High-pressure NMR spectroscopy for characterizing folding intermediates and denatured states of proteins

Extensive structural studies using high-pressure NMR spectroscopy have recently been carried out on proteins, which potentially contribute to our understanding of the mechanisms of protein folding. Pressure shifts the conformational equilibrium from higher to lower volume conformers. If the pressure is varied, starting from the folded native structure, in many cases we observe intermediate conformers before the onset of total unfolding. This enables the investigation of details of the structure and thermodynamic characteristics of various intermediate conformers of proteins under equilibrium conditions. We can also examine pressure effects on the structure and stability of some typical denatured states such as helical denatured, molten globule, and unfolded states. The high-pressure NMR method can also be used to investigate association/dissociation equilibria of oligomeric or aggregated proteins. Beside direct observation of kinetic intermediates upon pressure jump, NMR structural investigations of equilibrium conformers under pressure provide information about the structures of kinetic intermediates during folding/unfolding reactions.     

Basic folded and low-populated locally disordered conformers of SUMO-2 characterized by NMR spectroscopy at varying pressures

SUMO proteins, a group of post-translational ubiquitin-like modifiers, have target enzymes (E1 and E2) like other ubiquitin-like modifiers, e.g., ubiquitin and NEDD8, but their physiological roles are quite different. In an effort to determine the characteristic molecular design of ubiquitin-like modifiers, we have investigated the structure of human SUMO-2 in solution not only in its basic folded state but also in its higher-energy state by utilizing standard and variable-pressure NMR spectroscopy, respectively. We have determined average coordinates of the basic folded conformer at ambient pressure, which gives a backbone structure almost identical with those of ubiquitin and NEDD8. We have further investigated conformational fluctuations in a wide conformational space using variable-pressure NMR spectroscopy in the range of 30-3 kbar, by which we find a low-populated ( approximately 2.5%) alternative conformer preferentially disordered in the enzyme-binding segment. The alternative conformer is structurally very close to but markedly different in equilibrium population from those for ubiquitin and NEDD8. These results support our notion that post-translational ubiquitin-like modifiers are evolutionarily designed for function both structurally and thermodynamically in their low-populated, high-energy conformers rather than in their basic folded conformers.     

Conformational fluctuations of proteins revealed by variable pressure NMR

With the high-resolution variable-pressure NMR spectroscopy, one can study conformational fluctuations of proteins in a much wider conformational space than hitherto explored by NMR and other spectroscopic techniques. This is because a protein in solution generally exists as a dynamic mixture of conformers mutually differing in partial molar volume, and pressure can select the population of a conformer according to its relative volume. In this review, we describe how variable-pressure NMR can be used to probe conformational fluctuations of proteins in a wide conformational space from the folded to the fully unfolded structures, with actual examples. Furthermore, the newly emerging technique "NMR snapshots" expresses amply fluctuating protein structures as changes in atomic coordinates. Finally, the concept of conformational fluctuation is extended to include intermolecular association leading to amyloidosis.     

Insight into polyproline II helical bundle stability in an antifreeze protein denatured state

The use of polyproline II (PPII) helices in protein design is currently hindered by limitations in our understanding of their conformational stability and folding. Recent studies of the snow flea antifreeze protein (sfAFP), a useful model system composed of six PPII helices, suggested that a low denatured state entropy contributes to folding thermodynamics. Here, circular dichroism spectroscopy revealed minor populations of PPII like conformers at low temperature. To get atomic level information on the conformational ensemble and entropy of the reduced, denatured state of sfAFP, we have analyzed its chemical shifts and {¹H}-¹⁵N relaxation parameters by NMR spectroscopy at four experimental conditions. No significant populations of stable secondary structure were detected. The stiffening of certain N-terminal residues at neutral versus acidic pH and shifted pK_a values leads us to suggest that favorable charge-charge interactions could bias the conformational ensemble to favor the formation the C1-C28 disulfide bond during nascent folding, although no evidence for preferred contacts between these positions was detected by paramagnetic relaxation enhancement under denaturing conditions. Despite a high content of flexible glycine residues, the mobility of the sfAFP denatured ensemble is similar for denatured α/β proteins both on fast ps/ns as well as slower μs/ms timescales. These results are in line with a conformational entropy in the denatured ensemble resembling that of typical proteins and suggest that new structures based on PPII helical bundles should be amenable to protein design.     

