Measuring internal friction of an ultrafast-folding protein

Nanosecond laser T-jump was used to measure the viscosity dependence of the folding kinetics of the villin subdomain under conditions where the viscogen has no effect on its equilibrium properties. The dependence of the unfolding/refolding relaxation time on solvent viscosity indicates a major contribution to the dynamics from internal friction. The internal friction increases with increasing temperature, suggesting a shift in the transition state along the reaction coordinate toward the native state with more compact structures, and therefore, a smaller diffusion coefficient due to increased landscape roughness. Fitting the data with an Ising-like model yields a relatively small position dependence for the diffusion coefficient. This finding is consistent with the excellent correlation found between experimental and calculated folding rates based on free energy barrier heights using the same diffusion coefficient for every protein.     

Structure and folding of a designed knotted protein

A very small number of natural proteins have folded configurations in which the polypeptide backbone is knotted. Relatively little is known about the folding energy landscapes of such proteins, or how they have evolved. We explore those questions here by designing a unique knotted protein structure. Biophysical characterization and X-ray crystal structure determination show that the designed protein folds to the intended configuration, tying itself in a knot in the process, and that it folds reversibly. The protein folds to its native, knotted configuration approximately 20 times more slowly than a control protein, which was designed to have a similar tertiary structure but to be unknotted. Preliminary kinetic experiments suggest a complicated folding mechanism, providing opportunities for further characterization. The findings illustrate a situation where a protein is able to successfully traverse a complex folding energy landscape, though the amino acid sequence of the protein has not been subjected to evolutionary pressure for that ability. The success of the design strategy--connecting two monomers of an intertwined homodimer into a single protein chain--supports a model for evolution of knotted structures via gene duplication.     

Coevolutionary information,protein folding landscapes,and the thermodynamics of natural selection

The energy landscape used by nature over evolutionary timescales to select protein sequences is essentially the same as the one that folds these sequences into functioning proteins, sometimes in microseconds. We show that genomic data, physical coarse-grained free energy functions, and family-specific information theoretic models can be combined to give consistent estimates of energy landscape characteristics of natural proteins. One such characteristic is the effective temperature T_sel at which these foldable sequences have been selected in sequence space by evolution. T_sel quantifies the importance of folded-state energetics and structural specificity for molecular evolution. Across all protein families studied, our estimates for T_sel are well below the experimental folding temperatures, indicating that the energy landscapes of natural foldable proteins are strongly funneled toward the native state.The physics and natural history of proteins are inextricably intertwined (1, 2). The cooperative manner in which proteins find their way to a folded structure is the result of proteins having undergone natural selection and not typical of random polymers (3, 4). Likewise, the requirement that most proteins must fold to function is a strong constraint on their phylogeny. The unavoidable random mutation events that proteins have undergone throughout their evolution have provided countless numbers of physicochemical experiments on folding landscapes. Thus, the evolutionary patterns of proteins found through comparative sequence analysis can be used to understand protein structure and energetics. In this paper, we compare the information content in the correlated changes that have occurred in protein sequences of common ancestry with energies from a transferable energy function to quantify the influence of maintaining foldability on molecular evolution.     

Making connections between ultrafast protein folding kinetics and molecular dynamics simulations

Determining the rate of forming the truly folded conformation of ultrafast folding proteins is an important issue for both experiments and simulations. The double-norleucine mutant of the 35-residue villin subdomain is the focus of recent computer simulations with atomistic molecular dynamics because it is currently the fastest folding protein. The folding kinetics of this protein have been measured in laser temperature-jump experiments using tryptophan fluorescence as a probe of overall folding. The conclusion from the simulations, however, is that the rate determined by fluorescence is significantly larger than the rate of overall folding. We have therefore employed an independent experimental method to determine the folding rate. The decay of the tryptophan triplet-state in photoselection experiments was used to monitor the change in the unfolded population for a sequence of the villin subdomain with one amino acid difference from that of the laser temperature-jump experiments, but with almost identical equilibrium properties. Folding times obtained in a two-state analysis of the results from the two methods at denaturant concentrations varying from 1.5-6.0 M guanidinium chloride are in excellent agreement, with an average difference of only 20%. Polynomial extrapolation of all the data to zero denaturant yields a folding time of 220 (+100,-70) ns at 283 K, suggesting that under these conditions the barrier between folded and unfolded states has effectively disappeared--the so-called "downhill scenario."     

