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.

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.

Designed protein reveals structural determinants of extreme kinetic stability.

The design of stable, functional proteins is difficult. Improved design requires a deeper knowledge of the molecular basis for design outcomes and properties. We previously used a bioinformatics and energy function method to design a symmetric superfold protein composed of repeating structural elements with multivalent carbohydrate-binding function, called ThreeFoil. This and similar methods have produced a notably high yield of stable proteins. Using a battery of experimental and computational analyses we show that despite its small size and lack of disulfide bonds, ThreeFoil has remarkably high kinetic stability and its folding is specifically chaperoned by carbohydrate binding. It is also extremely stable against thermal and chemical denaturation and proteolytic degradation. We demonstrate that the kinetic stability can be predicted and modeled using absolute contact order (ACO) and long-range order (LRO), as well as coarse-grained simulations; the stability arises from a topology that includes many long-range contacts which create a large and highly cooperative energy barrier for unfolding and folding. Extensive data from proteomic screens and other experiments reveal that a high ACO/LRO is a general feature of proteins with strong resistances to denaturation and degradation. These results provide tractable approaches for predicting resistance and designing proteins with sufficient topological complexity and long-range interactions to accommodate destabilizing functional features as well as withstand chemical and proteolytic challenge.

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.

Nonnative interactions regulate folding and switching of myristoylated protein.

We present an integrated experimental and computational study of the molecular mechanisms by which myristoylation affects protein folding and function, which has been little characterized to date. Myristoylation, the covalent linkage of a hydrophobic C14 fatty acyl chain to the N-terminal glycine in a protein, is a common modification that plays a critical role in vital regulated cellular processes by undergoing reversible energetic and conformational switching. Coarse-grained folding simulations for the model pH-dependent actin- and membrane-binding protein hisactophilin reveal that nonnative hydrophobic interactions of the myristoyl with the protein as well as nonnative electrostatic interactions have a pronounced effect on folding rates and thermodynamic stability. Folding measurements for hydrophobic residue mutations of hisactophilin and atomistic simulations indicate that the nonnative interactions of the myristoyl group in the folding transition state are nonspecific and robust, and so smooth the energy landscape for folding. In contrast, myristoyl interactions in the native state are highly specific and tuned for sensitive control of switching functionality. Simulations and amide hydrogen exchange measurements provide evidence for increases as well as decreases in stability localized on one side of the myristoyl binding pocket in the protein, implicating strain and altered dynamics in switching. The effects of folding and function arising from myristoylation are profoundly different from the effects of other post-translational modifications.

Energetics of oligomeric protein folding and association.

In nature, proteins most often exist as complexes, with many of these consisting of identical subunits. Understanding of the energetics governing the folding and misfolding of such homooligomeric proteins is central to understanding their function and misfunction, in disease or biotechnology. Much progress has been made in defining the mechanisms and thermodynamics of homooligomeric protein folding. In this review, we outline models as well as calorimetric and spectroscopic methods for characterizing oligomer folding, and describe extensive results obtained for diverse proteins, ranging from dimers to octamers and higher order aggregates. To our knowledge, this area has not been reviewed comprehensively in years, and the collective progress is impressive. The results provide evolutionary insights into the development of subunit interfaces, mechanisms of oligomer folding, and contributions of oligomerization to protein stability, function and regulation. Thermodynamic analyses have also proven valuable for understanding protein misfolding and aggregation mechanisms, suggesting new therapeutic avenues. Successful recent designs of novel, functional proteins demonstrate increased understanding of oligomer folding. Further rigorous analyses using multiple experimental and computational approaches are still required, however, to achieve consistent and accurate prediction of oligomer folding energetics. Modeling the energetics remains challenging but is a promising avenue for future advances.

On the analytical representation of free energy profiles with a Morse/long-range model: application to the water dimer.

We investigate the analytical representation of potentials of mean force (pmf) using the Morse/long-range (MLR) potential approach. The MLR method had previously been used to represent potential energy surfaces, and we assess its validity for representing free-energies. The advantage of the approach is that the potential of mean force data only needs to be calculated in the short to medium range region of the reaction coordinate while the long range can be handled analytically. This can result in significant savings in terms of computational effort since one does not need to cover the whole range of the reaction coordinate during simulations. The water dimer with rigid monomers whose interactions are described by the commonly used TIP4P model [W. Jorgensen and J. Madura, Mol. Phys. 56, 1381 (1985)] is used as a test case. We first calculate an "exact" pmf using direct Monte Carlo (MC) integration and term such a calculation as our gold standard (GS). Second, we compare this GS with several MLR fits to the GS to test the validity of the fitting procedure. We then obtain the water dimer pmf using metadynamics simulations in a limited range of the reaction coordinate and show how the MLR treatment allows the accurate generation of the full pmf. We finally calculate the transition state theory rate constant for the water dimer dissociation process using the GS, the GS MLR fits, and the metadynamics MLR fits. Our approach can yield a compact, smooth, and accurate analytical representation of pmf data with reduced computational cost.

