Search NASA⌕ Search

SEARCH · Search NASA

Results for “Protein Science”

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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

J-domain proteins interaction with neurodegenerative disease-related proteins

HSP70 chaperones, J-domain proteins (JDPs) and nucleotide exchange factors (NEF) form functional networks that have the ability to prevent and reverse the aggregation of proteins associated with neurodegenerative diseases. JDPs can interact with specific substrate proteins, hold them in a refolding-competent conformation and target them to specific HSP70 chaperones for remodeling. Thereby, JDPs select specific substrates and constitute an attractive target for pharmacological intervention of neurodegenerative diseases. This, under the condition that the exact mechanism of JDPs interaction with specific substrates is unveiled. In this review, we provide an overview of the structural and functional variety of JDPs that interact with neurodegenerative disease-associated proteins and we highlight those studies that identified specific residues, domains or regions of JDPs that are crucial for substrate binding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Synthetic β-sheets mimicking fibrillar and oligomeric structures for evaluation of spectral X-ray scattering technique for biomarker quantification

Archetypical cross-β spines sharpen the boundary between functional and pathological proteins including β-amyloid, tau, α-synuclein and transthyretin are linked to many debilitating human neurodegenerative and non-neurodegenerative amyloidoses. An increased focus on development of pathogenic β-sheet specific fluid and imaging structural biomarkers and conformation-specific monoclonal antibodies in targeted therapies has been recently observed. Identification and quantification of pathogenic oligomers remain challenging for existing neuroimaging modalities. We propose two artificial β-sheets which can mimic the nanoscopic structural characteristics of pathogenic oligomers and fibrils for evaluating the performance of a label free, X-ray based biomarker detection and quantification technique. Highly similar structure with elliptical cross-section and parallel cross-β motif is observed among recombinant α-synuclein fibril, Aβ-42 fibril and artificial β-sheet fibrils. We then use these β-sheet models to assess the performance of spectral small angle X-ray scattering (sSAXS) technique for detecting β-sheet structures. sSAXS showed quantitatively accurate detection of antiparallel, cross-β artificial oligomers from a tissue mimicking environment and significant distinction between different oligomer packing densities such as diffuse and dense packings. The proposed synthetic β-sheet models mimicked the nanoscopic structural characteristics of β-sheets of fibrillar and oligomeric states of Aβ and α-synuclein based on the ATR-FTIR and SAXS data. The tunability of β-sheet proportions and shapes of structural motifs, and the low-cost of these β-sheet models can become useful test materials for evaluating β-sheet or amyloid specific biomarkers in a wide range of neurological diseases. By using the proposed synthetic β-sheet models, our study indicates that the sSAXS has potential to evaluate different stages of β-sheet-enriched structures including oligomers of pathogenic proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Interleukin-2 superkines by computational design

Significance While computational engineering of therapeutic proteins is a desirable goal, in practice the optimization of protein–protein interactions requires substantial experimental intervention. We present here a computational approach that focuses on stabilizing core protein structures rather than engineering the protein–protein interface. Using this approach, we designed thermostabilized interleukin-2 (IL-2) variants that bind tightly to their receptor without experimental optimization, mimicking the properties of the yeast-display engineered IL-2 variant “super-2.” Our results suggest that structure-guided stabilization may be a general method for in silico affinity maturation of protein–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Towards a dynamic photosynthesis model to guide yield improvement in C4 crops

