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Results for “Protein Design”

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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predicting metal-binding proteins and structures through integration of evolutionary-scale and physics-based modeling

Metals are essential elements in all living organisms, binding to approximately 50% of proteins. They serve to stabilize proteins, catalyze reactions, regulate activities, and fulfill various physiological and pathological functions. While there have been many advancements in determining the structures of protein-metal complexes, numerous metal-binding proteins still need to be identified through computational methods and validated through experiments. Here, to address this need, we have developed the ESMBind workflow, which combines evolutionary scale modeling (ESM) for metal-binding prediction and physics-based protein-metal modeling. Our approach utilizes the ESM-2 and ESM-IF models to predict metal-binding probability at the residue level. In addition, we have designed a metal-placement method and energy minimization technique to generate detailed 3D structures of protein-metal complexes. Our workflow outperforms other models in terms of residue and 3D-level predictions. To demonstrate its effectiveness, we applied the workflow to 142 uncharacterized fungal pathogen proteins and predicted metal-binding proteins involved in fungal infection and virulence.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Materials processing in space tasks. WBS task 5.4: Generic tasks

This task encompassed a wide range of activities related to materials processing in space. For example, all aspects of the space station's flight and ground based systems design were assessed for the Office of Advanced Concepts and Technology (OACT) Space Processing Division Office. Activities for that organization also included the consolidation of space processing payload requirements for the space station and the development of an OACT payload operations plan. Similar duties were performed for the MSFC Payload Project Office. The SPACECOM database was used to conduct preliminary design studies for microgravity payload carriers and to conduct assessments of materials processing technology. Concepts for the Advanced Protein Crystal Growth Facility (APCGF) were developed. Materials processing vent products were analyzed and a furnace facility filter concept was developed using those studies. A preliminary design for a space station aluminum payload rack was developed. Analysis was conducted to characterize the acceleration environment onboard the space shuttle. Equipment for two fluid experiment apparatus was designed and manufactured for the Space Science Laboratory. The Fluids and Materials Experiments (FAME) data base was expanded. Also, Mir payload integration, technology transfer, and spacelab-to-space station transition studies were conducted.

Crull, Robert↗
DOE OSTI2025

Balancing Doses of EL222 and Light Improves Optogenetic Induction of Protein Production in Komagataella phaffii

ABSTRACT Komagataella phaffii, also known asPichia pastoris, is a powerful host for recombinant protein production, in part due to its exceptionally strong and tightly controlled P AOX1 promoter. MostK. phaffiibioprocesses for recombinant protein production rely on P AOX1 to achieve dynamic control in two‐phase processes. Cells are first grown under conditions that repress P AOX1 (growth phase), followed by methanol‐induced recombinant protein expression (production phase). In this study, we propose a methanol‐free approach for dynamic metabolic control inK. phaffiiusing optogenetics, which can help enhance input tunability and flexibility in process optimization and control. The light‐responsive transcription factor EL222 fromErythrobacter litoralisis used to regulate protein production from the P C120 promoter inK. phaffiiwith blue light. We used two system designs to explore the advantages and disadvantages of coupling or decoupling EL222 integration with that of the gene of interest. We investigate the relationship between EL222 gene copy number and light dosage to improve production efficiency for intracellular and secreted proteins. Experiments in lab‐scale bioreactors demonstrate the feasibility of the outlined optogenetic systems as potential alternatives to conventional methanol‐inducible bioprocesses usingK. phaffii.

Biotechnology & Applied Microbiology↗
DOE OSTI2026

Primary biomolecular adsorption energetics of core–shell nanocomplexes: Implications for biological interactions

Molecular organization at the nano-bio interface governing the colloidal stability, reactivity, immune recognition, and drug delivery performance of nanoparticles remains difficult to predict. Quantifying the primary hydration energetics of biomolecule-coated nanomaterials can determine those interactions and provide a basis for engineered nanocarriers with tailored behavior in biological systems. Here, we measured the thermodynamics of water adsorption on patchy dry magnetite (Fe 3 O 4 ) nanoparticles coated with three model biomolecules, bovine serum albumin, potato starch, and lauric acid and compared these properties to the hydration energetics of the corresponding free dry biomolecules. The results demonstrate how the surface functionalization alters the hydrophilicity, the accessible hydrophilic surface, and the interaction potential of the nanocomplex surface with biological media. The protein coating increases the interaction potential of the surface of the nanocomplex. The weaker interaction potential of the polysaccharide coating and the relatively large hydrophilic surface area allow dynamic and reversible binding, while the fatty acid rearranges into a partial bilayer with very strong hydrophilicity. The findings establish the hydration enthalpy as a quantitative basis to determine and interpret nanoparticle interactions with proteins, membranes, and biological fluids, and provide a thermodynamic foundation for designing nanocarriers with predictable biological reactivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Discovering novel therapeutic V H Hs for emerging viruses: perspectives from VEEV selection strategies