High pressure macromolecular crystallography for structural biology: a review

In recent years, significant progress in high pressure macromolecular crystallography has been observed. It can be attributed both to the developments in experimental techniques, as well as to recognition of importance of high pressure protein studies in biochemistry and biophysics. The number of protein structures determined at pressure up to 1 GPa is growing. The unique advantages of this method can greatly improve the investigation of higher energy conformers of functional significance and our understanding of functionally important conformers, protein folding processes and the structural base of conformational diseases.     

Side-chain entropy effects on protein secondary structure formation

Loss of conformational entropy is one of the primary factors opposing protein folding. Both the backbone and side-chain of each residue in a protein will have their freedom of motion restricted in the final folded structure. The type of secondary structure of which a residue is part will have a significant impact on how much side-chain entropy is lost. Side-chain conformational entropies have previously been determined for folded proteins, simple models of unfolded proteins, alpha-helices, and a dipeptide model for beta-strands, but not for polyproline II (PII) helices. In this work, we present side-chain conformational estimates for the three regular secondary structure types: alpha-helices, beta-strands, and PII helices. Entropies are estimated from Monte Carlo computer simulations. Beta-strands are modeled as two structures, parallel and antiparallel beta-strands. Our data indicate that restraining a residue to the PII helix or antiparallel beta-strand conformations results in side-chain entropies equal to or higher than those obtained by restraining residues to the parallel beta-strand conformation. Side-chains in the alpha-helix conformation have the lowest side-chain entropies. The observation that extended structures retain the most side-chain entropy suggests that such structures would be entropically favored in unfolded proteins under folding conditions. Our data indicate that the PII helix conformation would be somewhat favored over beta-strand conformations, with antiparallel beta-strand favored over parallel. Notably, our data imply that, under some circumstances, residues may gain side-chain entropy upon folding. Implications of our findings for protein folding and unfolded states are discussed.     

Noninteracting local-structure model of folding and unfolding transition in globular proteins. I. Formulation

A statistical-mechanical model (a noninteracting local structure model) of folding and unfolding transition in globular proteins is described and a formulation is given to calculate the partition function. The process of transition is discussed in this model within the framework of equilibrium statistical mechanics. In order to clarify the range of applicability of such an approach, the characteristics of the folding and unfolding transition in globular proteins are analyzed from the statistical-physical point of view. A theoretical advantage is pointed out in studying folding and unfolding processes taking place as conformational fluctuations in individual protein molecules under macroscopic equilibrium at the melting temperature. In this case, paths of folding and unfolding are shown to be identical in the statistical sense. A key to the noninteracting local structure model lies in the concept of local structures and the assumption of the absence of interactions between local structures. A local structure is defined as a continuous section of the chain which takes the same or similar local conformation as in the native conformation. The assumption of the absence of inter-actions between local structures endows the model with the remarkable character that its partition function can be calculated exactly; thereby the equilibrium population of various conformations along the folding and unfolding paths can be discussed only by a knowledge of the folded native conformation.     

Conformational comparison of mu-selective endomorphin-2 with its C-terminal free acid in DMSO solution, by 1H NMR spectroscopy and molecular modeling calculation.

