The stability of globular proteins

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

Mean-field models for the chemical fueling of transient soft matter states

The chemical fueling of transient states (CFTS) is a powerful process to control the nonequilibrium structuring and the homeostatic function of adaptive soft matter systems. Here, we introduce a simple mean-field model of CFTS based on the activation of metastable equilibrium states in a tilted 'Landau' bistable energy landscape along a coarse-grained reaction coordinate (or 'order parameter') triggered by a nonmonotonic two-step chemical fueling reaction. Evaluation of the model in the quasi-static (QS) limit-valid for fast system relaxation-allows us to extract useful analytical laws for the critical activation concentration and duration of the transient states in dependence of physical parameters, such as rate constants, fuel concentrations, and the system's distance to its equilibrium transition point. We apply our model in the QS limit explicitly to recent experiments of CFTS of collapsing responsive microgels and find a very good performance with only a few global and physically interpretable fitting parameters, which can be employed for programmable material design. Moreover, our model framework also allows a thermodynamic analysis of the energy and performed work in the system. Finally, we go beyond the QS limit, where the system's response is slow and retarded versus the chemical reaction, using an overdamped Smoluchowski approach. The latter demonstrates how internal system time scales can be used to tune the time-dependent behavior and programmed delay of the transient states in full nonequilibrium.

Synergistic chemomechanical dynamics of feedback-controlled microreactors

The experimental control of synergistic chemomechanical dynamics of catalytically active microgels (microreactors) is a key prerequisite for the design of adaptive and biomimetic materials. Here, we report a minimalistic model of feedback-controlled microreactors based on the coupling between the hysteretic polymer volume phase transition and a volume-controlled permeability for the internal chemical conversion. We categorize regimes of mono- and bistability, excitability, damped oscillations, as well as sustained oscillatory states with tunable amplitude, as indicated by experiments and representable by the FitzHugh-Nagumo dynamics for neurons. We summarize the features of such a "colloidal neuron" in bifurcation diagrams with respect to microgel design parameters, such as permeability and relaxation times, as a guide for experimental synthesis.

Thermodynamic Modeling and Experimental Data Reveal That Sugars Stabilize Proteins According to an Excluded Volume Mechanism

We present a new thermodynamic model to investigate the relative effects of excluded volume and soft interaction contributions in determining whether a cosolute will either destabilize or stabilize a protein in solution. This model is unique in considering an atomistically detailed model of the protein and accounting for the preferential accumulation/exclusion of the osmolyte molecules from the protein surface. Importantly, we use molecular dynamics simulations and experiments to validate the model. The experimental approach presents a unique means of decoupling excluded volume and soft interaction contributions using a linear polymeric series of cosolutes with different numbers of glucose subunits, from 1 (glucose) to 8 (maltooctaose), as well as an 8-mer of glucose units in the closed form (γ-CD). By studying the stabilizing effect of cosolutes along this polymeric series using lysozyme as a model protein, we validate the thermodynamic model and show that sugars stabilize proteins according to an excluded volume mechanism.

The "Beacon" Structural Model of Protein Folding: Application for Trp-Cage in Water

Protein folding is a process in which a polypeptide must undergo folding process to obtain its three-dimensional structure. Thermodynamically, it is a process of enthalpy to overcome the loss of conformational entropy in folding. Folding is primarily related to hydrophobic interactions and intramolecular hydrogen bondings. During folding, hydrophobic interactions are regarded to be the driving forces, especially in the initial structural collapse of a protein. Additionally, folding is guided by the strong interactions within proteins, such as intramolecular hydrogen bondings related to the α-helices and β-sheets of proteins. Therefore, a protein is divided into the folding key (FK) regions related to intramolecular hydrogen bondings and the non-folding key (non-FK) regions. Various conformations are expected for FK and non-FK regions. Different from non-FK regions, it is necessary for FK regions to form the specific conformations in folding, which are regarded as the necessary folding pathways (or "beacons"). Additionally, sequential folding is expected for the FK regions, and the intermediate state is found during folding. They are reflected on the local basins in the free energy landscape (FEL) of folding. To demonstrate the structural model, molecular dynamics (MD) simulations are conducted on the folding pathway of the TRP-cage in water.

