Native Fold Research Articles

Assessing the impact of conformational perturbants on folding and aggregation pathways of a β-barrel fold.

Here we explore the interplay between physical and chemical perturbants to unravel links among native folding, amorphous and ordered aggregation scenarios in IFABP (rat intestinal fatty acid binding protein). This small beta-barrel protein undergoes amyloid-like aggregation above 15% v/v trifluoroethanol. Our aim was to address the influence of sub-aggregating TFE concentrations on the unfolding transitions of IFABP. The urea-induced unfolding process can bona fide be considered a two-state transition where no aggregation takes place. On the other hand, with GdmCl, the appearance of amyloid-like aggregation becomes evident upon TFE challenge. Temperature-induced denaturation profiles show that both additives, TFE and GdmCl decrease protein stability. Whereas amorphous aggregation occurs upon heating in the presence of TFE, no aggregation takes place with GdmCl. Conversely, when both additives are present, amyloid-like aggregation prevails. The explanation for the choice of amorphous or amyloid-like pathways must reconcile the effects of perturbants on both the protein and solvent structures. Key points include the TFE-promoted desolvation of the polypeptide, a process further enhanced by heat. Although GdmCl might prevent amorphous thermal aggregation by solubilizing non-native states, this effect could also favor amyloid aggregation. In addition, the electrolyte-induced segregation of TFE at high enough GdmCl concentration might contribute to the development and/or stabilization of TFE clusters that could act as nucleation-inducing interfaces, thus leading to the observed amyloid aggregation outcome.

Systematic characterization of indel variants using a yeast-based protein folding sensor.

Gene variants resulting in insertions or deletions of amino acid residues (indels) have important consequences for evolution and are often linked to disease, yet, compared to missense variants, the effects of indels are poorly understood and predicted. We developed a sensitive protein folding sensor based on the complementation of uracil auxotrophy in yeast by circular permutated orotate phosphoribosyltransferase (CPOP). The sensor reports on the folding of disease-linked missense variants and de-novo-designed proteins. Applying the folding sensor to a saturated library of single-residue indels in human dihydrofolate reductase (DHFR) revealed that most regions that tolerate indels are confined to internal loops, the termini, and a central α helix. Several indels are temperature sensitive, and folding is rescued upon binding to methotrexate. Rosetta and AlphaFold2 predictions correlate with the observed effects, suggesting that most indels destabilize the native fold and that these computational tools are useful for the classification of indels observed in population sequencing.

A Self-Consistent Molecular Mechanism of β2-Microglobulin Aggregation.

Despite the consensus on the origin of dialysis-related amyloidosis (DRA) being β2-microglobulin (β2m) aggregation, the debate on the underlying mechanism persists because of the continuous emergence of β2m variant- and pH-dependent contradictory results. By characterizing the native monomeric (initiation) and aggregated fibrillar (termination) states of β2m via a combination of two enhanced sampling approaches, we here propose a mechanism that explains the heterogeneous behavior of wild-type (WT) and pathogenic (V27M and D76N) β2m variants in physiological and disease-pertinent acidic pH environments. It appears that the higher retainment of monomeric native folds at neutral pH (native-like) distinguishes pathogenic β2m mutants from the WT (moderate loss). However, at acidic pH, all three variants behave similarly in producing a substantial amount of partially unfolded states (conformational switch, propensity), though with different extents (WT < V27M < D76N). Whereas at the fibrillar end, all β2m variants display a pH-dependent protofilament separation pathway and a higher protofilament binding affinity (stability) at acidic pH, where the relative order of binding affinity (WT < V27M < D76N) remains consistent with pH modulation. Combining these observations, we conclude that β2m variants possibly shift from native-like aggregation to conformational switch-initiated fibrillation as the pH is altered from neutral to acidic. The combined propensity-stability approach based on the initiation and termination points of β2m aggregation not only assists us in deciphering the mechanism but also emphasizes the protagonistic roles of both terminal points in the overall aggregation process.

Seeing Double: The Persistent Dimer-of-Dimers Structure of Drug Resistant Influenza A M2.