A designed protein as experimental model of primordial folding

How do proteins accomplish folding during early evolution? Theoretically the mechanism involves the selective stabilization of the native structure against all other competing compact conformations in a process that involves cumulative changes in the amino acid sequence along geological timescales. Thus, an evolved protein folds into a single structure at physiological temperature, but the conformational competition remains latent. For natural proteins such competition should emerge only near cryogenic temperatures, which places it beyond experimental testing. Here, we introduce a designed monomeric miniprotein (FSD-1ss) that within biological temperatures (330–280 K) switches between simple fast folding and highly complex conformational dynamics in a structurally degenerate compact ensemble. Our findings demonstrate the physical basis for protein folding evolution in a designed protein, which exhibits poorly evolved or primordial folding. Furthermore, these results open the door to the experimental exploration of primitive folding and the switching between alternative protein structures that takes place in evolutionary branching points and prion diseases, as well as the benchmarking of de novo design methods.     

Simulating replica exchange simulations of protein folding with a kinetic network model

Replica exchange (RE) is a generalized ensemble simulation method for accelerating the exploration of free-energy landscapes, which define many challenging problems in computational biophysics, including protein folding and binding. Although temperature RE (T-RE) is a parallel simulation technique whose implementation is relatively straightforward, kinetics and the approach to equilibrium in the T-RE ensemble are very complicated; there is much to learn about how to best employ T-RE to protein folding and binding problems. We have constructed a kinetic network model for RE studies of protein folding and used this reduced model to carry out "simulations of simulations" to analyze how the underlying temperature dependence of the conformational kinetics and the basic parameters of RE (e.g., the number of replicas, the RE rate, and the temperature spacing) all interact to affect the number of folding transitions observed. When protein folding follows anti-Arrhenius kinetics, we observe a speed limit for the number of folding transitions observed at the low temperature of interest, which depends on the maximum of the harmonic mean of the folding and unfolding transition rates at high temperature. The results shown here for the network RE model suggest ways to improve atomic-level RE simulations such as the use of "training" simulations to explore some aspects of the temperature dependence for folding of the atomic-level models before performing RE studies.     

An experimentally determined protein folding energy landscape

Energy landscapes have been used to conceptually describe and model protein folding but have been difficult to measure experimentally, in large part because of the myriad of partly folded protein conformations that cannot be isolated and thermodynamically characterized. Here we experimentally determine a detailed energy landscape for protein folding. We generated a series of overlapping constructs containing subsets of the seven ankyrin repeats of the Drosophila Notch receptor, a protein domain whose linear arrangement of modular structural units can be fragmented without disrupting structure. To a good approximation, stabilities of each construct can be described as a sum of energy terms associated with each repeat. The magnitude of each energy term indicates that each repeat is intrinsically unstable but is strongly stabilized by interactions with its nearest neighbors. These linear energy terms define an equilibrium free energy landscape, which shows an early free energy barrier and suggests preferred low-energy routes for folding.     

Comparison of successive transition states for folding reveals alternative early folding pathways of two homologous proteins

The energy landscape theory provides a general framework for describing protein folding reactions. Because a large number of studies, however, have focused on two-state proteins with single well-defined folding pathways and without detectable intermediates, the extent to which free energy landscapes are shaped up by the native topology at the early stages of the folding process has not been fully characterized experimentally. To this end, we have investigated the folding mechanisms of two homologous three-state proteins, PTP-BL PDZ2 and PSD-95 PDZ3, and compared the early and late transition states on their folding pathways. Through a combination of Φ value analysis and molecular dynamics simulations we obtained atomic-level structures of the transition states of these homologous three-state proteins and found that the late transition states are much more structurally similar than the early ones. Our findings thus reveal that, while the native state topology defines essentially in a unique way the late stages of folding, it leaves significant freedom to the early events, a result that reflects the funneling of the free energy landscape toward the native state.     

