Effective stochastic dynamics on a protein folding energy landscape

We present an approach to protein folding kinetics using stochastic reaction-coordinate dynamics, in which the effective drift velocities and diffusion coefficients are determined from microscopic simulation data. The resultant Langevin equation can then be used to directly simulate the folding process. Here, we test this approach by applying it to a toy two-state dynamical system and to a funnellike structure-based (Go-type) model. The folding time predictions agree very well with full simulation results. Therefore, we have in hand a fast numerical tool for calculating the folding kinetic properties, even when full simulations are not feasible. In addition, the local drift and diffusion coefficients provide an alternative way to compute the free energy profile in cases where only local sampling can be achieved.     

Theoretical characterization of alpha-helix and beta-hairpin folding kinetics

By means of the conformational free energy surface and corresponding diffusion coefficients, as obtained by long time scale atomistic molecular dynamics simulations (mus time scale), we model the folding kinetics of alpha-helix and beta-hairpin peptides as a diffusive process over the free energy surface. The two model systems studied in this paper (the alpha-helical temporin L and the beta-hairpin prion protein H1 peptide) exhibit a funnel-like almost barrierless free energy profile, leading to nonexponential folding kinetics matching rather well the available experimental data. Moreover, using the free energy profile provided by Mu?oz et al. [Mu?oz et al. Nature 1997, 390: 196-199], this model was also applied to reproduce the two-state folding kinetics of the C-terminal beta-hairpin of protein GB1, yielding an exponential folding kinetics with a time constant (approximately 5 micros) in excellent agreement with the experimentally observed one (approximately 6 micros). Finally, the folding kinetics obtained by solving the diffusion equation, considering either a one-dimensional or a two-dimensional free energy surface, are also compared in order to understand the relevance of the possible kinetic coupling between conformational degrees of freedom in the folding process.     

Highly anisotropic stability and folding kinetics of a single coiled coil protein under mechanical tension

Coiled coils are one of the most abundant protein structural motifs and widely mediate protein interactions and force transduction or sensation. They are thus model systems for protein engineering and folding studies, particularly the GCN4 coiled coil. Major single-molecule methods have also been applied to this protein and revealed its folding kinetics at various spatiotemporal scales. Nevertheless, the folding energy and the kinetics of a single GCN4 coiled coil domain have not been well determined at a single-molecule level. Here we used high-resolution optical tweezers to characterize the folding and unfolding reactions of a single GCN4 coiled coil domain and their dependence on the pulling direction. In one axial and two transverse pulling directions, we observed reversible, two-state transitions of the coiled coil in real time. The transitions equilibrate at pulling forces ranging from 6 to 12 pN, showing different stabilities of the coiled coil in regard to pulling direction. Furthermore, the transition rates vary with both the magnitude and the direction of the pulling force by greater than 1000 folds, indicating a highly anisotropic and topology-dependent energy landscape for protein transitions under mechanical tension. We developed a new analytical theory to extract energy and kinetics of the protein transition at zero force. The derived folding energy does not depend on the pulling direction and is consistent with the measurement in bulk, which further confirms the applicability of the single-molecule manipulation approach for energy measurement. The highly anisotropic thermodynamics of proteins under tension should play important roles in their biological functions.     

Scaling of folding times with protein size

Current experimental data show a 9-orders-of-magnitude span in the folding times of proteins. Such a wide range is typically considered a direct consequence of the complexity in structural and sequence patterns of natural proteins. By using a database of 69 proteins and peptides analyzed experimentally, we observe that the folding time scales with the number of residues in the protein. The correlation coefficient is 0.74 or higher, and indicates that it is possible to predict the folding time of a protein with a precision of approximately 1.1 times decades from just its size. A simple thermodynamic analysis of this correlation suggests that the smallest proteins are expected to have very marginal free energy barriers to folding.     

Nanosecond folding dynamics of a three-stranded beta-sheet

We studied conformational stability and folding kinetics of a three-stranded beta-sheet containing two rigid turns. Static infrared measurements indicate that this beta-sheet undergoes a broad but cooperative thermal unfolding transition with a midpoint at approximately 53 degrees C. Interestingly, time-resolved infrared experiments show that its relaxation kinetics in response to a temperature-jump (T-jump) occur on the nanosecond time scale (e.g., the relaxation time is approximately 140 ns at 35.0 degrees C), thereby suggesting that the conformational relaxation encounters only a small free energy barrier or even proceeds in a downhill manner. Further Langevin dynamics simulations suggest that the observed T-jump relaxation kinetics could be modeled by a conformational diffusion process along a single-well free energy profile, which allowed us to determine the effective diffusion constant and also the roughness of the folding energy landscape.     

