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                <authority type="jury">Marc Baaden [Rapporteur]</authority>
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                <term xml:lang="en">Green chemistry</term>
                <term xml:lang="en">Antibacterial</term>
                <term xml:lang="en">Skin permeability</term>
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                <term xml:lang="en">Cosmetics</term>
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                <term xml:lang="fr">Antibactérien</term>
                <term xml:lang="fr">Perméabilité cutanée</term>
                <term xml:lang="fr">Chimie verte</term>
                <term xml:lang="fr">SGTM</term>
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              <p>Cette thèse présente des approches chimi-informatiques pour la conception d’ingrédients cosmétiques bio-sourcés et polyfonctionnels dans le cadre du projet CosMoPoly. Une bibliothèque virtuelle de 25289 molécules a été générée à partir de blocs de construction renouvelables selon les principes de la chimie verte. Des modèles de Relations Quantitatives Structure-Activité/Propriété (QSAR/QSPR) ont été développés pour prédire la perméabilité cutanée et l’activité antibactérienne contre Staphylococcus aureus et S. epidermidis. Le Generative Topographic Mapping (GTM) et son extension sphérique (SGTM) ont été utilisés pour visualizer la bibliothèque CosMoPoly et construire des paysages de propriétés, offrant une meilleure compréhension de la diversité moléculaire et des prédictions des modèles. Ce travail démontre comment la chimie durable et la modélisation prédictive favorisent la découverte de molécules innovantes et éco-responsables.</p>
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