The denatured state dictates the topology of two proteins with almost identical sequence but different native structure and function

Aromatic-aromatic interactions drive fold switch of GA95 and GB95 with three residue difference

Proteins typically adopt a single fold to carry out their function, but metamorphic proteins, with multiple folding states, defy this norm. Deciphering the mechanism of conformational interconversion of metamorphic proteins is challenging. Herein, we employed nuclear magnetic resonance (NMR), circular dichroism (CD), and all-atom molecular dynamics (MD) simulations to elucidate the mechanism of fold switching in proteins GA95 and GB95, which share 95% sequence homology. The results reveal that long-range interactions, especially aromatic π-π interactions involving residues F52, Y45, F30, and Y29, are critical for the protein switching from a 3α to a 4β + α fold. This study contributes to understanding how proteins with highly similar sequences fold into distinct conformations and may provide valuable insights into the protein folding code.

New GO-based measures in multiple network alignment

MOTIVATION

Protein-protein interaction (PPI) networks provide valuable insights into the function of biological systems. Aligning multiple PPI networks may expose relationships beyond those observable by pairwise comparisons. However, assessing the biological quality of multiple network alignments is a challenging problem.

RESULTS

We propose two new measures to evaluate the quality of multiple network alignments using functional information from Gene Ontology (GO) terms. When aligning multiple real PPI networks across species, we observe that both measures are highly correlated with objective quality indicators, such as common orthologs. Additionally, our measures strongly correlate with an alignment's ability to predict novel GO annotations, which is a unique advantage over existing GO-based measures.

AVAILABILITY AND IMPLEMENTATION

The scripts and the links to the raw and alignment data can be accessed at https://github.com/kimiayazdani/GO_Measures.git.

SANA: cross-species prediction of Gene Ontology GO annotations via topological network alignment

Topological network alignment aims to align two networks node-wise in order to maximize the observed common connection (edge) topology between them. The topological alignment of two protein-protein interaction (PPI) networks should thus expose protein pairs with similar interaction partners allowing, for example, the prediction of common Gene Ontology (GO) terms. Unfortunately, no network alignment algorithm based on topology alone has been able to achieve this aim, though those that include sequence similarity have seen some success. We argue that this failure of topology alone is due to the sparsity and incompleteness of the PPI network data of almost all species, which provides the network topology with a small signal-to-noise ratio that is effectively swamped when sequence information is added to the mix. Here we show that the weak signal can be detected using multiple stochastic samples of "good" topological network alignments, which allows us to observe regions of the two networks that are robustly aligned across multiple samples. The resulting network alignment frequency (NAF) strongly correlates with GO-based Resnik semantic similarity and enables the first successful cross-species predictions of GO terms based on topology-only network alignments. Our best predictions have an AUPR of about 0.4, which is competitive with state-of-the-art algorithms, even when there is no observable sequence similarity and no known homology relationship. While our results provide only a "proof of concept" on existing network data, we hypothesize that predicting GO terms from topology-only network alignments will become increasingly practical as the volume and quality of PPI network data increase.

On the current failure-but bright future-of topology-driven biological network alignment

Since the function of a protein is defined by its interaction partners, and since we expect similar interaction patterns across species, the alignment of protein-protein interaction (PPI) networks between species, based on network topology alone, should uncover functionally related proteins across species. Surprisingly, despite the publication of more than fifty algorithms aimed at performing PPI network alignment, few have demonstrated a statistically significant link between network topology and functional similarity, and none have demonstrated that orthologs can be recovered using network topology alone. We find that the major contributing factors to this surprising failure are: (i) edge densities in most currently available experimental PPI networks are demonstrably too low to expect topological network alignment to succeed; (ii) in the few cases where the edge densities are high enough, some measures of topological similarity easily uncover functionally similar proteins while others do not; and (iii) most network alignment algorithms to date perform poorly at optimizing even their own topological objective functions, hampering their ability to use topology effectively. We demonstrate that SANA-the Simulated Annealing Network Aligner-significantly outperforms existing aligners at optimizing their own objective functions, even achieving near-optimal solutions when the optimal solution is known. We offer the first demonstration of global network alignments based on topology alone that align functionally similar proteins with p-values in some cases below 10^-300. We predict that topological network alignment has a bright future as edge densities increase toward the value where good alignments become possible. We demonstrate that when enough common topology is present at high enough edge densities-for example in the recent, partly synthetic networks of the Integrated Interaction Database-topological network alignment easily recovers most orthologs, paving the way toward high-throughput functional prediction based on topology-driven network alignment.