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

The understanding of protein–ligand binding is of critical importance for biomedical research, yet the process itself has been very difficult to study because of its intrinsically dynamic character. Here, we have been able to quantitatively reconstruct the complete binding process of the enzyme-inhibitor complex trypsin-benzamidine by performing 495 molecular dynamics simulations of free ligand binding of 100 ns each, 187 of which produced binding events with an rmsd less than 2 Å compared to the crystal structure. The binding paths obtained are able to capture the kinetic pathway of the inhibitor diffusing from solvent (S0) to the bound (S4) state passing through two metastable intermediate states S2 and S3. Rather than directly entering the binding pocket the inhibitor appears to roll on the surface of the protein in its transition between S3 and the final binding pocket, whereas the transition between S2 and the bound pose requires rediffusion to S3. An estimation of the standard free energy of binding gives ΔG° = -5.2 ± 0.4 kcal/mol (cf. the experimental value -6.2 kcal/mol), and a two-states kinetic model k_on = (1.5 ± 0.2) × 10⁸ M^-1 s^-1 and k_off = (9.5 ± 3.3) × 10⁴ s^-1 for unbound to bound transitions. The ability to reconstruct by simple diffusion the binding pathway of an enzyme-inhibitor binding process demonstrates the predictive power of unconventional high-throughput molecular simulations. Moreover, the methodology is directly applicable to other molecular systems and thus of general interest in biomedical and pharmaceutical research.     

Effect of glycosylation on protein folding: a close look at thermodynamic stabilization

Glycosylation is one of the most common posttranslational modifications to occur in protein biosynthesis, yet its effect on the thermodynamics and kinetics of proteins is poorly understood. A minimalist model based on the native protein topology, in which each amino acid and sugar ring was represented by a single bead, was used to study the effect of glycosylation on protein folding. We studied in silico the folding of 63 engineered SH3 domain variants that had been glycosylated with different numbers of conjugated polysaccharide chains at different sites on the protein's surface. Thermal stabilization of the protein by the polysaccharide chains was observed in proportion to the number of attached chains. Consistent with recent experimental data, the degree of thermal stabilization depended on the position of the glycosylation sites, but only very weakly on the size of the glycans. A thermodynamic analysis showed that the origin of the enhanced protein stabilization by glycosylation is destabilization of the unfolded state rather than stabilization of the folded state. The higher free energy of the unfolded state is enthalpic in origin because the bulky polysaccharide chains force the unfolded ensemble to adopt more extended conformations by prohibiting formation of a residual structure. The thermodynamic stabilization induced by glycosylation is coupled with kinetic stabilization. The effects introduced by the glycans on the biophysical properties of proteins are likely to be relevant to other protein polymeric conjugate systems that regularly occur in the cell as posttranslational modifications or for biotechnological purposes.     

A biophysical protein folding model accounts for most mutational fitness effects in viruses

Fitness effects of mutations fall on a continuum ranging from lethal to deleterious to beneficial. The distribution of fitness effects (DFE) among random mutations is an essential component of every evolutionary model and a mathematical portrait of robustness. Recent experiments on five viral species all revealed a characteristic bimodal-shaped DFE featuring peaks at neutrality and lethality. However, the phenotypic causes underlying observed fitness effects are still unknown and presumably, are thought to vary unpredictably from one mutation to another. By combining population genetics simulations with a simple biophysical protein folding model, we show that protein thermodynamic stability accounts for a large fraction of observed mutational effects. We assume that moderately destabilizing mutations inflict a fitness penalty proportional to the reduction in folded protein, which depends continuously on folding free energy (ΔG). Most mutations in our model affect fitness by altering ΔG, whereas based on simple estimates, ~10% abolish activity and are unconditionally lethal. Mutations pushing ΔG > 0 are also considered lethal. Contrary to neutral network theory, we find that, in mutation/selection/drift steady state, high mutation rates (m) lead to less stable proteins and a more dispersed DFE (i.e., less mutational robustness). Small population size (N) also decreases stability and robustness. In our model, a continuum of nonlethal mutations reduces fitness by ~2% on average, whereas ~10-35% of mutations are lethal depending on N and m. Compensatory mutations are common in small populations with high mutation rates. More broadly, we conclude that interplay between biophysical and population genetic forces shapes the DFE.     

