A conserved folding nucleus sculpts the free energy landscape of bacterial and archaeal orthologs from a divergent TIM barrel family

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A

The surface hydration diffusivity of Bacillus subtilis Lipase A (BSLA) has been characterized by low-field Overhauser dynamic nuclear polarization (ODNP) relaxometry using a series of spin-labeled constructs. Sites for spin-label incorporation were previously designed via an atomistic computational approach that screened for surface exposure, reflective of the surface hydration comparable to other proteins studied by this method, as well as minimal impact on protein function, dynamics, and structure of BSLA by excluding any surface site that participated in greater than 30% occupancy of a hydrogen bonding network within BSLA. Experimental ODNP relaxometry coupling factor results verify the overall surface hydration behavior for these BSLA spin-labeled sites similar to other globular proteins. Here, by plotting the ODNP parameters of relative diffusive water versus the relative bound water, we introduce an effective "phase-space" analysis, which provides a facile visual comparison of the ODNP parameters of various biomolecular systems studied to date. We find notable differences when comparing BSLA to other systems, as well as when comparing different clusters on the surface of BSLA. Specifically, we find a grouping of sites that correspond to the spin-label surface location within the two main hydrophobic core clusters of the branched aliphatic amino acids isoleucine, leucine, and valine cores observed in the BSLA crystal structure. The results imply that hydrophobic clustering may dictate local surface hydration properties, perhaps through modulation of protein conformations and samplings of the unfolded states, providing insights into how the dynamics of the hydration shell is coupled to protein motion and fluctuations.

Immunoanalytical Detection of Conserved Peptides: Refining the Universe of Biomarker Targets in Planetary Exploration

Ancient peptides are remnants of early biochemistry that continue to play pivotal roles in current proteins. They are simple molecules yet complex enough to exhibit independent functions, being products of an evolved biochemistry at the interface of life and nonlife. Their adsorption to minerals may contribute to their stabilization and preservation over time. To investigate the feasibility of conserved peptide sequences and structures as target biomarkers for the search for life on Mars or other planetary bodies, we conducted a bioinformatics selection of well-conserved ancient peptides and produced polyclonal antibodies for their detection using fluorescence microarray immunoassays. Additionally, we explored how adsorbing peptides to Mars-representative minerals to form organomineral complexes could affect their immunological detection. The results demonstrated that the selected peptides exhibited autonomous folding, with some of them regaining their structure, even after denaturation. Furthermore, their cognate antibodies detected their conformational features regardless of amino acid sequences, thereby broadening the spectrum of target peptide sequences. While certain antibodies displayed unspecific binding to bare minerals, we validated that peptide-mineral complexes can be detected using sandwich immunoassays, as confirmed through desorption and competitive assays. Consequently, we conclude that the diversity of peptide sequences and structures suitable for use as target biomarkers in astrobiology can be constrained to a few well conserved sets, and they can be detected even if they are adsorbed in organomineral complexes.

Evaluating Mass Spectrometry-Based Hydroxyl Radical Protein Footprinting of a Benchtop Flash Oxidation System against a Synchrotron X-ray Beamline

Hydroxyl radical protein footprinting (HRPF) using synchrotron X-ray radiation (XFP) and mass spectrometry is a well-validated structural biology method that provides critical insights into macromolecular structural dynamics, such as determining binding sites, measuring affinity, and mapping epitopes. Numerous alternative sources for generating the hydroxyl radicals (•OH) needed for HRPF, such as laser photolysis and plasma irradiation, complement synchrotron-based HRPF, and a recently developed commercially available instrument based on flash lamp photolysis, the FOX system, enables access to laboratory benchtop HRPF. Here, we evaluate performing HRPF experiments in-house with a benchtop FOX instrument compared to synchrotron-based X-ray footprinting at the NSLS-II XFP beamline. Using lactate oxidase (LOx) as a model system, we carried out •OH labeling experiments using both instruments, followed by nanoLC-MS/MS bottom-up peptide mass mapping. Experiments were performed under high glucose concentrations to mimic the highly scavenging conditions present in biological buffers and human clinical samples, where less •OH are available for reaction with the biomolecule(s) of interest. The performance of the FOX and XFP HRPF methods was compared, and we found that tuning the •OH dosage enabled optimal labeling coverage for both setups under physiologically relevant highly scavenging conditions. Our study demonstrates the complementarity of FOX and XFP labeling approaches, demonstrating that benchtop instruments such as the FOX photolysis system can increase both the throughput and the accessibility of the HRPF technique.