The denatured state of HIV-1 protease under native conditions

The denatured state of several proteins has been shown to display transient structures that are relevant for folding, stability, and aggregation. To detect them by nuclear magnetic resonance (NMR) spectroscopy, the denatured state must be stabilized by chemical agents or changes in temperature. This makes the environment different from that experienced in biologically relevant processes. Using high‐resolution heteronuclear NMR spectroscopy, we have characterized several denatured states of a monomeric variant of HIV‐1 protease, which is natively structured in water, induced by different concentrations of urea, guanidinium chloride, and acetic acid. We have extrapolated the chemical shifts and the relaxation parameters to the denaturant‐free denatured state at native conditions, showing that they converge to the same values. Subsequently, we characterized the conformational properties of this biologically relevant denatured state under native conditions by advanced molecular dynamics simulations and validated the results by comparison to experimental data. We show that the denatured state of HIV‐1 protease under native conditions displays rich patterns of transient native and non‐native structures, which could be of relevance to its guidance through a complex folding process.

Exposing the distinctive modular behavior of β-strands and α-helices in folded proteins

Although folded proteins are commonly depicted as simplistic combinations of β-strands and α-helices, the actual properties and functions of these secondary-structure elements in their native contexts are just partly understood. The principal reason is that the behavior of individual β- and α-elements is obscured by the global folding cooperativity. In this study, we have circumvented this problem by designing frustrated variants of the mixed α/β-protein S6, which allow the structural behavior of individual β-strands and α-helices to be targeted selectively by stopped-flow kinetics, X-ray crystallography, and solution-state NMR. Essentially, our approach is based on provoking intramolecular "domain swap." The results show that the α- and β-elements have quite different characteristics: The swaps of β-strands proceed via global unfolding, whereas the α-helices are free to swap locally in the native basin. Moreover, the α-helices tend to hybridize and to promote protein association by gliding over to neighboring molecules. This difference in structural behavior follows directly from hydrogen-bonding restrictions and suggests that the protein secondary structure defines not only tertiary geometry, but also maintains control in function and structural evolution. Finally, our alternative approach to protein folding and native-state dynamics presents a generally applicable strategy for in silico design of protein models that are computationally testable in the microsecond-millisecond regime.

Shared unfolding pathways of unrelated immunoglobulin-like β-sandwich proteins

The Dynameomics project contains native state and unfolding simulations of 807 protein domains, where each domain is representative of a different metafold; these metafolds encompass ~97% of protein fold space. There is a long-standing question in structural biology as to whether proteins in the same fold family share the same folding/unfolding characteristics. Using molecular dynamics simulations from the Dynameomics project, we conducted a detailed study of protein unfolding/folding pathways for 5 protein domains from the immunoglobulin (Ig)-like β-sandwich metafold (the highest ranked metafold in our database). The domains have sequence similarities ranging from 4 to 15% and are all from different SCOP superfamilies, yet they share the same overall Ig-like topology. Despite having very different amino acid sequences, the dominant unfolding pathway is very similar for the 5 proteins, and the secondary structures that are peripheral to the aligned, shared core domain add variability to the unfolding pathway. Aligned residues in the core domain display consensus structure in the transition state primarily through conservation of hydrophobic positions. Commonalities in the obligate folding nucleus indicate that insights into the major events in the folding/unfolding of other domains from this metafold may be obtainable from unfolding simulations of a few representative proteins.

Recent advances in understanding catalysis of protein folding by molecular chaperones

Molecular chaperones are highly conserved proteins that promote proper folding of other proteins in vivo. Diverse chaperone systems assist de novo protein folding and trafficking, the assembly of oligomeric complexes, and recovery from stress-induced unfolding. A fundamental function of molecular chaperones is to inhibit unproductive protein interactions by recognizing and protecting hydrophobic surfaces that are exposed during folding or following proteotoxic stress. Beyond this basic principle, it is now clear that chaperones can also actively and specifically accelerate folding reactions in an ATP-dependent manner. We focus on the bacterial Hsp70 and chaperonin systems as paradigms, and review recent work that has advanced our understanding of how these chaperones act as catalysts of protein folding.

