Allison Ferguson

Desolvation Barrier Effects Are a Likely Contributor to the Remarkable Diversity in the Folding Rates of Small Proteins

The variation in folding rate among single-domain natural proteins is tremendous, but common models with explicit representations of the protein chain are either demonstrably insufficient or unclear as to their capability for rationalizing the experimental diversity in folding rates. In view of the critical role of water exclusion in cooperative folding, we apply native-centric, coarse-grained chain modeling with elementary desolvation barriers to investigate solvation effects on folding rates. For a set of 13 proteins, folding rates simulated with desolvation barriers cover approximately 4.6 orders of magnitude, spanning a range essentially identical to that observed experimentally. In contrast, folding rates simulated without desolvation barriers cover only approximately 2.2 orders of magnitude. Following a Hammond-like trend, the folding transition-state ensemble (TSE) of a protein model with desolvation barriers generally has a higher average number of native contacts and is structurally more specific, that is, less diffused, than the TSE of the corresponding model without desolvation barriers. Folding is generally significantly slower in models with desolvation barriers because of their higher overall macroscopic folding barriers as well as slower conformational diffusion speeds in the TSE that are approximately 1/50 times those in models without desolvation barriers. Nonetheless, the average root-mean-square deviation between the TSE and the native conformation is often similar in the two modeling approaches, a finding suggestive of a more robust structural requirement for the folding rate-limiting step. The increased folding rate diversity in models with desolvation barriers originates from the tendency of these microscopic barriers to cause more heightening of the overall macroscopic folding free-energy barriers for proteins with more nonlocal native contacts than those with fewer such contacts. Thus, the enhancement of folding cooperativity by solvation effects is seen as positively correlated with a proteins native topological complexity.

Secondary structures in long compact polymers.

Compact polymers are self-avoiding random walks that visit every site on a lattice. This polymer model is used widely for studying statistical problems inspired by protein folding. One difficulty with using compact polymers to perform numerical calculations is generating a sufficiently large number of randomly sampled configurations. We present a Monte Carlo algorithm that uniformly samples compact polymer configurations in an efficient manner, allowing investigations of chains much longer than previously studied. Chain configurations generated by the algorithm are used to compute statistics of secondary structures in compact polymers. We determine the fraction of monomers participating in secondary structures, and show that it is self-averaging in the long-chain limit and strictly less than 1. Comparison with results for lattice models of open polymer chains shows that compact chains are significantly more likely to form secondary structure.

Growing length scale in gravity-driven dense granular flow

We report simulations of a two-dimensional, dense, bidisperse system of inelastic hard disks falling down a vertical tube under the influence of gravity. We examine the approach to jamming as the average flow of particles down the tube is slowed by making the outlet narrower. Defining coarse-grained velocity and stress fields, we study two-point temporal and spatial correlation functions of these fields in a region of the tube where the time-averaged velocity is spatially uniform. We find that fluctuations in both velocity and stress become increasingly correlated as the system approaches jamming. We extract a growing length scale and time scale from these correlations.

Stress and large-scale spatial structures in dense, driven granular flows.

We study the appearance of large-scale dynamical heterogeneities in a simplified model of a driven, dissipative granular system. Simulations of steady-state gravity-driven flows of inelastically colliding hard disks show the formation of large-scale linear structures of particles with a high collision frequency. These chains can be shown to carry much of the collisional stress in the system due to a dynamical correlation that develops between the momentum transfer and time between collisions in these frequently colliding particles. The lifetime of these dynamical stress heterogeneities is seen to grow as the flow velocity decreases toward jamming, leading to slowly decaying stress correlations reminiscent of the slow dynamics observed in supercooled liquids.

Spatially heterogenous dynamics in dense, driven granular flows

Interest in the dynamical arrest leading to a fluid → solid transition in thermal and athermal systems has led to questions about the nature of these transitions. These jamming transitions may be dependent on the influence of extended structures on the dynamics of the system. Here we show results from a simple driven, dissipative, non-equilibrium system which exhibits dynamical heterogeneities similar to those observed in a supercooled liquid which is a system in thermal equilibrium. Observations of the time τR(r) required for a particular particle to move a distance r reveal the existence of large-scale correlated dynamical regions with characteristic time scales chosen from a broad distribution. The mean squared displacement of ensembles of particles with varying characteristic τR(r) reveals an intriguing spatially heterogenous mobility. This suggests that a unified framework for jamming will have to be based on the connection between the nature of these heterogeneities and the effective dynamics.