Kinetic stability of the streptavidin-biotin interaction enhanced in the gas phase.

Results of the first detailed study of the structure and kinetic stability of the model high-affinity protein-ligand interaction between biotin (B) and the homotetrameric protein complex streptavidin (S(4)) in the gas phase are described. Collision cross sections (Ω) measured for protonated gaseous ions of free and ligand-bound truncated (residues 13-139) wild-type (WT) streptavidin, i.e., S(4)(n+) and (S(4)+4B)(n+) at charge states n = 12-16, were found to be independent of charge state and in agreement (within 10%) with values estimated for crystal structures reported for S(4) and (S(4)+4B). These results suggest that significant structural changes do not occur upon transfer of the complexes from solution to the gas phase by electrospray ionization. Temperature-dependent rate constants were measured for the loss of B from the protonated (S(4)+4B)(n+) ions. Over the temperature range investigated, the kinetic stability increases with decreasing charge state, from n = 16 to 13, but is indistinguishable for n = 12 and 13. A comparison of the activation energies (E(a)) measured for the loss of B from the (S(4)+4B)(13+) ions composed of WT streptavidin and five binding site mutants (Trp79Phe, Trp108Phe, Trp120Phe, Ser27Ala, and Tyr43Ala) suggests that at least some of the specific intermolecular interactions are preserved in the gas phase. The results of molecular dynamics simulations performed on WT (S(4)+4B)(12+) ions with different charge configurations support this conclusion. The most significant finding of this study is that the gaseous WT (S(4)+4B)(n+) ions at n = 12-14, owing to a much larger E(a) (by as much as 13 kcal mol(-1)) for the loss of B, are dramatically more stable kinetically at 25 °C than the (S(4)+4B) complex in aqueous neutral solution. The differences in E(a) values measured for the gaseous (S(4)+4B)(n+) ions and solvated (S(4)+4B) complex can be largely accounted for by a late dissociative transition state and the rehydration of B and the protein binding cavity in solution.

Personalized oncology and BRAFK601N melanoma: model development, drug discovery, and clinical correlation.

PURPOSE: Mutations in BRAF are the most prominent activating mutations in melanoma and are increasingly recognized in other cancers. There is currently no accepted treatment regimen for patients with mutant BRAFK601N melanoma, and the study of melanoma driven by BRAF mutations at the 601 locus is lacking due to a paucity of cellular model systems. Therefore, we sought to better understand the treatment and clinical approach to patients with mutant BRAFK601N melanoma and subsequently develop a novel personalized oncology platform for rare or treatment-refractory cancers. METHODS: We developed and characterized the first patient-derived, naturally occurring BRAFK601N melanoma model, described herein as OHRI-MEL-13, and assessed efficacy using the Prestwick Chemical Library and select targeted therapeutics. RESULTS: OHRI-MEL-13 exhibits loss of heterozygosity of BRAF, closely mimics the original tumor's gene expression profile, is tumorigenic in immune-deficient murine models, and is available for public accession through American Type Culture Collection. We present in silico modeling data, which illustrates the therapeutic failure of BRAFV600E-targeted therapies in BRAFK601N mutants. Our platform elucidated a unique role for MEK inhibition with cobimetinib, which resulted in short-term clinical success by reducing the metastatic burden. CONCLUSION: Our model of BRAFK601N-activated melanoma was developed, thoroughly characterized, and made available for public accession. This model served to demonstrate the feasibility of a novel personalized oncology platform that could be optimized at an institutional level for rare variant or treatment-refractory cancers. We also demonstrate the clinical utility of monotherapy MEK inhibition in a case of BRAFK601N melanoma.

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.

Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico.

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (kcat/KM 146 M-1s-1). We observe that catalytic residues are increasingly rigidified, the active site becomes better pre-organized, and its entrance is widened. Based on these observations, we engineer HG4, an efficient biocatalyst (kcat/KM 103,000 M-1s-1) containing key first and second-shell mutations found during evolution. HG4 structures reveal that its active site is pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

Folding and association of thermophilic dimeric and trimeric DsrEFH proteins: Tm0979 and Mth1491.

