Determination of the structures of distinct transition state ensembles for a β-sheet peptide with parallel folding pathways

Differentiating between the sequence of structural events on alternative pathways of folding of a heterodimeric protein

Distinguishing between competing pathways of folding of a protein, on the basis of how they differ in their progress of structure acquisition, remains an important challenge in protein folding studies. A previous study had shown that the heterodimeric protein, double chain monellin (dcMN) switches between alternative folding pathways upon a change in guanidine hydrochloride (GdnHCl) concentration. In the current study, the folding of dcMN has been characterized by the pulsed hydrogen exchange (HX) labeling methodology used in conjunction with mass spectrometry. Quantification of the extent to which folding intermediates accumulate and then disappear with time of folding at both low and high GdnHCl concentrations, where the folding pathways are known to be different, shows that the folding mechanism is describable by a triangular three-state mechanism. Structural characterization of the productive folding intermediates populated on the alternative pathways has enabled the pathways to be differentiated on the basis of the progress of structure acquisition that occurs on them. The intermediates on the two pathways differ in the extent to which the α-helix and the rest of the β-sheet have acquired structure that is protective against HX. The major difference is, however, that β2 has not acquired any protective structure in the intermediate formed on one pathway, but it has acquired significant protective structure in the intermediate formed on the alternative pathway. Hence, the sequence of structural events is different on the two alternative pathways.

Process, Outcomes and Possible Elimination of Aggregation with Special Reference to Heme Proteins; Likely Remediations of Proteinopathies

Protein folding is a natural phenomenon through which a linear polypeptide possessing necessary information attains three-dimension functionally active conformation. This is a complex and multistep process and therefore, the presence of several intermediary structures could be speculated as a result of protein folding. In in vivo, this folding process is governed by the assistance of other proteins called molecular chaperones and heat shock proteins. Due to the mechanism of protein folding, these intermediary structures remain major challenge for modern biology. Mutation in gene encoding amino acid can cause adverse environmental conditions which may result in misfolding of the linear polypeptide followed by the formation of aggregates and amyloidosis. Aggregation contributes to the pathophysiology of several maladies including diabetes mellitus, Huntington's and Alzheimer's disease. The propensity of native structure to form aggregated and fibrillar assemblies is a hallmark of amyloidosis. During aggregation of a protein, transition from α helix to β sheet is observed, and mainly β sheeted structure is visualised in a mature fibril. Heme proteins are very crucial for major life activities like transport of oxygen and carbon dioxide, synthesis of ATP, role in electron transport chain, and detoxification of free radicals formed during biochemical reactions. Any structural variation in the heme proteins may lead to a fatal response. Hence characterization of the folding intermediates becomes crucial. The characterization has been deciphered with the help of strong denaturants like acetonitrile and TFE. Moreover, possible role of elimination of these aggregates and prevention of protein denaturation is also discussed. Current review deals with the basic process and mechanism of the protein folding in general and the ultimate outcomes of the protein misfolding. Since Native conformation of heme proteins is essential for some vital activities as listed above, we have discussed possible prevention of denaturation and aggregation of heme proteins such as Hb, cyt c, catalase & peroxidase.

