Engineering the kinetic stability of a ß-trefoil protein by tuning its topological complexity.

Kinetic stability, defined as the rate of protein unfolding, is central to determining the functional lifetime of proteins, both in nature and in wide-ranging medical and biotechnological applications. Further, high kinetic stability is generally correlated with high resistance against chemical and thermal denaturation, as well as proteolytic degradation. Despite its significance, specific mechanisms governing kinetic stability remain largely unknown, and few studies address the rational design of kinetic stability. Here, we describe a method for designing protein kinetic stability that uses protein long-range order, absolute contact order, and simulated free energy barriers of unfolding to quantitatively analyze and predict unfolding kinetics. We analyze two ß-trefoil proteins: hisactophilin, a quasi-three-fold symmetric natural protein with moderate stability, and ThreeFoil, a designed three-fold symmetric protein with extremely high kinetic stability. The quantitative analysis identifies marked differences in long-range interactions across the protein hydrophobic cores that partially account for the differences in kinetic stability. Swapping the core interactions of ThreeFoil into hisactophilin increases kinetic stability with close agreement between predicted and experimentally measured unfolding rates. These results demonstrate the predictive power of readily applied measures of protein topology for altering kinetic stability and recommend core engineering as a tractable target for rationally designing kinetic stability that may be widely applicable.

Immature ALS-associated mutant superoxide dismutases form variable aggregate structures through distinct oligomerization processes.

Protein misfolding and aggregation are hallmarks of many diseases, including amyotrophic lateral sclerosis (ALS). In familial ALS, aberrant self-association of mutant Cu,Zn-superoxide dismutase (SOD1) is implicated as a key contributor to disease. Mutations have the largest impacts on the stability of the most immature form of SOD1, the unmetallated, disulfide-reduced monomer (apoSH SOD1). Here we demonstrate that, despite the marginal stability of apoSH SOD1, aggregation is little correlated with the degree of protein unfolding, and multiple modes of aggregation occur, depending on the mutation and solution conditions. Light scattering and atomic force microscopy reveal two distinct mutant SOD1 behaviours: high aggregator mutants form abundant small assemblies, while low aggregator mutants form fewer, more fibre-like aggregates. Attenuated total reflectance-Fourier transform infrared spectroscopy and Thioflavin T binding show the aggregates maintain native-like anti-parallel beta structure. These results provide new evidence that ALS-associated mutations promote the aggregation of apoSH SOD1 through multiple pathways, with broad implications for understanding mechanisms of protein self-association in disease and biotechnology.

Methodological advances and strategies for high resolution structure determination of cellular protein aggregates.

Aggregation of proteins is at the nexus of molecular processes crucial to aging, disease, and employing proteins for biotechnology and medical applications. There has been much recent progress in determining the structural features of protein aggregates that form in cells; yet, owing to prevalent heterogeneity in aggregation, many aspects remain obscure and often experimentally intractable to define. Here, we review recent results of structural studies for cell-derived aggregates of normally globular proteins, with a focus on high-resolution methods for their analysis and prediction. Complementary results obtained by solid-state NMR spectroscopy, FTIR spectroscopy and microspectroscopy, cryo-EM, and amide hydrogen/deuterium exchange measured by NMR and mass spectrometry, applied to bacterial inclusion bodies and disease inclusions, are uncovering novel information on in-cell aggregation patterns as well as great diversity in the structural features of useful and aberrant protein aggregates. Using these advances as a guide, this review aims to advise the reader on which combination of approaches may be the most appropriate to apply to their unique system.

A fine balance of hydrophobic-electrostatic communication pathways in a pH-switching protein.

Allostery is the phenomenon of coupling between distal binding sites in a protein. Such coupling is at the crux of protein function and regulation in a myriad of scenarios, yet determining the molecular mechanisms of coupling networks in proteins remains a major challenge. Here, we report mechanisms governing pH-dependent myristoyl switching in monomeric hisactophilin, whereby the myristoyl moves between a sequestered state, i.e., buried within the core of the protein, to an accessible state, in which the myristoyl has increased accessibility for membrane binding. Measurements of the pH and temperature dependence of amide chemical shifts reveal protein local structural stability and conformational heterogeneity that accompany switching. An analysis of these measurements using a thermodynamic cycle framework shows that myristoyl-proton coupling at the single-residue level exists in a fine balance and extends throughout the protein. Strikingly, small changes in the stereochemistry or size of core and surface hydrophobic residues by point mutations readily break, restore, or tune myristoyl switch energetics. Synthesizing the experimental results with those of molecular dynamics simulations illuminates atomistic details of coupling throughout the protein, featuring a large network of hydrophobic interactions that work in concert with key electrostatic interactions. The simulations were critical for discerning which of the many ionizable residues in hisactophilin are important for switching and identifying the contributions of nonnative interactions in switching. The strategy of using temperature-dependent NMR presented here offers a powerful, widely applicable way to elucidate the molecular mechanisms of allostery in proteins at high resolution.

