| KEYWORD |
Computational design and in silico prediction of the mode of action of novel alpha synuclein inhibitors as future Parkinson's disease therapeutics
keywords ALPHA SYNUCLEIN, COMPUTATIONAL DRUG DESIGN, INTRINSICALLY DISORDERED PROTEINS, PARKINSON'S DISEASE
Reference persons JACEK ADAM TUSZYNSKI
External reference persons Prof. Maral Aminpour, Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
Research Groups 28- biomedica
Thesis type COMPUTATIONAL
Description Parkinson's disease is a neurodegenerative disorder associated with pathological aggregation of an intrinsically disordered protein called alpha synuclein. In collaboration with researchers at the University of Alberta, we have performed computational modeling of alpha synuclein and its aggregation. The initial virtual screening campaign resulted in the identification of several compounds from public medicinal databases which have been validated in force-extension experiments using laser tweezers. With the validated model and several active compounds, we can now perform optimization of these molecules by enriching the library and derivatization. This project will explore both the existing chemical space for optimized binding to alpha synculein and improved pharmacokinetic properties and derivatization potential of the identified active compounds.
Required skills basic molecular modeling skills: docking, molecular mechanics, visualization
bioinformatics and chemo-informatics
Notes This project may lead to an internship period at the University of Alberta, Canada.
Deadline 24/11/2023
PROPONI LA TUA CANDIDATURA