Protein Misfolding Diseases and Therapeutic Approaches

Protein folding is the process by which a polypeptide chain acquires its functional, native 3D structure. Protein misfolding, on the other hand, is a process in which protein fails to fold into its native functional conformation. This misfolding of proteins may lead to precipitation of a number of serious diseases such as Cystic Fibrosis (CF), Alzheimer's Disease (AD), Parkinson's Disease (PD), and Amyotrophic Lateral Sclerosis (ALS) etc. Protein Quality-control (PQC) systems, consisting of molecular chaperones, proteases and regulatory factors, help in protein folding and prevent its aggregation. At the same time, PQC systems also do sorting and removal of improperly folded polypeptides. Among the major types of PQC systems involved in protein homeostasis are cytosolic, Endoplasmic Reticulum (ER) and mitochondrial ones. The cytosol PQC system includes a large number of component chaperones, such as Nascent-polypeptide-associated Complex (NAC), Hsp40, Hsp70, prefoldin and T Complex Protein-1 (TCP-1) Ring Complex (TRiC). Protein misfolding diseases caused due to defective cytosolic PQC system include diseases involving keratin/collagen proteins, cardiomyopathies, phenylketonuria, PD and ALS. The components of PQC system of Endoplasmic Reticulum (ER) include Binding immunoglobulin Protein (BiP), Calnexin (CNX), Calreticulin (CRT), Glucose-regulated Protein GRP94, the thiol-disulphide oxidoreductases, Protein Disulphide Isomerase (PDI) and ERp57. ER-linked misfolding diseases include CF and Familial Neurohypophyseal Diabetes Insipidus (FNDI). The components of mitochondrial PQC system include mitochondrial chaperones such as the Hsp70, the Hsp60/Hsp10 and a set of proteases having AAA+ domains similar to the proteasome that are situated in the matrix or the inner membrane. Protein misfolding diseases caused due to defective mitochondrial PQC system include medium-chain acyl-CoA dehydrogenase (MCAD)/Short-chain Acyl-CoA Dehydrogenase (SCAD) deficiency diseases, hereditary spastic paraplegia. Among therapeutic approaches towards the treatment of various protein misfolding diseases, chaperones have been suggested as potential therapeutic molecules for target based treatment. Chaperones have been advantageous because of their efficient entry and distribution inside the cells, including specific cellular compartments, in therapeutic concentrations. Based on the chemical nature of the chaperones used for therapeutic purposes, molecular, chemical and pharmacological classes of chaperones have been discussed.

Bayesian ensemble refinement by replica simulations and reweighting

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Network approach to identify the folding transition states of peptides and proteins

Folding transition states and their structures are crucial in understanding protein folding pathways and folding dynamics. As they cannot be detected directly by experiments due to their instability, many computational methods have been proposed to solve this problem. However, each of these methods can give only one part of the transition state ensemble for a peptide or protein. Here we present a folding-network approach to identify the transition states of peptides or proteins and test it on the β-hairpin peptide trpzip2, with the result that we identify all the folding transition states of tripzip2, which may only be determined separately by other methods. This suggests that the network approach can provide more complete information about the folding transition states, at least for peptides.

Defective protein folding and aggregation as the basis of neurodegenerative diseases: the darker aspect of proteins

The ability of a polypeptide to fold into a unique, functional, and three-dimensional structure depends on the intrinsic properties of the amino acid sequence, function of the molecular chaperones, proteins, and enzymes. Every polypeptide has a finite tendency to misfold and this forms the darker side of the protein world. Partially folded and misfolded proteins that escape the cellular quality control mechanism have the high tendency to form inter-molecular hydrogen bonding between the same protein molecules resulting in aggregation. This review summarizes the underlying and universal mechanism of protein folding. It also deals with the factors responsible for protein misfolding and aggregation. This article describes some of the consequences of such behavior particularly in the context of neurodegenerative conformational diseases such as Alzheimer's, Parkinson's, Huntington's, amyotrophic lateral sclerosis and other non-neurodegenerative conformational diseases such as cancer and cystic fibrosis etc. This will encourage a more proactive approach to the early diagnosis of conformational diseases and nutritional counseling for patients.

Folding pathways and rates for the three-stranded beta-sheet peptide Beta3s using discrete path sampling

The discrete path sampling method was used to investigate the folding of a three-stranded antiparallel beta-sheet peptide, Beta3s, described by an empirical potential and implicit solvent model. After application of a coarse-graining scheme that groups together sets of minima in local equilibrium, the calculated folding time was in reasonable agreement with other simulations and consistent with the experimental upper bound. The folding mechanism exhibited by the most significant discrete paths involves early formation of the C-terminal hairpin followed by docking of the N-terminal strand.