The currently circulating S31N variant of the M2 proton channel of influenza A is resistant to antiviral drugs. Recently, there has been a growing concern regarding the impact of the lipid environment on the structural features of the S31N variant. The native symmetry of the M2 tetramer remains controversial. Here we show that S31N M2 persists in a dimer-of-dimers structure in different lipid preparations independent of the amount of solvating lipids up to at least 180 lipids per tetramer. NMR spectra clearly detect the characteristic resonances of the dimer-of-dimers of M2 (residues 18-60 or 18-62) reconstituted in lipids. NMR-based distance measurements indicate that two isoleucine residues with upfield shifted alpha carbon resonances, typical of extended conformations, are compatible with a particular side-chain rotameric state and helical backbone geometry. These chemical shifts are therefore compatible with the expected native transmembrane helical fold. Symmetry breaking at the pH sensing H37 residues, detected via peak doubling, is a stable feature of S31N M2 based on the reference strain Udorn/1972(H3N2). By contrast, the spectrum is dramatically altered for Columbia/2014/(H3N2) M2, which differs in sequence in the amphipathic helices. This highlights an allosteric coupling between the amphipathic helices and the pH sensing residues.

Immobilized Horseradish Peroxidase on Enriched Diazo-Activated Silica Gel Harnessed High Biocatalytic Performance at a Steady State in Organic Solvent.

Dimethyldichlorosilane (DMDCS), an efficient silane coupling reagent appearing between the -OH groups of silica gel (SG) and picric acid, instantaneously produces a derivative enriched with nitro groups. The nitro group acting as an end-cap terminates the reaction and subsequently was converted into diazo to couple tyrosine's phenol ring via its O-carbon, the inert center to immobilize horseradish peroxidase (HRP) in a multipoint mode. It maintains the status quo of the native enzyme's protein folding and the entire protein groups' chemistry. The molecular formula of the synthesized material was verified and appeared as {Si(OSi)4 (H2O)x}n{-O-Si(CH3)2-O-C6H2(N+≡N)3(HRP)}4·yH2O; the parameters were evaluated as x = 0.5, n = 1158, and y = 752. The immobilized biocatalyst's activity in organic solvents was 1.5 times better than that in an aqueous medium; it worked smoothly, wherein the activity in both solvents stabilized at six months and continued up to nine months at 63 ± 3% compared to the initial.

Advancing Native Mass Spectrometry Toward Cellular Biology.

Protein structure, including various post-translational modifications and higher-order structures, regulates diverse biological functions. Native mass spectrometry (native MS) is a powerful analytical technique used to determine the masses of biomolecules, such as proteins and their complexes, while preserving their native folding in solution. This method provides structural information on the composition of monomers or complexes and the stoichiometry of subunits within each complex, significantly contributing to protein structural analysis. Native MS has evolved to incorporate top-down approaches, enabling the characterization of proteoforms and non-covalent interactions between metabolites or proteins and specific targets. This perspective highlights the advancements in native MS for intracellular proteins and protein complexes, and discusses future research directions toward cellular biology.

RNA fold prediction by Monte Carlo in graph space and the statistical mechanics of tertiary interactions.

Using a graph representation of RNA structures, we have studied the ensembles of secondary and tertiary graphs of two sets of RNA with Monte Carlo simulations. The first consisted of 91 target ribozyme and riboswitch sequences of moderate lengths (<150 nt) having a variety of secondary, H-type pseudoknots and kissing loop interactions. The second set consisted of 71 more diverse sequences across many RNA families. Using a simple empirical energy model for tertiary interactions and only sequence information for each target as input, the simulations examined how tertiary interactions impact the statistical mechanics of the fold ensembles. The results show that the graphs proliferate enormously when tertiary interactions are possible, producing an entropic driving force for the ensemble to access folds having tertiary structures even though they are overall energetically unfavorable in the energy model. For each of the targets in the two test sets, we assessed the quality of the model and the simulations by examining how well the simulated structures were able to predict the native fold, and compared the results to fold predictions from ViennaRNA. Our model generated good or excellent predictions in a large majority of the targets. Overall, this method was able to produce predictions of comparable quality to Vienna, but it outperformed Vienna for structures with H-type pseudoknots. The results suggest that while tertiary interactions are predicated on real-space contacts, their impacts on the folded structure of RNA can be captured by graph space information for sequences of moderate lengths, using a simple tertiary energy model for the loops, the base pairs, and base stacks.