Visualizing Protein Folding and Unfolding

Protein folding/unfolding is a complicated process that defies high-resolution characterization by experimental methods. As an alternative, atomistic molecular dynamics simulations are now routinely employed to elucidate and magnify the accompanying conformational changes and the role of solvent in the folding process. However, the level of detail necessary to map the process at high spatial-temporal resolution provides an overwhelming amount of data. As more and better tools are developed for analysis of these large data sets and validation of the simulations, one is still left with the problem of visualizing the results in ways that provide insight into the folding/unfolding process. While viewing and interrogating static crystal structures has become commonplace, more and different approaches are required for dynamic, interconverting, unfolding, and refolding proteins. Here we review a variety of approaches, ranging from straightforward to complex and unintuitive for multiscale analysis and visualization of protein folding and unfolding.

Investigating the Molecular Basis of the Aggregation Propensity of the Pathological D76N Mutant of Beta-2 Microglobulin: Role of the Denatured State

Beta-2 microglobulin (β2m) is a protein responsible for a pathologic condition, known as dialysis-related amyloidosis (DRA), caused by its aggregation and subsequent amyloid formation. A naturally occurring mutation of β2m, D76N, presents a higher amyloidogenic propensity compared to the wild type counterpart. Since the three-dimensional structure of the protein is essentially unaffected by the mutation, the increased aggregation propensity of D76N has been generally ascribed to its lower thermodynamic stability and increased dynamics. In this study we compare the equilibrium unfolding and the aggregation propensity of wild type β2m and D76N variant at different experimental conditions. Our data revealed a surprising effect of the D76N mutation in the residual structure of the denatured state, which appears less compact than that of the wild type protein. A careful investigation of the structural malleability of the denatured state of wild type β2m and D76N pinpoint a clear role of the denatured state in triggering the amyloidogenic propensity of the protein. The experimental results are discussed in the light of the previous work on β2m and its role in disease.

The Folding Pathway of the KIX Domain

The KIX domain is an 89-residues globular domain with an important role in mediating protein-protein interactions. The presence of two distinct binding sites in such a small domain makes KIX a suitable candidate to investigate the effect of the potentially divergent demands between folding and function. Here, we report an extensive mutational analysis of the folding pathway of the KIX domain, based on 30 site-directed mutants, which allow us to assess the structures of both the transition and denatured states. Data reveal that, while the transition state presents mostly native-like interactions, the denatured state is somewhat misfolded. We mapped some of the non-native contacts in the denatured state using a second round of mutagenesis, based on double mutant cycles on 15 double mutants. Interestingly, such a misfolding arises from non-native interactions involving the residues critical for the function of the protein. The results described in this work appear to highlight the diverging demands between folding and function that may lead to misfolding, which may be observed in the early stages of folding.

The Dynameomics Entropy Dictionary: A Large-Scale Assessment of Conformational Entropy across Protein Fold Space

Molecular dynamics (MD) simulations contain considerable information with regard to the motions and fluctuations of a protein, the magnitude of which can be used to estimate conformational entropy. Here we survey conformational entropy across protein fold space using the Dynameomics database, which represents the largest existing data set of protein MD simulations for representatives of essentially all known protein folds. We provide an overview of MD-derived entropies accounting for all possible degrees of dihedral freedom on an unprecedented scale. Although different side chains might be expected to impose varying restrictions on the conformational space that the backbone can sample, we found that the backbone entropy and side chain size are not strictly coupled. An outcome of these analyses is the Dynameomics Entropy Dictionary, the contents of which have been compared with entropies derived by other theoretical approaches and experiment. As might be expected, the conformational entropies scale linearly with the number of residues, demonstrating that conformational entropy is an extensive property of proteins. The calculated conformational entropies of folding agree well with previous estimates. Detailed analysis of specific cases identifies deviations in conformational entropy from the average values that highlight how conformational entropy varies with sequence, secondary structure, and tertiary fold. Notably, α-helices have lower entropy on average than do β-sheets, and both are lower than coil regions.