In order to make clear the structural role of the C-terminal amide group of endomorphin-2 (EM2, H-Tyr-Pro-Phe-Phe-NH2), an endogenous mu-receptor ligand, in the biological function, the solution conformations of endomorphin-2 and its C-terminal free acid (EM2OH, H-Tyr-Pro-Phe-Phe-OH), studied using two-dimensional 1H NMR measurements and molecular modeling calculations, were compared. Both peptides were in equilibrium between the cis and trans isomers around the Tyr-Pro omega bond in a population ratio of approximately/= 1:2. The lack of significant temperature and concentration dependence of NH protons suggested that the NMR spectra reflected the conformational features of the respective molecules themselves. Fifty possible 3D structures for the each isomer were generated by the dynamical simulated annealing method under the proton-proton distance constraints derived from the ROE cross-peaks. These energy-minimized conformers, which were all in the phi torsion angles estimated from J(NHCalphaH) coupling constants within +/- 30 degrees, were then classified in groups one or two according to the folding backbone structures. All trans and cis EM2 conformers adopt an open conformation in which their extended backbone structures are twisted at the Pro2-Phe3 moiety. In contrast, the trans and cis conformers of EM2OH show conformational variation between the 'bow'-shaped extended and folded backbone structures, although the cis conformers of its zwitterionic form are refined into the folded structure of the close disposition of C- and N-terminal groups. These results indicate clearly that the substitution of carboxyl group for C-terminal amide group makes the peptide flexible. The conformational requirement for mu-receptor activation has been discussed based on the active form proposed for endomorphin-1 and by comparing conformational features of EM2 and EM2OH.     

Disorder transitions and conformational diversity cooperatively modulate biological function in proteins

Structural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered‐disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins become more ordered after ligand binding, while 40% more disordered. As protein conformational diversity is inherently connected with protein function our analysis suggests differences in structure‐function relationships related to order‐disorder transitions.     

Designing proteins from the inside out

Globular proteins are characterized by the specific and tight packing of hydrophobic side-chains in the so-called "hydrophobic core." Formation of the core is key in folding, stabilization, and conformational specificity. The critical role of hydrophobic cores in maintaining the highly ordered structures present in natural proteins justifies the tremendous efforts devoted to their redesign. Both experimental and computational combinatorial-based approaches have been reported in the last years as powerful protein design tools. These manage to explore large regions of the sequence/conformational space, allowing the search for alternative protein core arrangements displaying native-like properties. The overall results obtained from core design projects have contributed significantly to our present knowledge of protein folding and function. In addition, core design has worked as a benchmark for the development of ambitious protein design projects that nowadays are allowing the de novo design of novel protein structures and functions.     

核磁共振波谱应用于结构生物学的研究进展

综述了核磁共振波谱在结构生物学研究中的进展。在溶液中测定生物大分子的结构,分子大小的限制正被减少,尽管新结构的测定仍然需要付出比较大的努力。核磁共振是一个有效的手段,可用于研究在许多细胞过程中存在的弱的或者瞬态的蛋白质-蛋白质相互作用。结构的柔性在蛋白质分子功能中起了中心作用。由于最近方法学的发展,使NMR可以表征蛋白质的动力学,从而可以对分子机制有新的认识。核磁共振波谱可以在原子分辨率下表征无序的蛋白质系统,可以研究折叠路径。跨膜蛋白在细胞中起了关键作用,这使它们成为药物的靶标。应用液体和固体核磁共振技术已经成功测定了跨膜蛋白质的结构。     

Exploring the relationship between funneled energy landscapes and two-state protein folding

It should take an astronomical time span for unfolded protein chains to find their native state based on an unguided conformational random search. The experimental observation that folding is fast can be rationalized by assuming that protein energy landscapes are sloped towards the native state minimum, such that rapid folding can proceed from virtually any point in conformational space. Folding transitions often exhibit two-state behavior, involving extensively disordered and highly structured conformers as the only two observable kinetic species. This study employs a simple Brownian dynamics model of "protein particles" moving in a spherically symmetrical potential. As expected, the presence of an overall slope towards the native state minimum is an effective means to speed up folding. However, the two-state nature of the transition is eradicated if a significant energetic bias extends too far into the non-native conformational space. The breakdown of two-state cooperativity under these conditions is caused by a continuous conformational drift of the unfolded proteins. Ideal two-state behavior can only be maintained on surfaces exhibiting large regions that are energetically flat, a result that is supported by other recent data in the literature (Kaya and Chan, Proteins: Struct Funct Genet 2003;52:510-523). Rapid two-state folding requires energy landscapes exhibiting the following features: (i) A large region in conformational space that is energetically flat, thus allowing for a significant degree of random sampling, such that unfolded proteins can retain a random coil structure; (ii) a trapping area that is strongly sloped towards the native state minimum.     