Exploring “dark-matter” protein folds using deep learning

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting "designable" structural templates to guide the sequence searches toward adopting target structures. We present a convolutional variational autoencoder that learns patterns of protein structure, dubbed Genesis. We coupled Genesis with trRosetta to design sequences for a set of protein folds and found that Genesis is capable of reconstructing native-like distance and angle distributions for five native folds and three novel, the so-called "dark-matter" folds as a demonstration of generalizability. We used a high-throughput assay to characterize the stability of the designs through protease resistance, obtaining encouraging success rates for folded proteins. Genesis enables exploration of the protein fold space within minutes, unrestricted by protein topologies. Our approach addresses the backbone designability problem, showing that small neural networks can efficiently learn structural patterns in proteins. A record of this paper's transparent peer review process is included in the supplemental information.

A conserved H-bond network in human aquaporin-1 is necessary for native folding and oligomerization

Aquaporins (AQPs) are α-helical transmembrane proteins that conduct water through membranes with high selectivity and permeability. For human AQP1, in addition to the functional Asn-Pro-Ala motifs and the aromatic/Arg selectivity filter within the pore, there are several highly conserved residues that form an expansive hydrogen-bonding network. Previous solid-state nuclear magnetic resonance studies and structural conservation analysis have detailed which residues may be involved in this network. We explored this network by mutating the side chains or backbones involved in hydrogen-bonding, generating the following mutants: N127A, V133P, E142A, T187A, R195A, and S196A. The fold and stability of these mutants were assessed with attenuated total reflection Fourier transform infrared spectroscopy coupled with hydrogen/deuterium exchange upon increasing temperature. We found that replacement of any of the chosen residues to alanine leads to either partial instability or outright misfolding at room temperature, with the latter being most pronounced for the N127A, V133P, T187A, and R195A mutants. Deconvolution analysis of the amide I band revealed considerable secondary structure deviations, with some mutants exhibiting new random coil and β sheet structures. We also found that some of these mutations potentially disrupt the oligomerization of human AQP1. BN-PAGE and DLS data provide evidence toward the loss of tetramers within most of the mutants, meanwhile only the S196A mutant retains tetrameric organization. The molecular dynamics simulation of the wild-type, and the N127A, E142A, and T187A mutants show that these mutations result in major rearrangements of intra- and intermonomer hydrogen-bond networks. Overall, we show that specific point mutations that perturb hydrogen-bonding clusters result in severe misfolding in hAQP1 and disruption of its oligomerization. These data provide valuable insight into the structural stability of human aquaporin-1 and have implications toward other members of the AQP family, as these networks are largely conserved among a variety of human and nonmammalian AQP homologs.

Structure-aided function assignment to the transcriptomic conopeptide Am931

Implementation of the next-generation technologies for gene sequencing of venom duct transcriptome has provided a large number of peptide sequences of marine cone snails. Emerging technologies on computational platforms are now rapidly evolving for the accurate predictions of the 3D structure of the polypeptide using the primary sequence. The current report aims to integrate the information derived from these two technologies to develop the concept of structure-aided function assignment of Conus peptides. The proof of the concept was demonstrated using the transcriptomic peptide Am931 of C. amadis. The 3D structure of Am931 was computed using Density Functional Theory (DFT) and the quality of the predicted structure was confirmed using 2D NMR spectroscopy of the corresponding synthetic peptide. The computed structure of Am931 aligns with the active site motif of thioredoxins, possess catalytic disulfide conformation of (+, −)AntiRHHook and selectively modulate the N-terminal Cys3 thiol. These structural features indicate that Am931 may act as a disulfide isomerase and modulate the oxidative folding of conotoxins. Synthetic peptide Am931 provides proof-of-function by exhibiting catalytic activity on the oxidative folding of α-conotoxin ImI and improving the yield of native globular fold. The approach of integration of new technologies in the Conus peptide research may help to accelerate the discovery pipeline of new/improved conotoxin functional.

Amino-Acid Characteristics in Protein Native State Structures.

The molecular machines of life, proteins, are made up of twenty kinds of amino acids, each with distinctive side chains. We present a geometrical analysis of the protrusion statistics of side chains in more than 4000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of Cα atoms and consider just the heavy atoms of the side chains. We study the large variety of behaviors of the amino acids based on both rudimentary structural chemistry as well as geometry. Our geometrical analysis uses a backbone Frenet coordinate system for the common study of all amino acids. Our analysis underscores the richness of the repertoire of amino acids that is available to nature to design protein sequences that fit within the putative native state folds.

Stabilization of Non-Native Folds and Programmable Protein Gelation in Compositionally Designed Deep Eutectic Solvents.