Molecular dynamics simulations from putative transition states of alpha-spectrin SH3 domain

A series of molecular dynamics simulations in explicit solvent were started from nine structural models of the transition state of the SH3 domain of alpha-spectrin, which were generated by Lindorff-Larsen et al. (Nat Struct Mol Biol 2004;11:443-449) using molecular dynamics simulations in which experimental Phi - values were incorporated as restraints. Two of the nine models were simulated 10 times for 200 ns and the remaining models simulated two times for 200 ns. Complete folding was observed in one case, while in the other simulations partial folding or unfolding events were observed, which were characterized by a regularization of elements of secondary structure. These results are consistent with recent experimental evidence that the folding of SH3 domains involves low populated intermediate states.

Transition states in protein folding kinetics: modeling phi-values of small beta-sheet proteins

Small single-domain proteins often exhibit only a single free-energy barrier, or transition state, between the denatured and the native state. The folding kinetics of these proteins is usually explored via mutational analysis. A central question is which structural information on the transition state can be derived from the mutational data. In this article, we model and structurally interpret mutational Phi-values for two small beta-sheet proteins, the PIN and the FBP WW domains. The native structure of these WW domains comprises two beta-hairpins that form a three-stranded beta-sheet. In our model, we assume that the transition state consists of two conformations in which either one of the hairpins is formed. Such a transition state has been recently observed in molecular dynamics folding-unfolding simulations of a small designed three-stranded beta-sheet protein. We obtain good agreement with the experimental data 1), by splitting up the mutation-induced free-energy changes into terms for the two hairpins and for the small hydrophobic core of the proteins; and 2), by fitting a single parameter, the relative degree to which hairpins 1 and 2 are formed in the transition state. The model helps us to understand how mutations affect the folding kinetics of WW domains, and captures also negative Phi-values that have been difficult to interpret.

Simulation studies of the fidelity of biomolecular structure ensemble recreation

We examine the ability of Bayesian methods to recreate structural ensembles for partially folded molecules from averaged data. Specifically we test the ability of various algorithms to recreate different transition state ensembles for folding proteins using a multiple replica simulation algorithm using input from "gold standard" reference ensembles that were first generated with a Go-like Hamiltonian having nonpairwise additive terms. A set of low resolution data, which function as the "experimental" phi values, were first constructed from this reference ensemble. The resulting phi values were then treated as one would treat laboratory experimental data and were used as input in the replica reconstruction algorithm. The resulting ensembles of structures obtained by the replica algorithm were compared to the gold standard reference ensemble, from which those "data" were, in fact, obtained. It is found that for a unimodal transition state ensemble with a low barrier, the multiple replica algorithm does recreate the reference ensemble fairly successfully when no experimental error is assumed. The Kolmogorov-Smirnov test as well as principal component analysis show that the overlap of the recovered and reference ensembles is significantly enhanced when multiple replicas are used. Reduction of the multiple replica ensembles by clustering successfully yields subensembles with close similarity to the reference ensembles. On the other hand, for a high barrier transition state with two distinct transition state ensembles, the single replica algorithm only samples a few structures of one of the reference ensemble basins. This is due to the fact that the phi values are intrinsically ensemble averaged quantities. The replica algorithm with multiple copies does sample both reference ensemble basins. In contrast to the single replica case, the multiple replicas are constrained to reproduce the average phi values, but allow fluctuations in phi for each individual copy. These fluctuations facilitate a more faithful sampling of the reference ensemble basins. Finally, we test how robustly the reconstruction algorithm can function by introducing errors in phi comparable in magnitude to those suggested by some authors. In this circumstance we observe that the chances of ensemble recovery with the replica algorithm are poor using a single replica, but are improved when multiple copies are used. A multimodal transition state ensemble, however, turns out to be more sensitive to large errors in phi (if appropriately gauged) and attempts at successful recreation of the reference ensemble with simple replica algorithms can fall short.