Effect of alanine versus serine at position 88 of human transthyretin mutants on the protein stability

Human transthyretin (TTR) is a homo-tetrameric plasma protein associated with a high percentage of β-sheet forming amyloid fibrils. It accumulates in tissues or extracellular matrices to cause amyloid diseases. Free energy simulations with thermodynamic integration based on all-atom molecular dynamics simulations have been carried out to analyze the effects of the His88 → Ala and Ser mutations on the stability of human TTR. The calculated free energy change differences (ΔΔG) caused by the His88 → Ala and His88 → Ser mutations are -1.84 ± 0.86 and 7.56 ± 0.55 kcal/mol, respectively, which are in excellent agreement with prior reported experimental values. The simulation results show that the H88A mutant is more stable than the wild type, whereas the H88S mutant is less stable than the wild type. The free energy component analysis shows that the contribution to the free energy change difference (ΔΔG) for the His88 → Ala and His88 → Ser mutations mainly arise from electrostatic and van der Waals interactions, respectively. The electrostatic term stabilizes the H88A mutant more than the wild type, but the van der Waals interaction destabilizes the H88S mutant relative to the wild type. Individual residue contributions to the free energy change show neighboring residues exert stabilizing and destabilizing influence on the mutants. The implications of the simulation results for understanding the stabilizing and destabilizing effect and its contribution to protein stability are discussed.

Fused in sarcoma undergoes cold denaturation: Implications for phase separation

The mediation of liquid-liquid phase separation (LLPS) for fused in sarcoma (FUS) protein is generally attributed to the low-complexity, disordered domains and is enhanced at low temperature. The role of FUS folded domains on the LLPS process remains relatively unknown since most studies are mainly based on fragmented FUS domains. Here, we investigate the effect of metabolites on full-length (FL) FUS LLPS using turbidity assays and differential interference contrast (DIC) microscopy, and explore the behavior of the folded domains by nuclear magnetic resonance (NMR) spectroscopy. FL FUS LLPS is maximal at low concentrations of glucose and glutamate, moderate concentrations of NaCl, Zn²⁺ , and Ca²⁺ and at the isoelectric pH. The FUS RNA recognition motif (RRM) and zinc-finger (ZnF) domains are found to undergo cold denaturation above 0°C at a temperature that is determined by the conformational stability of the ZnF domain. Cold unfolding exposes buried nonpolar residues that can participate in LLPS-promoting hydrophobic interactions. Therefore, these findings constitute the first evidence that FUS globular domains may have an active role in LLPS under cold stress conditions and in the assembly of stress granules, providing further insight into the environmental regulation of LLPS.

Recent Advances in the Enzymatic Synthesis of Polyester

Polyester is a kind of polymer composed of ester bond-linked polybasic acids and polyol. This type of polymer has a wide range of applications in various industries, such as automotive, furniture, coatings, packaging, and biomedical. The traditional process of synthesizing polyester mainly uses metal catalyst polymerization under high-temperature. This condition may have problems with metal residue and undesired side reactions. As an alternative, enzyme-catalyzed polymerization is evolving rapidly due to the metal-free residue, satisfactory biocompatibility, and mild reaction conditions. This article presented the reaction modes of enzyme-catalyzed ring-opening polymerization and enzyme-catalyzed polycondensation and their combinations, respectively. In addition, the article also summarized how lipase-catalyzed the polymerization of polyester, which includes (i) the distinctive features of lipase, (ii) the lipase-catalyzed polymerization and its mechanism, and (iii) the lipase stability under organic solvent and high-temperature conditions. In addition, this article also focused on the advantages and disadvantages of enzyme-catalyzed polyester synthesis under different solvent systems, including organic solvent systems, solvent-free systems, and green solvent systems. The challenges of enzyme optimization and process equipment innovation for further industrialization of enzyme-catalyzed polyester synthesis were also discussed in this article.

Protein stability [determination] problems

Human health depends on the correct folding of proteins, for misfolding and aggregation lead to diseases. An unfolded (denatured) protein can refold to its original folded state. How does this occur is known as the protein folding problem. One of several related questions to this problem is that how much more stable is the folded state than the unfolded state. There are several measures of protein stability. In this article, protein stability is given a thermodynamic definition and is measured by Gibbs free energy change (ΔGD0) associated with the equilibrium, native (N) conformation ↔ denatured (D) conformation under the physiological condition usually taken as dilute buffer (or water) at 25 °C. We show that this thermodynamic quantity (ΔGD0), where subscript D represents transition between N and D states, and superscript 0 (zero) represents the fact that the transition occurs in the absence of denaturant, can be neither measured nor predicted under physiological conditions. However, ΔGD can be measured in the presence of strong chemical denaturants such as guanidinium chloride and urea which are shown to destroy all noncovalent interactions responsible for maintaining the folded structure. A problem with this measurement is that the estimate of ΔGD0 comes from the analysis of the plot of ΔGDversus denaturant concentration, which requires a long extrapolation of values of ΔGD, and all the three methods of extrapolation give three different values of ΔGD0 for a protein. Thus, our confidence in the authentic value of ΔGD0 is eroded. Another problem with this in vitro measurement of ΔGD0 is that it is done on the pure protein sample in dilute buffer which is a very large extrapolation of the in vivo conditions, for the crowding effect on protein stability is ignored.

