| KEYWORD |
Computational search for potential inhibitors of toxic mutatants of APP as candidates for Alzheimer disease therapeutics
Parole chiave ALZHEIMER DISEASE, APP PROTEIN, DRUG DESIGN, MOLECULAR SIMULATIONS, TOXIC MUTATIONS
Riferimenti JACEK ADAM TUSZYNSKI
Riferimenti esterni Dr. Maral Aminpour of the Department of Biomedical Engineering, University of Alberta, Edmonton, Canada.
Gruppi di ricerca 28- biomedica
Tipo tesi COMPUTATIONAL
Descrizione The onset of Alzheimer disease is correlated with the accumulation of Aβ peptides as amply demonstrated by the Amyloid hypothesis. These peptides are obtained from the intracellular cleavage of the APP by two proteolytic enzymes, the β- and γ- secretases. APP is present at the neuronal synapses and is greatly expressed in the brain. It is responsible for synaptic plasticity, cell-cell and cell-matrix interactions, neuroprotection, and regulation of neuronal cell development. However, detrimental APP cleavage taking place within the amyloidogenic pathway leads to the formation of insoluble Aβ peptides, made up of 40-42 amino acids, which tend to form extracellular neurotoxic aggregates. The difference between the Aβ1-40 and Aβ1-42 peptides consists of two additional amino acids, I41 and A42, that seem to confer greater toxicity. In the brains of AD patients, those peptides can assemble in hierarchically organized structures called fibrils and fibres, which then assemble into plaques. This Aβ aggregates formation ultimately leads to neuronal death. In this project, the student will use computational modeling tools to search for inhibitors of these mutants using structure-based drug discovery employing MOE software and large medicinal chemistry compound databases.
Conoscenze richieste molecular modeling, familiarity with MOE software or equivalent tools, basic bioinformatics, medicinal chemistry databases, familiarity with the Protein Data Bank (PDB) and NCBI.
Scadenza validita proposta 23/07/2025
PROPONI LA TUA CANDIDATURA