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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Computationally restoring the potency of a clinical antibody against Omicron

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs and revealed how quickly viral escape can curtail effective options. When the SARS-CoV-2 Omicron variant emerged in 2021, many antibody drug products lost potency, including Evusheld and its constituent, cilgavimab. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination4 and is challenging to replace with existing approaches. Rapidly modifying such high-value antibodies to restore efficacy against emerging variants is a compelling mitigation strategy. We sought to redesign and renew the efficacy of COV2-2130 against Omicron BA.1 and BA.1.1 strains while maintaining efficacy against the dominant Delta variant. Here we show that our computationally redesigned antibody, 2130-1-0114-112, achieves this objective, simultaneously increases neutralization potency against Delta and subsequent variants of concern, and provides protection in vivo against the strains tested: WA1/2020, BA.1.1 and BA.5. Deep mutational scanning of tens of thousands of pseudovirus variants reveals that 2130-1-0114-112 improves broad potency without increasing escape liabilities. Our results suggest that computational approaches can optimize an antibody to target multiple escape variants, while simultaneously enriching potency. Our computational approach does not require experimental iterations or pre-existing binding data, thus enabling rapid response strategies to address escape variants or lessen escape vulnerabilities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Learning protein fitness models from evolutionary and assay-labeled data

Machine learning-based models of protein fitness typically learn from either unlabeled, evolutionarily related sequences or variant sequences with experimentally measured labels. For regimes where only limited experimental data are available, recent work has suggested methods for combining both sources of information. Toward that goal, we propose a simple combination approach that is competitive with, and on average outperforms more sophisticated methods. Our approach uses ridge regression on site-specific amino acid features combined with one probability density feature from modeling the evolutionary data. Within this approach, we find that a variational autoencoder-based probability density model showed the best overall performance, although any evolutionary density model can be used. Moreover, our analysis highlights the importance of systematic evaluations and sufficient baselines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Photoinduced chemomimetic biocatalysis for enantioselective intermolecular radical conjugate addition

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical con- jugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Here, mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps

Abstract Interpretation of cryo-electron microscopy (cryo-EM) maps requires building and fitting 3D atomic models of biological molecules. AlphaFold-predicted models generate initial 3D coordinates; however, model inaccuracy and conformational heterogeneity often necessitate labor-intensive manual model building and fitting into cryo-EM maps. In this work, we designed a protein model-building workflow, which combines a deep-learning cryo-EM map feature enhancement tool, CryoFEM (Cryo-EM Feature Enhancement Model) and AlphaFold. A benchmark test using 36 cryo-EM maps shows that CryoFEM achieves state-of-the-art performance in optimizing the Fourier Shell Correlations between the maps and the ground truth models. Furthermore, in a subset of 17 datasets where the initial AlphaFold predictions are less accurate, the workflow significantly improves their model accuracy. Our work demonstrates that the integration of modern deep learning image enhancement and AlphaFold may lead to automated model building and fitting for the atomistic interpretation of cryo-EM maps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Synthesis of site-specific antibody-drug conjugates by ADP-ribosyl cyclases

Most of the current antibody-drug conjugates (ADCs) in clinic are heterogeneous mixtures. To produce homogeneous ADCs, established procedures often require multiple steps or long reaction times. The introduced mutations or foreign sequences may cause high immunogenicity. Here, we explore a new concept of transforming CD38 enzymatic activity into a facile approach for generating site-specific ADCs. This was achieved through coupling bifunctional antibody-CD38 fusion proteins with designer dinucleotide-based covalent inhibitors with stably attached payloads. The resulting adenosine diphosphate–ribosyl cyclase–enabled ADC (ARC-ADC) with a drug-to-antibody ratio of 2 could be rapidly generated through single-step conjugation. The generated ARC-ADC targeting human epidermal growth factor receptor 2 (HER2) displays excellent stability and potency against HER2-positive breast cancer both in vitro and in vivo. This proof-of-concept study demonstrates a new strategy for production of site-specific ADCs. It may provide a general approach for the development of a novel class of ADCs with potentially enhanced properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

mRNA-LNP HIV-1 trimer boosters elicit precursors to broad neutralizing antibodies

Germline-targeting (GT) HIV vaccine strategies are predicated on deriving broadly neutralizing antibodies (bnAbs) through multiple boost immunogens. However, as the recruitment of memory B cells (MBCs) to germinal centers (GCs) is inefficient and may be derailed by serum antibody–induced epitope masking, driving further B cell receptor (BCR) modification in GC-experienced B cells after boosting poses a challenge. Using humanized immunoglobulin knockin mice, we found that GT protein trimer immunogen N332-GT5 could prime inferred-germline precursors to the V3-glycan–targeted bnAb BG18 and that B cells primed by N332-GT5 were effectively boosted by either of two novel protein immunogens designed to have minimum cross-reactivity with the off-target V1-binding responses. The delivery of the prime and boost immunogens as messenger RNA lipid nanoparticles (mRNA-LNPs) generated long-lasting GCs, somatic hypermutation, and affinity maturation and may be an effective tool in HIV vaccine development.

Science & Technology - Other Topics↗
DOE OSTI2024

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↗
DOE OSTI2022

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↗
DOE OSTI2022

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↗
DOE OSTI2021

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↗
DOE OSTI2026

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↗
DOE OSTI2024

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↗
DOE OSTI2023

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↗
DOE OSTI2024

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↗
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↗