AlphaFold 2 and NMR Spectroscopy: Partners to Understand Protein Structure, Dynamics and Function

The artificial intelligence program AlphaFold 2 is revolutionizing the field of protein structure determination as it accurately predicts the 3D structure of two thirds of the human proteome. Its predictions can be used directly as structural models or indirectly as aids for experimental structure determination using X-ray crystallography, CryoEM or NMR spectroscopy. Nevertheless, AlphaFold 2 can neither afford insight into how proteins fold, nor can it determine protein stability or dynamics. Rare folds or minor alternative conformations are also not predicted by AlphaFold 2 and the program does not forecast the impact of post translational modifications, mutations or ligand binding. The remaining third of human proteome which is poorly predicted largely corresponds to intrinsically disordered regions of proteins. Key to regulation and signaling networks, these disordered regions often form biomolecular condensates or amyloids. Fortunately, the limitations of AlphaFold 2 are largely complemented by NMR spectroscopy. This experimental approach provides information on protein folding and dynamics as well as biomolecular condensates and amyloids and their modulation by experimental conditions, small molecules, post translational modifications, mutations, flanking sequence, interactions with other proteins, RNA and virus. Together, NMR spectroscopy and AlphaFold 2 can collaborate to advance our comprehension of proteins.

The Importance of Weakly Co-Evolving Residue Networks in Proteins is Revealed by Visual Analytics

Small changes in a protein’s core packing produce changes in function, and even small changes in function bias species fitness and survival. Therefore individually deleterious mutations should be evolutionarily coupled with compensating mutations that recover fitness. Co-evolving pairs of mutations should be littered across evolutionary history. Despite longstanding intuition, the results of co-evolution analyses have largely disappointed expectations. Regardless of the statistics applied, only a small majority of the most strongly co-evolving residues are typically found to be in contact, and much of the “meaning” of observed co-evolution has been opaque. In a medium-sized protein of 300 amino acids, there are almost 20 million potentially-important interdependencies. It is impossible to understand this data in textual format without extreme summarization or truncation. And, due to summarization and truncation, it is impossible to identify most patterns in the data. We developed a visualization approach that eschews the common “look at a long list of statistics” approach and instead enables the user to literally look at all of the co-evolution statistics simultaneously. Users of our tool reported visually obvious “clouds” of co-evolution statistics forming distinct patterns in the data, and analysis demonstrated that these clouds had structural relevance. To determine whether this phenomenon generalized, we repeated this experiment in three proteins we had not previously studied. The results provide evidence about how structural constrains have impacted co-evolution, why previous “examine the most frequently co-evolving residues” approaches have had limited success, and additionally shed light on the biophysical importance of different types of co-evolution.

Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias B_M . The models were externally validated on three test data sets probing different pathologies and for internal consistency (symmetry and neutrality). Model structure and performance substantially depended on training data and even fitting method. We developed two final models: SimBa-IB for typical natural mutations and SimBa-SYM for situations where stabilizing and destabilizing mutations occur to a similar extent. SimBa-SYM, despite is simplicity, is essentially non-biased (vs. the S^sym data set) while still performing well for all data sets (R ~ 0.46-0.54, MAE = 1.16-1.24 kcal/mol). The simple models provide advantage in terms of interpretability, use and future improvement, and are freely available on GitHub.

Self-Healing Behavior of Polymer/Protein Hybrid Hydrogels

The paper presents the viscoelastic properties of new hybrid hydrogels containing poly(vinyl alcohol) (PVA), hydroxypropylcellulose (HPC), bovine serum albumin (BSA) and reduced glutathione (GSH). After heating the mixture at 55 °C, in the presence of GSH, a weak network is formed due to partial BSA unfolding. By applying three successive freezing/thawing cycles, a stable porous network structure with elastic properties is designed, as evidenced by SEM and rheology. The hydrogels exhibit self-healing properties when the samples are cut into two pieces; the intermolecular interactions are reestablished in time and therefore the fragments repair themselves. The effects of the BSA content, loaded deformation and temperature on the self-healing ability of hydrogels are presented and discussed through rheological data. Due to their versatile viscoelastic behavior, the properties of PVA/HPC/BSA hydrogels can be tuned during their preparation in order to achieve suitable biomaterials for targeted applications.

Analyzing the Effects of Silica Nanospheres on the Sol-Gel Transition Profile of Thermosensitive Hydrogels

The insertion of nanoparticles into smart hydrogels can diversify their functionalities by a synergistic combination of the components properties within the hydrogels. While these hybrid systems are attractive to the biomaterials field, careful design and control of their properties are required since the new interactions between the polymer and the nanoparticles can result in changes or the loss of hydrogels stimuli response. In order to understand the physicochemical aspects of the thermoresponsive systems, nanocomposites of poly(N-vinylcaprolactam) (PNVCL) and silica nanoparticles with different sizes and concentrations were synthesized. The UV-vis and DLS techniques showed that the PNVCL has a sharp phase transition at 34 °C, while the nanocomposites have a diffuse transition. The nanocomposites showed an initial coil-globule transition before the phase transition takes place. This was identified by the evolution of the hydrodynamic diameter of the nanocomposite globules before the cloud point temperature (T_cp), which remained constant for PNVCL. This new transition profile can be described by two stages in which microscopic volume transitions occur first, followed by the macroscopic transition that forms the hydrogel. These results show that the proposed nanocomposites can be designed to have tunable stimuli response to smaller temperature variations with the formation of intermediate globule states.