Stepwise introduction of stabilizing mutations reveals nonlinear additive effects in de novo TIM barrels

Over the past decades, the TIM-barrel fold has served as a model system for the exploration of how changes in protein sequences affect their structural, stability, and functional characteristics, and moreover, how this information can be leveraged to design proteins from the ground up. After numerous attempts to design de novo proteins with this specific fold, sTIM11 was the first validated de novo design of an idealized four-fold symmetric TIM barrel. Subsequent efforts to enhance the stability of this initial design resulted in the development of DeNovoTIMs, a family of de novo TIM barrels with various stabilizing mutations. In this study, we present an investigation into the biophysical and thermodynamic effects upon introducing a varying number of stabilizing mutations per quarter along the sequence of a four-fold symmetric TIM barrel. We compared the base design DeNovoTIM0 without any stabilizing mutations with variants containing mutations in one, two, three, and all four quarters-designated TIM1q, TIM2q, TIM3q, and DeNovoTIM6, respectively. This analysis revealed a stepwise and nonlinear change in the thermodynamic properties that correlated with the number of mutated quarters, suggesting positive nonadditive effects. To shed light on the significance of the location of stabilized quarters, we engineered two variants of TIM2q which contain the same number of mutations but positioned in different quarter locations. Characterization of these TIM2q variants revealed that the mutations exhibit varying effects on the overall protein stability, contingent upon the specific region in which they are introduced. These findings emphasize that the amount and location of stabilized interfaces among the four quarters play a crucial role in shaping the conformational stability of these four-fold symmetric TIM barrels. Analysis of de novo proteins, as described in this study, enhances our understanding of how sequence variations can finely modulate stability in both naturally occurring and computationally designed proteins.

A rapid discriminative hydrogen-deuterium exchange and LC-HRMS/MS strategy for primary and higher order structural mapping of therapeutic proteins: a case study using filgrastim

A vast number of therapeutic proteins are approved and available on the market. However, there are very limited analytical approaches available for the rapid determination of primary and higher-order structures which can be utilized for counterfeit identification. In the present study, filgrastim biosimilar products from different manufacturers were considered for developing discriminative orthogonal analytical techniques to determine structural variations. The developed intact mass analytical method and peptide mapping through LC-HRMS were able to differentiate three biosimilars based on deconvoluted mass and possible structural modification, respectively. Another structural attribute employed was charge heterogeneity through isoelectric focusing, which provides a snapshot of the presence of charge variants/impurities and was able to differentiate various marketed formulations of filgrastim. These three techniques can certainly differentiate the products that contain counterfeit drugs due to their capability concerning selectivity. Additionally, a unique HDX technique on LC-HRMS was developed, which can determine the labile hydrogen exposed to deuterium exchange in a specified time. HDX aids in identifying the workup process or changes in the host cell in the counterfeit product by differentiating the protein based on its higher-order structure.

Circuit topology predicts pathogenicity of missense mutations

The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the rate of folding. Circuit topology is emerging as another fundamental descriptor of biomolecular structure, with predicted effects on the folding rate. We analyze the residue‐based circuit topological environments of 21 K mutations labeled as pathogenic or benign. Multiple statistical lines of reasoning support the conclusion that the number of contacts in two specific circuit topological arrangements, namely inverse parallel and cross relations, with contacts involving the mutated residue have discriminatory value in determining the pathogenicity of human variants. We investigate how results vary with residue type and according to whether the gene is essential. We further explore the relationship to a number of structural features and find that circuit topology provides nonredundant information on protein structures and pathogenicity of mutations. Results may have implications for the polymer physics of protein folding and suggest that “local” topological information, including residue‐based circuit topology and residue contact order, could be useful in improving state‐of‐the‐art machine learning algorithms for pathogenicity prediction.

