Conformational properties of unfolded HypF-N

Kinetics of Loop Closure in Disordered Proteins: Theory vs Simulations vs Experiments

We study intrachain dynamics of intrinsically disordered proteins, as manifested by the time scales of loop formation, using atomistic simulations, experiment-parametrized coarse-grained models, and one-dimensional theories assuming Markov or non-Markov dynamics along the reaction coordinate. Despite the generally non-Markov character of monomer dynamics in polymers, we find that the simplest model of one-dimensional diffusion along the reaction coordinate (equated to the distance between the loop-forming monomers) well captures the mean first passage times to loop closure measured in coarse-grained and atomistic simulations, which, in turn, agree with the experimental values. This justifies use of the one-dimensional diffusion model in interpretation of experimental data. At the same time, the transition path times for loop closure in longer polypeptide chains show significant non-Markov effects; at intermediate times, these effects are better captured by the generalized Langevin equation model. At long times, however, atomistic simulations predict long tails in the distributions of transition path times, which are at odds with both the one-dimensional diffusion model and the generalized Langevin equation model.

Intramolecular Diffusion in α-Synuclein: It Depends on How You Measure It

Intramolecular protein diffusion, the motion of one part of the polypeptide chain relative to another part, is a fundamental aspect of protein folding and may modulate amyloidogenesis of disease-associated intrinsically disordered proteins. Much work has determined such diffusion coefficients using a variety of probes, but there has been an apparent discrepancy between measurements using long-range probes, such as fluorescence resonance energy transfer, and short-range probes, such as Trp-Cys quenching. In this work, we make both such measurements on the same protein, α-synuclein, and confirm that such discrepancy exists. Molecular dynamics simulations suggest that such differences result from a diffusion coefficient that depends on the spatial distance between probes. Diffusional estimates in good quantitative agreement with experiment are obtained by accounting for the distinct distance ranges probed by fluorescence resonance energy transfer and Trp-Cys quenching.

Protein unfolding mechanisms and their effects on folding experiments

In this review, I discuss the various methods researchers use to unfold proteins in the lab in order to understand protein folding both in vitro and in vivo. The four main techniques, chemical-, heat-, pressure- and force-denaturation, produce distinctly different unfolded conformational ensembles. Recent measurements have revealed different folding kinetics from different unfolding mechanisms. Thus, comparing these distinct unfolded ensembles sheds light on the underlying free energy landscape of folding.

Prion protein dynamics before aggregation

Prion diseases, like Alzheimer's disease and Parkinson disease, are rapidly progressive neurodegenerative disorders caused by misfolding followed by aggregation and accumulation of protein deposits in neuronal cells. Here we measure intramolecular polypeptide backbone reconfiguration as a way to understand the molecular basis of prion aggregation. Our hypothesis is that when reconfiguration is either much faster or much slower than bimolecular diffusion, biomolecular association is not stable, but as the reconfiguration rate becomes similar to the rate of biomolecular diffusion, the association is more stable and subsequent aggregation is faster. Using the technique of Trp-Cys contact quenching, we investigate the effects of various conditions on reconfiguration dynamics of the Syrian hamster and rabbit prion proteins. This protein exhibits behavior in all three reconfiguration regimes. We conclude that the hamster prion is prone to aggregation at pH 4.4 because its reconfiguration rate is slow enough to expose hydrophobic residues on the same time scale that bimolecular association occurs, whereas the rabbit sequence avoids aggregation by reconfiguring 10 times faster than the hamster sequence.

Monomer Dynamics of Alzheimer Peptides and Kinetic Control of Early Aggregation in Alzheimer's Disease

The rate of reconfiguration-or intramolecular diffusion-of monomeric Alzheimer (Aβ) peptides is measured and, under conditions that aggregation is more likely, peptide diffusion slows down significantly, which allows bimolecular associations to be initiated. By using the method of Trp-Cys contact quenching, the rate of reconfiguration is observed to be about five times faster for Aβ₄₀ , which aggregates slowly, than that for Aβ₄₂ , which aggregates quickly. Furthermore, the rate of reconfiguration for Aβ₄₂ speeds up at higher pH, which slows aggregation, and in the presence of the aggregation inhibitor curcumin. The measured reconfiguration rates are able to predict the early aggregation behavior of the Aβ peptide and provide a kinetic basis for why Aβ₄₂ is more prone to aggregation than Aβ₄₀ , despite a difference of only two amino acids.