Three Simple Properties Explain Protein Stability Change upon Mutation

Accurate prediction of protein stability upon mutation enables rational engineering of new proteins and insights into protein evolution and monogenetic diseases caused by single-point amino acid substitutions. Many tools have been developed to this aim, ranging from energy-based models to machine-learning methods that use large amounts of experimental data. However, as the methods become more complex, the interpretation of the chemistry underlying the protein stability effects becomes obscure. It is thus of interest to identify the simplest prediction model that retains complete amino acid specific interpretation; for a given number of input descriptors, we expect such a model to be almost universal. In this study, we identify such a limiting model, SimBa, a simple multilinear regression model trained on a substitution-type-balanced experimental data set. The model accounts only for the solvent accessibility of the site, volume difference, and polarity difference caused by mutation. Our results show that this very simple and directly applicable model performs comparably to other much more complex, widely used protein stability prediction methods. This suggests that a hard limit of ∼1 kcal/mol numerical accuracy and an R ∼ 0.5 trend accuracy exists and that new features, such as account of unfolded states, water colocalization, and amino acid correlations, are required to improve accuracy to, e.g., 1/2 kcal/mol.

Brain Metabolite, N-Acetylaspartate Is a Potent Protein Aggregation Inhibitor

Deposition of toxic protein inclusions is a common hallmark of many neurodegenerative disorders including Alzheimer's disease, Parkinson disease etc. N-acetylaspartate (NAA) is an important brain metabolite whose levels got altered under various neurodegenerative conditions. Indeed, NAA has been a widely accepted biological marker for various neurological disorders. We have also reported that NAA is a protein stabilizer. In the present communication, we investigated the role of NAA in modulating the aggregation propensity on two model proteins (carbonic anhydrase and catalase). We discovered that NAA suppresses protein aggregation and could solubilize preformed aggregates.

Structural and Energetic Characterization of the Denatured State from the Perspectives of Peptides, the Coil Library, and Intrinsically Disordered Proteins

The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations. Here, we compare results from peptide-based studies of intrinsic conformational propensities and surveys of the protein coil library to those of the sequence-based analysis of heat effects on IDP hydrodynamic size, showing that a common structural and thermodynamic description of the protein denatured state is obtained.

Effects of Ionic Liquids on Metalloproteins

In the past decade, innovative protein therapies and bio-similar industries have grown rapidly. Additionally, ionic liquids (ILs) have been an area of great interest and rapid development in industrial processes over a similar timeline. Therefore, there is a pressing need to understand the structure and function of proteins in novel environments with ILs. Understanding the short-term and long-term stability of protein molecules in IL formulations will be key to using ILs for protein technologies. Similarly, ILs have been investigated as part of therapeutic delivery systems and implicated in numerous studies in which ILs impact the activity and/or stability of protein molecules. Notably, many of the proteins used in industrial applications are involved in redox chemistry, and thus often contain metal ions or metal-associated cofactors. In this review article, we focus on the current understanding of protein structure-function relationship in the presence of ILs, specifically focusing on the effect of ILs on metal containing proteins.

Zinc shapes the folding landscape of p53 and establishes a pathway for reactivating structurally diverse cancer mutants

Missense mutations in the p53 DNA-binding domain (DBD) contribute to half of new cancer cases annually. Here we present a thermodynamic model that quantifies and links the major pathways by which mutations inactivate p53. We find that DBD possesses two unusual properties—one of the highest zinc affinities of any eukaryotic protein and extreme instability in the absence of zinc—which are predicted to poise p53 on the cusp of folding/unfolding in the cell, with a major determinant being available zinc concentration. We analyze the 20 most common tumorigenic p53 mutations and find that 80% impair zinc affinity, thermodynamic stability, or both. Biophysical, cell-based, and murine xenograft experiments demonstrate that a synthetic zinc metallochaperone rescues not only mutations that decrease zinc affinity, but also mutations that destabilize DBD without impairing zinc binding. The results suggest that zinc metallochaperones have the capability to treat 120,500 patients annually in the U.S.

