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Modulation of α-synuclein Aggregation Amid Diverse Environmental Perturbation

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Journal Elife
Specialty Biology
Date 2024 Aug 1
PMID 39087984
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Abstract

Intrinsically disordered protein α-synuclein (αS) is implicated in Parkinson's disease due to its aberrant aggregation propensity. In a bid to identify the traits of its aggregation, here we computationally simulate the multi-chain association process of αS in aqueous as well as under diverse environmental perturbations. In particular, the aggregation of αS in aqueous and varied environmental condition led to marked concentration differences within protein aggregates, resembling liquid-liquid phase separation (LLPS). Both saline and crowded settings enhanced the LLPS propensity. However, the surface tension of αS droplet responds differently to crowders (entropy-driven) and salt (enthalpy-driven). Conformational analysis reveals that the IDP chains would adopt extended conformations within aggregates and would maintain mutually perpendicular orientations to minimize inter-chain electrostatic repulsions. The droplet stability is found to stem from a diminished intra-chain interactions in the C-terminal regions of αS, fostering inter-chain residue-residue interactions. Intriguingly, a graph theory analysis identifies within droplets across environmental conditions, suggesting the prevalence of a consensus interaction patterns among the chains. Together these findings suggest a delicate balance between molecular grammar and environment-dependent nuanced aggregation behavior of αS.

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Modulation of α-synuclein aggregation amid diverse environmental perturbation.

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PMID: 39087984 PMC: 11293868. DOI: 10.7554/eLife.95180.

References
1.
Joseph J, Reinhardt A, Aguirre A, Chew P, Russell K, Espinosa J . Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy. Nat Comput Sci. 2022; 1(11):732-743. PMC: 7612994. DOI: 10.1038/s43588-021-00155-3. View

2.
Benayad Z, von Bulow S, Stelzl L, Hummer G . Simulation of FUS Protein Condensates with an Adapted Coarse-Grained Model. J Chem Theory Comput. 2020; 17(1):525-537. PMC: 7872324. DOI: 10.1021/acs.jctc.0c01064. View

3.
Tesei G, Lindorff-Larsen K . Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range. Open Res Eur. 2023; 2:94. PMC: 10450847. DOI: 10.12688/openreseurope.14967.2. View

4.
Ahmed M, Skaanning L, Jussupow A, Newcombe E, Kragelund B, Camilloni C . Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods. Front Mol Biosci. 2021; 8:654333. PMC: 8100456. DOI: 10.3389/fmolb.2021.654333. View

5.
Best R, Zheng W, Mittal J . Balanced Protein-Water Interactions Improve Properties of Disordered Proteins and Non-Specific Protein Association. J Chem Theory Comput. 2014; 10(11):5113-5124. PMC: 4230380. DOI: 10.1021/ct500569b. View