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Results for “Protein Structure, Secondary”

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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure

Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toho-1 β-lactamase: backbone chemical shift assignments and changes in dynamics upon binding with avibactam

Backbone chemical shift assignments for the Toho-1 β-lactamase (263 amino acids, 28.9 kDa) are reported based on triple resonance solution-state NMR experiments performed on a uniformly 2 H, 13 C, 15 N-labeled sample. These assignments allow for subsequent site-specific characterization at the chemical, structural, and dynamical levels. At the chemical level, titration with the non-β-lactam β-lactamase inhibitor avibactam is found to give chemical shift perturbations indicative of tight covalent binding that allow for mapping of the inhibitor binding site. At the structural level, protein secondary structure is predicted based on the backbone chemical shifts and protein residue sequence using TALOS-N and found to agree well with structural characterization from X-ray crystallography. At the dynamical level, model-free analysis of 15 N relaxation data at a single field of 16.4 T reveals well-ordered structures for the ligand-free and avibactam-bound enzymes with generalized order parameters of ~0.85. Complementary relaxation dispersion experiments indicate that there is an escalation in motions on the millisecond timescale in the vicinity of the active site upon substrate binding. The combination of high rigidity on short timescales and active site flexibility on longer timescales is consistent with hypotheses for achieving both high catalytic efficiency and broad substrate specificity: the induced active site dynamics allows variously sized substrates to be accommodated and increases the probability that the optimal conformation for catalysis will be sampled.

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

A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

Chemistry↗
DOE OSTI2025

PNNL-Predictive-Phenomics/ProCaliper

ProCaliper is a Python library that curates, organizes, and computes protein structure features in a way that easily interfaces with user-provided experimental data. It extracts or computes protein binding site, active site, charge, pLDDT (order/disorder), acid dissociation, protonation, solvent accessible surface area, disulfide bond distance, and protein secondary structure data using precomputed protein structures and publicly available databases. It provides a unified API for integrating additional residue-level data and for visualizing residue features in 3D.

Rozum, Jordan [Pacific Northwest National Lab]↗
DOE OSTI2019

Systematic sequencing of chloroplast transcript termini from Arabidopsis thaliana reveals >200 transcription initiation sites and the extensive imprints of RNA-binding proteins and secondary structures

Abstract Chloroplast transcription requires numerous quality control steps to generate the complex but selective mixture of accumulating RNAs. To gain insight into how this RNA diversity is achieved and regulated, we systematically mapped transcript ends by developing a protocol called Terminome-seq. Using Arabidopsis thaliana as a model, we catalogued >215 primary 5′ ends corresponding to transcription start sites (TSS), as well as 1628 processed 5′ ends and 1299 3′ ends. While most termini were found in intergenic regions, numerous abundant termini were also found within coding regions and introns, including several major TSS at unexpected locations. A consistent feature was the clustering of both 5′ and 3′ ends, contrasting with the prevailing description of discrete 5′ termini, suggesting an imprecision of the transcription and/or RNA processing machinery. Numerous termini correlated with the extremities of small RNA footprints or predicted stem-loop structures, in agreement with the model of passive RNA protection. Terminome-seq was also implemented for pnp1–1, a mutant lacking the processing enzyme polynucleotide phosphorylase. Nearly 2000 termini were altered in pnp1–1, revealing a dominant role in shaping the transcriptome. In summary, Terminome-seq permits precise delineation of the roles and regulation of the many factors involved in organellar transcriptome quality control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Stereochemistry of polypeptoid chain configurations

Abstract Like polypeptides, peptoids, or N ‐substituted glycine oligomers, have intrinsic conformational preferences due to their amide backbones and close spacing of side chain substituents. However, the conformations that peptoids adopt are distinct from polypeptides due to several structural differences: the peptoid backbone is composed of tertiary amide bonds that have trans and cis conformers similar in energy, they lack a backbone hydrogen bond donor, and have an N ‐substituent. To better understand how these differences manifest in actual peptoid structures, we analyzed 46 high quality, experimentally determined peptoid structures reported in the literature to extract their backbone conformational preferences. One hundred thirty‐two monomer dihedral angle pairs were compared to the calculated energy landscape for the peptoid Ramachandran plot, and were found to fall within the expected minima. Interestingly, only two regions of the backbone dihedral angles ϕ and ψ were found to be populated that are mirror images of each other. Furthermore, these two conformers are present in both cis and trans forms. Thus, there are four primary conformers that are sufficient to describe almost all known backbone conformations for peptoid oligomers, despite conformational constraints imposed by a variety of side chains, macrocyclization, or crystal packing forces. Because these conformers are predominant in peptoid structure, and are distinct from those found in protein secondary structures, we propose a simple naming system to aid in the description and classification of peptoid structure.

