Abstract
Polyglutamine (polyQ) aggregation plays a central role in several neurodegenerative diseases, including Huntington's disease. To investigate the underlying mechanisms of polyQ aggregation, we developed a coarse-grained molecular dynamics model calibrated using atomistic simulations and experimental data. To assess the model's predictive power beyond the calibrated parameter set, we systematically varied side chain interaction strength and hydrogen bonding strength to explore a broader range of aggregation pathways. These pathways ranged from nucleated growth to liquid-to-solid phase transitions. Through seeded aggregation simulations, we observed that amyloid growth occurs primarily in the β-sheet elongation direction, although growth through steric zippering was also observed. Longer polyQ sequences (Q48) exhibited significantly faster growth compared to shorter sequences (Q23), underscoring the role of chain length in aggregation kinetics. Our model provides a versatile framework for studying polyQ aggregation and offers a foundation for investigating broader aggregation mechanisms and sequence variations.