Insights from molecular dynamics simulations for computational protein design

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Insights into Unfolded Proteins from the Intrinsic ϕ/ψ Propensities of the AAXAA Host-Guest Series

Various host-guest peptide series are used by experimentalists as reference conformational states. One such use is as a baseline for random-coil NMR chemical shifts. Comparison to this random-coil baseline, through secondary chemical shifts, is used to infer protein secondary structure. The use of these random-coil data sets rests on the perception that the reference chemical shifts arise from states where there is little or no conformational bias. However, there is growing evidence that the conformational composition of natively and nonnatively unfolded proteins fail to approach anything that can be construed as random coil. Here, we use molecular dynamics simulations of an alanine-based host-guest peptide series (AAXAA) as a model of unfolded and denatured states to examine the intrinsic propensities of the amino acids. We produced ensembles that are in good agreement with the experimental NMR chemical shifts and confirm that the sampling of the 20 natural amino acids in this peptide series is be far from random. Preferences toward certain regions of conformational space were both present and dependent upon the environment when compared under conditions typically used to denature proteins, i.e., thermal and chemical denaturation. Moreover, the simulations allowed us to examine the conformational makeup of the underlying ensembles giving rise to the ensemble-averaged chemical shifts. We present these data as an intrinsic backbone propensity library that forms part of our Structural Library of Intrinsic Residue Propensities to inform model building, to aid in interpretation of experiment, and for structure prediction of natively and nonnatively unfolded states.

Activation Barrier-Limited Folding and Conformational Sampling of a Dynamic Protein Domain

Folding reaction mechanisms of globular protein domains have been extensively studied by both experiment and simulation and found to be highly concerted chemical reactions in which numerous noncovalent bonds form in an apparent two-state fashion. However, less is known regarding intrinsically disordered proteins because their folding can usually be studied only in conjunction with binding to a ligand. We have investigated by kinetics the folding mechanism of such a disordered protein domain, the nuclear coactivator-binding domain (NCBD) from CREB-binding protein. While a previous computational study suggested that NCBD folds without an activation free energy barrier, our experimental data demonstrate that NCBD, despite its highly dynamic structure, displays relatively slow folding (∼10 ms at 277 K) consistent with a barrier-limited process. Furthermore, the folding kinetics corroborate previous nuclear magnetic resonance data showing that NCBD exists in two folded conformations and one more denatured conformation at equilibrium and, thus, that the folding mechanism is a three-state mechanism. The refolding kinetics is limited by unfolding of the less populated folded conformation, suggesting that the major route for interconversion between the two folded states is via the denatured state. Because the two folded conformations have been suggested to bind distinct ligands, our results have mechanistic implications for conformational sampling in protein-protein interactions.

Molecular dynamics simulations on the conformational transitions from the GA 98 (GA 88) to GB 98 (GB 88) proteins

We performed conventional and targeted molecular dynamics simulations to address the dynamic transition mechanisms of the conformational transitions from the G_A 98 protein with only 1 mutation of Leu45Tyr to G_B 98 and from the G_A 88 protein with 7 mutations of Gly24Ala, Ile25Thr, Ile30Phe, Ile33Tyr, Leu45Tyr, Ile49Thr, and Leu50Lys to G_B 88. The results show that the conformational transition mechanism from the mutated 3α G_A 98 (G_A 88) state to the α+4β G_B 98 (G_B 88) state via several intermediate conformations involves the bending of loops at the N and C termini firstly, the unfolding of αA and αC, then the traversing of αB, and the formation of the 4β layer with the conversion of the hydrophobic core. The bending of loops at the N and C termini and the formation of the crucial transition conformation with the full unfolded structure are key factors in their transition processes. The communication of the interaction network, the bending directions of loops, and the traversing site of αB in the transition of G_A 98 to G_B 98 are markedly different from those in G_A 88 to G_B 88 because of the different mutated residues. The analysis of the correlations and the calculated mass center distances between some segments further supported their conformational transition mechanisms. These results could help people to better understand the Paracelsus challenge. Copyright © 2016 John Wiley & Sons, Ltd.