Stretched versus compressed exponential kinetics in α-helix folding

In a recent paper (J. Bredenbeck, J. Helbing, J.R. Kumita, G.A. Woolley, P. Hamm, α-helix formation in a photoswitchable peptide tracked from picoseconds to microseconds by time resolved IR spectroscopy, Proc. Natl. Acad. Sci USA 102 (2005) 2379), we have investigated the folding of a photo-switchable α-helix with a kinetics that could be fit by a stretched exponential function exp(−(t/τ)^β). The stretching factor β became smaller as the temperature was lowered, a result which has been interpreted in terms of activated diffusion on a rugged energy surface. In the present paper, we discuss under which conditions diffusion problems occur with stretched exponential kinetics (β < 1) and under which compressed exponential kinetics is obtained (β > 1). We show that diffusion problems do have a strong tendency to yield stretched exponential kinetics, yet, that there are conditions (strong perturbation from equilibrium, performing the experiment in the folding direction) under which compressed exponential kinetics would be expected instead. We discuss the kinetics on free energy surfaces predicted by simple initiation-propagation models (zipper models) of α-helix folding, as well as by folding funnel models. We show that our recent experiment has been performed under condition for which models with strong downhill driving force, such as the zipper model, would predict compressed, rather than stretched exponential kinetics, in disagreement with the experimental observation. We therefore propose that the free energy surface along a reaction coordinate that governs the folding kinetics must be relatively flat and has a shape similar to a 1D golf course. We discuss how this conclusion can be unified with the thermodynamically well established zipper model by introducing an additional kinetic reaction coordinate.     

Folding time distributions as an approach to protein folding kinetics

A 27-residue lattice heteropolymer subject to Monte Carlo dynamics on a simple cubic lattice is studied over a range of temperatures. Folding time distributions are used to obtain information concerning the details of folding kinetics. The results are compared with those from methods based on mean force surfaces expressed in terms of a reduced set of variables and on a disconnectivity graph for the same system. A detailed analysis of the folding trajectories is given, and the importance of dead-end traps in determining the folding time is demonstrated. We show that the calculated folding kinetics can be modeled by a system of kinetic equations, with the essential rate constants determined from the Monte Carlo simulations and the resulting folding time distributions. The kinetic equations make possible an analysis of the variation of the importance of different channels with temperature. In particular, we show that the presence of intermediates may be masked in the folding time distributions, with the mean folding time being independent of the height of the barrier between the intermediates and collapsed globule state of the system. This and other results demonstrate that care has to be used in interpreting experimental folding data in terms of the underlying kinetics. Correspondingly, simulations are shown to have to satisfy certain requirements to obtain proper sampling of the dead-end traps.     

Exploring the energy landscape of a small RNA hairpin

The energy landscape of a small RNA tetraloop hairpin is explored by temperature jump kinetics and base-substitution. The folding kinetics are single-exponential near the folding transition midpoint T(m). An additional fast phase appears below the midpoint, and an additional slow phase appears above the midpoint. Stem mutation affects the high-temperature phase, while loop mutation affects the low-temperature phase. An adjusted 2-D lattice model reproduces the temperature-dependent phases, although it oversimplifies the structural interpretation. A four-state free energy landscape model is generated based on the lattice model. This model explains the thermodynamics and multiphase kinetics over the full temperature range of the experiments. An analysis of three variants shows that one of the intermediate RNA structures is a stacking-related trap affected by stem but not loop modification, while the other is an early intermediate that forms some stem and loop structure. Even a very fast-folding 8-mer RNA with an ideal tetraloop sequence has a rugged energy landscape, ideal for testing analytical and computational models.     

Protein structure and dynamics from single-molecule fluorescence resonance energy transfer

The pros and cons of single-molecule vs ensemble-averaged fluorescence resonance energy transfer (FRET) experiments, performed on proteins, are explored with the help of Langevin dynamics simulations. An off-lattice model of the polypeptide chain is employed, which gives rise to a well-defined native state and two-state folding kinetics. A detailed analysis of the distribution of the donor-acceptor distance is presented at different points along the denaturation curve, along with its dependence on the averaging time window. We show that unique information on the correlation between structure and dynamics, which can only be obtained from single-molecule experiments, is contained in the correlation between the donor-acceptor distance and its displacement. The latter is shown to provide useful information on the free energy landscape of the protein, which is complementary to that obtained from the distribution of donor-acceptor distances.     