Structural and thermodynamic characterization of a highly stable conformation of Rv2966c, a 16S rRNA methyltransferase, at low pH

Rv2966c is a highly specific methyltransferase that methylates G966 at the N2 position in 16S rRNA of mycobacterial ribosome and can be secreted inside the host cell to methylate host DNA. However, how the secreted protein retains its structure and function in the harsh environment of host cell, remains unclear. In this work, we investigate structural features of Rv2966c at pH 4.0 and pH 7.5 by far-UV- and near-UV-circular dichroism (CD) and fluorescence spectroscopy, to gain insights into its folding and stability at the acidic pH, that it is likely to encounter inside the macrophage. We show that Rv2966c exists in a compact, folded state at both pH 7.5 and pH 4.0, a result corroborated by molecular dynamics simulations as a function of pH. In fact, Rv2966c was found to be more stable at pH 4.0 than pH 7.5, as evidenced by thermal-induced CD and nanodifferential scanning fluorimetry, and urea-induced denaturation measurements. Interestingly, unlike pH 7.5 (two-state unfolding), denaturation of Rv2966c at pH 4.0 occurs in a biphasic (N ↔ X ↔ U) manner. Further spectroscopic characterization of 'X' state, identifies characteristics of a molten globule-like intermediate. We finally conclude that Rv2966c maintains a compact folded state at pH 4.0 akin to that at pH 7.5 but with higher stability.

Solvent-free liquid avidin as a step toward cold chain elimination

The temperature sensitivity of vaccines and therapeutic proteins forces the distribution of life-saving treatments to rely heavily on the temperature-controlled (usually 2-8°C) supply and distribution network known as the cold chain. Here, using avidin as a model, we demonstrate how surface engineering could significantly increase the thermal stability of therapeutic proteins. A combination of spectroscopic (Fourier transform infrared, circular dichroism, and ultraviolet-visible) and scattering techniques (dynamic light scattering, small-angle, and wide-angle X-ray scattering) were deployed to probe the activity, structure, and stability of the model protein. Temperature-dependent synchrotron radiation circular dichroism spectroscopy was used to demonstrate a significant increase in thermal stability, with a half denaturation temperature of 139.0°C and reversible unfolding with modified avidin returning to a 90% folded state when heated to temperatures below 100°C. Accelerated aging studies revealed that modified avidin retained its secondary structure after storage at 40°C for 56 days, equivalent to 160 days at 25°C. Furthermore, binding studies with multiple ligands revealed that the binding site remained functional after modification. As a result, this approach has potential as a storage technology for therapeutic proteins and the elimination of the cold chain, enabling the dissemination of life-saving vaccines worldwide.

ADD Force Field for Sugars and Polyols: Predicting the Additivity of Protein-Osmolyte Interaction

The protein–osmolyte interaction has been shown experimentally to follow an additive construct, where the individual osmolyte–backbone and osmolyte–side-chain interactions contribute to the overall conformational stability of proteins. Here, we computationally reconstruct this additive relation using molecular dynamics simulations, focusing on sugars and polyols, including sucrose and sorbitol, as model osmolytes. A new set of parameters (ADD) is developed for this purpose, using the individual Kirkwood–Buff integrals for sugar–backbone and sugar–side-chain interactions as target experimental data. We show that the ADD parameters can reproduce the additivity of protein–sugar interactions and correctly predict sucrose and sorbitol self-association and their interaction with water. The accurate description of the separate osmolyte–backbone and osmolyte–side-chain contributions also automatically translates into a good prediction of preferential exclusion from the surface of ribonuclease A and α-chymotrypsinogen A. The description of sugar polarity is improved compared to previous force fields, resulting in closer agreement with the experimental data and better compatibility with charged groups, such as the guanidinium moiety. The ADD parameters are developed in combination with the CHARMM36m force field for proteins, but good compatibility is also observed with the AMBER 99SB-ILDN and the OPLS-AA force fields. Overall, exploiting the additivity of protein–osmolyte interactions is a promising approach for the development of new force fields.

Structural, kinetic and thermodynamic characterizations of SDS-induced molten globule state of a highly negatively charged cytochrome c

This study presents the structural, kinetic and thermodynamic characterizations of previously unknown submicellar concentrations of SDS-induced molten globule (MGSDS) state of a highly negatively charged base-denatured ferricytochrome c (UB-state) at pH ∼12.8 (±0.2). The far-UV CD, near-UV CD, ANS-fluorescence data of UB-state in the presence of different concentrations of SDS indicate that the submicellar concentrations of SDS (≤0.4 mM) transform the UB-state to MGSDS-state. The MGSDS-state has native-like α-helical secondary structure but lacks tertiary structure. The free energy change (ΔG°D) for UB→ MGSDS transition determined by far-UV CD (∼2.7 kcal mol-1) is slightly higher than those determined by fluorescence (∼2.0 kcal mol-1) at 25°C. At very low SDS and NaCl concentrations, the MGSDS-state undergoes cold denaturation. As SDS concentration is increased, the thermal denaturation temperature increases and the cold denaturation temperature decrease. Kinetic experiments involving the measurement of the CO-association rate to the base-denatured ferrocytochrome c at pH ≈12.8 (±0.2), 25°C indicate that the submicellar concentrations of SDS restrict the internal dynamics of base-denatured protein.

