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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 199 records · Page 11

Supercharged cellulases show superior thermal stability and enhanced activity towards pretreated biomass and cellulose

Non-productive binding of cellulolytic enzymes to various plant cell wall components, such as lignin and cellulose, necessitates high enzyme loadings to achieve efficient conversion of pretreated lignocellulosic biomass to fermentable sugars. Protein supercharging was previously employed as one of the strategies to reduce non-productive binding to biomass. However, various questions remain unanswered regarding the hydrolysis kinetics of supercharged enzymes towards pretreated biomass substrates and the role played by enzyme interactions with individual cell wall polymers such as cellulose and xylan. In this study, CBM2a (from Thermobifida fusca ) fused with endocellulase Cel5A (from T. fusca ) was used as the model wild-type enzyme and CBM2a was supercharged using Rosetta, to obtain eight variants with net charges spanning -14 to +6. These enzymes were recombinantly expressed in E. coli , purified from cell lysates, and their hydrolytic activities were tested against pretreated biomass substrates (AFEX and EA treated corn stover). Although the wild-type enzyme showed greater activity compared to both negatively and positively supercharged enzymes towards pretreated biomass, thermal denaturation assays identified two negatively supercharged constructs that perform better than the wild-type enzyme (~3 to 4-fold difference in activity) upon thermal deactivation at higher temperatures. To better understand the causal factor of reduced supercharged enzyme activity towards AFEX corn stover, we performed hydrolysis assays on cellulose-I/xylan/pNPC, lignin inhibition assays, and thermal stability assays. Altogether, these assays showed that the negatively supercharged mutants were highly impacted by reduced activity towards xylan whereas the positively supercharged mutants showed dramatically reduced activity towards cellulose and xylan. It was identified that a combination of impaired cellulose binding and lower thermal stability was the cause of reduced hydrolytic activity of positively supercharged enzyme sub-group. Overall, this study demonstrated a systematic approach to investigate the behavior of supercharged enzymes and identified supercharged enzyme constructs that show superior activity at elevated temperatures. Future work will address the impact of parameters such as pH, salt concentration, and assay temperature on the hydrolytic activity and thermal stability of supercharged enzymes.

09 BIOMASS FUELS↗

Myosin Heavy Chain Gene Expression in Developing Neonatal Skeletal Muscle: Involvement of the Nerve, Gravity, and Thyroid State

The myosin heavy chain (MHC) gene family encodes at least six MHC proteins (herein designated as neonatal, embryonic, slow type I (beta), and fast IIa, IIx, and IIb) that are expressed in skeletal muscle in a muscle-specific and developmentally-regulated fashion. At birth, both antigravity (e.g. soleus) and locomotor (e.g., plantaris) skeletal muscles are undifferentiated relative to the adult MHC phenotype such that the neonatal and embryonic MHC isoforms account for 80 - 90% of the MHC pool in a fast locomotor muscle; whereas, the embryonic and slow, type I isoforms account for approx. 90% of the pool in a typical antigravity muscle. The goal of this study was to investigate the role of an intact nerve, gravity and thyroid hormone (T3), as well as certain interactions of these interventions, on MHC gene expression in developing neonatal skeletal muscles of rodents.

Baldwin, K. M.↗

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗

Engineered pH-Sensitive Protein G/IgG Interaction

While natural protein–protein interactions have evolved to be induced by complex stimuli, rational design of interactions that can be switched-on-demand still remain challenging in the protein design world. Here, we demonstrate that a computationally redesigned natural interface for improved binding affinity could further be mutated to adopt a pH switchable interaction. The redesigned interface of Protein G/human IgG Fc domain (referred to as PrG/hIgG), when incorporated with histidine and glutamic acid on PrG (PrG-EHHE), showed a switch in binding affinity by 50-fold when the pH was altered from mild acidic to mild basic. The wild-type (WT) interface showed a negligible switch. The overall binding affinity under mild acidic pH for PrG-EHHE outperformed the wild-type PrG (PrG-WT) interaction. Overall, we find that the new reagent PrG-EHHE can be revolutionary in IgG purification, since the standard method of using an extreme acidic pH for elution can be circumvented.

59 BASIC BIOLOGICAL SCIENCES↗

Beyond Component Optimization: Systems Level Biodesign for Lanthanide Recovery

Global demand for lanthanides (Ln) is projected to rise sharply over the next decade, while geographically concentrated supply chains and the low concentrations and matrix complexity of secondary feedstocks limit the reach of conventional hydro- and pyrometallurgical separation. Engineered biological systems offer a selective, low-energy alternative, and component-level advances in Ln-binding proteins, AI-designed selective scaffolds, and cell-surface display platforms now rival synthetic chelators in affinity and selectivity. These components, however, remain functionally isolated. Currently, there are no engineered chassis coupling recognition, intracellular trafficking, accumulation, and controlled release into an end-to-end pipeline. Here, we outline how new biodesign strategies and chassis selection must move beyond bioleaching to encompass the full recovery pathway. Achieving this requires integrating AI/ML-guided design, genome-scale build tools, high-throughput phenotyping, and biophysical transport modeling within a Design–Build–Test–Learn cycle tuned to recognition, trafficking, accumulation, and release.