Influence of the chain stiffness on the thermodynamics of a Gō-type model for protein folding

The relative importance of local and long range interactions in the characteristics of the protein folding process has long been a matter of controversy. Computer simulations based on Gō-type models have been widely used to study this topic, but without much agreement on which type of interactions is more relevant for the foldability of a protein. In this work, the authors also employ a topology-based potential and simulation model to analyze the influence of local and long range interactions on the thermodynamics of the folding transition. The former are mainly used to control the degree of flexibility (or stiffness) of the chain, mostly appreciable in the unfolded (noncompact) state. Our results show the different effects that local and nonlocal interactions have on the entropy and the energy of the system. This implies that a balance between both types of interactions is required, so that a free energy barrier exists between the native and the denatured states. The variations in the contribution of both types of interactions have also a direct effect on the stability of the chain conformations, including the possible appearance of thermodynamic folding intermediates.     

Diffusion models of protein folding

In theory and in the analysis of experiments, protein folding is often described as diffusion along a single coordinate. We explore here the application of a one-dimensional diffusion model to interpret simulations of protein folding, where the parameters of a model that "best" describes the simulation trajectories are determined using a Bayesian analysis. We discuss the requirements for such a model to be a good approximation to the global dynamics, and several methods for testing its accuracy. For example, one test considers the effect of an added bias potential on the fitted free energies and diffusion coefficients. Such a bias may also be used to extend our approach to determining parameters for the model to systems that would not normally explore the full coordinate range on accessible time scales. Alternatively, the propagators predicted from the model at different "lag" times may be compared with observations from simulation. We then present some applications of the model to protein folding, including Kramers-like turnover in folding rates of coarse-grained models, the effect of non-native interactions on folding, and the effect of the chosen coordinate on the observed position-dependence of the diffusion coefficients. Lastly, we consider how our results are useful for the interpretation of experiments, and how this type of Bayesian analysis may eventually be applied directly to analyse experimental data.     

Peptide chain dynamics in light and heavy water: zooming in on internal friction

Frictional effects due to the chain itself, rather than the solvent, may have a significant effect on protein dynamics. Experimentally, such "internal friction" has been investigated by studying folding or binding kinetics at varying solvent viscosity; however, the molecular origin of these effects is hard to pinpoint. We consider the kinetics of disordered glycine-serine and α-helix forming alanine peptides and a coarse-grained protein folding model in explicit-solvent molecular dynamics simulations. By varying the solvent mass over more than two orders of magnitude, we alter only the solvent viscosity and not the folding free energy. Folding dynamics at the near-vanishing solvent viscosities accessible by this approach suggests that solvent and internal friction effects are intrinsically entangled. This finding is rationalized by calculation of the polymer end-to-end distance dynamics from a Rouse model that includes internal friction. An analysis of the friction profile along different reaction coordinates, extracted from the simulation data, demonstrates that internal as well as solvent friction varies substantially along the folding pathways and furthermore suggests a connection between friction and the formation of hydrogen bonds upon folding.     

Quantifying heterogeneity and conformational dynamics from single molecule FRET of diffusing molecules: recurrence analysis of single particles (RASP)

Single molecule F?rster resonance energy transfer (FRET) experiments are a versatile method for investigating the conformational distributions and dynamics of biological macromolecules. In a common type of experiment, the fluorescence bursts from individual molecules freely diffusing in solution are detected as they pass through the observation volume of a confocal microscope. Correlation analysis of the fluorescence bursts shows that under typical experimental conditions, for time scales up to several tens of milliseconds, the probability for a molecule to return to the confocal volume is greater than the probability of a new molecule being detected. Here we present RASP (recurrence analysis of single particles), a method that is based on this recurrence behavior and allows us to significantly extend the information that can be extracted from single molecule FRET experiments. The number and peak shapes of subpopulations within the sample can be identified essentially in a model-free way by constructing recurrence FRET efficiency histograms. These are obtained by first selecting photon bursts from a small transfer efficiency range (initial bursts), and then building the FRET efficiency histogram only from bursts detected within a short time (the recurrence interval) after the initial bursts. Systematic variation of the recurrence interval allows the kinetics of interconversion between subpopulations to be determined on time scales from ~50 μs up to ~100 ms from equilibrium measurements. We demonstrate the applicability of the method on measurements of several peptides and proteins with different degrees of conformational heterogeneity and folding dynamics. The concepts presented here can be extended to other observables available from single molecule fluorescence experiments.     