Conformational dynamics of a crystalline protein from microsecond-scale molecular dynamics simulations and diffuse X-ray scattering

X-ray diffraction from protein crystals includes both sharply peaked Bragg reflections and diffuse intensity between the peaks. The information in Bragg scattering is limited to what is available in the mean electron density. The diffuse scattering arises from correlations in the electron density variations and therefore contains information about collective motions in proteins. Previous studies using molecular-dynamics (MD) simulations to model diffuse scattering have been hindered by insufficient sampling of the conformational ensemble. To overcome this issue, we have performed a 1.1-μs MD simulation of crystalline staphylococcal nuclease, providing 100-fold more sampling than previous studies. This simulation enables reproducible calculations of the diffuse intensity and predicts functionally important motions, including transitions among at least eight metastable states with different active-site geometries. The total diffuse intensity calculated using the MD model is highly correlated with the experimental data. In particular, there is excellent agreement for the isotropic component of the diffuse intensity, and substantial but weaker agreement for the anisotropic component. Decomposition of the MD model into protein and solvent components indicates that protein–solvent interactions contribute substantially to the overall diffuse intensity. We conclude that diffuse scattering can be used to validate predictions from MD simulations and can provide information to improve MD models of protein motions.Proteins explore many conformations while carrying out their functions in biological systems (1–3). X-ray crystallography is the dominant source of information about protein structure; however, crystal structure models usually consist of just a single major conformation and at most a small portion of the model as alternate conformations. Crystal structures therefore are missing many details about the underlying conformational ensemble (4).Proteins assembled in crystalline arrays, like proteins in solution, exhibit rich conformational diversity (4) and often can perform their native functions (5). Many methods have emerged for using Bragg data to model conformational diversity in protein crystals (6–17). The development of these methods has been important as conformational diversity can lead to inaccuracies in protein structure models (9, 18–20). A key limitation of using the Bragg data, however, is that different models of conformational diversity can yield the same mean electron density.Whereas the Bragg scattering only contains information about the mean electron density, diffuse scattering (diffraction resulting in intensity between the Bragg peaks) is sensitive to spatial correlations in electron density variations (21–28) and therefore contains information about the way that atomic positions vary together in protein crystals. Because models that yield the same mean electron density can yield different correlations in electron density variations, diffuse scattering provides a means to increase the accuracy of crystallography for determining protein conformational variations (29). Peter Moore (30) and Mark Wilson (31) have argued that diffuse scattering should be used to test models of conformational diversity in X-ray crystallography.Several pioneering studies used diffuse scattering to reveal insights into correlated motions in proteins (17, 30, 32–49). Some of these studies used diffuse scattering to experimentally validate predictions of correlated motions from molecular-dynamics (MD) simulations (35–37, 40, 42–44). These studies revealed important insights but were limited by inadequate sampling of the conformational ensemble, leading to lack of convergence of the diffuse scattering calculations (35). Microsecond-scale simulations of staphylococcal nuclease were predicted to be adequate for convergence of diffuse scattering calculations (42). Modern simulation algorithms and computer hardware now enable microsecond or longer MD simulations of protein crystals (50).Here, we present calculations of diffuse X-ray scattering using a 1.1-μs MD simulation of crystalline staphylococcal nuclease. The results demonstrate that we have overcome the past limitation of inadequate sampling. We chose staphylococcal nuclease because the experiments of Wall et al. (49) still represent the only complete, high-quality, 3D diffuse scattering data set from a protein crystal. The calculated diffuse intensity is very similar using two independent halves of the trajectory; the results therefore are reproducible and can be meaningfully compared with the experimental data. The MD simulation provides a rich picture of conformational diversity in the energy landscape of a protein crystal, consisting of at least eight metastable states. Like previous MD studies of crystalline staphylococcal nuclease (42–44), the agreement of the simulation with the total experimental diffuse intensity is excellent, supporting the use of MD simulations to model diffuse scattering data. Unlike previous MD studies, we separately compared the more finely structured, anisotropic component of the diffuse intensity with experimental data. The agreement is substantial but weaker than for the isotropic component, indicating there are inaccuracies in the MD models. Our results therefore point toward using diffuse scattering to improve MD models of protein motions.     

