Search NASA⌕ Search

SEARCH · Search NASA

Results for “Protein interactions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗
NASA NTRS1994

Pr-specific phytochrome phosphorylation in vitro by a protein kinase present in anti-phytochrome maize immunoprecipitates

Protein kinase activity has repeatedly been found to co-purify with the plant photoreceptor phytochrome, suggesting that light signals received by phytochrome may be transduced or modulated through protein phosphorylation. In this study immunoprecipitation techniques were used to characterize protein kinase activity associated with phytochrome from maize (Zea mays L.). A protein kinase that specifically phosphorylated phytochrome was present in washed anti-phytochrome immunoprecipitates of etiolated coleoptile proteins. No other substrate tested was phosphorylated by this kinase. Adding salts or detergents to disrupt low-affinity protein interactions reduced background phosphorylation in immunoprecipitates without affecting phytochrome phosphorylation, indicating that the protein kinase catalytic activity is either intrinsic to the phytochrome molecule or associated with it by high-affinity interactions. Red irradiation (of coleoptiles or extracts) sufficient to approach photoconversion saturation reduced phosphorylation of immunoprecipitated phytochrome. Subsequent far-red irradiation reversed the red-light effect. Phytochrome phosphorylation was stimulated about 10-fold by a co-immunoprecipitated factor. The stimulatory factor was highest in immunoprecipitates when Mg2+ was present in immunoprecipitation reactions but remained in the supernatant in the absence of Mg2+. These observations provide strong support for the hypothesis that phytochrome-associated protein kinase modulates light responses in vivo. Since only phytochrome was found to be phosphorylated, the co-immunoprecipitated protein kinase may function to regulate receptor activity.

NASA Discipline Plant Biology↗
DOE OSTI2023

Bioexcitons by Design: How Do We Get There?

Biological pigment-protein complexes (PPCs) exhibit a remarkable ability to tune the optical properties of biological excitons (bioexcitons) through specific pigment-protein interactions. While such fine-tuning allows natural systems (e.g., photosynthetic proteins) to carry out their native functions with near-optimal performance, native function itself is often suboptimal for applications such as biofuel production or quantum technology development. Furthermore, this perspective offers a look at near-term prospects for the rational reoptimization of PPC bioexcitons for new functions using site-directed mutagenesis. The primary focus is on the "structure-spectrum" challenge of understanding the relationships between structural features and spectroscopic properties. While recent examples demonstrate that site-directed mutagenesis can be used to tune nearly all key bioexciton parameters (e.g., site energies, inter-pigment couplings, and electronic-vibrational interactions), critical challenges remain before we achieve truly rational design of bioexciton properties.

09 BIOMASS FUELS↗
DOE OSTI2022

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Multivalent interactions between CsoS2 and Rubisco mediate α-carboxysome formation

Carboxysomes are bacterial microcompartments that function as the centerpiece of the bacterial CO 2 -concentrating mechanism by facilitating high CO 2 concentrations near the carboxylase Rubisco. The carboxysome self-assembles from thousands of individual proteins into icosahedral-like particles with a dense enzyme cargo encapsulated within a proteinaceous shell. In the case of the α-carboxysome, there is little molecular insight into protein–protein interactions that drive the assembly process. In this work, studies on the α-carboxysome from Halothiobacillus neapolitanus demonstrate that Rubisco interacts with the N terminus of CsoS2, a multivalent, intrinsically disordered protein. X-ray structural analysis of the CsoS2 interaction motif bound to Rubisco reveals a series of conserved electrostatic interactions that are only made with properly assembled hexadecameric Rubisco. Although biophysical measurements indicate that this single interaction is weak, its implicit multivalency induces high-affinity binding through avidity. Taken together, our results indicate that CsoS2 acts as an interaction hub to condense Rubisco and enable efficient α-carboxysome formation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Water as a matrix for life

Life is based on non-covalent interactions. They might be either specific (enzyme-substrate interactions, selective ion transport) or nonspecific (lipid-lipid and lipid-protein interactions needed for membrane integrity, fusion and division). Their strength needs to be properly tuned, and this is mediated by the solvent. If interactions are too weak, there might be undesired response to natural fluctuations of physical and chemical parameters. If they are too strong it could impede kinetics and energetics of cellular processes. Thus, the solvent must allow for balancing these interactions. Physical and chemical properties of solvent provide strong constraints for life. Water exhibits a remarkable trait that it promotes both solvophobic and solvophilic interactions. Solvophobic interactions; related to high dielectric constant of the solvent) are necessary for self-organization of matter whereas solvophilic interactions are needed to ensure solubility of polar species. Water offers a large temperature domain of stable liquid and the characteristics hydrophobic effects are a consequence of the temperature in sensitivity of essential properties of its liquid state. Water, however, is not the only liquid with these favorable properties. I will compare in detail properties of water and other pure liquids or their mixtures that have a high dielectric constant and simultaneously support self-organization. I will also discuss properties of water that are unfavorable to life (e.g. its chemical activity against polymerization reactions) and close with summarizing what are alternatives to water as a matrix of life in space.

