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http://dspace1.univ-tlemcen.dz/handle/112/19632
Titre: | Élucidations de processus de pathologies neurodégénératives par modélisation moléculaires Maladie d’Alzheimer. |
Auteur(s): | NEBIA-MEZIANE, Assia |
Mots-clés: | Molecular docking, ButylCholinesterase, Alzheimer's, treatments Docking moléculaire, ButylCholinestérase, Alzheimer, traitements |
Date de publication: | 25-jui-2022 |
Editeur: | 17-11-2022 |
Référence bibliographique: | salle des thèses |
Collection/Numéro: | BFST2808; |
Résumé: | To treat Alzheimer’s Disease (AD), which is the most prevalent form of dementia, cholinesterase enzymes (AChE and BuChE) and amyloid-beta (Aβ) are attractive targets. In this work, different computational approach namely Density Functional Theory (DFT), Molecular Docking, and multiQSAR modeling were performed on 22 donepezil-based derivatives which were reported as potent dual Aβ and (AChE and BuChE) inhibitors. The molecular geometries of the studied derivatives were carried out using GAUSSIAN 09 software with the level of theory (DFT, 6/31g*). The dual inhibitors adopted minimum energy. The results pointed out the importance of the inhibitors' geometries in enzyme inhibition. The QSAR models elaborated by means of Molecular Operating Environment (MOE) package, showed good statistical values for targets AChE (R²adj = 0.976, q2 = 0.871, RMS = 0.130), BuChE (R²adj = 0.976, q2 = 0.554, RMS = 0.092) and Aβ (R²adj = 0.861, q2 = 0.525, RMS = 0.113). To identify the binding pattern between the ligands and target enzymes, we implemented molecular docking studies for the datasets. The obtained information was related to the essential structural features that were related to the QSAR of the predicted models. |
URI/URL: | http://dspace.univ-tlemcen.dz/handle/112/19632 |
Collection(s) : | Doctorat LMD en chimie |
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thèse doctorat meziane corrigé (2).pdf | CD | 2,24 MB | Adobe PDF | Voir/Ouvrir |
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