Quenched hydrogen-deuterium amide exchange optimization for high-resolution structural analysis of cellular protein aggregates.

Inclusion bodies (IBs) are large, insoluble aggregates that often form during the overexpression of proteins in bacteria. These aggregates are of broad fundamental and practical significance, for recombinant protein preparation and due to their relevance to aggregation-related medical conditions and their recent emergence as promising functional nanomaterials. Despite their significance, high resolution knowledge of IB structure remains very limited. Such knowledge will advance understanding and control of IB formation and properties in myriad practical applications. Here, we report a detailed quenched hydrogen-deuterium amide exchange (qHDX) method with NMR readout to define the structure of IBs at the level of individual residues throughout the protein. Applying proper control of experimental conditions, such as sample pH, water content, temperature, and intrinsic rate of amide exchange, yields in depth results for these cellular protein aggregates. qHDX results illustrated for Cu, Zn superoxide dismutase 1 (SOD1) and Adnectins show their IBs include native-like structure and some but not all mutations alter IB structure.

High-Resolution NMR H/D Exchange of Human Superoxide Dismutase Inclusion Bodies Reveals Significant Native Features Despite Structural Heterogeneity.

Protein aggregation is central to aging, disease and biotechnology. While there has been recent progress in defining structural features of cellular protein aggregates, many aspects remain unclear due to heterogeneity of aggregates presenting obstacles to characterization. Here we report high-resolution analysis of cellular inclusion bodies (IBs) of immature human superoxide dismutase (SOD1) mutants using NMR quenched amide hydrogen/deuterium exchange (qHDX), FTIR and Congo red binding. The extent of aggregation is correlated with mutant global stability and, notably, the free energy of native dimer dissociation, indicating contributions of native-like monomer associations to IB formation. This is further manifested by a common pattern of extensive protection against H/D exchange throughout nine mutant SOD1s despite their diverse characteristics. These results reveal multiple aggregation-prone regions in SOD1 and illuminate how aggregation may occur via an ensemble of pathways.

Design for Solubility May Reveal Induction of Amide Hydrogen/Deuterium Exchange by Protein Self-Association.

Structural heterogeneity often constrains the characterization of aggregating proteins to indirect or low-resolution methods, obscuring mechanistic details of association. Here, we report progress in understanding the aggregation of Adnectins, engineered binding proteins with an immunoglobulin-like fold. We rationally design Adnectin solubility and measure amide hydrogen/deuterium exchange (HDX) under conditions that permit transient protein self-association. Protein-protein binding commonly slows rates of HDX; in contrast, we find that Adnectin association may induce faster HDX for certain amides, particularly in the C-terminal ß-strand. In aggregation-prone proteins, we identify a pattern of very different rates of amide HDX for residues linked by reciprocal hydrogen bonds in the native structure. These results may be explained by local loss of native structure and formation of an inter-protein interface. Amide HDX induced by self-association, detected here by deliberate modulation of propensity for such interactions, may be a general phenomenon with the potential to expose mechanisms of aggregation by diverse proteins.

Wild-type and mutant SOD1 localizes to RNA-rich structures in cells and mice but does not bind RNA.

Many of the genes whose mutation causes Amyotrophic Lateral Sclerosis (ALS) are RNA-binding proteins which localize to stress granules, while others impact the assembly, stability, and elimination of stress granules. This has led to the hypothesis that alterations in the dynamics of stress granules and RNA biology cause ALS. Genetic mutations in Superoxide Dismutase 1 (SOD1) also cause ALS. Evidence demonstrates that SOD1 harboring ALS-linked mutations is recruited to stress granules, induces changes in alternative splicing, and could be an RNA-binding protein. Whether SOD1 inclusions contain RNA in disease models and whether SOD1 directly binds RNA remains uncertain. We applied methods including cross-linking immunoprecipitation and in vitro gel shift assays to detect binding of SOD1 to RNA in vitro, in cells with and without stress granules, and in mice expressing human SOD1 G93A. We find that SOD1 localizes to RNA-rich structures including stress granules, and SOD1 inclusions in mice contain mRNA. However, we find no evidence that SOD1 directly binds RNA. This suggests that SOD1 may impact stress granules, alternative splicing and RNA biology without binding directly to RNA.

