Thermodynamics of Huntingtin Aggregation

Abstract

Amyloid aggregates are found in many neurodegenerative diseases, including Huntington's, Alzheimer's, and prion diseases. The precise role of the aggregates in disease progression has been difficult to elucidate because of the diversity of aggregated states they can adopt. Here, we study the formation of fibrils and oligomers by exon 1 of huntingtin protein. We show that the oligomer states are consistent with polymer micelles that are limited in size by the stretching entropy of the polyglutamine region. The model shows how the sequences flanking the amyloid core modulate aggregation behavior. The N17 region promotes aggregation through weakly attractive interactions, whereas the C38 tail opposes aggregation via steric repulsion. We also show that the energetics of cross-β stacking by polyglutamine would produce fibrils with many alignment defects, but minor perturbations from the flanking sequences are sufficient to reduce the defects to the level observed in experiment. We conclude with a discussion of the implications of this model for other amyloid-forming molecules.

Figure 1

Cartoon representation of the three states of Htt. In the monomer state, the peptide collapses into a globule containing both polyQ and N-terminal regions. The oligomer state is a micelle-like assembly of a few thousand monomers with a spherical core containing the polyQ and N-terminal regions. The fibril state is a cross-β amyloid core of polyQ flanked by disordered tails on both sides. To see this figure in color, go online.

Figure 2

Cartoon representation of the in-register state and misregistered states. The registry variable, R, defines the alignment of an incoming molecule with the existing fibril. R = 0 indicates perfect alignment of the polyQ region, whereas negative and positive values indicate N-terminal and C-terminal shifts, respectively. To see this figure in color, go online.

Figure 3

Comparison between the theoretical model and experimentally measured critical concentrations. The model captures the effects of N17 and increasing polyQ length in promoting aggregation and the effect of C38 in inhibiting it. To see this figure in color, go online.

Figure 4

Predicted free energy of monomer collapse for peptides with and without the N-terminal tail as a function of ${\ell }_Q$. The results show that peptides with fewer glutamines will prefer the expanded state, whereas longer glutamine peptides will favor the collapsed states. The presence of the N17 tail contributes to the collapse free energy, but less strongly than glutamine residues. To see this figure in color, go online.

Figure 5

(A) Predicted free energy of oligomer formation for ${\ell }_Q$ = 20, 30, and 40 in the presence and absence of N- and C-terminal tails. Increasing the length of the polyQ region or adding the N17 tail results in larger oligomers because the extra length more easily stretches to fill the oligomer core. However, adding the C38 tail adds a repulsive energy that favors smaller oligomers. (B) Changing the polyQ length has an exponential effect on the critical concentration for oligomer formation. The critical concentration drops by more than a factor of 10³ upon changing the ${\ell }_Q$ from 20 to 40. To see this figure in color, go online.

Figure 6

Probabilities of misaligned molecules within an Htt fibril as a function of the alignment registry R and ε_CQ (for ε_β = −0.91 k_BT). The inset shows alignment probabilities for ε_CQ = 0.5 k_BT, with an additional constraint preventing states with R > 1 because this would lead to the burial of the lysine charge. To see this figure in color, go online.