Summary The most productive C4 food and biofuel crops, such as Saccharum officinarum (sugarcane), Sorghum bicolor (sorghum) and Zea mays (maize), all use NADP‐ME‐type C4 photosynthesis. Despite high productivities, these crops fall well short of the theoretical maximum solar conversion efficiency of 6%. Understanding the basis of these inefficiencies is key for bioengineering and breeding strategies to increase the sustainable productivity of these major C4 crops. Photosynthesis is studied predominantly at steady state in saturating light. In field stands of these crops light is continually changing, and often with rapid fluctuations. Although light may change in a second, the adjustment of photosynthesis may take many minutes, leading to inefficiencies. We measured the rates of CO 2 uptake and stomatal conductance of maize, sorghum and sugarcane under fluctuating light regimes. The gas exchange results were combined with a new dynamic photosynthesis model to infer the limiting factors under non‐steady‐state conditions. The dynamic photosynthesis model was developed from an existing C4 metabolic model for maize and extended to include: (i) post‐translational regulation of key photosynthetic enzymes and their temperature responses; (ii) dynamic stomatal conductance; and (iii) leaf energy balance. Testing the model outputs against measured rates of leaf CO 2 uptake and stomatal conductance in the three C4 crops indicated that Rubisco activase, the pyruvate phosphate dikinase regulatory protein and stomatal conductance are the major limitations to the efficiency of NADP‐ME‐type C4 photosynthesis during dark‐to‐high light transitions. We propose that the level of influence of these limiting factors make them targets for bioengineering the improved photosynthetic efficiency of these key crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Local Topological Free Energy of the SARS-CoV-2 Spike Protein

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Purification of native histidine-rich protein 2 (nHRP2) from Plasmodium falciparum culture supernatant, infected RBCs, and parasite lysate

Background: Despite the widespread use of histidine-rich protein 2 (HRP2)-based rapid diagnostic tests (RDTs), purified native HRP2 antigen is not standardly used in research applications or assessment of RDTs used in the field. Methods: This report describes the purification of native HRP2 (nHRP2) from the HB3 Plasmodium falciparum culture strain. As this culture strain lacks pfhrp3 from its genome, it is an excellent source of HRP2 protein only and does not produce the closely-related HRP3. The nHRP2 protein was isolated from culture supernatant, infected red blood cells (iRBCs), and whole parasite lysate using nickel-metal chelate chromatography. Biochemical characterization of nHRP2 from HB3 culture was conducted by SDS-PAGE and western blotting, and nHRP2 was assayed by RDT, ELISA, and bead-based immunoassay. Results: Purified nHRP2 was identified by SDS-PAGE and western blot as a –60 kDa protein that bound anti-HRP-2 monoclonal antibodies. Mouse anti-HRP2 monoclonal antibody was found to produce high optical density readings between dilutions of 1:100 and 1:3,200 by ELISA with assay signal observed up to a 1:200,000 dilution. nHRP2 yield from HB3 culture by bead-based immunoassay revealed that both culture supernatant and iRBC lysate were practical sources of large quantities of this antigen, producing a total yield of 292.4 µg of nHRP2 from two pooled culture preparations. Assessment of nHRP2 recognition by RDTs revealed that Carestart Pf HRP2 and HRP2/pLDH RDTs detected purified nHRP2 when applied at concentrations between 20.6 and 2060 ng/mL, performing within a log-fold dilution of commercially-available recombinant HRP2. The band intensity observed for the nHRP2 dilutions was equivalent to that observed for P. falciparum culture strain dilutions of 3D7 and US06 F Nigeria XII between 12.5 and 1000 parasites/µL. Conclusions: Purified nHRP2 could be a valuable reagent for laboratory applications as well as assessment of new and existing RDTs prior to their use in clinical settings. These results establish that it is possible to extract microgram quantities of the native HRP2 antigen from HB3 culture and that this purified protein is well recognized by existing monoclonal antibody lines and RDTs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

X-ray crystal structure of the Escherichia coli RadD DNA repair protein bound to ADP reveals a novel zinc ribbon domain

Genome maintenance is an essential process in all cells. In prokaryotes, the RadD protein is important for survival under conditions that include DNA-damaging radiation. Precisely how RadD participates in genome maintenance remains unclear. Here we present a high-resolution X-ray crystal structure of ADP-bound Escherichia coli RadD, revealing a zinc-ribbon element that was not modelled in a previous RadD crystal structure. Insights into the mode of nucleotide binding and additional structure refinement afforded by the new RadD model will help to drive investigations into the activity of RadD as a genome stability and repair factor.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Excessive Aurantiochytrium acetophilum docosahexaenoic acid supplementation decreases growth performance and breast muscle mass of broiler chickens