Theoretical Insights into the Biophysics of Protein Bi-stability and Evolutionary Switches

Deciphering the effects of nonsynonymous mutations on protein structure is central to many areas of biomedical research and is of fundamental importance to the study of molecular evolution. Much of the investigation of protein evolution has focused on mutations that leave a protein’s folded structure essentially unchanged. However, to evolve novel folds of proteins, mutations that lead to large conformational modifications have to be involved. Unraveling the basic biophysics of such mutations is a challenge to theory, especially when only one or two amino acid substitutions cause a large-scale conformational switch. Among the few such mutational switches identified experimentally, the one between the G_A all-α and G_B α+β folds is extensively characterized; but all-atom simulations using fully transferrable potentials have not been able to account for this striking switching behavior. Here we introduce an explicit-chain model that combines structure-based native biases for multiple alternative structures with a general physical atomic force field, and apply this construct to twelve mutants spanning the sequence variation between G_A and G_B. In agreement with experiment, we observe conformational switching from G_A to G_B upon a single L45Y substitution in the GA98 mutant. In line with the latent evolutionary potential concept, our model shows a gradual sequence-dependent change in fold preference in the mutants before this switch. Our analysis also indicates that a sharp G_A/G_B switch may arise from the orientation dependence of aromatic π-interactions. These findings provide physical insights toward rationalizing, predicting and designing evolutionary conformational switches.

The biological functions of globular proteins are intimately related to their folded structures and their associated conformational fluctuations. Evolution of new structures is an important avenue to new functions. Although many mutations do not change the folded state, experiments indicate that a single amino acid substitution can lead to a drastic change in the folded structure. The physics of this switch-like behavior remains to be elucidated. Here we develop a computational model for the relevant physical forces, showing that mutations can lead to new folds by passing through intermediate sequences where the old and new folds occur with varying probabilities. Our approach helps provide a general physical account of conformational switching in evolution and mutational effects on conformational dynamics.

Studying protein fold evolution with hybrids of differently folded homologs

To study the sequence determinants governing protein fold evolution, we generated hybrid sequences from two homologous proteins with 40% identity but different folds: Pfl 6 Cro, which has a mixed α + β structure, and Xfaso 1 Cro, which has an all α-helical structure. First, we first examined eight chimeric hybrids in which the more structurally conserved N-terminal half of one protein was fused to the more structurally divergent C-terminal half of the other. None of these chimeras folded, as judged by circular dichroism spectra and thermal melts, suggesting that both halves have strong intrinsic preferences for the native global fold pattern, and/or that the interfaces between the halves are not readily interchangeable. Second, we examined 10 hybrids in which blocks of the structurally divergent C-terminal region were exchanged. These hybrids showed varying levels of thermal stability and suggested that the key residues in the Xfaso 1 C terminus specifying the all-α fold were concentrated near the end of helix 4 in Xfaso 1, which aligns to the end of strand 2 in Pfl 6. Finally, we generated hybrid substitutions for each individual residue in this critical region and measured thermal stabilities. The results suggested that R47 and V48 were the strongest factors that excluded formation of the α + β fold in the C-terminal region of Xfaso 1. In support of this idea, we found that the folding stability of one of the original eight chimeras could be rescued by back-substituting these two residues. Overall, the results show not only that the key factors for Cro fold specificity and evolution are global and multifarious, but also that some all-α Cro proteins have a C-terminal subdomain sequence within a few substitutions of switching to the α + β fold.

Better theoretical models and protein design experiments can help to understand protein folding

In our study, we have concluded that two proteins with 88% homology choose different energetically favorable pathways in the very early stage of the folding process to attain their native folds. Subsequent reports from other investigators by performing folding and unfolding kinetics experiments concur with our findings. We herewith discuss the key papers revealing computational and experimental analysis of two designed proteins with similar sequence distant folds. Further we suggest that the theoretical/computational analysis of protein sequences and structures along with the relevant experiments provide a better understanding of the relationship between protein sequence, folding, and structure.

Proteinquakes in the Evolution of Influenza Virus Hemagglutinin (A/H1N1) under Opposing Migration and Vaccination Pressures

Influenza virus contains two highly variable envelope glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Here we show that, while HA evolution is much more complex than NA evolution, it still shows abrupt punctuation changes linked to punctuation changes of NA. HA exhibits proteinquakes, which resemble earthquakes and are related to hydropathic shifting of sialic acid binding regions. HA proteinquakes based on shifting sialic acid interactions are required for optimal balance between the receptor-binding and receptor-destroying activities of HA and NA for efficient virus replication. Our comprehensive results present a historical (1945–2011) panorama of HA evolution over thousands of strains and are consistent with many studies of HA and NA interactions based on a few mutations of a few strains.

