abstract>
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