Slipknotting upon native-like loop formation in a trefoil knot protein

Protein knots and slipknots, mostly regarded as intriguing oddities, are gradually being recognized as significant structural motifs. Recent experimental results show that knotting, starting from a fully extended polypeptide, has not yet been observed. Understanding the nucleation process of folding knots is thus a natural challenge for both experimental and theoretical investigation. In this study, we employ energy landscape theory and molecular dynamics to elucidate the entire folding mechanism. The full free energy landscape of a knotted protein is mapped using an all-atom structure-based protein model. Results show that, due to the topological constraint, the protein folds through a three-state mechanism that contains (i) a precise nucleation site that creates a correctly twisted native loop (first barrier) and (ii) a rate-limiting free energy barrier that is traversed by two parallel knot-forming routes. The main route corresponds to a slipknot conformation, a collapsed configuration where the C-terminal helix adopts a hairpin-like configuration while threading, and the minor route to an entropically limited plug motion, where the extended terminus is threaded as through a needle. Knot formation is a late transition state process and results show that random (nonspecific) knots are a very rare and unstable set of configurations both at and below folding temperature. Our study shows that a native-biased landscape is sufficient to fold complex topologies and presents a folding mechanism generalizable to all known knotted protein topologies: knotting via threading a native-like loop in a preordered intermediate.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Direct calculation of ice homogeneous nucleation rate for a molecular model of water

Ice formation is ubiquitous in nature, with important consequences in a variety of environments, including biological cells, soil, aircraft, transportation infrastructure, and atmospheric clouds. However, its intrinsic kinetics and microscopic mechanism are difficult to discern with current experiments. Molecular simulations of ice nucleation are also challenging, and direct rate calculations have only been performed for coarse-grained models of water. For molecular models, only indirect estimates have been obtained, e.g., by assuming the validity of classical nucleation theory. We use a path sampling approach to perform, to our knowledge, the first direct rate calculation of homogeneous nucleation of ice in a molecular model of water. We use TIP4P/Ice, the most accurate among existing molecular models for studying ice polymorphs. By using a novel topological approach to distinguish different polymorphs, we are able to identify a freezing mechanism that involves a competition between cubic and hexagonal ice in the early stages of nucleation. In this competition, the cubic polymorph takes over because the addition of new topological structural motifs consistent with cubic ice leads to the formation of more compact crystallites. This is not true for topological hexagonal motifs, which give rise to elongated crystallites that are not able to grow. This leads to transition states that are rich in cubic ice, and not the thermodynamically stable hexagonal polymorph. This mechanism provides a molecular explanation for the earlier experimental and computational observations of the preference for cubic ice in the literature.Ice nucleation affects the behavior of many systems (1–6). For example, the formation of ice crystals inside the cytoplasm can damage living cells (1). The amount of ice in a cloud determines both its light-absorbing properties (5) and its precipitation propensity (6), and is therefore an important input parameter in many meteorological models (7, 8). However, current experiments are incapable of uncovering the kinetics and the molecular mechanism of freezing due to their limited spatiotemporal resolution. The ice that nucleates homogeneously in the atmosphere and vapor chamber experiments is predominantly comprised of the cubic-rich stacking-disordered polymorph, not the thermodynamically stable hexagonal polymorph (9, 10). This observation has been rationalized invoking the Ostwald step rule (11). However, the molecular origin of this preference is unknown, due to the limited spatiotemporal resolution of existing experimental techniques. Furthermore, experimental measurements of nucleation rates are only practical over narrow ranges of temperatures (12), with any extrapolation being prone to large uncertainties.Computer simulations are attractive alternatives in this quest, as they make it possible to obtain, at any given thermodynamic condition, a statistically representative sample of nucleation events that can then be used to estimate the rates and identify the mechanism of nucleation. This, however, has only been achieved (13–15) for coarse-grained representations of water, such as the monoatomic water (mW) model (16). For the more realistic molecular force fields, all of the existing studies have relied either on launching a few-microseconds-long molecular dynamics (MD) trajectories (17, 18), or on applying external fields (19), or biasing potentials along prechosen reaction coordinates (20) to drive nucleation, and the generation of statistically representative nucleation trajectories that can allow direct and accurate rate predictions has so far been beyond reach.In this work, we achieve this goal in a system of 4,096 water molecules at 230 K and 1 bar by introducing a novel coarse-graining modification to the path sampling method known as forward-flux sampling (FFS) (21). In the FFS approach, the nucleation process is sampled in stages defined by an order parameter, λ. In crystallization studies, λ is typically chosen as the size of the largest crystalline nucleus in the system (13–15). Individual molecules are labeled as solid- or liquid-like based on the Steinhardt order parameters (22), and the neighboring solid-like molecules are connected to form a cluster (for further details, refer to SI Text, Fig. S1). The cumulative probability of growing a crystallite with λ molecules is then computed from the success probabilities at individual stages (e.g., Fig. 1). If a sufficiently large number of trajectories are sampled at each stage, the nucleation mechanism can be accurately determined by inspecting the ensemble of pseudotrajectories that connect the liquid and crystalline basins. We use the term “pseudotrajectory” as, during FFS, all velocities are randomized at any given milestone.Open in a separate windowFig. 1.Cumulative transition probability vs. size of the largest crystalline nucleus in the TIP4P/Ice system at 230 K and 1 bar. The inflection region is shown in shaded purple. Several representative crystallites are also depicted. The cumulative probability curve for the LJ system simulated at k_BT/? = 0.82 and pσ³/? = 5.68 is shown in the Inset with ε and σ the LJ energy and size parameters. No inflection region is observed in the LJ system.