Intramolecular diffusion controls aggregation of the PAPf39 peptide

The 39-residue fragment of human prostatic acidic phosphatase (PAP) is found in high concentrations in semen and easily form fibrils. Previous work has shown that fibrillization is accelerated with a deletion of the first 8, mostly charged residues and it was hypothesized that fibrillization depended on the dynamics of these peptides. To test this hypothesis we have measured the intramolecular diffusion of the full length and 8-residue deletion peptides at two different pHs and found a correlation with fibrillization lag time. These results can be explained by a simple kinetic model of the early stages of aggregation in which oligomerization is controlled by the rate of peptide reconfiguration.

Effects of Mutations on the Reconfiguration Rate of α-Synuclein

It is still poorly understood why α-synuclein, the intrinsically disordered protein involved in Parkinson's and other neurodegenerative diseases, is so prone to aggregation. Recent work has shown a correlation between the aggregation rate and the rate of diffusional reconfiguration by varying temperature and pH. Here we examine the effects of several point mutations in the sequence on the conformational ensemble and reconfiguration rate. We find that at lower temperatures the PD causing aggregation enhancing mutations slow down and aggregation reducing mutations drastically speed up intramolecular diffusion, as compared to the wild type sequence. However, at higher temperatures, one of three familial mutations that enhance aggregation slows intramolecular diffusion while non-natural mutations that inhibit aggregation speed up intramolecular diffusion. These results support the hypothesis that the first step of aggregation is kinetically controlled by reconfiguration in which the protein chain cannot reconfigure rapidly enough to escape oligomerization. Finally we provide physical and chemical insights into why small point mutations cause these dramatic changes in the conformational ensemble and dynamics.

The roughness of the protein energy landscape results in anomalous diffusion of the polypeptide backbone

Recombination of photolysed protein disulfide bonds confirms subdiffusional backbone motion and measures the roughness of the protein's energy landscape.

Reconstructing folding energy landscapes by single-molecule force spectroscopy

Folding may be described conceptually in terms of trajectories over a landscape of free energies corresponding to different molecular configurations. In practice, energy landscapes can be difficult to measure. Single-molecule force spectroscopy (SMFS), whereby structural changes are monitored in molecules subjected to controlled forces, has emerged as a powerful tool for probing energy landscapes. We summarize methods for reconstructing landscapes from force spectroscopy measurements under both equilibrium and nonequilibrium conditions. Other complementary, but technically less demanding, methods provide a model-dependent characterization of key features of the landscape. Once reconstructed, energy landscapes can be used to study critical folding parameters, such as the characteristic transition times required for structural changes and the effective diffusion coefficient setting the timescale for motions over the landscape. We also discuss issues that complicate measurement and interpretation, including the possibility of multiple states or pathways and the effects of projecting multiple dimensions onto a single coordinate.

Understanding protein aggregation from the view of monomer dynamics

Much work in recent years has been devoted to understanding the complex process of protein aggregation. This review looks at the earliest stages of aggregation, long before the formation of fibrils that are the hallmark of many aggregation-based diseases, and proposes that the first steps are controlled by the reconfiguration dynamics of the monomer. When reconfiguration is much faster or much slower than bimolecular diffusion, then aggregation is slow, but when they are similar, aggregation is fast. The experimental evidence for this model is reviewed and the prospects for small molecule aggregation inhibitors to prevent disease are discussed.

Energy landscape analysis of native folding of the prion protein yields the diffusion constant, transition path time, and rates

