Abstract

Despite a large amount of time and effort invested, the development of drugs targeting intrinsically disordered proteins (IDPs) is a major open problem in pharmacology. Classic drug development strategies are impeded by the highly dynamic nature of IDPs. We propose a strategy to identify inhibitors of the pathological aggregation of the IDP tau, implicated in Alzheimer's disease and other neurodegenerative disorders. We approach this problem by utilizing computational approaches and in vitro experiments to develop new modulators of tau aggregation as discussed below.Initially, computational simulations were used to generate conformational ensembles of tau244-372, the aggregation-prone microtubule binding region of tau. For this purpose, conventional molecular dynamics (MD) simulations were compared against enhanced sampling methods, including a recently developed novel approach based on repeated simulated annealing (ReSA).Preferentially sampled conformations within these dynamic ensembles were identified based on local and global structural similarity. To do this, the structures were grouped together based on root mean standard deviations (RMSD) between conformations and representative structures then generated from these groups. Subsequent computational screening identified selective ligands of these preferentially sampled structures by creating receptor force-fields from the representative structures and scoring potential ligand affinity based on steric, electrostatic and hydrophobic properties.Finally, computational hits were validated using a variety of biophysical methods including fibril-formation assays and single-molecule fluorescence approaches such as fluorescence correlation spectroscopy.This strategy has the potential to enhance our ability to rationally target IDPs for pharmacological intervention and may prove valuable in tackling other IDP-related pathologies such as Parkinson's disease, Diabetes, and Huntington's disease.

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