Kinetic definition of protein folding transition state ensembles and reaction coordinates

Using distributed molecular dynamics simulations we located four distinct folding transitions for a 39-residue betabetaalphabeta protein fold. To characterize the nature of each room temperature transition, we calculated the probability of transmission for 500 points along each free energy barrier. We introduced a method for determining transition states by employing the transmission probability, Ptrans, and determined which conformations were transition state ensemble members (Ptrans approximately 0.5). The transmission probability may be used to characterize the barrier in several ways. For example, we ran simulations at 82 degrees C, determined the change in Ptrans with temperature for all 2,000 conformations, and quantified Hammond behavior directly using Ptrans correlation. Additionally, we propose that diffusion along Ptrans may provide the configurational diffusion rate at the top of the barrier. Specifically, given a transition state conformation x0 with estimated Ptrans=0.5, we selected a large set of subsequent conformations from independent trajectories, each exactly a small time deltat after x0 (250 ps). Calculating Ptrans for the new trial conformations, we generated the P(Ptrans|deltat=250 ps) distribution that reflected diffusion. This approach provides a novel perspective on the diffusive nature of a protein folding transition and provides a framework for a quantitative study of activated relaxation kinetics.

Structural interpretation of hydrogen exchange protection factors in proteins: characterization of the native state fluctuations of CI2

Protection factors obtained from equilibrium hydrogen exchange experiments are an important source of structural information on both native and nonnative states of proteins. We present a method for determining ensembles of protein structures by using hydrogen exchange data as restraints in molecular dynamics simulations in conjunction with an empirical force-field. The method is applied to determine the ensemble of structures representing the native state of chymotrypsin inhibitor 2 (CI2), including the rare, large fluctuations responsible for hydrogen exchange.

Structural comparison of the two alternative transition states for folding of TI I27

TI I27, a beta-sandwich domain from the human muscle protein titin, has been shown to fold via two alternative pathways, which correspond to a change in the folding mechanism. Under physiological conditions, TI I27 folds by a classical nucleation-condensation mechanism (diffuse transition state), whereas at extreme conditions of temperature and denaturant it switches to having a polarized transition state. We have used experimental Phi-values as restraints in ensemble-averaged molecular dynamics simulations to determine the ensembles of structures representing the two transition states. The comparison of these ensembles indicates that when native interactions are substantially weakened, a protein may still be able to fold if it can access an alternative transition state characterized by a much larger entropic contribution. Analysis of the probability distribution of Phi-values derived from ensemble averaged simulations, enables us to identify residues that form contacts in some members of the ensemble but not in others illustrating that many interactions present in transition states are not strictly required for the successful completion of the folding process.

Symmetric connectivity of secondary structure elements enhances the diversity of folding pathways

The influence of native connectivity of secondary structure elements (SSE) on folding is studied using coarse-grained models of proteins with mixed alpha and beta structure and the analysis of the structural database of wild-type proteins. We found that the distribution of SSE along a sequence determines the diversity of folding pathways. If alpha and beta SSE are localized in different parts of a sequence, the diversity of folding pathways is restricted. An even (symmetric) distribution of alpha and beta SSE with respect to sequence midpoint favors multiple folding routes. Simulations are supplemented by the database analysis of the distribution of SSE in wild-type protein sequences. On an average, two-thirds of wild-type proteins with mixed alpha and beta structure have symmetric distribution of alpha and beta SSE. The propensity for symmetric distribution of SSE is especially evident for large proteins with the number of SSE > or = 10. We suggest that symmetric SSE distribution in protein sequences may arise due to nearly random allocation of alpha and beta structure along wild-type sequences. The tendency of long sequences to misfold is perhaps compensated by the enhanced pathway diversity. In addition, folding pathways are shown to progress via hierarchic assembly of SSE in accordance with their proximity along a sequence. We demonstrate that under mild denaturation conditions folding and unfolding pathways are similar. However, the reversibility of folding/unfolding pathways is shown to depend on the distribution of SSE. If alpha and beta SSE are localized in different parts of a sequence, folding and unfolding pathways are likely to coincide.