Insight into the Autosomal-Dominant Inheritance Pattern of SOD1-Associated ALS from Native Mass Spectrometry.

About 20% of all familial amyotrophic lateral sclerosis (ALS) cases are associated with mutations in superoxide dismutase (SOD1), a homodimeric protein. The disease has an autosomal-dominant inheritance pattern. It is, therefore, important to determine whether wild-type and mutant SOD1 subunits self-associate randomly or preferentially. A measure for the extent of bias in subunit association is the coupling constant determined in a double-mutant cycle type analysis. Here, cell lysates containing co-expressed wild-type and mutant SOD1 subunits were analyzed by native mass spectrometry to determine these coupling constants. Strikingly, we find a linear positive correlation between the coupling constant and the reported average duration of the disease. Our results indicate that inter-subunit communication and a preference for heterodimerization greatly increase the disease severity.

Computational Modeling of Protein Stability: Quantitative Analysis Reveals Solutions to Pervasive Problems.

Accurate modeling of the effects of mutations on protein stability is central to understanding and controlling proteins in myriad natural and applied contexts. Here, we reveal through rigorous quantitative analysis that stability prediction tools often favor mutations that increase stability at the expense of solubility. Moreover, while these tools may accurately identify strongly destabilizing mutations, the experimental effect of mutations predicted to stabilize is actually near neutral on average. The commonly used "classification accuracy" metric obscures this reality; accordingly, we recommend performance measures, such as the Matthews correlation coefficient (MCC). We demonstrate that an absurdly simple machine-learning algorithm-a neural network of just two neurons-unexpectedly achieves high classification accuracy, but its inadequacies are revealed by a low MCC. Despite the above limitations, making multiple mutations markedly improves the prospects for achieving a stabilization target, and modest improvements in the precision of future tools may yield disproportionate gains.

TNF receptor-associated factor 6 interacts with ALS-linked misfolded superoxide dismutase 1 and promotes aggregation.

Amyotrophic lateral sclerosis (ALS) is a fatal disease, characterized by the selective loss of motor neurons leading to paralysis. Mutations in the gene encoding superoxide dismutase 1 (SOD1) are the second most common cause of familial ALS, and considerable evidence suggests that these mutations result in an increase in toxicity due to protein misfolding. We previously demonstrated in the SOD1G93A rat model that misfolded SOD1 exists as distinct conformers and forms deposits on mitochondrial subpopulations. Here, using SOD1G93A rats and conformation-restricted antibodies specific for misfolded SOD1 (B8H10 and AMF7-63), we identified the interactomes of the mitochondrial pools of misfolded SOD1. This strategy identified binding proteins that uniquely interacted with either AMF7-63 or B8H10-reactive SOD1 conformers as well as a high proportion of interactors common to both conformers. Of this latter set, we identified the E3 ubiquitin ligase TNF receptor-associated factor 6 (TRAF6) as a SOD1 interactor, and we determined that exposure of the SOD1 functional loops facilitates this interaction. Of note, this conformational change was not universally fulfilled by all SOD1 variants and differentiated TRAF6 interacting from TRAF6 noninteracting SOD1 variants. Functionally, TRAF6 stimulated polyubiquitination and aggregation of the interacting SOD1 variants. TRAF6 E3 ubiquitin ligase activity was required for the former but was dispensable for the latter, indicating that TRAF6-mediated polyubiquitination and aggregation of the SOD1 variants are independent events. We propose that the interaction between misfolded SOD1 and TRAF6 may be relevant to the etiology of ALS.

Temperature dependence of NMR chemical shifts: Tracking and statistical analysis.

Isotropic chemical shifts measured by solution nuclear magnetic resonance (NMR) spectroscopy offer extensive insights into protein structure and dynamics. Temperature dependences add a valuable dimension; notably, the temperature dependences of amide proton chemical shifts are valuable probes of hydrogen bonding, temperature-dependent loss of structure, and exchange between distinct protein conformations. Accordingly, their uses include structural analysis of both folded and disordered proteins, and determination of the effects of mutations, binding, or solution conditions on protein energetics. Fundamentally, these temperature dependences result from changes in the local magnetic environments of nuclei, but correlations with global thermodynamic parameters measured via calorimetric methods have been observed. Although the temperature dependences of amide proton and nitrogen chemical shifts are often well approximated by a linear model, deviations from linearity are also observed and may be interpreted as evidence of fast exchange between distinct conformational states. Here, we describe computational methods, accessible via the Shift-T web server, including an automated tracking algorithm that propagates initial (single temperature) 1 H15 N cross peak assignments to spectra collected over a range of temperatures. Amide proton and nitrogen temperature coefficients (slopes determined by fitting chemical shift vs. temperature data to a linear model) are subsequently calculated. Also included are methods for the detection of systematic, statistically significant deviation from linearity (curvature) in the temperature dependences of amide proton chemical shifts. The use and utility of these methods are illustrated by example, and the Shift-T web server is freely available at http://meieringlab.uwaterloo.ca/shiftt.