The kinetics of folding of frataxin

The role of the denatured state in protein folding represents a key issue for the proper evaluation of folding kinetics and mechanisms. The yeast ortholog of the human frataxin, a mitochondrial protein essential for iron homeostasis and responsible for Friedreich's ataxia, has been shown to undergo cold denaturation above 0 °C, in the absence of chemical denaturants. This interesting property provides the unique opportunity to explore experimentally the molecular mechanism of both the hot and cold denaturation. In this work, we present the characterization of the temperature and urea dependence of the folding kinetics of yeast frataxin, and show that while at neutral pH and in the absence of a denaturant a simple two-state model may satisfactorily describe the temperature dependence of the folding and unfolding rate constants, the results obtained in urea over a wide range of pH reveal an intriguing complexity, suggesting that folding of frataxin involves a broad smooth free energy barrier.

The folding pathway of a functionally competent C-terminal domain of nucleophosmin: protein stability and denatured state residual structure

Nucleophosmin (NPM1) is a nucleolar protein implicated in ribosome biogenesis, centrosome duplication and cell cycle control; the NPM1 gene is the most frequent target for mutations in Acute Myeloid Leukemia. Mutations map to the C-terminal domain of the protein and cause its unfolding, loss of DNA binding properties and aberrant cellular localization. Here we investigate the folding pathway and denatured state properties of a NPM1 C-terminal domain construct encompassing the last 70 residues in the reference sequence. This construct is more stable than the previously characterized domain, which consisted of the last 53 residues. Data reveal that, similarly to what was discovered for the shorter construct, also the 70-residue construct of NPM1 displays a detectable residual structure in its denatured state. The higher stability of the latter domain allows us to conclude that the denatured state is robust to changes in solvent composition and that it consists of a discrete state in equilibrium with the expanded fully unfolded conformation. This observation, which might appear as a technicality, is in fact of general importance for the understanding of the folding of proteins. The implications of our results are discussed in the context of previous works on single domain helical proteins.

HASH: a program to accurately predict protein Hα shifts from neighboring backbone shifts

Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H(α) chemical shifts suffer from the following limitations. (1) For large proteins, the H(α) chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C(α) that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H(α) chemical shifts. Predicting accurate H(α) chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called HASH, to predict H(α) chemical shifts. HASH combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H(α) chemical shifts. Our testing results on different possible combinations of input data indicate that HASH has a wide rage of potential NMR applications in structural and biological studies of proteins.

Take home lessons from studies of related proteins

The 'Fold Approach' involves a detailed analysis of the folding of several topologically, structurally and/or evolutionarily related proteins. Such studies can reveal determinants of the folding mechanism beyond the gross topology, and can dissect the residues required for folding from those required for stability or function. While this approach has not yet matured to the point where we can predict the native conformation of any polypeptide chain in silico, it has been able to highlight, amongst others, the specific residues that are responsible for nucleation, pathway malleability, kinetic intermediates, chain knotting, internal friction and Paracelsus switches. Some of the most interesting discoveries have resulted from the attempt to explain differences between homologues.

Designing redox potential-controlled protein switches based on mutually exclusive proteins

Synthetic/artificial protein switches provide an efficient means of controlling protein functions using chemical signals and stimuli. Mutually exclusive proteins, in which only the host or guest domain can remain folded at a given time owing to conformational strain, have been used to engineer novel protein switches that can switch enzymatic functions on and off in response to ligand binding. To further explore the potential of mutually exclusive proteins as protein switches and sensors, we report here a new redox-based approach to engineer a mutually exclusive folding-based protein switch. By introducing a disulfide bond into the host domain of a mutually exclusive protein, we demonstrate that it is feasible to use redox potential to switch the host domain between its folded and unfolded conformations via the mutually exclusive folding mechanism, and thus switching the functionality of the host domain on and off. Our study opens a new and potentially general avenue that uses mutually exclusive proteins to design novel switches able to control the function of a variety of proteins.