Transition State Contact Orders Correlate with Protein Folding Rates

We have used molecular dynamics simulations restrained by experimental phi values derived from protein engineering experiments to determine the structures of the transition state ensembles of ten proteins that fold with two-state kinetics. For each of these proteins we then calculated the average contact order in the transition state ensemble and compared it with the corresponding experimental folding rate. The resulting correlation coefficient is similar to that computed for the contact orders of the native structures, supporting the use of native state contact orders for predicting folding rates. The native contacts in the transition state also correlate with those of the native state but are found to be about 30% lower. These results show that, despite the high levels of heterogeneity in the transition state ensemble, the large majority of contributing structures have native-like topologies and that the native state contact order captures this phenomenon.

Determination of the folding transition states of barnase by using PhiI-value-restrained simulations validated by double mutant PhiIJ-values

The protein barnase folds from the denatured state into its native conformation via a high-energy intermediate. Using PhiI-values determined experimentally from single-point mutations as restraints in all-atom molecular dynamics simulations, we have determined ensembles of structures corresponding to the transition states for the formation of the folding intermediate and its conversion into the native state. We have also introduced a stringent validation of the approach used to calculate such structures by predicting interaction PhiIJ-values determined experimentally from a series of double-mutant cycles. The ensembles that we have obtained illustrate the heterogeneity in the nucleation-condensation process by which barnase folds. Obligatory steps of this process include the sequential formation of two folding nuclei, which correspond to the two main hydrophobic cores of the protein. Nonobligatory steps include the elongation of the strand beta1 and the formation of the helix alpha2. The results confirm that the use of experimental observables such as PhiI-values as restraints in molecular dynamics simulations is a powerful general strategy to characterize the relatively heterogeneous structural ensembles that populate nonnative regions of the energy landscapes of proteins.

Towards complete descriptions of the free-energy landscapes of proteins

In recent years increasingly detailed information about the structures and dynamics of protein molecules has been obtained by innovative applications of experimental techniques, in particular nuclear magnetic resonance spectroscopy and protein engineering, and theoretical methods, notably molecular dynamics simulations. In this article we discuss how such approaches can be combined by incorporating a wide range of different types of experimental data as restraints in computer simulations to provide unprecedented detail about the ensembles of structures that describe proteins in a wide variety of states from the native structure to highly unfolded species. Knowledge of these ensembles is beginning to enable the complete free-energy landscapes of individual proteins to be defined at atomic resolution. This strategy has provided new insights into the mechanism by which proteins are able to fold into their native states, or by which they fail to do so and give rise to harmful aggregates that are associated with a wide range of debilitating human diseases.

Phi-value analysis by molecular dynamics simulations of reversible folding

In Phi-value analysis, the effects of mutations on the folding kinetics are compared with the corresponding effects on thermodynamic stability to investigate the structure of the protein-folding transition state (TS). Here, molecular dynamics (MD) simulations (totaling 0.65 ms) have been performed for a large set of single-point mutants of a 20-residue three-stranded antiparallel beta-sheet peptide. Between 57 and 120 folding events were sampled at near equilibrium for each mutant, allowing for accurate estimates of folding/unfolding rates and stability changes. The Phi values calculated from folding and unfolding rates extracted from the MD trajectories are reliable if the stability loss upon mutation is larger than approximately 0.6 kcal/mol, which is observed for 8 of the 32 single-point mutants. The same heterogeneity of the TS of the wild type was found in the mutated peptides, showing two possible pathways for folding. Single-point mutations can induce significant TS shifts not always detected by Phi-value analysis. Specific nonnative interactions at the TS were observed in most of the peptides studied here. The interpretation of Phi values based on the ratio of atomic contacts at the TS over the native state, which has been used in the past in MD and Monte Carlo simulations, is in agreement with the TS structures of wild-type peptide. However, Phi values tend to overestimate the nativeness of the TS ensemble, when interpreted neglecting the nonnative interactions.