Biodesign↗

Structure and Antigenicity of the Porcine Astrovirus 4 Capsid Spike

Porcine astrovirus 4 (PoAstV4) has been recently associated with respiratory disease in pigs. In order to understand the scope of PoAstV4 infections and to support the development of a vaccine to combat PoAstV4 disease in pigs, we designed and produced a recombinant PoAstV4 capsid spike protein for use as an antigen in serological assays and for potential future use as a vaccine antigen. Structural prediction of the full-length PoAstV4 capsid protein guided the design of the recombinant PoAstV4 capsid spike domain expression plasmid. The recombinant PoAstV4 capsid spike was expressed in Escherichia coli, purified by affinity and size-exclusion chromatography, and its crystal structure was determined at 1.85 Å resolution, enabling structural comparisons to other animal and human astrovirus capsid spike structures. The recombinant PoAstV4 capsid spike protein was also used as an antigen for the successful development of a serological assay to detect PoAstV4 antibodies, demonstrating that the recombinant PoAstV4 capsid spike retains antigenic epitopes found on the native PoAstV4 capsid. These studies lay a foundation for seroprevalence studies and the development of a PoAstV4 vaccine for swine.

Virology↗

Development of a Space Compatible Biomanufacturing System

Space biomanufacturing is a potential In Situ Resource Utilization (ISRU) strategy to provide critical consumables and products while minimizing the launched mass for long-duration, deep space missions. On Earth, the primary biological conversion of CO 2 to biomass is through photosynthesis, and sugars from photosynthetic organisms are used as feedstocks for microbial biomanufacturing. The efficiency of non-biological reduction of CO 2 to organic molecules, such as acetate or ethanol, has greatly increased in recent years. We are designing a biomanufacturing system to rely on electrochemical CO 2 conversion products for carbon substrates to support microbial growth and production of recombinant proteins. The preliminary design includes a gas-permeable membrane bioreactor with dry salts that are rehydrated and mixed with the carbon source to support growth of bacteria or yeast. The system architecture has a partially automated bioprocessing system to concentrate biomass and purify recombinant protein. This system is designed to operate semi-autonomously with minimal crew intervention. The specific use-case scenario is to produce a thermal stable carbonic anhydrase to increase the efficiency of a proposed liquid amine CO 2 removal subsystem of an environmental control and life-support system (ECLSS) on Mars.

Recombinant↗

A Bis(imidazole)-based cysteine labeling tool for metalloprotein assembly

Precise metal-protein coordination by design remains a considerable challenge. Polydentate, high-metal-affinity protein modifications, both chemical and recombinant, can enable metal localization. However, these constructs are often bulky, conformationally and stereochemically ill-defined, or coordinately saturated. Here, we expand the biomolecular metal-coordination toolbox with the irreversible attachment to cysteine of bis(1-methylimidazol-2-yl)ethene (“BMIE”), which generates a compact imidazole-based metal-coordinating ligand. Conjugate additions of small-molecule thiols (thiocresol and N-Boc-Cys) with BMIE confirm general thiol reactivity. The BMIE adducts are shown to complex the divalent metal ions Cu ++ and Zn ++ in bidentate (N 2 ) and tridentate (N 2 S*) coordination geometries. Cysteine-targeted BMIE modification (>90% yield at pH 8.0) of a model protein, the S203C variant of carboxypeptidase G2 (CPG2), measured with ESI-MS, confirms its utility as a site-selective bioconjugation method. ICP-MS analysis confirms mono-metallation of the BMIE-modified CPG2 protein with Zn ++ , Cu ++ , and Co ++ . EPR characterization of the BMIE-modified CPG2 protein reveals the structural details of the site selective 1:1 BMIE-Cu ++ coordination and symmetric tetragonal geometry under physiological conditions and in the presence of various competing and exchangeable ligands (H 2 O/HO – , tris, and phenanthroline). An X-ray protein crystal structure of BMIE-modified CPG2-S203C demonstrates that the BMIE modification is minimally disruptive to the overall protein structure, including the carboxypeptidase active sites, although Zn ++ metalation could not be conclusively discerned at the resolution obtained. The carboxypeptidase catalytic activity of BMIE-modified CPG2-S203C was also assayed and found to be minimally affected. Finally, these features, combined with ease of attachment, define the new BMIE-based ligation as a versatile metalloprotein design tool, and enable future catalytic and structural applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Blueprinting extendable nanomaterials with standardized protein blocks

A wooden house frame consists of many different lumber pieces, but because of the regularity of these building blocks, the structure can be designed using straightforward geometrical principles. The design of multicomponent protein assemblies, in comparison, has been much more complex, largely owing to the irregular shapes of protein structures. Here we describe extendable linear, curved and angled protein building blocks, as well as inter-block interactions, that conform to specified geometric standards; assemblies designed using these blocks inherit their extendability and regular interaction surfaces, enabling them to be expanded or contracted by varying the number of modules, and reinforced with secondary struts. Using X-ray crystallography and electron microscopy, we validate nanomaterial designs ranging from simple polygonal and circular oligomers that can be concentrically nested, up to large polyhedral nanocages and unbounded straight ‘train track’ assemblies with reconfigurable sizes and geometries that can be readily blueprinted. Because of the complexity of protein structures and sequence–structure relationships, it has not previously been possible to build up large protein assemblies by deliberate placement of protein backbones onto a blank three-dimensional canvas; the simplicity and geometric regularity of our design platform now enables construction of protein nanomaterials according to ‘back of an envelope’ architectural blueprints.

36 MATERIALS SCIENCE↗

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↗

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Blanchard, Andrew E.↗

De novo design of monomeric helical bundles for pH ‐controlled membrane lysis

Abstract Targeted intracellular delivery via receptor‐mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH‐responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli , 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH‐dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH‐responsiveness and control lysis of model membranes within a very narrow range of pH (6.0–5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.

59 BASIC BIOLOGICAL SCIENCES↗