Folding pathways of proteins with increasing degree of sequence identities but different structure and function

Much experimental work has been devoted in comparing the folding behavior of proteins sharing the same fold but different sequence. The recent design of proteins displaying very high sequence identities but different 3D structure allows the unique opportunity to address the protein-folding problem from a complementary perspective. Here we explored by Φ-value analysis the pathways of folding of three different heteromorphic pairs, displaying increasingly high-sequence identity (namely, 30%, 77%, and 88%), but different structures called G(A) (a 3-α helix fold) and G(B) (an α/β fold). The analysis, based on 132 site-directed mutants, is fully consistent with the idea that protein topology is committed very early along the pathway of folding. Furthermore, data reveals that when folding approaches a perfect two-state scenario, as in the case of the G(A) domains, the structural features of the transition state appear very robust to changes in sequence composition. On the other hand, when folding is more complex and multistate, as for the G(B)s, there are alternative nuclei or accessible pathways that can be alternatively stabilized by altering the primary structure. The implications of our results in the light of previous work on the folding of different members belonging to the same protein family are discussed.

Tryptophan stabilizes His-heme loops in the denatured state only when it is near a loop end

We use a host-guest approach to evaluate the effect of Trp guest residues relative to Ala on the kinetics and thermodynamics of formation of His-heme loops in the denatured state of iso-1-cytochrome c at 1.5, 3.0, and 6.0 M guanidine hydrochloride (GdnHCl). Trp guest residues are inserted into an alanine-rich segment placed after a unique His near the N-terminus of iso-1-cytochrome c. Trp guest residues are either 4 or 10 residues from the His end of the 28-residue loop. We find the guest Trp stabilizes the His-heme loop at all GdnHCl concentrations when it is the 4th, but not the 10th, residue from the His end of the loop. Thus, residues near loop ends are most important in developing topological constraints in the denatured state that affect protein folding. In 1.5 M GdnHCl, the loop stabilization is ~0.7 kcal/mol, providing a thermodynamic rationale for the observation that Trp often mediates residual structure in the denatured state. Measurement of loop breakage rate constants, k(b,His), indicates that loop stabilization by the Trp guest residues occurs completely after the transition state for loop formation in 6.0 M GdnHCl. Under poorer solvent conditions, approximately half of the stabilization of the loop develops in the transition state, consistent with contacts in the denatured state being energetically downhill and providing evidence for funneling even near the rim of the folding funnel.

Conformational properties of the unfolded state of Im7 in nondenaturing conditions

The unfolded ensemble in aqueous solution represents the starting point of protein folding. Characterisation of this species is often difficult since the native state is usually predominantly populated at equilibrium. Previous work has shown that the four-helix protein, Im7 (immunity protein 7), folds via an on-pathway intermediate. While the transition states and folding intermediate have been characterised in atomistic detail, knowledge of the unfolded ensemble under the same ambient conditions remained sparse. Here, we introduce destabilising amino acid substitutions into the sequence of Im7, such that the unfolded state becomes predominantly populated at equilibrium in the absence of denaturant. Using far- and near-UV CD, fluorescence, urea titration and heteronuclear NMR experiments, we show that three amino acid substitutions (L18A-L19A-L37A) are sufficient to prevent Im7 folding, such that the unfolded state is predominantly populated at equilibrium. Using measurement of chemical shifts, (15)N transverse relaxation rates and sedimentation coefficients, we show that the unfolded species of L18A-L19A-L37A deviates significantly from random-coil behaviour. Specifically, we demonstrate that this unfolded species is compact (R(h)=25 Å) relative to the urea-denatured state (R(h)≥30 Å) and contains local clusters of hydrophobic residues in regions that correspond to the four helices in the native state. Despite these interactions, there is no evidence for long-range stabilising tertiary interactions or persistent helical structure. The results reveal an unfolded ensemble that is conformationally restricted in regions of the polypeptide chain that ultimately form helices I, II and IV in the native state.

Residual structure in unfolded proteins

The denatured state ensemble (DSE) of unfolded proteins, once considered to be well-modeled by an energetically featureless random coil, is now well-known to contain flickering elements of residual structure. The position and nature of DSE residual structure may provide clues toward deciphering the protein folding code. This review focuses on recent advances in our understanding of the nature of DSE collapse under folding conditions, the quantification of the stability of residual structure in the DSE, the determination of the location and types of residues involved in thermodynamically significant residual structure and advances in detection of long-range interactions in the DSE.