Multiplex Chemical Labeling of Amino Acids for Protein Footprinting Structure Assessment

Protein footprinting with mass spectrometry is an established structural biology technique for mapping solvent accessibility and assessing molecular-level interactions of proteins. In hydroxyl radical protein footprinting (HRPF), hydroxyl (OH) radicals generated by water radiolysis or other methods covalently label protein side chains. Because of the wide dynamic range of OH reactivity, not all side chains are easily detected in a single experiment. Novel reagent development and the use of radical chain reactions for labeling, including trifluoromethyl radicals, is a potential approach to normalize the labeling across a diverse set of residues. HRPF in the presence of a trifluoromethylation reagent under the right conditions could provide a "one-pot" reaction for multiplex labeling of protein side chains. Toward this goal, we have systematically evaluated amino acid labeling with the recently investigated Langlois' reagent (LR) activated by X-ray-mediated water radiolysis, followed by three different mass spectrometry methods. We compared the reactivity of CF₃ and OH radical labeling for all 20 protein side chains in a competition-free environment. We found that all 20 amino acids exhibited CF₃ or OH labeling in LR. Our investigations provide the evidence and knowledge set to perfect hydroxyl radical-activated trifluoromethyl chemistry as "one-pot" reaction for multiplex labeling of protein side chains to achieve higher resolution in HRPF.

Folding and Evolution of a Repeat Protein on the Ribosome

Life on earth is the result of the work of proteins, the cellular nanomachines that fold into elaborated 3D structures to perform their functions. The ribosome synthesizes all the proteins of the biosphere, and many of them begin to fold during translation in a process known as cotranslational folding. In this work we discuss current advances of this field and provide computational and experimental data that highlight the role of ribosome in the evolution of protein structures. First, we used the sequence of the Ankyrin domain from the Drosophila Notch receptor to launch a deep sequence-based search. With this strategy, we found a conserved 33-residue motif shared by different protein folds. Then, to see how the vectorial addition of the motif would generate a full structure we measured the folding on the ribosome of the Ankyrin repeat protein. Not only the on-ribosome folding data is in full agreement with classical in vitro biophysical measurements but also it provides experimental evidence on how folded proteins could have evolved by duplication and fusion of smaller fragments in the RNA world. Overall, we discuss how the ribosomal exit tunnel could be conceptualized as an active site that is under evolutionary pressure to influence protein folding.

Rational Design of Protein-Specific Folding Modifiers

Protein-folding can go wrong in vivo and in vitro, with significant consequences for the living organism and the pharmaceutical industry, respectively. Here we propose a design principle for small-peptide-based protein-specific folding modifiers. The principle is based on constructing a "xenonucleus", which is a prefolded peptide that mimics the folding nucleus of a protein. Using stopped-flow kinetics, NMR spectroscopy, Förster resonance energy transfer, single-molecule force measurements, and molecular dynamics simulations, we demonstrate that a xenonucleus can make the refolding of ubiquitin faster by 33 ± 5%, while variants of the same peptide have little or no effect. Our approach provides a novel method for constructing specific, genetically encodable folding catalysts for suitable proteins that have a well-defined contiguous folding nucleus.

Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders

Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.

Pharmacological chaperones are small molecule drugs that bind to proteins to help stabilize the folded state. One set of diseases for which this treatment has been effective is the lysosomal storage disorders, which are caused by defective lysosomal enzymes. However, not all genotypes are equally responsive to treatment. For instance, missense mutants that are particularly destabilized relative to WT are less likely to respond. The availability of datasets containing responsiveness data for large numbers of mutants, along with crystal structures of the protein involved in each disease, make machine learning methods incorporating sequence-based and structural data feasible. We hypothesize that data from two diseases, Fabry and Pompe disease, may be useful for predicting responsiveness of variants in the related Gaucher disease. Results suggest that many rare variants in Gaucher disease could be amenable to existing drugs. Results also suggest that drug responsiveness depends on protein topology in such a way that mutations in early-to-fold residues are more likely to be non-responsive to pharmacological chaperone treatment, which is consistent with a simple kinetic model of stability rescue. This study provides an example of how machine learning can be used to inform further studies towards personalized treatment in medicine.