Summary
Protein aggregation hallmarks several neurodegenerative diseases, including Alzheimer's and Parkinson's. In Parkinson's, aggregation of the intrinsically disordered protein (IDP) alpha-synuclein (αSyn) leads to its intracellular deposition into Lewy bodies, which causes neuronal dysfunction. Recently it was discovered that αSyn can undergo liquid-liquid phase separation (LLPS), whereby a protein solution spontaneously separates into a dense and a dilute phase. This process is initially reversible, but the high concentrations of the dense phase strongly favor the aggregation of αSyn into amyloid fibrils. Structural characterization of the transient αSyn conformations during LLPS and amyloid formation is therefore crucial for understanding the disease pathology on the molecular level. This project aims to develop a novel experimental concept for the high-resolution conformational analysis of αSyn assembly and aggregation using scanning mutagenesis combined with cutting-edge high-throughput biophysical techniques and computational analysis. The core idea is to apply multiple biophysical assays to quantify the effects of hundreds of αSyn mutations on the kinetics and thermodynamics of LLPS and amyloid formation. The resulting multidimensional experimental datasets will be processed within the phi-value analysis framework originally derived for protein folding and combined with molecular dynamics simulations. The integrated methodology will allow gaining important structural and mechanistic insights into the early-aggregation events of αSyn at a single amino acid level of resolution. The project includes extensive training to enhance my scientific skills in modern experimental and computational methods. The proposed strategy is widely applicable to other IDP systems that can undergo LLPS and aggregation and paves the way for the design of rational and precisely tailored intervention strategies against the diseases associated with these phenomena.
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| Web resources: | https://cordis.europa.eu/project/id/101106115 |
| Start date: | 01-08-2023 |
| End date: | 31-07-2025 |
| Total budget - Public funding: | - 214 934,00 Euro |
Cordis data
Original description
Protein aggregation hallmarks several neurodegenerative diseases, including Alzheimer's and Parkinson's. In Parkinson's, aggregation of the intrinsically disordered protein (IDP) alpha-synuclein (αSyn) leads to its intracellular deposition into Lewy bodies, which causes neuronal dysfunction. Recently it was discovered that αSyn can undergo liquid-liquid phase separation (LLPS), whereby a protein solution spontaneously separates into a dense and a dilute phase. This process is initially reversible, but the high concentrations of the dense phase strongly favor the aggregation of αSyn into amyloid fibrils. Structural characterization of the transient αSyn conformations during LLPS and amyloid formation is therefore crucial for understanding the disease pathology on the molecular level. This project aims to develop a novel experimental concept for the high-resolution conformational analysis of αSyn assembly and aggregation using scanning mutagenesis combined with cutting-edge high-throughput biophysical techniques and computational analysis. The core idea is to apply multiple biophysical assays to quantify the effects of hundreds of αSyn mutations on the kinetics and thermodynamics of LLPS and amyloid formation. The resulting multidimensional experimental datasets will be processed within the phi-value analysis framework originally derived for protein folding and combined with molecular dynamics simulations. The integrated methodology will allow gaining important structural and mechanistic insights into the early-aggregation events of αSyn at a single amino acid level of resolution. The project includes extensive training to enhance my scientific skills in modern experimental and computational methods. The proposed strategy is widely applicable to other IDP systems that can undergo LLPS and aggregation and paves the way for the design of rational and precisely tailored intervention strategies against the diseases associated with these phenomena.Status
SIGNEDCall topic
HORIZON-MSCA-2022-PF-01-01Update Date
31-07-2023
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