A polymer physics perspective on driving forces and mechanisms for protein aggregation

Abstract

Protein aggregation is a commonly occurring problem in biology. Cells have evolved stress-response mechanisms to cope with problems posed by protein aggregation. Yet, these quality control mechanisms are overwhelmed by chronic aggregation-related stress and the resultant consequences of aggregation become toxic to cells. As a result, a variety of systemic and neurodegenerative diseases are associated with various aspects of protein aggregation and rational approaches to either inhibit aggregation or manipulate the pathways to aggregation might lead to an alleviation of disease phenotypes. To develop such approaches, one needs a rigorous and quantitative understanding of protein aggregation. Much work has been done in this area. However, several unanswered questions linger, and these pertain primarily to the actual mechanism of aggregation as well as to the types of inter-molecular associations and intramolecular fluctuations realized at low protein concentrations. It has been suggested that the concepts underlying protein aggregation are similar to those used to describe the aggregation of synthetic polymers. Following this suggestion, the relevant concepts of polymer aggregation are introduced. The focus is on explaining the driving forces for polymer aggregation and how these driving forces vary with chain length and solution conditions. It is widely accepted that protein aggregation is a nucleation-dependent process. This view is based mainly on the presence of long times for the accumulation of aggregates and the elimination of these lag times with "seeds". In this sense, protein aggregation is viewed as being analogous to the aggregation of colloidal particles. The theories for polymer aggregation reviewed in this work suggest an alternative mechanism for the origin of long lag times in protein aggregation. The proposed mechanism derives from the recognition that polymers have unique dynamics that distinguish them from other aggregation-prone systems such as colloidal particles.

Figure 1

Sketch of the coil-to-globule transition for generic, flexible polymers as a function of solvent quality. The abscissa shows improving solvent quality, i.e., it goes from being poor to good. In a poor solvent, the chain prefers compact species, with small R_g, and in a good solvent the chain is swollen, with large R_g, to promote favorable contacts with the surrounding solvent. The transition between these two stable states is sharp, and the sharpness increases with chain length, N. In the schematic, N₁ > N₂ > N₃ and the shaded region delineates the transition region. The midpoint of the transition, which is reliably identified for longer chains, is the theta point.

Figure 2

Illustration of the parsing of a full-length protein sequence into blob-sized segments. The figure also shows the mutual repulsion of these blobs in a good solvent (top) and the mutual attraction of blobs in a poor solvent (bottom). Here, the number of residues in a blob is taken to be 7 and this is based on previous analysis of correlation lengths within protein sequences [33].

Figure 3

Typical thermodynamic phase diagram for polymer solutions. The ordinate denotes improving solvent quality expressed either as temperature or as Flory’s χ-parameter. At the theta-temperature, T_θ, and beyond (good solvent regime) no phase separation is observed. The overlap concentration at the theta point is marked by the green dotted line. For T < T_θ, a homogeneous mixed phase of polymer in solvent is formed in region 2, and of solvent in polymer in region 6. Conversely, phase separation is realized in regions 3, 4, and 5. The solid red curve denotes the binodal, while the dashed red curve denotes the spinodal. The dotted red lines denote the critical point (ϕ_c, T_c), while ϕ′ and ϕ″ indicate the polymer volume fractions on the coexistence curve (binodal) for a specific temperature, and hence define the miscibility gap.

Figure 4

Sketch of the process by which clusters of globules are predicted to form during the lag phase in protein aggregation. Each species in the schematic is labeled by the size of the largest cluster within the species, n_c. The conformational ensemble for the monomer is heterogeneous as is the ensemble of oligomer species that forms via intermolecular associations. Additionally, there will be multiple routes to cluster formation and the clusters could either be kinetic or equilibrium intermediates. For isolated globules and for small clusters, individual chains experience finite surface tension due to unfavorable interfaces with the surrounding solvent. Consequently, conformational conversion in smaller clusters will be slow. The stabilities of clusters, the rates for conformational conversion, and the surface tension per chain will vary with chain length, protein sequence, protein concentration, and solution conditions. When the cluster size grows, individual chains become sequestered from unfavorable interfaces with solvent and average surface tension per molecule becomes negligible. This in turn promotes the unraveling and entanglement of individual chains. Ordered aggregation follows rapidly because of chain entanglement. The key point is that, there are no prerequisites for specific conformations of individual chains or cluster sizes for formation and growth of clusters of chains in poor solvents.