Table S1.

Technical specifications of the MD simulations and the order parameter

Mechanistic basis for ubiquitin modulation of a protein energy landscape

Ubiquitin is a common posttranslational modification canonically associated with targeting proteins to the 26S proteasome for degradation and also plays a role in numerous other nondegradative cellular processes. Ubiquitination at certain sites destabilizes the substrate protein, with consequences for proteasomal processing, while ubiquitination at other sites has little energetic effect. How this site specificity—and, by extension, the myriad effects of ubiquitination on substrate proteins—arises remains unknown. Here, we systematically characterize the atomic-level effects of ubiquitination at various sites on a model protein, barstar, using a combination of NMR, hydrogen–deuterium exchange mass spectrometry, and molecular dynamics simulation. We find that, regardless of the site of modification, ubiquitination does not induce large structural rearrangements in the substrate. Destabilizing modifications, however, increase fluctuations from the native state resulting in exposure of the substrate’s C terminus. Both of the sites occur in regions of barstar with relatively high conformational flexibility. Nevertheless, destabilization appears to occur through different thermodynamic mechanisms, involving a reduction in entropy in one case and a loss in enthalpy in another. By contrast, ubiquitination at a nondestabilizing site protects the substrate C terminus through intermittent formation of a structural motif with the last three residues of ubiquitin. Thus, the biophysical effects of ubiquitination at a given site depend greatly on local context. Taken together, our results reveal how a single posttranslational modification can generate a broad array of distinct effects, providing a framework to guide the design of proteins and therapeutics with desired degradation and quality control properties.