Folding funnels, binding funnels, and protein function.

Folding funnels have been the focus of considerable attention during the last few years. These have mostly been discussed in the general context of the theory of protein folding. Here we extend the utility of the concept of folding funnels, relating them to biological mechanisms and function. In particular, here we describe the shape of the funnels in light of protein synthesis and folding; flexibility, conformational diversity, and binding mechanisms; and the associated binding funnels, illustrating the multiple routes and the range of complexed conformers. Specifically, the walls of the folding funnels, their crevices, and bumps are related to the complexity of protein folding, and hence to sequential vs. nonsequential folding. Whereas the former is more frequently observed in eukaryotic proteins, where the rate of protein synthesis is slower, the latter is more frequent in prokaryotes, with faster translation rates. The bottoms of the funnels reflect the extent of the flexibility of the proteins. Rugged floors imply a range of conformational isomers, which may be close on the energy landscape. Rather than undergoing an induced fit binding mechanism, the conformational ensembles around the rugged bottoms argue that the conformers, which are most complementary to the ligand, will bind to it with the equilibrium shifting in their favor. Furthermore, depending on the extent of the ruggedness, or of the smoothness with only a few minima, we may infer nonspecific, broad range vs. specific binding. In particular, folding and binding are similar processes, with similar underlying principles. Hence, the shape of the folding funnel of the monomer enables making reasonable guesses regarding the shape of the corresponding binding funnel. Proteins having a broad range of binding, such as proteolytic enzymes or relatively nonspecific endonucleases, may be expected to have not only rugged floors in their folding funnels, but their binding funnels will also behave similarly, with a range of complexed conformations. Hence, knowledge of the shape of the folding funnels is biologically very useful. The converse also holds: If kinetic and thermodynamic data are available, hints regarding the role of the protein and its binding selectivity may be obtained. Thus, the utility of the concept of the funnel carries over to the origin of the protein and to its function.     

Strategies for dealing with conformational sampling in structural calculations of flexible or kinked transmembrane peptides.

Peptides corresponding to transmembrane (TM) segments from membrane proteins provide a potential route for the determination of membrane protein structure. We have determined that 2 functionally critical TM segments from the mammalian Na+/H+ exchanger display well converged structure in regions separated by break points. The flexibility of these break points results in conformational sampling in solution. A brief review of available NMR structures of helical membrane proteins demonstrates that there are a number of published structures showing similar properties. Such flexibility is likely indicative of kinks in the full-length protein. This minireview focuses on methods and protocols for NMR structure calculation and analysis of peptide structures under conditions of conformational sampling. The methods outlined allow the identification and analysis of structured peptides containing break points owing to conformational sampling and the differentiation between oligomerization and ensemble-averaged observation of multiple peptide conformations.     

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available.     

Predicting Protein Function and Binding Profile via Matching of Local Evolutionary and Geometric Surface Patterns