The Singular NMR Fingerprint of a Polyproline II Helical Bundle

Polyproline II (PPII) helices play vital roles in biochemical recognition events and structures like collagen and form part of the conformational landscapes of intrinsically disordered proteins (IDPs). Nevertheless, this structure is generally hard to detect and quantify. Here, we report the first thorough NMR characterization of a PPII helical bundle protein, the Hypogastrura harveyi "snow flea" antifreeze protein (sfAFP). J-couplings and nuclear Overhauser enhancement spectroscopy confirm a natively folded structure consisting of six PPII helices. NMR spectral analyses reveal quite distinct Hα2 versus Hα3 chemical shifts for 28 Gly residues as well as ¹³Cα, ¹⁵N, and ¹HN conformational chemical shifts (Δδ) unique to PPII helical bundles. The ¹⁵N Δδ and ¹HN Δδ values and small negative ¹HN temperature coefficients evince hydrogen-bond formation. ¹H-¹⁵N relaxation measurements reveal that the backbone structure is generally highly rigid on ps-ns time scales. NMR relaxation parameters and biophysical characterization reveal that sfAFP is chiefly a dimer. For it, a structural model featuring the packing of long, flat hydrophobic faces at the dimer interface is advanced. The conformational stability, measured by amide H/D exchange to be 6.24 ± 0.2 kcal·mol^-1, is elevated. These are extraordinary findings considering the great entropic cost of fixing Gly residues and, together with the remarkable upfield chemical shifts of 28 Gly ¹Hα, evidence significant stabilizing contributions from CαHα ||| O═C hydrogen bonds. These stabilizing interactions are corroborated by density functional theory calculations and natural bonding orbital analysis. The singular conformational chemical shifts, J-couplings, high hNOE ratios, small negative temperature coefficients, and slowed H/D exchange constitute a unique set of fingerprints to identify PPII helical bundles, which may be formed by hundreds of Gly-rich motifs detected in sequence databases. These results should aid the quantification of PPII helices in IDPs, the development of improved antifreeze proteins, and the incorporation of PPII helices into novel designed proteins.

Synchronous fluorescence spectroscopy for detecting blood meal and blood products

Fluorescence spectroscopy is a powerful method for protein analysis. Its sensitivity and selectivity allow its use for the detection of blood meal and blood products. This study proposes a novel approach for the detection of hemoglobin in animal feed by synchronous fluorescence spectroscopy (SFS). The objective was to develop a fast and easy method to detect hemoglobin powder and blood meal. Analyses were carried out on standard reference material (hemoglobin and albumin) in order to optimize SFS method conditions for hemoglobin detection. The method was then applied to protein extracts of commercial feed material and compound feed. The results showed that SFS spectra of blood meal and blood products (hemoglobin powder and plasma powder) could be used to characterize hemoglobin. Principal component analysis (PCA) applied to area-normalized SFS spectra of artificially adulterated samples made it possible to define a limit of detection of hemoglobin powder or blood meal of 0.5-1% depending on the feed material. The projection in the PCA graphs of SFS spectra of real commercial compound feeds known to contain or to be free from blood-derived products showed that it was possible to discriminate samples according to the presence of hemoglobin. These results confirmed that SFS is a promising screening method for the detection of hemoglobin in animal feed.

Comparison of exosomes and ferritin protein nanocages for the delivery of membrane protein therapeutics

Exosomes are small membrane vesicles secreted by most cell types that play an important role in intercellular communication. Due to the characteristic of transferring their biomacromolecules, exosomes have potential as a new alternative for delivering protein therapeutics. Here, we investigate whether exosomes provide crucial advantages over other nanoparticles, in particular protein nanocage formulations, as a delivery system for membrane protein therapeutics. We characterized membrane-scaffold-based exosomes and protein-scaffold-based ferritin nanocages, both harboring SIRPα (signal regulatory protein α), an antagonist of CD47 on tumor cells. The efficacy of these two systems in delivering protein therapeutics was compared by testing their ability to enhance phagocytosis of tumor cells by bone-marrow-derived macrophages and subsequent inhibition of in vivo tumor growth. These analyses allowed us to comprehensively conclude that the therapeutic index of exosome-mediated CD47 blockade against tumor growth inhibition was higher than that of the same dose of ferritin-SIRPα. The results of this analysis reveal the importance of the unique characteristics of exosomes, in particular their membrane scaffold, in improving therapeutic protein delivery compared with protein-scaffold-based nanocages.