Protein folding is described conceptually in terms of diffusion over a configurational free-energy landscape, typically reduced to a one-dimensional profile along a reaction coordinate. In principle, kinetic properties can be predicted directly from the landscape profile using Kramers theory for diffusive barrier crossing, including the folding rates and the transition time for crossing the barrier. Landscape theory has been widely applied to interpret the time scales for protein conformational dynamics, but protein folding rates and transition times have not been calculated directly from experimentally measured free-energy profiles. We characterized the energy landscape for native folding of the prion protein using force spectroscopy, measuring the change in extension of a single protein molecule at high resolution as it unfolded/refolded under tension. Key parameters describing the landscape profile were first recovered from the distributions of unfolding and refolding forces, allowing the diffusion constant for barrier crossing and the transition path time across the barrier to be calculated. The full landscape profile was then reconstructed from force-extension curves, revealing a double-well potential with an extended, partially unfolded transition state. The barrier height and position were consistent with the previous results. Finally, Kramers theory was used to predict the folding rates from the landscape profile, recovering the values observed experimentally both under tension and at zero force in ensemble experiments. These results demonstrate how advances in single-molecule theory and experiment are harnessing the power of landscape formalisms to describe quantitatively the mechanics of folding.

Aggregation of α-synuclein is kinetically controlled by intramolecular diffusion

We hypothesize that the first step of aggregation of disordered proteins, such as α-synuclein, is controlled by the rate of backbone reconfiguration. When reconfiguration is fast, bimolecular association is not stable, but as reconfiguration slows, association is more stable and subsequent aggregation is faster. To investigate this hypothesis, we have measured the rate of intramolecular diffusion in α-synuclein, a protein involved in Parkinson's disease, under solvent conditions that accelerate or decelerate aggregation. Using the method of tryptophan-cysteine (Trp-Cys) quenching, the rate of intramolecular contact is measured in four different loops along the chain length. This intrinsically disordered protein is highly diffusive at low temperature at neutral pH, when aggregation is slow, and compacts and diffuses more slowly at high temperature or low pH, when aggregation is rapid. Diffusion also slows with the disease mutation A30P. This work provides unique insights into the earliest steps of α-synuclein aggregation pathway and should provide the basis for the development of drugs that can prevent aggregation at the initial stage.

Curcumin prevents aggregation in α-synuclein by increasing reconfiguration rate

α-Synuclein is a protein that is intrinsically disordered in vitro and prone to aggregation, particularly at high temperatures. In this work, we examined the ability of curcumin, a compound found in turmeric, to prevent aggregation of the protein. We found strong binding of curcumin to α-synuclein in the hydrophobic non-amyloid-β component region and complete inhibition of oligomers or fibrils. We also found that the reconfiguration rate within the unfolded protein was significantly increased at high temperatures. We conclude that α-synuclein is prone to aggregation because its reconfiguration rate is slow enough to expose hydrophobic residues on the same time scale that bimolecular association occurs. Curcumin rescues the protein from aggregation by increasing the reconfiguration rate into a faster regime.

A general polymer model of unfolded proteins under folding conditions

There is increasing evidence that a polypeptide chain in solvent conditions that favor folding may have transient structure and is significantly more compact than a fully denatured chain. However, there is no sequence-dependent model to capture such interactions. In this work, we present a simple and computationally inexpensive model based on a wormlike chain with excluded volume. The probability distribution of millions of such chains is reweighted to bias compact conformations in which residues of similar hydrophobicity are located near each other. This model, which has one adjustable parameter, is fit to measured values of intramolecular contact formation, which has been shown to be extremely sensitive to various models of intrachain distances. We show that under various denaturant concentrations, there is good convergence of the model for several different sequences with a wide range of dynamics. We also show that this model quantitatively predicts paramagnetic resonance enhancement (PRE) measurements with no adjustable parameters. Therefore a simple, probabilistic model that accounts for sequence-specific interactions may give a more realistic starting point for predictions of protein folding.

Extremely slow intramolecular diffusion in unfolded protein L

A crucial parameter in many theories of protein folding is the rate of diffusion over the energy landscape. Using a microfluidic mixer we have observed the rate of intramolecular diffusion within the unfolded B1 domain of protein L before it folds. The diffusion-limited rate of intramolecular contact is about 20 times slower than the rate in 6 M GdnHCl, and because in these conditions the protein is also more compact, the intramolecular diffusion coefficient decreases 100-500 times. The dramatic slowdown in diffusion occurs within the 250 micros mixing time of the mixer, and there appears to be no further evolution of this rate before reaching the transition state of folding. We show that observed folding rates are well predicted by a Kramers model with a denaturant-dependent diffusion coefficient and speculate that this diffusion coefficient is a significant contribution to the observed rate of folding.