| KEYWORD |
Computational investigations of the link between heperphosphorylation of MAP tau and zinc binding in Alzheimer's disease
keywords ALZHEIMER'S DISEASE, COMPUTATIONAL MODELING, HYPERPHOSPHORYLATION, RATIONAL DRUG DESIGN, TAUOPATHY
Reference persons MARCO AGOSTINO DERIU, JACEK ADAM TUSZYNSKI
External reference persons Prof. Maral Aminpour, Department of Biomedical Engineering, University of Alberta
Research Groups 28- biomedica
Thesis type COMPUTATIONAL
Description This project will address one of the main pathological manifestations of Alzheimer's disease, namely tauopathy. Chronic and progressive neurodegenerative diseases (NDDs) such as Alzheimer’s pose a critical challenge to the healthcare system because an aging population is rapidly increasing the number of people at risk, yet there is no effective disease-modifying therapy. Lack of therapeutic solutions for Alzheimer's disease is largely due to a complex molecular mechanism that still needs to find a real causative effect. Many attempts to find drugs that can inhibit pathological aggregation of proteins such as MAP-tau, a typical hallmark in Alzheimer's, had little to no success to date. A typical process observed at a cellular level that leads to NDDs is the disruption of the structural dynamics of microtubules (MTs), following an abnormal dysregulation of the MT- associated protein tau (MAPtau) due to its hyperphosphorylation and subsequent detachment from MTs. In this research we will first examine the hypothesized connection between zinc binding to tau that may trigger hyperphosphorylation and detachment from MTs followed by MT destabilization. The computational strategy will focus on MAPtau and attempt to create homology models of zinc-binding regions and phosphorylations sites followed by their equilibration and refinement of homology models. We will then perform docking, screening, ranking and re-design of suitable compounds to act as inhibitors. Algorithms, such as AUTODOCK, are able to identify small molecules that can fit into the ligand binding sites on proteins of known structure and have been used successfully to identify novel protein-ligand interactions. These compounds are further filtered with post-screening methods such as detailed MD calculations. These results will be the basis for commercial acquisition of the top ranked compounds as only publicly available databases will be screened in view of the limited time and budget available. The experimental validation aspect of the project will be performed in collaboration with Prof. Rudy Tanzi at the Harvard Medical School, Cambridge, Mass. while the computational work will be performed at the University of Alberta with the assistance of Prof. Maral Aminpour (Department of Biomedical Engineering). The student is expected to spend some of the time in Canada.
Required skills basic computational modeling using MOE, docking, homology modeling, molecular dynamic
Notes Due to on-going COVID pandemic, travel to Canada will require mandatory vaccination and approval from the University of Alberta as a formal exchange student. The tuition fees at the University of Alberta will be paid by the host.
Deadline 30/11/2022
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