We show, using simulations of src SH3 domain, that mechanical force enhances the population of the aggregation-prone (N⁎) states, which are rarely populated under force free native conditions but are encoded in the spectrum of native fluctuations.
Though breeding populations were clearly subdivided, dispersal at these rates may offset effects of genetic drift and inbreeding depression by increasing effective population size (through the aggregation of breeding populations).
The increase in the population of the structures in the aggregation-prone Basin I in E22Q, which occurs solely due to the difference in charge states between the Dutch mutant and the WT, gives a structural explanation of the somewhat larger aggregation rate in the mutant.
The kinetics of the monomer loss can be modeled using the following equation: (1) X = A 1 exp (− k 1 t ) + A 2 where X is the fraction of residual soluble monomer and A1 represents the population of protein undergoing aggregation or fragmentation with the rate k1, and A2 is the population that remains unaffected.
When the polyQ tail is added, the population of aggregation intermediates increases by 1 2 orders of magnitude (depending on the polyQ length) already at room temperature, without the appearance of additional species.
Following a large disturbance, and if the loads have a large response delay, then the resulting oscillations may lock large fractions of the population and render the aggregation uncontrollable.
We also examined fine scale population structure of the three aggregations using principle coordinates analysis (PCoA) and standard F-statistics.
Whether these PUFs can be stabilised by the binding of ligands (and therefore may represent functional species) or whether their population increases due to point mutations, giving rise to the population of aggregation-competent states, remains to be shown.
Family-based linkage studies are aimed at identifying genomic regions harbouring genetic variants that are typically rare in the general population, and responsible for the aggregation of a disease in families with multiple affected individuals.
This function has been considered as an adequate distribution function derived from several explanatory stochastic process models including sampling genera from a heterogeneous biological population [ 38] and the aggregation process of particles [ 39].