We report Docosahexaenoic acid (DHA) is an n-3 polyunsaturated fatty acid with health-promoting potential. This study was to investigate effects of supplemental DHA from Aurantiochytrium acetophilum on growth performance, health status, meat quality, and protein synthesis signaling of broiler chickens. Day-old male chicks were housed in an environmental control room (6 cages/treatment, 8 chicks/cage), and fed a corn-soybean meal basal diet supplemented with the DHA-rich A. acetophilum biomass (Heliae, Gilbert, AZ) at 0, 1, 2, and 4% (0, 1.7, 3.4 and 6.8 g DHA/kg diet) for 6 weeks. Growth performance was measured weekly. Blood samples were collected at weeks 3 and 6 (2 chicks/cage). Four tissues were sampled (2 chicks/cage) for biochemical and meat quality analyses. Data were analyzed by one-way ANOVA and regression. Compared with the control, the 4% A. acetophilum diet decreased (p < 0.05) body weight gain (19%) and gain to feed ratio (19%) during weeks 4–6. The A. acetophilum supplementation dose-dependently decreased (p < 0.05, R 2 = 0.21–0.54) plasma alanine amino transferase activity and glucose concentrations, but had little effect on plasma activity of alkaline phosphatase or concentrations of inorganic phosphorus and uric acid at weeks 3 and 6. Compared with the control, the 4% A. acetophilum diet decreased (p < 0.05) breast muscle weight by 21%, and down-regulated (p < 0.05) mRNA levels of mammalian target of rapamycin and ribosomal s6 protein (S6), and protein levels of phosphorylated S6 to S6 and phosphorylated S6 kinase beta 1 to S6 kinase beta 1. The A. acetophilum supplementation linearly increased (p < 0.01) lipid peroxidation (R 2 = 0.62–0.90) and hardness and chewiness (R 2 = 0.34–0.44) of breast and thigh muscles. In conclusion, supplemental 4% (6.8 g DHA/kg), but not 1 or 2%, of A. acetophilum impaired growth performance, breast muscle mass accumulation, and(or) protein synthesis signaling of broilers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge

Elucidating protein–ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein–ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein–ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein–ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein–ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein–ligand interactions on cryo-EM data using prior structural information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ADEPT: a domain independent sequence alignment strategy for gpu architectures

Bioinformatic workflows frequently make use of automated genome assembly and protein clustering tools. At the core of most of these tools, a significant portion of execution time is spent in determining optimal local alignment between two sequences. This task is performed with the Smith-Waterman algorithm, which is a dynamic programming based method. With the advent of modern sequencing technologies and increasing size of both genome and protein databases, a need for faster Smith-Waterman implementations has emerged. Multiple SIMD strategies for the Smith-Waterman algorithm are available for CPUs. However, with the move of HPC facilities towards accelerator based architectures, a need for an efficient GPU accelerated strategy has emerged. Existing GPU based strategies have either been optimized for a specific type of characters (Nucleotides or Amino Acids) or for only a handful of application use-cases. In this paper, we present ADEPT, a new sequence alignment strategy for GPU architectures that is domain independent, supporting alignment of sequences from both genomes and proteins. Our proposed strategy uses GPU specific optimizations that do not rely on the nature of sequence. We demonstrate the feasibility of this strategy by implementing the Smith-Waterman algorithm and comparing it to similar CPU strategies as well as the fastest known GPU methods for each domain. ADEPT’s driver enables it to scale across multiple GPUs and allows easy integration into software pipelines which utilize large scale computational systems. We have shown that the ADEPT based Smith-Waterman algorithm demonstrates a peak performance of 360 GCUPS and 497 GCUPs for protein based and DNA based datasets respectively on a single GPU node (8 GPUs) of the Cori Supercomputer. Overall ADEPT shows 10x faster performance in a node-to-node comparison against a corresponding SIMD CPU implementation. ADEPT demonstrates a performance that is either comparable or better than existing GPU strategies. We demonstrated the efficacy of ADEPT in supporting existing bionformatics software pipelines by integrating ADEPT in MetaHipMer a high-performance denovo metagenome assembler and PASTIS a high-performance protein similarity graph construction pipeline. Our results show 10% and 30% boost of performance in MetaHipMer and PASTIS respectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its “fitness” for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Orthogonal Degron System for Controlled Protein Degradation in Cyanobacteria