Spectrophotometric method for simultaneous measurement of zinc and copper in metalloproteins using 4-(2-pyridylazo)resorcinol.

Bound metals are observed in a great many natural proteins, where they perform diverse roles in determining protein folding, stability and function. Due to the broad impact of bound metals on biophysical and biochemical properties of proteins, it is valuable to have accurate and facile methods for determining the metal content of proteins. Here we describe an optimized methodology using 4-(2-pyridylazo)resorcinol (PAR) to simultaneously quantify two metal ions in solution. The assay is demonstrated for quantification of Cu2+ and Zn2+ ions in human Cu, Zn superoxide dismutases (SOD1s); however, the method is general and can be applied to various combinations of metal ions. Advantages of the assay are that it is rapid and inexpensive, requires little sample and preparation, and has simple data analysis. We show that spectral decomposition software can accurately resolve the absorption bands of Cu2+ and Zn2+ with high accuracy and precision. Using the PAR assay, we determined that metal binding is altered in disease-associated mutants of SOD1, with comparable results to those determined by ICP-AES. In addition, we highlight key issues for using spectrophotometric chelators such as PAR for metal analysis of proteins.

Effects of maturation on the conformational free-energy landscape of SOD1.

Amyotrophic lateral sclerosis (ALS) is a devastating fatal syndrome characterized by very rapid degeneration of motor neurons. A leading hypothesis is that ALS is caused by toxic protein misfolding and aggregation, as also occurs in many other neurodegenerative disorders, such as prion, Alzheimer's, Parkinson's, and Huntington's diseases. A prominent cause of familial ALS is mutations in the protein superoxide dismutase (SOD1), which promote the formation of misfolded SOD1 conformers that are prone to aberrant interactions both with each other and with other cellular components. We have shown previously that immature SOD1, lacking bound Cu and Zn metal ions and the intrasubunit disulfide bond (apoSOD12SH), has a rugged free-energy surface (FES) and exchanges with four other conformations (excited states) that have millisecond lifetimes and sparse populations on the order of a few percent. Here, we examine further states of SOD1 along its maturation pathway, as well as those off-pathway resulting from metal loss that have been observed in proteinaceous inclusions. Metallation and disulfide bond formation lead to structural transformations including local ordering of the electrostatic loop and native dimerization that are observed in rare conformers of apoSOD12SH; thus, SOD1 maturation may occur via a population-switch mechanism whereby posttranslational modifications select for preexisting structures on the FES. Metallation and oxidation of SOD1 stabilize the native, mature conformation and decrease the number of detected excited conformational states, suggesting that it is the immature forms of the protein that contribute to misfolded conformations in vivo rather than the highly stable enzymatically active dimer.

Computational tools help improve protein stability but with a solubility tradeoff.

Accurately predicting changes in protein stability upon amino acid substitution is a much sought after goal. Destabilizing mutations are often implicated in disease, whereas stabilizing mutations are of great value for industrial and therapeutic biotechnology. Increasing protein stability is an especially challenging task, with random substitution yielding stabilizing mutations in only ∼2% of cases. To overcome this bottleneck, computational tools that aim to predict the effect of mutations have been developed; however, achieving accuracy and consistency remains challenging. Here, we combined 11 freely available tools into a meta-predictor (meieringlab.uwaterloo.ca/stabilitypredict/). Validation against ∼600 experimental mutations indicated that our meta-predictor has improved performance over any of the individual tools. The meta-predictor was then used to recommend 10 mutations in a previously designed protein of moderate thermodynamic stability, ThreeFoil. Experimental characterization showed that four mutations increased protein stability and could be amplified through ThreeFoil's structural symmetry to yield several multiple mutants with >2-kcal/mol stabilization. By avoiding residues within functional ties, we could maintain ThreeFoil's glycan-binding capacity. Despite successfully achieving substantial stabilization, however, almost all mutations decreased protein solubility, the most common cause of protein design failure. Examination of the 600-mutation data set revealed that stabilizing mutations on the protein surface tend to increase hydrophobicity and that the individual tools favor this approach to gain stability. Thus, whereas currently available tools can increase protein stability and combining them into a meta-predictor yields enhanced reliability, improvements to the potentials/force fields underlying these tools are needed to avoid gaining protein stability at the cost of solubility.