"Cooperative collapse" of the denatured state revealed through Clausius-Clapeyron analysis of protein denaturation phase diagrams

Protein phase diagrams have a unique potential to identify the presence of additional thermodynamic states even when non-2-state character is not readily apparent from the experimental observables used to follow protein unfolding transitions. Two-state analysis of the von Willebrand factor A3 domain has previously revealed a discrepancy in the calorimetric enthalpy obtained from thermal unfolding transitions as compared with Gibbs-Helmholtz analysis of free energies obtained from the Linear Extrapolation Method (Tischer and Auton, Prot Sci 2013; 22(9):1147-60). We resolve this thermodynamic conundrum using a Clausius-Clapeyron analysis of the urea-temperature phase diagram that defines how Δ H and the urea m-value interconvert through the slope of c_m versus T, ( ∂ c m / ∂ T ) = Δ H / ( m T ) . This relationship permits the calculation of Δ H at low temperature from m-values obtained through iso-thermal urea denaturation and high temperature m-values from Δ H obtained through iso-urea thermal denaturation. Application of this equation uncovers sigmoid transitions in both cooperativity parameters as temperature is increased. Such residual thermal cooperativity of Δ H and the m-value confirms the presence of an additional state which is verified to result from a cooperative phase transition between urea-expanded and thermally-compact denatured states. Comparison of the equilibria between expanded and compact denatured ensembles of disulfide-intact and carboxyamidated A3 domains reveals that introducing a single disulfide crosslink does not affect the presence of the additional denatured state. It does, however, make a small thermodynamically favorable free energy (∼-13 ± 1 kJ/mol) contribution to the cooperative denatured state collapse transition as temperature is raised and urea concentration is lowered. The thermodynamics of this "cooperative collapse" of the denatured state retain significant compensations between the enthalpy and entropy contributions to the overall free energy.

Helical Propensity Affects the Conformational Properties of the Denatured State of Cytochrome c'

Changing the helical propensity of a polypeptide sequence might be expected to affect the conformational properties of the denatured state of a protein. To test this hypothesis, alanines at positions 83 and 87 near the center of helix 3 of cytochrome c' from Rhodopseudomonas palustris were mutated to serine to decrease the stability of this helix. A set of 13 single histidine variants in the A83S/A87S background were prepared to permit assessment of the conformational properties of the denatured state using histidine-loop formation in 3 M guanidine hydrochloride. The data are compared with previous histidine-heme loop formation data for wild-type cytochrome c'. As expected, destabilization of helix 3 decreases the global stabilities of the histidine variants in the A83S/A87S background relative to the wild-type background. Loop stability versus loop size data yields a scaling exponent of 2.1 ± 0.2, similar to the value of 2.3 ± 0.2 obtained for wild-type cytochrome c'. However, the stabilities of all histidine-heme loops, which contain the helix 3 sequence segment, are increased in the A83S/A87S background compared to the wild-type background. Rate constants for histidine-heme loop breakage are similar for the wild-type and A83S/A87S variants. However, for histidine-heme loops that contain the helix 3 sequence segment, the rate constants for loop formation increase in the A83S/A87S background compared to the wild-type background. Thus, residual helical structure appears to stiffen the polypeptide chain slowing loop formation in the denatured state. The implications of these results for protein folding mechanisms are discussed.

Denaturant-specific effects on the structural energetics of a protein-denatured ensemble

Protein thermodynamic stability is intricately linked to cellular function, and altered stability can lead to dysfunction and disease. The linear extrapolation model (LEM) is commonly used to obtain protein unfolding free energies ([Formula: see text]) by extrapolation of solvent denaturation data to zero denaturant concentration. However, for some proteins, different denaturants result in non-coincident LEM-derived [Formula: see text] values, raising questions about the inherent assumption that the obtained [Formula: see text] values are intrinsic to the protein. Here, we used single-molecule FRET measurements to better understand such discrepancies by directly probing changes in the dimensions of the protein G B1 domain (GB1), a well-studied protein folding model, upon urea and guanidine hydrochloride denaturation. A comparison of the results for the two denaturants suggests denaturant-specific structural energetics in the GB1 denatured ensemble, revealing a role of the denatured state in the variable thermodynamic behavior of proteins.