Optimal combination of theory and experiment for the characterization of the protein folding landscape of S6: how far can a minimalist model go?

The detailed characterization of the overall free energy landscape associated with the folding process of a protein is the ultimate goal in protein folding studies. Modern experimental techniques provide accurate thermodynamic and kinetic measurements on restricted regions of a protein landscape. Although simplified protein models can access larger regions of the landscape, they are oftentimes built on assumptions and approximations that affect the accuracy of the results. We present a new methodology that allows to combine the complementary strengths of theory and experiment for a more complete characterization of a protein folding landscape. We prove that this new procedure allows a simplified protein model to reproduce remarkably well (correlation coefficient > 0.9) all experimental data available on free energies differences upon single mutations for S6 ribosomal protein and two circular permutants. Our results confirm and quantify the hypothesis, recently formulated on the basis of experimental data, that the folding landscape of protein S6 is strongly affected by an atypical distribution of contact energies.

Principles of protein folding, misfolding and aggregation

This review summarises our current understanding of the underlying and universal mechanism by which newly synthesised proteins achieve their biologically functional states. Protein molecules, however, all have a finite tendency either to misfold, or to fail to maintain their correctly folded states, under some circumstances. This article describes some of the consequences of such behaviour, particularly in the context of the aggregation events that are frequently associated with aberrant folding. It focuses in particular on the emerging links between protein aggregation and the increasingly prevalent forms of debilitating disease with which it is now known to be associated.

Simulation, experiment, and evolution: understanding nucleation in protein S6 folding

In this study, we explore nucleation and the transition state ensemble of the ribosomal protein S6 using a Monte Carlo (MC) Go model in conjunction with restraints from experiment. The results are analyzed in the context of extensive experimental and evolutionary data. The roles of individual residues in the folding nucleus are identified, and the order of events in the S6 folding mechanism is explored in detail. Interpretation of our results agrees with, and extends the utility of, experiments that shift phi-values by modulating denaturant concentration and presents strong evidence for the realism of the mechanistic details in our MC Go model and the structural interpretation of experimental phi-values. We also observe plasticity in the contacts of the hydrophobic core that support the specific nucleus. For S6, which binds to RNA and protein after folding, this plasticity may result from the conformational flexibility required to achieve biological function. These results present a theoretical and conceptual picture that is relevant in understanding the mechanism of nucleation in protein folding.

Transition states for protein folding have native topologies despite high structural variability

We present a structural analysis of the folding transition states of three SH3 domains. Our results reveal that the secondary structure is not yet fully formed at this stage of folding and that the solvent is only partially excluded from the interior of the protein. Comparison of the members of the transition state ensemble with a database of native folds shows that, despite substantial local variability, the transition state structures can all be classified as having the topology characteristic of an SH3 domain. Our results suggest a mechanism for folding in which the formation of a network of interactions among a subset of hydrophobic residues ensures that the native topology is generated. Such a mechanism enables high fidelity in folding while minimizing the need to establish a large number of specific interactions in the conformational search.

Thermodynamic Characterisation of Two Transition States Along Parallel Protein Folding Pathways

Recent work has shown that a beta-sandwich domain from the human muscle protein titin (TI I27) unfolds via more than one pathway, providing experimental evidence for a long-standing theoretical prediction in protein folding. Here we present a thermodynamic analysis of two transition states along different folding pathways for this protein. The unusual upwards curvature previously observed in the denaturant-dependent unfolding kinetics is increased at both high and low temperatures, indicating that the high denaturant pathway is becoming more accessible. The transition states in each pathway are structurally distinct and have very different heat capacities. Interestingly the nucleation-condensation pathway is dominant at all physiologically relevant temperatures, supporting the suggestion that pathways with diffuse rather than localised transition states have been selected for by evolution to prevent misfolding.