Synechococcus elongatus PCC 7942 is a model cyanobacterium for study of the circadian clock, photosynthesis, and bioproduction of chemicals, yet nearly 40% of its gene identities and functions remain unknown, in part due to limitations of the existing genetic toolkit. While classical techniques for the study of genes (e.g., deletion or mutagenesis) can yield valuable information about the absence of a gene and its associated protein, there are limits to these approaches, particularly in the study of essential genes. In this research, we developed a tool for inducible degradation of target proteins in S. elongatus by adapting a method using degron tags from the Mesoplasma florum transfer-messenger RNA (tmRNA) system. We observed that M. florum lon protease can rapidly degrade exogenous and native proteins tagged with the cognate sequence within hours of induction. We used this system to inducibly degrade the essential cell division factor, FtsZ, as well as shell protein components of the carboxysome. Our results have implications for carboxysome biogenesis and the rate of carboxysome turnover during cell growth. Lon protease control of proteins offers an alternative approach for the study of essential proteins and protein dynamics in cyanobacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Virus-Like Particles (VLPs) as a Platform for Hierarchical Compartmentalization

Hierarchically self-assembled structures are common in biology, but it is often challenging to design and fabricate synthetic analogs. The archetypal cell is defined by hierarchically organized multicompartmentalized structures with boundaries that delineate the interior from exterior environments and is an inspiration for complex functional materials. Here, we have demonstrated an approach to the design and construction of a nested protein cage system that can additionally incorporate the packing of other functional macromolecules and exhibit some of the features of a minimal synthetic cell-like material. We have demonstrated a strategy for controlled co-packaging of subcompartments, ferritin (Fn) cages, together with active cellobiose-hydrolyzing β-glycosidase enzyme macromolecules, CelB, inside the sequestered volume of the bacteriophage P22 capsid. Using controlled in vitro assembly, we were able to modulate the stoichiometry of Fn cages and CelB encapsulated inside the P22 to control the degree of compartmentalization. The co-encapsulated enzyme CelB showed catalytic activity even when packaged at high total macromolecular concentrations comparable to an intracellular environment. Here, this approach could be used as a model to create synthetic protein-based protocells that can confine smaller functionalized proto-organelles and additional macromolecules to support a range of biochemical reactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Exploring the binding properties and activities of ancestral expansins

Bacterial expansins are non-lytic proteins capable of loosening cellulose networks, offering promising applications in agriculture, biotechnology, and material science. Their ability to disrupt noncovalent interactions in biopolymer matrices such as cellulose and chitin positions them as valuable tools for upgrading abundant natural materials. However, their industrial use remains limited due to their relatively low wall-loosening activity compared to plant expansins. To address this limitation, we applied Ancestral Sequence Resurrection (ASR) to reconstruct and characterize ancient variants of the Bacillus subtilis expansin BsEXLX1. ASR is a powerful evolutionary tool that enables the inference and synthesis of ancestral proteins, allowing researchers to explore functional traits that may have been lost over time. This approach not only provides insights into protein evolution but also facilitates the design of proteins with enhanced properties, such as improved substrate affinity or structural stability. In this study, we combined biochemical and biophysical assays to evaluate the activity and binding behavior of ancestral expansins. Our results reveal that ancestral variants exhibit increased cellulose affinity, reduced binding to acidic polysaccharides, and greater salt resistance. Furthermore, these traits enhance their wall-loosening activity and demonstrate the utility of ASR in engineering surface-active proteins for industrial applications, particularly in biomass processing and cellulose modification.

09 BIOMASS FUELS↗