Proteins are adjustable units from which biomaterials with designed properties can be developed. However, non-native folded states with controlled topologies are hardly accessible in aqueous environments, limiting their prospects as building blocks. Here, we demonstrate the ability of a series of anhydrous deep eutectic solvents (DESs) to precisely control the conformational landscape of proteins. We reveal that systematic variations in the chemical composition of binary and ternary DESs dictate the stabilization of a wide range of conformations, that is, compact globular folds, intermediate folding states, or unfolded chains, as well as controlling their collective behavior. Besides, different conformational states can be visited by simply adjusting the composition of ternary DESs, allowing for the refolding of unfolded states and vice versa. Notably, we show that these intermediates can trigger the formation of supramolecular gels, also known as eutectogels, where their mechanical properties correlate to the folding state of the protein. Given the inherent vulnerability of proteins outside the native fold in aqueous environments, our findings highlight DESs as tailorable solvents capable of stabilizing various non-native conformations on demand through solvent design.

Protein Editing using a Concerted Transposition Reaction.

Protein engineering through the chemical or enzymatic ligation of polypeptide fragments has proven enormously powerful for studying countless biochemical processes in vitro. In general, this strategy necessitates a protein folding step following ligation of the unstructured fragments, a requirement that constrains the types of systems amenable to the approach. Here, we report an in vitro strategy that allows internal regions of target proteins to be replaced in a single operation. Conceptually, our system is analogous to a DNA transposition reaction, but employs orthogonal pairs of split inteins to swap out a designated region of a host protein with an exogenous molecular cassette. We show using isotopic labeling experiments that this 'protein transposition' reaction is concerted when the kinetics for the embedded intein pairs are suitably matched. Critically, this feature allows for efficient manipulation of protein primary structure in the context of a native fold. The utility of this method is illustrated using several protein systems including the multisubunit chromatin remodeling complex, ACF, where we also show protein transposition can occur in situ within the cell nucleus. By carrying out a molecular 'cut and paste' on a protein or protein complex under native folding conditions, our approach dramatically expands the scope of protein semisynthesis.

Molecular Chaperonin HSP60: Current Understanding and Future Prospects.

Molecular chaperones are highly conserved across evolution and play a crucial role in preserving protein homeostasis. The 60 kDa heat shock protein (HSP60), also referred to as chaperonin 60 (Cpn60), resides within mitochondria and is involved in maintaining the organelle's proteome integrity and homeostasis. The HSP60 family, encompassing Cpn60, plays diverse roles in cellular processes, including protein folding, cell signaling, and managing high-temperature stress. In prokaryotes, HSP60 is well understood as a GroEL/GroES complex, which forms a double-ring cavity and aids in protein folding. In eukaryotes, HSP60 is implicated in numerous biological functions, like facilitating the folding of native proteins and influencing disease and development processes. Notably, research highlights its critical involvement in sustaining oxidative stress and preserving mitochondrial integrity. HSP60 perturbation results in the loss of the mitochondria integrity and activates apoptosis. Currently, numerous clinical investigations are in progress to explore targeting HSP60 both in vivo and in vitro across various disease models. These studies aim to enhance our comprehension of disease mechanisms and potentially harness HSP60 as a therapeutic target for various conditions, including cancer, inflammatory disorders, and neurodegenerative diseases. This review delves into the diverse functions of HSP60 in regulating proteo-homeostasis, oxidative stress, ROS, apoptosis, and its implications in diseases like cancer and neurodegeneration.

Critical assessment of popular biomolecular force fields for molecular dynamics simulations of folding and enzymatic activity of main protease of coronavirus SARS-CoV-2

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents.

Basic leucine zipper transcription activators - tools to improve production and quality of human erythropoietin in Nicotiana benthamiana.

Human erythropoietin (hEPO) is one of the most in-demand biopharmaceuticals, however, its production is challenging. When produced in a plant expression system, hEPO results in extensive plant tissue damage and low expression. It is demonstrated that the modulation of the plant protein synthesis machinery enhances hEPO production. Co-expression of basic leucine zipper transcription factors with hEPO prevents plant tissue damage, boosts expression, and increases hEPO solubility. bZIP28 co-expression up-regulates genes associated with the unfolded protein response, indicating that the plant tissue damage caused by hEPO expression is due to the native protein folding machinery being overwhelmed and that this can be overcome by co-expressing bZIP28.

A Conformational-Dependent Interdomain Redox Relay at the Core of Protein Disulfide Isomerase Activity.