Spencer, Ryan K.↗
DOE OSTI2017

Hydrogen bonds are a primary driving force for de novo protein folding

The protein-folding mechanism remains a major puzzle in life science. Purified soluble activation-induced cytidine deaminase (AID) is one of the most difficult proteins to obtain. Starting from inclusion bodies containing a C-terminally truncated version of AID (residues 1–153; AID 153 ), an optimized in vitro folding procedure was derived to obtain large amounts of AID 153 , which led to crystals with good quality and to final structural determination. Interestingly, it was found that the final refolding yield of the protein is proline residue-dependent. The difference in the distribution of cis and trans configurations of proline residues in the protein after complete denaturation is a major determining factor of the final yield. A point mutation of one of four proline residues to an asparagine led to a near-doubling of the yield of refolded protein after complete denaturation. It was concluded that the driving force behind protein folding could not overcome the cis -to- trans proline isomerization, or vice versa , during the protein-folding process. Furthermore, it was found that successful refolding of proteins optimally occurs at high pH values, which may mimic protein folding in vivo . It was found that high pH values could induce the polarization of peptide bonds, which may trigger the formation of protein secondary structures through hydrogen bonds. It is proposed that a hydrophobic environment coupled with negative charges is essential for protein folding. Combined with our earlier discoveries on protein-unfolding mechanisms, it is proposed that hydrogen bonds are a primary driving force for de novo protein folding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structure of the Core Postfusion Porcine Endogenous Retrovirus Fusion Protein

Retroviral elements from endogenous retroviruses have functions in mammalian physiology. The best-known examples are the envelope proteins that function in placenta development and immune suppression. Porcine endogenous retroviruses (PERVs) are an understudied class of endogenous retroviruses that infect cultured human cells, raising concern regarding porcine xenografts. The PERV envelope glycoprotein has also been proposed as a possible swine syncytin with a role in placental development. Despite the growing interest in PERVs, their envelope glycoproteins remain poorly characterized. Here, we successfully determined the postfusion crystal structure of the PERV core fusion ectodomain. The PERV fusion protein structure reveals a conserved class I viral fusion protein six-helix bundle. Biophysical experiments demonstrated that the thermodynamic stability of the PERV fusion protein secondary structure was the same at physiological and acidic pHs. A conserved surface analysis highlights the high degree of sequence conservation among retroviral fusogens in the chain reversal region that facilitates the large-scale conformational change required for membrane fusion. Further structural alignment of class I viral fusogens revealed a phylogenetic clustering that shows evolution into various lineages that correlate with virus mechanisms of cell entry. Our work indicates that structural dendrograms can be used to qualitatively infer insights into the fusion mechanisms of newly discovered class I viral fusogen structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Long-term, non-invasive FTIR detection of low-dose ionizing radiation exposure

Non-invasive methods of detecting radiation exposure show promise to improve upon current approaches to biological dosimetry in ease, speed, and accuracy. Here we developed a pipeline that employs Fourier transform infrared (FTIR) spectroscopy in the mid-infrared spectrum to identify a signature of low dose ionizing radiation exposure in mouse ear pinnae over time. Mice exposed to 0.1 to 2 Gy total body irradiation were repeatedly measured by FTIR at the stratum corneum of the ear pinnae. We found significant discriminative power for all doses and time-points out to 90 days after exposure. Classification accuracy was maximized when testing 14 days after exposure (specificity > 0.9 with a sensitivity threshold of 0.9) and dropped by roughly 30% sensitivity at 90 days. Infrared frequencies point towards biological changes in DNA conformation, lipid oxidation and accumulation and shifts in protein secondary structure. Since only hundreds of samples were used to learn the highly discriminative signature, developing human-relevant diagnostic capabilities is likely feasible and this non-invasive procedure points toward rapid, non-invasive, and reagent-free biodosimetry applications at population scales.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Post-translational thioamidation of methyl-coenzyme M reductase, a key enzyme in methanogenic and methanotrophic Archaea

Methyl-coenzyme M reductase (MCR), found in strictly anaerobic methanogenic and methanotrophic archaea, catalyzes the reversible production and consumption of the potent greenhouse gas methane. The α subunit of MCR (McrA) contains several unusual post-translational modifications, including a rare thioamidation of glycine. Based on the presumed function of homologous genes involved in the biosynthesis of thioviridamide, a thioamide-containing natural product, we hypothesized that the archaeal tfuA and ycaO genes would be responsible for post-translational installation of thioglycine into McrA. Mass spectrometric characterization of McrA from the methanogenic archaeon Methanosarcina acetivorans lacking tfuA and/or ycaO revealed the presence of glycine, rather than thioglycine, supporting this hypothesis. Phenotypic characterization of the ∆ycaO-tfuA mutant revealed a severe growth rate defect on substrates with low free energy yields and at elevated temperatures (39°C - 45°C). Our analyses support a role for thioglycine in stabilizing the protein secondary structure near the active site.