Development of Escherichia coli Asparaginase II for Immunosensing: A Trade-Off between Receptor Density and Sensing Efficiency

The clinical success of Escherichia colil-asparaginase II (EcAII) as a front line chemotherapeutic agent for acute lymphoblastic leukemia (ALL) is often compromised because of its silent inactivation by neutralizing antibodies. Timely detection of silent immune response can rely on immobilizing EcAII, to capture and detect anti-EcAII antibodies. Having recently reported the use of a portable surface plasmon resonance (SPR) sensing device to detect anti-EcAII antibodies in undiluted serum from children undergoing therapy for ALL (Aubé et al., ACS Sensors2016, 1 (11), 1358-1365), here we investigate the impact of the quaternary structure and the mode of immobilization of EcAII onto low-fouling SPR sensor chips on the sensitivity and reproducibility of immunosensing. We show that the native tetrameric structure of EcAII, while being essential for activity, is not required for antibody recognition because monomeric EcAII is equally antigenic. By modulating the mode of immobilization, we observed that low-density surface coverage obtained upon covalent immobilization allowed each tetrameric EcAII to bind up to two antibody molecules, whereas high-density surface coverage arising from metal chelation by N- or C-terminal histidine-tag reduced the sensing efficiency to less than one antibody molecule per tetramer. Nonetheless, immobilization of EcAII by metal chelation procured up to 10-fold greater surface coverage, thus resulting in increased SPR sensitivity and allowing reliable detection of lower analyte concentrations. Importantly, only metal chelation achieved highly reproducible immobilization of EcAII, providing the sensing reproducibility that is required for plasmonic sensing in clinical samples. This report sheds light on the impact of multiple factors that need to be considered to optimize the practical applications of plasmonic sensors.

Fluorescence correlation spectroscopy reveals a cooperative unfolding of monomeric amyloid-β 42 with a low Gibbs free energy

The amyloid-beta peptide (Aβ) plays a major role in the progression of Alzheimer's disease. Due to its high toxicity, the 42 amino acid long isoform Aβ42 has become of considerable interest. The Aβ42 monomer is prone to aggregation down to the nanomolar range which makes conventional structural methods such as NMR or X-ray crystallography infeasible. Conformational information, however, will be helpful to understand the different aggregation pathways reported in the literature and will allow to identify potential conditions that favour aggregation-incompetent conformations. In this study, we applied fluorescence correlation spectroscopy (FCS) to investigate the unfolding of Alexa Fluor 488 labelled monomeric Aβ42 using guanidine hydrochloride as a denaturant. We show that our Aβ42 pre-treatment and the low-nanomolar concentrations, typically used for FCS measurements, strongly favour the presence of monomers. Our results reveal that there is an unfolding/folding behaviour of monomeric Aβ42. The existence of a cooperative unfolding curve suggests the presence of structural elements with a Gibbs free energy of unfolding of about 2.8 kcal/mol.

Green synthesis of enzyme/metal-organic framework composites with high stability in protein denaturing solvents

OBJECTIVES

Enzyme/metal-organic framework composites with high stability in protein denaturing solvents were reported in this study.

RESULTS

Encapsulation of enzyme in metal-organic frameworks (MOFs) via co-precipitation process was realized, and the generality of the synthesis was validated by using cytochrome c, horseradish peroxidase, and Candida antarctica lipase B as model enzymes. The stability of encapsulated enzyme was greatly increased after immobilization on MOFs. Remarkably, when exposed to protein denaturing solvents including dimethyl sulfoxide, dimethyl formamide, methanol, and ethanol, the enzyme/MOF composites still preserved almost 100% of activity. In contrast, free enzymes retained no more than 20% of their original activities at the same condition. This study shows the extraordinary protecting effect of MOF shell on increasing enzyme stability at extremely harsh conditions.

CONCLUSION

The enzyme immobilized in MOF exhibited enhanced thermal stability and high tolerance towards protein denaturing organic solvents.

Beyond the Hofmeister Series: Ion-Specific Effects on Proteins and Their Biological Functions

Ions differ in their ability to salt out proteins from solution as expressed in the lyotropic or Hofmeister series of cations and anions. Since its first formulation in 1888, this series has been invoked in a plethora of effects, going beyond the original salting out/salting in idea to include enzyme activities and the crystallization of proteins, as well as to processes not involving proteins like ion exchange, the surface tension of electrolytes, or bubble coalescence. Although it has been clear that the Hofmeister series is intimately connected to ion hydration in homogeneous and heterogeneous environments and to ion pairing, its molecular origin has not been fully understood. This situation could have been summarized as follows: Many chemists used the Hofmeister series as a mantra to put a label on ion-specific behavior in various environments, rather than to reach a molecular level understanding and, consequently, an ability to predict a particular effect of a given salt ion on proteins in solutions. In this Feature Article we show that the cationic and anionic Hofmeister series can now be rationalized primarily in terms of specific interactions of salt ions with the backbone and charged side chain groups at the protein surface in solution. At the same time, we demonstrate the limitations of separating Hofmeister effects into independent cationic and anionic contributions due to the electroneutrality condition, as well as specific ion pairing, leading to interactions of ions of opposite polarity. Finally, we outline the route beyond Hofmeister chemistry in the direction of understanding specific roles of ions in various biological functionalities, where generic Hofmeister-type interactions can be complemented or even overruled by particular steric arrangements in various ion binding sites.