SummaryPolyglutamine expansions within different proteins are associated with nine different neurodegenerative diseases. There is growing interest in understanding the roles of flanking sequences from disease-relevant proteins on the intrinsic conformational and aggregation properties of polyglutamine. We report results, from atomistic simulations and circular dichroism experiments that quantify the effect of the N-terminal 17-residue (Nt17) segment of the huntingtin protein on polyglutamine conformations and intermolecular interactions. We show that the Nt17 segment and polyglutamine domains become increasingly disordered as polyglutamine length (N) increases in Nt17-Q N constructs. Hydrophobic groups within Nt17 become sequestered in intramolecular, interdomain interfaces. We also show that the Nt17 segment suppresses the intrinsic propensity of polyglutamine aggregation. This inhibition arises from the incipient micellar structures adopted by monomeric forms of the peptides with Nt17 segments. The degree of intermolecular association increases with increasing polyglutamine length and is governed mainly by associations between polyglutamine domains. Comparative analysis of intermolecular associations for different polyglutamine containing constructs leads to clearer interpretations of recently published experimental data. Our results suggest a framework for fibril formation, and identify roles for flanking sequences in modulating polyglutamine aggregation.

We describe a method by which a single experiment can reveal both association model (pathway and constants) and low-resolution structures of a self-associating system. Small-angle scattering data are collected from solutions at a range of concentrations. These scattering data curves are mass-weighted linear combinations of the scattering from each oligomer. Singular value decomposition of the data yields a set of basis vectors from which the scattering curve for each oligomer is reconstructed using coefficients that depend on the association model. A search identifies the association pathway and constants that provide the best agreement between reconstructed and observed data. Using simulated data with realistic noise, our method finds the correct pathway and association constants. Depending on the simulation parameters, reconstructed curves for each oligomer differ from the ideal by 0.05-0.99% in median absolute relative deviation. The reconstructed scattering curves are fundamental to further analysis, including interatomic distance distribution calculation and low-resolution ab initio shape reconstruction of each oligomer in solution. This method can be applied to x-ray or neutron scattering data from small angles to moderate (or higher) resolution. Data can be taken under physiological conditions, or particular conditions (e.g., temperature) can be varied to extract fundamental association parameters (DeltaH(ass), DeltaS(ass)).

In studying interacting proteins, complementary insights are provided by analyzing both the association model (the stoichiometry and affinity constants of the intermediate and final complexes) and the quaternary structure of the resulting complexes. Many current methods for analyzing protein interactions either give a binary answer to the question of association and no information about quaternary structure or at best provide only part of the complete picture. Presented here is a method to extract both types of information from X-ray or neutron scattering data for a series of equilibrium mixtures containing the initial components at different concentrations. The method determines the association pathway and constants, along with the scattering curves of the individual members of the mixture, so as to best explain the scattering data for the mixtures. The derived curves then enable reconstruction of the intermediate and final complexes. Using simulated solution scattering data for four hetero-oligomeric complexes with different structures, molecular weights and association models, it is demonstrated that this method accurately determines the simulated association model and scattering profiles for the initial components and complexes. Recognizing that experimental mixtures contain static contaminants and nonspecific complexes with the lowest affinities (inter-particle interference) as well as the desired specific complex(es), a new analytical method is also employed to extend this approach to evaluating the association models and scattering curves in the presence of static contaminants, testing both a nonparticipating monomer and a large homo-oligomeric aggregate. It is demonstrated that the method is robust to both random noise and systematic noise from such contaminants, and the treatment of nonspecific complexes is discussed. Finally, it is shown that this method is applicable over a large range of weak association constants typical of specific but transient protein-protein complexes.