Although the majority of natural proteins exist as protein-protein complexes, the molecular basis for the formation and regulation of such interactions and the evolution of protein interfaces remain poorly understood. We have investigated these phenomena by characterizing the thermal and chemical denaturation of thermophilic DsrEFH proteins that have a common subunit fold but distinct quaternary structures: homodimeric Tm0979 and homotrimeric Mth1491. Tm0979 forms a moderate affinity dimer, and a monomeric intermediate is readily populated at equilibrium and during folding kinetics. In contrast, the Mth1491 trimer has extremely high stability, so that a monomeric form is not measurably populated at equilibrium, although it may be during folding kinetics. A common mechanism for evolution of quaternary structures may be facile formation of a relatively stable monomeric species, with stabilizing intermolecular interactions centering on alternative environments for a beta-strand at the edge of the monomer, augmented by malleable hydrophobic interactions. The exceptional trimer stability arises from a remarkably slow unfolding rate constant, 6.5 x 10(-13) s(-1), which is a common characteristic of highly stable thermophilic and/or oligomeric proteins. The folding characteristics of Tm0979 and Mth1491 have interesting implications for assembly and regulation of homo- and heterooligomeric proteins in vivo.

Origin of conformational dynamics in a globular protein.

Protein structures are dynamic, undergoing motions that can play a vital role in function. However, the link between primary sequence and conformational dynamics remains poorly understood. Here, we studied how conformational dynamics can arise in a globular protein by evaluating the impact of individual core-residue substitutions in DANCER-3, a streptococcal protein G domain ß1 variant that we previously designed to undergo a specific mode of conformational exchange that has never been observed in the wild-type protein. Using a combination of solution NMR experiments and molecular dynamics simulations, we demonstrate that only two mutations are necessary to create this conformational exchange, and that these mutations work synergistically, with one destabilizing the native structure and the other allowing two new conformational states to be accessed on the energy landscape. Overall, our results show how dynamics can appear in a stable globular fold, a critical step in the molecular evolution of dynamics-linked functions.

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.

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.

Protein unfolding rates correlate as strongly as folding rates with native structure.

Although the folding rates of proteins have been studied extensively, both experimentally and theoretically, and many native state topological parameters have been proposed to correlate with or predict these rates, unfolding rates have received much less attention. Moreover, unfolding rates have generally been thought either to not relate to native topology in the same manner as folding rates, perhaps depending on different topological parameters, or to be more difficult to predict. Using a dataset of 108 proteins including two-state and multistate folders, we find that both unfolding and folding rates correlate strongly, and comparably well, with well-established measures of native topology, the absolute contact order and the long range order, with correlation coefficient values of 0.75 or higher. In addition, compared to folding rates, the absolute values of unfolding rates vary more strongly with native topology, have a larger range of values, and correlate better with thermodynamic stability. Similar trends are observed for subsets of different protein structural classes. Taken together, these results suggest that choosing a scaffold for protein engineering may require a compromise between a simple topology that will fold sufficiently quickly but also unfold quickly, and a complex topology that will unfold slowly and hence have kinetic stability, but fold slowly. These observations, together with the established role of kinetic stability in determining resistance to thermal and chemical denaturation as well as proteases, have important implications for understanding fundamental aspects of protein unfolding and folding and for protein engineering and design.

Modular evolution and the origins of symmetry: reconstruction of a three-fold symmetric globular protein.

The high frequency of internal structural symmetry in common protein folds is presumed to reflect their evolutionary origins from the repetition and fusion of ancient peptide modules, but little is known about the primary sequence and physical determinants of this process. Unexpectedly, a sequence and structural analysis of symmetric subdomain modules within an abundant and ancient globular fold, the ß-trefoil, reveals that modular evolution is not simply a relic of the ancient past, but is an ongoing and recurring mechanism for regenerating symmetry, having occurred independently in numerous existing ß-trefoil proteins. We performed a computational reconstruction of a ß-trefoil subdomain module and repeated it to form a newly three-fold symmetric globular protein, ThreeFoil. In addition to its near perfect structural identity between symmetric modules, ThreeFoil is highly soluble, performs multivalent carbohydrate binding, and has remarkably high thermal stability. These findings have far-reaching implications for understanding the evolution and design of proteins via subdomain modules.