Pohorille, Andrew↗
DOE OSTI2023

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning

Deep learning methods that achieved great success in predicting intrachain residue-residue contacts have been applied to predict interchain contacts between proteins. However, these methods require multiple sequence alignments (MSAs) of a pair of interacting proteins (dimers) as input, which are often difficult to obtain because there are not many known protein complexes available to generate MSAs of sufficient depth for a pair of proteins. In recognizing that multiple sequence alignments of a monomer that forms homomultimers contain the co-evolutionary signals of both intrachain and interchain residue pairs in contact, we applied DNCON2 (a deep learning-based protein intrachain residue-residue contact predictor) to predict both intrachain and interchain contacts for homomultimers using multiple sequence alignment (MSA) and other co-evolutionary features of a single monomer followed by discrimination of interchain and intrachain contacts according to the tertiary structure of the monomer. We name this tool DNCON2_Inter. Allowing true-positive predictions within two residue shifts, the best average precision was obtained for the Top-L/10 predictions of 22.9% for homodimers and 17.0% for higher-order homomultimers. In some instances, especially where interchain contact densities are high, DNCON2_Inter predicted interchain contacts with 100% precision. We also developed Con_Complex, a complex structure reconstruction tool that uses predicted contacts to produce the structure of the complex. Using Con_Complex, we show that the predicted contacts can be used to accurately construct the structure of some complexes. Our experiment demonstrates that monomeric multiple sequence alignments can be used with deep learning to predict interchain contacts of homomeric proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

MONACO: accurate biological network alignment through optimal neighborhood matching between focal nodes

Motivation: Alignment of protein–protein interaction networks can be used for the unsupervised prediction of functional modules, such as protein complexes and signaling pathways, that are conserved across different species. To date, various algorithms have been proposed for biological network alignment, many of which attempt to incorporate topological similarity between the networks into the alignment process with the goal of constructing accurate and biologically meaningful alignments. Especially, random walk models have been shown to be effective for quantifying the global topological relatedness between nodes that belong to different networks by diffusing node-level similarity along the interaction edges. However, these schemes are not ideal for capturing the local topological similarity between nodes. Results: Here, we propose MONACO, a novel and versatile network alignment algorithm that finds highly accurate pairwise and multiple network alignments through the iterative optimal matching of ‘local’ neighborhoods around focal nodes. Extensive performance assessment based on real networks as well as synthetic networks, for which the ground truth is known, demonstrates that MONACO clearly and consistently outperforms all other state-of-the-art network alignment algorithms that we have tested, in terms of accuracy, coherence and topological quality of the aligned network regions. Furthermore, despite the sharply enhanced alignment accuracy, MONACO remains computationally efficient and it scales well with increasing size and number of networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

Protein machines and self assembly in muscle organization

The remarkable order of striated muscle is the result of a complex series of protein interactions at different levels of organization. Within muscle, the thick filament and its major protein myosin are classical examples of functioning protein machines. Our understanding of the structure and assembly of thick filaments and their organization into the regular arrays of the A-band has recently been enhanced by the application of biochemical, genetic, and structural approaches. Detailed studies of the thick filament backbone have shown that the myosins are organized into a tubular structure. Additional protein machines and specific myosin rod sequences have been identified that play significant roles in thick filament structure, assembly, and organization. These include intrinsic filament components, cross-linking molecules of the M-band and constituents of the membrane-cytoskeleton system. Muscle organization is directed by the multistep actions of protein machines that take advantage of well-established self-assembly relationships. Copyright 1999 John Wiley & Sons, Inc.

NASA Discipline Musculoskeletal↗
NASA NTRS1971

Experimental investigation on the origin of the genetic code.

A simple model of interacting complex systems of species is tested to assess the binding behavior of monomeric nucleic acid and protein components during evolution. Nine representative amino acids are immobilized by the formation of an amide linkage on a prepared chromatographic support. Selective binding of ribonucleoside 5-phosphates in these amino acids is achieved under standardized conditions, and a site-binding model is derived to characterize the binding. It is shown that the binding behavior of the reactants during nucleic acid-protein interactions depends on the nature of the base and the amino acid. The results of the study are assessed as useful for the interpretation of more complex nucleic acid-protein systems and of their role in the evolution of the cell.