03 NATURAL GAS↗
DOE OSTI2023

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

We report two generative deep-learning models that predict amino acid sequences and 3D protein structures on the basis of secondary-structure design objectives via either the overall content or the per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity because they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary-structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in the conditional generative design of various biological or engineering systems. Future work could include additional conditioning and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Conformations of peptoids in nanosheets result from the interplay of backbone energetics and intermolecular interactions

Significance Commonly observed secondary structures of proteins, such as α -helices and β -sheets, are built from a trans- amide backbone with residues sampling a single region of the Ramachandran plot. Here we report a secondary structure displayed by biomimetic peptoid polymers in which the backbone exhibits the cis conformation and alternating residues display rotational states of opposed (pseudo)chirality. This structure is linear and untwisted and enables strands to pack densely into extended bilayer nanosheets.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Hybrid Metasurface-Based Mid-Infrared Biosensor for Simultaneous Quantification and Identification of Monolayer Protein

Metasurfaces emerge as a promising photonic platform for biosensing because they offer strong optical confinement and tunable optical resonances. Here, we show that metasurface-based biosensors consisting of gold nanoantenna arrays loaded with graphene and working in the mid-infrared (mid-IR) spectral range can achieve simultaneous high-sensitivity and high-specificity detection of biomolecules. Strong light–molecule interactions in deeply subwavelength optical spots created by the biosensors allow us to determine the concentration of protein molecules via spectral shifts of the metasurface resonance. A combination of passive and active tuning of the metasurface sensors allows us to spectrally overlap the metasurface resonance and the protein vibrational modes, so that protein molecules can be identified via their characteristic mid-IR “fingerprints”. As a result, the high sensitivity and specificity of the metasurface sensors enable us to determine the secondary structure of protein immunoglobulin (IgG) molecules 4 orders of magnitude more sensitive than attenuated total reflection Fourier transform infrared spectroscopy.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Early Stage Detection of Stress Due to Copper on Maize (Zea mays L.) by Laser-Induced Fluorescence and Infrared Spectroscopy

Laser-induced fluorescence (LIF) and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been applied for the nondestructive, label free, and rapid analyses of the impact of copper (25, 50, and 75 μM) on maize seedlings at an early stage before the changes appear visually on the plant. The LIF measurement has been used to detect the signs of stress in the photosynthetic pigment. The integrated areal intensity and increasing fluorescence intensity ratios indicate decrease in the photosynthetic pigments in the leaves of maize plants stressed with copper. The ATR-FTIR technique has been utilized to estimate the changes arising in the cell wall polysaccharides, amino acid, secondary structure of protein and lipid content of the leaves of control and copper-treated maize seedlings. The second derivative and curve fitting analyses have been applied for the enhancement of the spectral variations and quantitative estimation of the changes arising in the biochemical profile. The result shows an increase in the pectin, lignin, amino acid, and protein content and reduction in the amount of cellulose and lipid in the leaves of maize seedlings due to the treatment of copper. This study indicates the toxic response of copper by hampering the growth and reduction in the photosynthetic pigments and biochemical content of the maize seedlings. This study also demonstrates the feasibility of the spectroscopic techniques (LIF and ATRFTIR) as a rapid, label free, and nondestructive probe for the assessment of stress and monitoring of crops.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

FTIR Spectroscopy of Protein Isolates of Salt-Tolerant Soybean Mutants

The effect of salinity on the conformation of proteins of four salt-tolerant M{sub 2} generation mutants of soybean plants (S04-05/150-2, S04-05/150-8, S04-05/150-106, and S04-05/150-114) was investigated using Fourier transform infrared (FTIR) spectroscopy. Salinity is one of the important abiotic stress factors that limits growth and productivity of plants. The mutants belonging to the M{sub 2} generation were determined as tolerant to 90 mM NaCl. The relative contents of α-helix, β-sheet, turn, and irregular conformations for the soybean protein isolates were determined depending on the analysis of the amide I region. The comparison of the secondary structures of soybean proteins of the mutants with those of the control group indicated that the α-helix structure percentage was diminished while β-turn and disordered structures were increased as a result of the salt stress.

60 APPLIED LIFE SCIENCES↗