Ubiquitin is an 8.5-kDa protein appended to target proteins as a posttranslational modification (PTM). Typically, ubiquitin is conjugated to the primary amine of substrate lysine residues, though noncanonical linkages to serine and cysteine also exist in vivo. Ubiquitin itself contains seven lysine residues, which allows building of ubiquitin chains with various linkages and topologies. Ubiquitination is most typically associated with targeting condemned proteins to the 26S proteasome for degradation; however, it is also involved in a large and ever-growing list of crucial regulatory, nondegradative cellular processes (1). A complex and highly regulated enzymatic cascade attaches ubiquitin to substrates and therefore plays a key role in determining the specific downstream effects of an individual ubiquitination event. There are several hundred E3 ligases, the terminal enzymes in this cascade (2), which give rise to broad proteome coverage and allow for some level of site specificity (3, 4).Multiple different ubiquitin chain linkages and topologies bind with high affinity to proteasomal ubiquitin receptors and promote degradation (5–8). However, the presence of a ubiquitin tag alone is not sufficient to ensure proteasomal degradation. In fact, a substantial proportion of ubiquitin-modified proteins that interact with the 26S proteasome are ultimately released (9, 10) and not degraded. The proteasome also relies on substrate conformational properties, initiating degradation at an unstructured region on the condemned protein (11, 12). Much work has been done to understand the requirements of this unstructured region with regard to length, sequence composition, and topological position (13–15), yet at least 30% of known proteasome clients lack such a region (16). While evidence suggests that well-folded proteins are processed by diverse cellular unfoldases, such as Cdc48/p97/VCP (17, 18), an intriguing possibility is that the ubiquitin modification itself can modulate the conformational landscape and thus regulate proteasome substrate selection. Simulations have suggested that ubiquitination can destabilize the folded state of the substrate protein, thereby allowing it to more readily adopt unfolded or partially unfolded conformations (19, 20).Recently, we demonstrated that this is indeed the case: ubiquitin can exert significant effects on a substrate’s energy landscape depending on the site of ubiquitination and the identity of the substrate protein. Moreover, these changes can have direct consequences for proteasomal processing (21). By examining the energetic effects of native, isopeptide-linked ubiquitin attachment to three different sites within the small protein barstar from Bacillus amyloliquefaciens, we found that ubiquitin attached at either lysine 2 or lysine 60 destabilizes the protein both globally and via subglobal fluctuations, and we thus refer to these residues as sensitive sites. By contrast, ubiquitination at lysine 78 produces little effect on the energy landscape (21), and we therefore term it a nonsensitive site. Another study found that ubiquitin, appended through a nonnative linkage, can destabilize a folded substrate as measured by changes in the midpoints for thermally induced unfolding transitions (22).Ubiquitination at the two sensitive sites in barstar increases the population of partially unfolded, high-energy states on the landscape sufficient for proteasomal engagement and degradation. Ubiquitination at the single nondestabilizing site does not allow for proteasomal degradation. These results suggest that ubiquitin-mediated destabilization can reveal an obligate unstructured region in substrates that otherwise lack such a region. Furthermore, ubiquitination at sensitive sites results in more rapid degradation of these barstar variants when a proteasome-engageable unstructured tail is fused to their C termini (21).This previous work clearly demonstrates that ubiquitin-mediated changes to the protein landscape can play an important role in proteasomal selectivity and processing; it did not, however, uncover the molecular mechanisms through which these site-specific effects arise. Here, we interrogate the molecular mechanisms of ubiquitin-induced changes for these same single-lysine variants of barstar. We investigate differences in the intrinsic dynamics of these regions within barstar and differences in how the protein responds to ubiquitination at these individual sites. We employed two sets of complementary approaches: 1) NMR and HDX-MS (hydrogen–deuterium exchange mass spectrometry) to characterize the equilibrium conformational fluctuations of the substrate protein in the presence and absence of ubiquitin and 2) molecular dynamics (MD) simulations to track the position of every atom in barstar, in the presence and absence of ubiquitin, starting from its native conformation over the timescale of microseconds.We find that ubiquitination has only subtle effects on the native structure of barstar. Ubiquitination at the sensitive sites, however, selectively increases fluctuations that expose barstar’s C terminus. While both of the sensitive sites arise in regions of barstar with relatively high conformational flexibility, the observed destabilization appears to occur through different thermodynamic mechanisms. By contrast, ubiquitination at the nonsensitive site has a protective effect on barstar’s C terminus. Thus, the effects of ubiquitination at each site are highly dependent on the local context. This mechanistic understanding of the site-specific effects of ubiquitination should aid in developing predictive models of the energetic consequences of individual ubiquitination events and also of the ways in which aberrant lysine targeting leads to disease (23–25).     

Barrier-limited, microsecond folding of a stable protein measured with hydrogen exchange: Implications for downhill folding

Folding experiments are conducted to test whether a covalently cross-linked coiled-coil folds so quickly that the process is no longer limited by a free-energy barrier. This protein is very stable and topologically simple, needing merely to "zipper up," while having an extrapolated folding rate of k(f) = 2 x 10(5) s(-1). These properties make it likely to attain the elusive "downhill folding" limit, at which a series of intermediates can be characterized. To measure the ultra-fast kinetics in the absence of denaturant, we apply NMR and hydrogen-exchange methods. The stability and its denaturant dependence for the hydrogen bonds in the central part of protein equal the values calculated for whole-molecule unfolding. Like-wise, their closing and opening rates indicate that these hydrogen bonds are broken and reformed in a single cooperative event representing the folding transition from the fully unfolded state to the native state. Additionally, closing rates for these hydrogen bonds agree with the extrapolated barrier-limited folding rate observed near the melting transition. Therefore, even in the absence of denaturant, where DeltaG(eq) approximately -6 kcal.mol(-1) (1 cal = 4.18 J) and tau(f) approximately 6 mus, folding remains cooperative and barrier-limited. Given that this prime candidate for downhill folding fails to do so, we propose that protein folding will remain barrier-limited for proteins that fold cooperatively.