Saxinger, C.↗
DOE OSTI2021

Hotspot Coevolution Is a Key Identifier of Near-Native Protein Complexes

Protein–protein interactions play a key role in mediating numerous biological functions, with more than half the proteins in living organisms existing as either homo- or hetero-oligomeric assemblies. Protein subunits that form oligomers minimize the free energy of the complex, but exhaustive computational search-based docking methods have not comprehensively addressed the challenge of distinguishing a natively bound complex from non-native forms. Current protein docking approaches address this problem by sampling multiple binding modes in proteins and scoring each mode, with the lowest-energy (or highest scoring) binding mode being regarded as a near-native complex. However, high-scoring modes often match poorly with the true bound form, suggesting a need for improvement of the scoring function. Here in this study, we propose a scoring function, KFC-E, that accounts for both conservation and coevolution of putative binding hotspot residues at protein–protein interfaces. We tested KFC-E on four benchmark sets of unbound examples and two benchmark sets of bound examples, with the results demonstrating a clear improvement over scores that examine conservation and coevolution across the entire interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Determination of affinities of lanthanide-binding proteins using chelator-buffered titrations

The recent discoveries of the first proteins that bind lanthanides as part of their biological function not only are relevant to the emerging field of lanthanide-dependent biology, but also hold promise to revolutionize the technologically critical rare earths industry. Although protocols to assess the thermodynamics of metal–protein interactions are well established for “traditional” metal ions in biology, the characterization of lanthanide-binding proteins presents a challenge to biochemists due to the lanthanides' Lewis acidity, propensity for hydrolysis, and high-affinity complexes with biological ligands. These properties necessitate the preparation of metal stock solutions with very low buffered “free” metal concentrations (e.g., femtomolar to nanomolar) for such determinations. Here in this paper we describe several protocols to overcome these challenges. First, we present standardization methods for the preparation of chelator-buffered solutions of lanthanide ions with easily calculated free metal concentrations. We also describe how these solutions can be used in concert with analytical methods including UV–visible spectrophotometry, circular dichroism spectroscopy, Förster resonance energy transfer (FRET), and sensitized terbium luminescence, in order to accurately determine dissociation constants (K d s) of lanthanide–protein complexes. Finally, we highlight how application of these methods to lanthanide-binding proteins, such as lanmodulin, has yielded insights into selective recognition of lanthanides in biology. We anticipate that these protocols will facilitate discovery and characterization of additional native lanthanide-binding proteins, will motivate the understanding of their biological context, and will prompt their applications in biotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

CUT&RUN identifies centromeric DNA regions of Rhodotorula toruloides IFO0880

ABSTRACT Rhodotorula toruloides has been increasingly explored as a host for bioproduction of lipids, fatty acid derivatives and terpenoids. Various genetic tools have been developed, but neither a centromere nor an autonomously replicating sequence (ARS), both necessary elements for stable episomal plasmid maintenance, has yet been reported. In this study, cleavage under targets and release using nuclease (CUT&RUN), a method used for genome-wide mapping of DNA–protein interactions, was used to identify R. toruloides IFO0880 genomic regions associated with the centromeric histone H3 protein Cse4, a marker of centromeric DNA. Fifteen putative centromeres ranging from 8 to 19 kb in length were identified and analyzed, and four were tested for, but did not show, ARS activity. These centromeric sequences contained below average GC content, corresponded to transcriptional cold spots, were primarily nonrepetitive and shared some vestigial transposon-related sequences but otherwise did not show significant sequence conservation. Future efforts to identify an ARS in this yeast can utilize these centromeric DNA sequences to improve the stability of episomal plasmids derived from putative ARS elements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Small molecule microarray identifies inhibitors of tyrosyl-DNA phosphodiesterase 1 that simultaneously access the catalytic pocket and two substrate binding sites

Tyrosyl-DNA phosphodiesterase 1 (TDP1) is a member of the phospholipase D family of enzymes, which catalyzes the removal of both 3'- and 5'-DNA phosphodiester adducts. Importantly, it is capable of reducing the anticancer effects of type I topoisomerase (TOP1) inhibitors by repairing the stalled covalent complexes of TOP1 with DNA. It achieves this by promoting the hydrolysis of the phosphodiester bond between the Y723 residue of human TOP1 and the 3'-phosphate of its DNA substrate. Blocking TDP1 function is an attractive means of enhancing the efficacy of TOP1 inhibitors and overcoming drug resistance. Previously, we reported the use of an X-ray crystallographic screen of more than 600 fragments to identify small molecule variations on phthalic acid and hydroxyquinoline motifs that bind within the TDP1 catalytic pocket. Yet, the majority of these compounds showed limited (millimolar) TDP1 inhibitory potencies. We now report examining a 21 000-member library of drug-like Small Molecules in Microarray (SMM) format for their ability to bind Alexa Fluor 647 (AF647)-labeled TDP1. The screen identified structurally similar N,2-diphenylimidazo[1,2-a]pyrazin-3-amines as TDP1 binders and catalytic inhibitors. We then explored the core heterocycle skeleton using one-pot Groebke–Blackburn–Bienayme multicomponent reactions and arrived at analogs having higher inhibitory potencies. Solving TDP1 co-crystal structures of a subset of compounds showed their binding at the TDP1 catalytic site, while mimicking substrate interactions. Although our original fragment screen differed significantly from the current microarray protocol, both methods identified ligand–protein interactions containing highly similar elements. Importantly inhibitors identified through the SMM approach show competitive inhibition against TDP1 and access the catalytic phosphate-binding pocket, while simultaneously providing extensions into both the substrate DNA and peptide-binding channels. As such, they represent a platform for further elaboration of trivalent ligands, that could serve as a new genre of potent TDP1 inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Charged Biological Membranes Repel Large Neutral Molecules by Surface Dielectrophoresis and Counterion Pressure