Kinetic partitioning mechanism as a unifying theme in the folding of biomolecules

We describe a unified approach to describe the kinetics of protein and RNA folding. The underlying conceptual basis for this framework relies on the notion that biomolecules are topologically frustrated due to their polymeric nature and due to the presence of conflicting energies. As a result, the free energy surface (FES) has, in addition to the native basin of attraction (NBA), several competing basins of attraction. A rough FES results in direct and indirect pathways to the NBA, i.e., a kinetic partitioning mechanism (KPM). The KPM leads to a foldability principle according to which fast folding sequences are characterized by the folding transition temperature T _F being close to the collapse transition temperature T _θ, at which a transition from the random coil to the compact structure takes place. Biomolecules with T _θ ≈ T _F , such as small proteins and tRNAs, are expected to fold rapidly with two-state kinetics. Estimates for the multiple time scales in KPM are also given. We show that experiments on proteins and RNA can be understood semi-quantitatively in terms of the KPM. Received: 14 January 1997 / Accepted: 23 January 1997     

Ultrafast folding of a computationally designed Trp-cage mutant: Trp2-cage

Miniproteins provide useful model systems for understanding the principles of protein folding and design. These proteins also serve as useful test cases for theories of protein folding, and their small size and ultrafast folding kinetics put them in a regime of size and time scales that is now becoming accessible to molecular dynamics simulations. Previous estimates have suggested the "speed limit" for folding is on the order of 1 mus. Here a computationally designed mutant of the 20-residue Trp-cage miniprotein, Trp2-cage, is presented. The Trp2-cage has greater stability than the parent and folds on the ultrafast time scale of 1 mICROs at room temperature, as determined from infrared temperature-jump experiments.     

Prediction of native-state hydrogen exchange from perfectly funneled energy landscapes

Simulations based on perfectly funneled energy landscapes often capture many of the kinetic features of protein folding. We examined whether simulations based on funneled energy functions can also describe fluctuations in native-state protein ensembles. We quantitatively compared the site-specific local stability determined from structure-based folding simulations, with hydrogen exchange protection factors measured experimentally for ubiquitin, chymotrypsin inhibitor 2, and staphylococcal nuclease. Different structural definitions for the open and closed states based on the number of native contacts for each residue, as well as the hydrogen-bonding state, or a combination of both criteria were evaluated. The predicted exchange patterns agree with the experiments under native conditions, indicating that protein topology indeed has a dominant effect on the exchange kinetics. Insights into the simplest mechanistic interpretation of the amide exchange process were thus obtained.     

Expanding the realm of ultrafast protein folding: gpW, a midsize natural single-domain with alpha+beta topology that folds downhill

All ultrafast folding proteins known to date are either very small in size (less than 45 residues), have an alpha-helix bundle topology, or have been artificially engineered. In fact, many of them share two or even all three features. Here we show that gpW, a natural 62-residue alpha+beta protein expected to fold slowly in a two-state fashion, folds in microseconds (i.e., from tau = 33 micros at 310 K to tau = 1.7 micros at 355 K). Thermodynamic analyses of gpW reveal probe dependent thermal denaturation, complex coupling between two denaturing agents, and differential scanning calorimetry (DSC) thermogram characteristic of folding over a negligible thermodynamic folding barrier. The free energy surface analysis of gpW folding kinetics also produces a marginal folding barrier of about thermal energy ( RT) at the denaturation midpoint. From these results we conclude that gpW folds in the downhill regime and is close to the global downhill limit. This protein seems to be poised toward downhill folding by a loosely packed hydrophobic core with low aromatic content, large stabilizing contributions from local interactions, and abundance of positive charges on the native surface. These special features, together with a complex functional role in bacteriophage lambda assembly, suggest that gpW has been engineered to fold downhill by natural selection.     

The protein folding transition-state ensemble from a Gō-like model

Characterizing the structure of transition states (TS) is a first step towards understanding two-state protein folding mechanisms. However, a direct experimental characterization of these states is challenging and indirect information derived from protein engineering methodologies (?-value analysis) is often difficult to interpret. We present here a theoretical study on the nature of the transition state ensemble for three representative proteins covering the major structural classes using a mean-field C(α)-based Gō-model. We identify that transition state ensembles are dominated by local contacts, indicating that most non-local contacts form only upon crossing the macroscopic folding free energy barrier. We demonstrate that the mean ?-value corresponds to the fraction of stabilization energy gained at the barrier-top in two-state-like systems, and that it depends monotonically on the stability conditions. Furthermore, we show that there is a fundamental connection between small destabilization and large ?-values that in turn depends on the location of the mutated residue in the structure. These results that are in agreement with the recent empirical findings highlight the importance of local energetics in determining folding mechanisms.