Wild-Type α-Synuclein Structure and Aggregation: A Comprehensive Coarse-Grained and All-Atom Molecular Dynamics...

Area of Science:

• Biophysics
• Computational Biology
• Neuroscience

Background:

• Alpha-synuclein (α-syn) is intrinsically disordered and central to Parkinson's disease pathogenesis.
• Accurately simulating α-syn structure and aggregation is crucial for understanding Parkinson's disease and developing therapies.
• Coarse-grained (CG) force fields offer a computationally efficient alternative to all-atom simulations for large intrinsically disordered proteins (IDPs).

Purpose of the Study:

• To compare the accuracy of different coarse-grained (CG) force fields (Martini3, Sirah2) and all-atom (AA) force fields (Amber99sb, Charmm36m) in simulating α-syn structure and aggregation.
• To investigate the impact of protein-water interactions and enhanced sampling methods on CG simulations of α-syn.
• To evaluate the stability of CG α-syn fibrils and the aggregation propensity of the NACore peptide.

Main Methods:

• Molecular dynamics simulations using Martini3, Sirah2, Amber99sb, and Charmm36m force fields.
• Analysis of α-syn monomer structure, dynamics, and fibril stability.
• Umbrella sampling simulations to calculate free energy profiles for α-syn and NACore peptide aggregation.
• Investigation of protein-water interactions and the necessity of enhanced sampling techniques.

Main Results:

• While Martini3 and Sirah2 models show similar α-syn monomer structures, they exhibit significant differences in aggregation behavior.
• The Martini3 fibril model proved unstable, and its binding free energy for α-syn and NACore was positive.
• Sirah2, particularly with enhanced protein-water interactions and neutral termini, demonstrated stable aggregation and provided free energy profiles comparable to all-atom models.

Conclusions:

• The choice of CG force field significantly impacts the simulation of α-syn aggregation.
• Sirah2, with optimized parameters for protein-water interactions and termini, is a suitable CG model for studying α-syn protein-protein and protein-drug interactions.
• Accurate simulation of α-syn aggregation using CG models holds promise for advancing Parkinson's disease research and therapeutic development.