Macromolecular crowding is the usual condition of cells. The implications of the crowded cellular environment for protein stability and folding, protein–protein interactions, and intracellular transport drive a growing interest in quantifying the effects of crowding. While the properties of crowded solutions have been extensively studied, less attention has been paid to the interaction of crowders with the cellular boundaries, i.e., membranes. However, membranes are key components of cells and most subcellular organelles, playing a central role in regulating protein channel and receptor functions by recruiting and binding charged and neutral solutes. While membrane interactions with charged solutes are dominated by electrostatic forces, here we show that significant charge-induced forces also exist between membranes and neutral solutes. Using neutron reflectometry measurements and molecular dynamics simulations of poly(ethylene glycol) (PEG) polymers of different molecular weights near charged and neutral membranes, we demonstrate the roles of surface dielectrophoresis and counterion pressure in repelling PEG from charged membrane surfaces. The resulting depletion zone is expected to have consequences for drug design and delivery, the activity of proteins near membrane surfaces, and the transport of small molecules along the membrane surface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification of structural transitions in bacterial fatty acid binding proteins that permit ligand entry and exit at membranes

Fatty acid (FA) transfer proteins extract FA from membranes and sequester them to facilitate their movement through the cytosol. Detailed structural information is available for these soluble protein–FA complexes, but the structure of the protein conformation responsible for FA exchange at the membrane is unknown. Staphylococcus aureus FakB1 is a prototypical bacterial FA transfer protein that binds palmitate within a narrow, buried tunnel. Here, we define the conformational change from a “closed” FakB1 state to an “open” state that associates with the membrane and provides a path for entry and egress of the FA. Using NMR spectroscopy, we identified a conformationally flexible dynamic region in FakB1, and X-ray crystallography of FakB1 mutants captured the conformation of the open state. In addition, molecular dynamics simulations show that the new amphipathic α-helix formed in the open state inserts below the phosphate plane of the bilayer to create a diffusion channel for the hydrophobic FA tail to access the hydrocarbon core and place the carboxyl group at the phosphate layer. The membrane binding and catalytic properties of site-directed mutants were consistent with the proposed membrane docked structure predicted by our molecular dynamics simulations. Finally, the structure of the bilayer-associated conformation of FakB1 has local similarities with mammalian FA binding proteins and provides a conceptual framework for how these proteins interact with the membrane to create a diffusion channel from the FA location in the bilayer to the protein interior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structure and identification of the native PLP synthase complex from Methanosarcina acetivorans lysate

Many protein-protein interactions behave differently in biochemically purified forms as compared to their in vivo states. As such, determining native protein structures may elucidate structural states previously unknown for even well-characterized proteins. Here, we apply the bottom-up structural proteomics method, cryoID , toward a model methanogenic archaeon. While they are keystone organisms in the global carbon cycle and active members of the human microbiome, there is a general lack of characterization of methanogen enzyme structure and function. Through the cryoID approach, we successfully reconstructed and identified the native Methanosarcina acetivorans pyridoxal 5′-phosphate (PLP) synthase (PdxS) complex directly from cryogenic electron microscopy (cryo-EM) images of fractionated cellular lysate. We found that the native PdxS complex exists as a homo-dodecamer of PdxS subunits, and the previously proposed supracomplex containing both the synthase (PdxS) and glutaminase (PdxT) was not observed in cellular lysate. Our structure shows that the native PdxS monomer fashions a single 8α/8β TIM-barrel domain, surrounded by seven additional helices to mediate solvent and interface contacts. A density is present at the active site in the cryo-EM map and is interpreted as ribose 5-phosphate. In addition to being the first reconstruction of the PdxS enzyme from a heterogeneous cellular sample, our results reveal a departure from previously published archaeal PdxS crystal structures, lacking the 37-amino-acid insertion present in these prior cases. This study demonstrates the potential of applying the cryoID workflow to capture native structural states at atomic resolution for archaeal systems, for which traditional biochemical sample preparation is nontrivial.

Methanosarcina acetivorans↗