Amyloid and amyloid-like fibrils are self-assembling protein nanostructures, of interest for their robust material properties and inherent biological compatibility as well as their putative role in a number of debilitating mammalian disorders. Understanding fibril formation is essential to the development of strategies to control, manipulate or prevent fibril growth. As such, this area of research has attracted significant attention over the last half century. This review describes a number of different models that have been formulated to describe the kinetics of fibril assembly. We describe the macroscopic implications of mechanisms in which secondary processes such as secondary nucleation, fragmentation or branching dominate the assembly pathway, compared to mechanisms dominated by the influence of primary nucleation. We further describe how experimental data can be analysed with respect to the predictions of kinetic models.

The aggregation and deposition of α-synuclein in Lewy bodies is associated with the progression of Parkinson's disease. Here, Mass Spectrometry (MS) is used in combination with Ion Mobility (IM), chemical crosslinking and Electron Capture Dissociation (ECD) to probe transient structural elements of α-synuclein and its oligomers. Each of these reveals different aspects of the conformational heterogeneity of this 14 kDa protein. IM-MS analysis indicates that this protein is highly disordered, presenting in positive ionisation mode with a charge state range of 5 ≤z≤ 21 for the monomer, along with a collision cross section range of ∼1600 Å(2). Chemical crosslinking applied in conjunction with IM-MS captures solution phase conformational families enabling comparison with those exhibited in the gas phase. Crosslinking IM-MS identifies 3 distinct conformational families, Compact (∼1200 Å(2)), Extended (∼1500 Å(2)) and Unfolded (∼2350 Å(2)) which correlate with those observed in solution. ECD-Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry (ECD-FT-ICR MS) highlights the effect of pH on α-synuclein structure, identifying the conformational flexibility of the N and C termini as well as providing evidence for structure in the core and at times the C terminus. A hypothesis is proposed for the variability displayed in the structural rearrangement of α-synuclein following changes in solution pH. Following a 120 h aggregation time course, we observe an increase in the ratio of dimer to monomer, but no gross conformational changes in either, beyond the significant variations that are observed day-to-day from this conformationally dynamic protein.

Kinetic measurements of the self-assembly of proteins into amyloid fibrils are often used to make inferences about molecular mechanisms. In particular, the lag time--the quiescent period before aggregates are detected--is often found to scale with the protein concentration as a power law, whose exponent has been used to infer the presence or absence of autocatalytic growth processes such as fibril fragmentation. Here we show that experimental data for lag time versus protein concentration can show signs of kinks: clear changes in scaling exponent, indicating changes in the dominant molecular mechanism determining the lag time. Classical models for the kinetics of fibril assembly suggest that at least two mechanisms are at play during the lag time: primary nucleation and autocatalytic growth. Using computer simulations and theoretical calculations, we investigate whether the competition between these two processes can account for the kinks which we observe in our and others' experimental data. We derive theoretical conditions for the crossover between nucleation-dominated and growth-dominated regimes, and analyze their dependence on system volume and autocatalysis mechanism. Comparing these predictions to the data, we find that the experimentally observed kinks cannot be explained by a simple crossover between nucleation-dominated and autocatalytic growth regimes. Our results show that existing kinetic models fail to explain detailed features of lag time versus concentration curves, suggesting that new mechanistic understanding is needed. More broadly, our work demonstrates that care is needed in interpreting lag-time scaling exponents from protein assembly data.

The ability to control the morphologies of biomolecular aggregates is a central objective in the study of self-assembly processes. The development of predictive models offers the surest route for gaining such control. Under the right conditions, proteins will self-assemble into fibers that may rearrange themselves even further to form diverse structures, including the formation of closed loops. In this study, chicken egg white ovalbumin is used as a model for the study of fibril loops. By monitoring the kinetics of self-assembly, we demonstrate that loop formation is a consequence of end-to-end association between protein fibrils. A model of fibril formation kinetics, including end-joining, is developed and solved, showing that end-joining has a distinct effect on the growth of fibrillar mass density (which can be measured experimentally), establishing a link between self-assembly kinetics and the underlying growth mechanism. These results will enable experimentalists to infer fibrillar morphologies from an appropriate analysis of self-assembly kinetic data.