Aims: Protein disulfide isomerases (PDIs) are a family of chaperones resident in the endoplasmic reticulum (ER). In addition to holdase function, some members catalyze disulfide bond formation and isomerization, a crucial step for native folding and prevention of aggregation of misfolded proteins. PDIs are characterized by an arrangement of thioredoxin-like domains, with the canonical protein disulfide isomerase A1 (PDIA1) organized as four thioredoxin-like domains forming a horseshoe with two active sites, a and a', at the extremities. We aimed to clarify important aspects underlying the catalytic cycle of PDIA1 in the context of the full pathways of oxidative protein folding operating in the ER. Results: Using two fluorescent redox sensors, redox green fluorescent protein 2 (roGFP2) and HyPer (circularly permutated yellow fluorescent protein containing the regulatory domain of the H2O2-sensing protein OxyR), either unfolded or native, as client substrates, we identified the N-terminal a active site of PDIA1 as the main oxidant of thiols. From there, electrons can flow to the C-terminal a' active site, with the redox-dependent conformational flexibility of PDIA1 allowing the formation of an interdomain disulfide bond. The a' active site then acts as a crossing point to redirect electrons to ER downstream oxidases or back to client proteins to reduce scrambled disulfide bonds. Innovation and Conclusions: The two active sites of PDIA1 work cooperatively as an interdomain redox relay mechanism that explains PDIA1 oxidative activity to form native disulfides and PDIA1 reductase activity to resolve scrambled disulfides. This mechanism suggests a new rationale for shutting down oxidative protein folding under ER redox imbalance. Whether it applies to physiological substrates in cells remains to be shown.

Probing the legitimate initiation of RNA synthesis by Qβ replicase with oligonucleotide primers.

Oligoribonucleotides complementary to the template 3' terminus were tested for their ability to initiate RNA synthesis on legitimate templates capable of exponential amplification by Qβ replicase. Oligonucleotides shorter than the distance to the nearest predicted template hairpin proved able to serve as primers, with the optimal length varying for different templates, suggesting that during initiation the template retains its native fold incorporating the 3' terminus. The priming activity of an oligonucleotide is greatly enhanced by its 5'-triphosphate group, the effect being strongly dependent on Mg2+ ions. This indicates that, unlike other studied RNA polymerases, Qβ replicase binds the 5'-triphosphate of the initiating nucleotide GTP, and this binding is needed for the replication of legitimate templates.

Protein structure generation via folding diffusion.

The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases. Despite recent advances in protein structure prediction, directly generating diverse, novel protein structures from neural networks remains difficult. In this work, we present a diffusion-based generative model that generates protein backbone structures via a procedure inspired by the natural folding process. We describe a protein backbone structure as a sequence of angles capturing the relative orientation of the constituent backbone atoms, and generate structures by denoising from a random, unfolded state towards a stable folded structure. Not only does this mirror how proteins natively twist into energetically favorable conformations, the inherent shift and rotational invariance of this representation crucially alleviates the need for more complex equivariant networks. We train a denoising diffusion probabilistic model with a simple transformer backbone and demonstrate that our resulting model unconditionally generates highly realistic protein structures with complexity and structural patterns akin to those of naturally-occurring proteins. As a useful resource, we release an open-source codebase and trained models for protein structure diffusion.

Deep Learning Enables Automatic Correction of Experimental HDX-MS Data with Applications in Protein Modeling.

Observed mass shifts associated with deuterium incorporation in hydrogen-deuterium exchange mass spectrometry (HDX-MS) frequently deviate from the initial signals due to back and forward exchange. In typical HDX-MS experiments, the impact of these disparities on data interpretation is generally low because relative and not absolute mass changes are investigated. However, for more advanced data processing including optimization, experimental error correction is imperative for accurate results. Here the potential for automatic HDX-MS data correction using models generated by deep neural networks is demonstrated. A multilayer perceptron (MLP) is used to learn a mapping between uncorrected HDX-MS data and data with mass shifts corrected for back and forward exchange. The model is rigorously tested at various levels including peptide level mass changes, residue level protection factors following optimization, and ability to correctly identify native protein folds using HDX-MS guided protein modeling. AI is shown to demonstrate considerable potential for amending HDX-MS data and improving fidelity across all levels. With access to big data, online tools may eventually be able to predict corrected mass shifts in HDX-MS profiles. This should improve throughput in workflows that require the reporting of real mass changes as well as allow retrospective correction of historic profiles to facilitate new discoveries with these data.