Inferring protein functions from structures is a challenging task, as a large number of orphan protein structures from structural genomics project are now solved without their biochemical functions characterized. For proteins binding to similar substrates or ligands and carrying out similar functions, their binding surfaces are under similar physicochemical constraints, and hence the sets of allowed and forbidden residue substitutions are similar. However, it is difficult to isolate such selection pressure due to protein function from selection pressure due to protein folding, and evolutionary relationship reflected by global sequence and structure similarities between proteins is often unreliable for inferring protein function. We have developed a method, called pevoSOAR (pocket-based evolutionary search of amino acid residues), for predicting protein functions by solving the problem of uncovering amino acids residue substitution pattern due to protein function and separating it from amino acids substitution pattern due to protein folding. We incorporate evolutionary information specific to an individual binding region and match local surfaces on a large scale with millions of precomputed protein surfaces to identify those with similar functions. Our pevoSOAR method also generates a probablistic model called the computed binding a profile that characterizes protein-binding activities that may involve multiple substrates or ligands. We show that our method can be used to predict enzyme functions with accuracy. Our method can also assess enzyme binding specificity and promiscuity. In an objective large-scale test of 100 enzyme families with thousands of structures, our predictions are found to be sensitive and specific: At the stringent specificity level of 99.98%, we can correctly predict enzyme functions for 80.55% of the proteins. The overall area under the receiver operating characteristic curve measuring the performance of our prediction is 0.955, close to the perfect value of 1.00. The best Matthews coefficient is 86.6%. Our method also works well in predicting the biochemical functions of orphan proteins from structural genomics projects.     

An Evolution-Based Approach to De Novo Protein Design and Case Study on Mycobacterium tuberculosis

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.     

Blind Test of Physics-Based Prediction of Protein Structures

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.     

Probabilistic sampling of protein conformations: New hope for brute force?

Protein structure prediction from sequence alone by "brute force" random methods is a computationally expensive problem. Estimates have suggested that it could take all the computers in the world longer than the age of the universe to compute the structure of a single 200-residue protein. Here we investigate the use of a faster version of our FOLDTRAJ probabilistic all-atom protein-structure-sampling algorithm. We have improved the method so that it is now over twenty times faster than originally reported, and capable of rapidly sampling conformational space without lattices. It uses geometrical constraints and a Leonard-Jones type potential for self-avoidance. We have also implemented a novel method to add secondary structure-prediction information to make protein-like amounts of secondary structure in sampled structures. In a set of 100,000 probabilistic conformers of 1VII, 1ENH, and 1PMC generated, the structures with smallest Calpha RMSD from native are 3.95, 5.12, and 5.95A, respectively. Expanding this test to a set of 17 distinct protein folds, we find that all-helical structures are "hit" by brute force more frequently than beta or mixed structures. For small helical proteins or very small non-helical ones, this approach should have a "hit" close enough to detect with a good scoring function in a pool of several million conformers. By fitting the distribution of RMSDs from the native state of each of the 17 sets of conformers to the extreme value distribution, we are able to estimate the size of conformational space for each. With a 0.5A RMSD cutoff, the number of conformers is roughly 2N where N is the number of residues in the protein. This is smaller than previous estimates, indicating an average of only two possible conformations per residue when sterics are accounted for. Our method reduces the effective number of conformations available at each residue by probabilistic bias, without requiring any particular discretization of residue conformational space, and is the fastest method of its kind. With computer speeds doubling every 18 months and parallel and distributed computing becoming more practical, the brute force approach to protein structure prediction may yet have some hope in the near future.     

The HPr proteins from the thermophile Bacillus stearothermophilus can form domain-swapped dimers

The study of proteins from extremophilic organisms continues to generate interest in the field of protein folding because paradigms explaining the enhanced stability of these proteins still elude us and such studies have the potential to further our knowledge of the forces stabilizing proteins. We have undertaken such a study with our model protein HPr from a mesophile, Bacillus subtilis, and a thermophile, Bacillus stearothermophilus. We report here the high-resolution structures of the wild-type HPr protein from the thermophile and a variant, F29W. The variant proved to crystallize in two forms: a monomeric form with a structure very similar to the wild-type protein as well as a domain-swapped dimer. Interestingly, the structure of the domain-swapped dimer for HPr is very different from that observed for a homologous protein, Crh, from B.subtilis. The existence of a domain-swapped dimer has implications for amyloid formation and is consistent with recent results showing that the HPr proteins can form amyloid fibrils. We also characterized the conformational stability of the thermophilic HPr proteins using thermal and solvent denaturation methods and have used the high-resolution structures in an attempt to explain the differences in stability between the different HPr proteins. Finally, we present a detailed analysis of the solution properties of the HPr proteins using a variety of biochemical and biophysical methods.