Commitment and Nucleation in the Protein G Transition State

An accurate characterization of the transition state ensemble (TSE) is central to furthering our understanding of the protein folding reaction. We have extensively tested a recently reported method for studying a protein's TSE, utilizing phi-value data from protein engineering experiments and computational studies as restraints in all-atom Monte Carlo (MC) simulations. The validity of interpreting experimental phi-values as the fraction of native contacts made by a residue in the TSE was explored, revealing that this definition is unable to uniquely specify a TSE. The identification of protein G's second hairpin, in both pre and post-transition conformations demonstrates that high experimental phi-values do not guarantee a residue's importance in the TSE. An analysis of simulations based on structures restrained by experimental phi-values is necessary to yield this result, which is not obvious from a simplistic interpretation of individual phi-values. The TSE that we obtain corresponds to a single, specific nucleation event, characterized by six residues common to all three observed, convergent folding pathways. The same specific nucleus was independently identified from computational and experimental data, and "Conservation of Conservation" analysis in the protein G fold. When associated strictly with complete nucleus formation and concomitant chain collapse, folding is a well-defined two state event. Once the nucleus has formed, the folding reaction enters a slow relaxation process associated with side-chain packing and small, local backbone rearrangements. A detailed analysis of phi-values and their relationship to the transition state ensemble allows us to construct a unified theoretical model of protein G folding.

Comparison of the transition state ensembles for folding of Im7 and Im9 determined using all-atom molecular dynamics simulations with ϕ value restraints

Delineation of the structural properties of transition states is key to deriving models for protein folding. Here we describe the structures of the transition states of the bacterial immunity proteins Im7 and Im9 obtained by all-atom molecular dynamics simulations with phi value restraints derived from protein engineering experiments. This pair of proteins is of special interest because, at pH 7 and 10 degrees C, Im7 folds via an intermediate while Im9 folds with a two-state transition. The structures of the transition states for Im7 and Im9, together with their radii of gyration and distances from the native state, are similar. The typical distance between any two members of the transition state ensemble of both proteins is large, with that of Im9 nearly twice that of Im7. Thus, a broad range of structures make up the transition state ensembles of these proteins. The ensembles satisfy the set of rather low phi values and yet are consistent with high beta(T) values (> 0.85 for both proteins). For both Im7 and Im9 the inter-helical angles are highly variable in the transition state ensembles, although the native contacts between helices I and IV are well conserved. By measuring the distribution of the accessible surface area for each residue we show that the hydrophobic residues that are buried in the native state remain buried in the transition state, corresponding to a hydrophobic collapse to a relatively ordered globule. The data provide new insights into the structural properties of the transition states of these proteins at an atomic level of detail and show that molecular dynamics simulations with phi value restraints can significantly enhance the knowledge of the transition state ensembles (TSE) provided by the experimental phi values alone.

Parallel protein-unfolding pathways revealed and mapped

Theoretical studies of protein folding suggest that multiple folding pathways should exist, but there is little experimental evidence to support this. Here we demonstrate changes in the flux between different transition states on parallel folding pathways, resulting in unprecedented upward curvature in the denaturant-dependent unfolding kinetics of a beta-sandwich protein. As denaturant concentration increases, the highly compact transition state of one pathway becomes destabilized and the dominant flux of protein molecules shifts toward another pathway with a less structured transition state. Furthermore, point mutations alter the relative accessibility of the pathways, allowing the structure of two transition states on separate, direct folding pathways to be mapped by systematic Phi-value analysis. It has been suggested that pathways with diffuse rather than localized transition states are evolutionarily selected to prevent misfolding, and indeed we find that the transition state favored at high concentrations of denaturant is more polarized than the physiologically relevant one.

Protein folding: bringing theory and experiment closer together

The ability to perform enzymatic function by harnessing random molecular motion into self-organized protein structures is one of the most fascinating results of evolution. A close interplay between theory and experiment is driving the progress in understanding the principles that determine the behaviour of proteins. New techniques that significantly increase the amount of information obtainable from experimental data have been recently proposed; it is now becoming possible to describe at atomic resolution the events that take place during the folding process. Successful predictions of these events are being reported at an increasing rate and general principles are being outlined.