Mechanisms and Kinetics of Amyloid Aggregation Investigated by a Phenomenological Coarse-Grained Model - Computational Modeling of Biological Systems - page 208

2 s at a surfactant:peptide ratio of 8:1, but instead oligomers of 40 peptides

form. These simulation results show that at a fourfold molar excess of surfactant,
the inhibition of fibrillation already depends strongly on the amyloidogenicity of the
CGF peptide model.

5.3 Macromolecular Crowding Effect on CGF Peptide

Aggregation

Simulations with the CGF peptide model together with softly repulsive spheres have
been carried out to assess the influence on the aggregation kinetics of excluded
volume and hindered peptide diffusion due to macromolecular crowding. [ 81 ]
As in the case of lipid-bilayer vesicles, the net effect of macromolecular crowding
crucially depends on the amyloidogenicity tendency of the CGF peptide. For
peptides with low aggregation propensity, the self-association process is transition-
state limited, where the kinetic bottleneck is the formation of the fibril nucleus.
In this case, since the oligomers, including the nucleus, are thermodynamically
favored (with respect to the isolated monomers) by the excluded volume effect,
macromolecular crowding accelerates peptide assembly and has an effect analogous
to that of an increase in peptide concentration (Fig. 13 , left). This trend is analogous
to that observed experimentally by Munishkina et al., who have studied the effect of
increasing the PEG concentration on the ˛-synuclein aggregation process. [ 71 ]
On the other hand, when the aggregation mechanism is fast and proceeds directly
from monomers to fibril, the process is diffusion limited, and the thermodynamic
stabilization of oligomers is less important than the reduction in peptide mobility.
In this case, the bottleneck is not the formation of the nucleus; the rate-limiting
step for peptides that show a direct aggregation mechanism is the elongation of
the fibril. Therefore, in this case macromolecular crowding is much less efficient
in accelerating the self-association of peptides than an equivalent increase in
peptide concentration, since the peptides diffusion is hindered by the crowders
(Fig. 13 , right).

6 Conclusion

Atomistic simulations of aggregation are limited by short timescale, while exper-
imental approaches to amyloid fibril formation have insufficient spatial resolution.
Coarse-grained models of polypeptide aggregation sacrifice atomistic detail to reach
timescales that allow the comparison with and interpretation of experimental data.
The models presented in this chapter have shed light upon amyloid aggregation
kinetics and mechanisms, which is helpful to formulate a unified picture of the
available experimental data.