Asymmetric Anchoring Is Required for Efficient Ω-Loop Opening and Closing in Cytosolic Phosphoenolpyruvate Carboxykinase.

Mobile Ω-loops play essential roles in the function of many enzymes. Here we investigated the importance of a residue lying outside of the mobile Ω-loop element in the catalytic function of an H477R variant of cytosolic phosphoenolpyruvate carboxykinase using crystallographic, kinetic, and computational analysis. The crystallographic data suggest that the efficient transition of the Ω-loop to the closed conformation requires stabilization of the N-terminus of the loop through contacts between R461 and E588. In contrast, the C-terminal end of the Ω-loop undergoes changing interactions with the enzyme body through contacts between H477 at the C-terminus of the loop and E591 located on the enzyme body. Potential of mean force calculations demonstrated that altering the anchoring of the C-terminus of the Ω-loop via the H477R substitution results in the destabilization of the closed state of the Ω-loop by 3.4 kcal mol-1. The kinetic parameters for the enzyme were altered in an asymmetric fashion with the predominant effect being observed in the direction of oxaloacetate synthesis. This is exemplified by a reduction in kcat for the H477R mutant by an order of magnitude in the direction of OAA synthesis, while in the direction of PEP synthesis, it decreased by a factor of only 2. The data are consistent with a mechanism for loop conformational exchange between open and closed states in which a balance between fixed anchoring of the N-terminus of the Ω-loop and a flexible, unattached C-terminus drives the transition between a disordered (open) state and an ordered (closed) state.

Exploring the relationships between protein sequence, structure and solubility.

Aggregation can be thought of as a form of protein folding in which intermolecular associations lead to the formation of large, insoluble assemblies. Various types of aggregates can be differentiated by their internal structures and gross morphologies (e.g., fibrillar or amorphous), and the ability to accurately predict the likelihood of their formation by a given polypeptide is of great practical utility in the fields of biology (including the study of disease), biotechnology, and biomaterials research. Here we review aggregation/solubility prediction methods and selected applications thereof. The development of increasingly sophisticated methods that incorporate knowledge of conformations possibly adopted by aggregating polypeptide monomers and predict the internal structure of aggregates is improving the accuracy of the predictions and continually expanding the range of applications.

Probing the free energy landscapes of ALS disease mutants of SOD1 by NMR spectroscopy.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that, in some cases, has been linked with mutations to the antioxidant metalloenzyme superoxide dismutase (SOD1). Although the mature form of this enzyme is highly stable and resistant to aggregation, the most immature form, lacking metal and a stabilizing intrasubunit disulfide bond, apoSOD12SH, is dynamic and hypothesized to be a major cause of toxicity in vivo. Previous solution NMR studies of wild-type apoSOD12SH have shown that the ground state interconverts with a series of sparsely populated and transiently formed conformers, some of which have aberrant nonnative structures. Here, we study seven disease mutants of apoSOD12SH and characterize their free energy landscapes as a first step in understanding the initial stages of disease progression and, more generally, to evaluate the plasticity of low-lying protein conformational states. The mutations lead to little change in the structures and dynamics of the ground states of the mutant proteins. By contrast, the numbers of low-lying excited states that are accessible to each of the disease mutants can vary significantly, with additional conformers accessed in some cases. Our study suggests that the diversity of these structures can provide alternate interaction motifs for different mutants, establishing additional pathways for new and often aberrant intra- and intermolecular contacts. Further, it emphasizes the potential importance of conformationally excited states in directing both folding and misfolding processes.

Using natural sequences and modularity to design common and novel protein topologies.

Protein design is still a challenging undertaking, often requiring multiple attempts or iterations for success. Typically, the source of failure is unclear, and scoring metrics appear similar between successful and failed cases. Nevertheless, the use of sequence statistics, modularity and symmetry from natural proteins, combined with computational design both at the coarse-grained and atomistic levels is propelling a new wave of design efforts to success. Here we highlight recent examples of design, showing how the wealth of natural protein sequence and topology data may be leveraged to reduce the search space and increase the likelihood of achieving desired outcomes.