Introduction: Evolution or emergence of a new viral variant is a significant public health concern. Alphaviruses, such as Venezuelan equine encephalitis virus (VEEV), are mosquito-borne viruses which are becoming more prevalent due to expansion of vector habitats. Despite this, there are currently no antiviral therapies or FDA-approved vaccines available to treat or prevent VEEV infection. The increased prevalence of such viruses provides opportunities for novel variants to evolve. Key therapeutic molecules that could be developed against viral pathogens are recombinant antibodies or antibody fragments, such as the variable heavy domain of heavy chain antibodies (V H Hs). Methods: In vitro selections offer a promising pathway for identification of therapeutic antibodies, here we explored isolation of V H Hs using phage and yeast display methodology with three antigen formats 1) recombinant E2, 2) linear peptides of E2, selected based on molecular dynamics analysis, and 3) UV inactivated virus. Results: Here we report four novel “human” V H Hs which bind to the VEEV E2 protein selected using different strategies that include both computational and biochemical design of suitable antigens and whole virus selections. These V H Hs have distinct complementarity-determining regions (CDRs). Multiple VHHs bind to the VEEV viral particles in ELISAs, and we report the peptide epitope recognized by these V H Hs. Discussion: Though non-neutralizing, these V H Hs bind to and sequester VEEV viral particles preventing infection, demonstrating the potential of these V H Hs to perform viral “sponging” which represents a novel therapeutic approach. The selection strategies we report may have applications to further antibody developments against other viruses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Protein crystal growth in low gravity

A study is presented of the crystallization of isocitrate lyase (ICL) and the influence of the lack of thermal solutal convection in microgravity on the morphology of ICL crystals is discussed. The latest results of studies with thermonucleation are presented. These include the nucleation of a protein with retrograde solubility and an unknown solubility curve. A new design for a more microgravity compatible thermonuclear is presented.

Feigelson, Robert S.↗
NASA NTRS2002

Regulation of collagenase-3 and osteocalcin gene expression by collagen and osteopontin in differentiating MC3T3-E1 cells

Both collagenase-3 and osteocalcin mRNAs are expressed maximally during the later stages of osteoblast differentiation. Here, we demonstrate that collagenase-3 mRNA expression in differentiating MC3T3-E1 cells is dependent upon the presence of ascorbic acid, is inhibited in the presence of the collagen synthesis inhibitor, 3,4-dehydroproline, and is stimulated by growth on collagen in the absence of ascorbic acid. Transient transfection studies show that collagenase-3 promoter activity increases during cell differentiation and requires the presence of ascorbic acid. Additionally, we show that, in differentiating MC3T3-E1 cells, collagenase-3 gene expression increases in the presence of an anti-osteopontin monoclonal antibody that binds near the RGD motif of this protein, whereas osteocalcin expression is inhibited. Furthermore, an RGD peptidomimetic compound, designed to block interaction of ligands to the alpha(v) integrin subunit, increases osteocalcin expression and inhibits collagenase-3 expression, suggesting that the RGD peptidomimetic initiates certain alpha(v) integrin signaling in osteoblastic cells. Overall, these studies demonstrate that stimulation of collagenase-3 expression during osteoblast differentiation requires synthesis of a collagenous matrix and that osteopontin and alpha(v) integrins exert divergent regulation of collagenase-3 and osteocalcin expression during osteoblast differentiation.

NASA Discipline Musculoskeletal↗
DOE OSTI2025

NEAR: Neural Embeddings for Amino acid Relationships

Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEAR’s ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the model’s value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗
NASA NTRS1999

Tissue-engineered human bioartificial muscles expressing a foreign recombinant protein for gene therapy

Murine skeletal muscle cells transduced with foreign genes and tissue engineered in vitro into bioartificial muscles (BAMs) are capable of long-term delivery of soluble growth factors when implanted into syngeneic mice (Vandenburgh et al., 1996b). With the goal of developing a therapeutic cell-based protein delivery system for humans, similar genetic tissue-engineering techniques were designed for human skeletal muscle stem cells. Stem cell myoblasts were isolated, cloned, and expanded in vitro from biopsied healthy adult (mean age, 42 +/- 2 years), and elderly congestive heart failure patient (mean age, 76 +/- 1 years) skeletal muscle. Total cell yield varied widely between biopsies (50 to 672 per 100 mg of tissue, N = 10), but was not significantly different between the two patient groups. Percent myoblasts per biopsy (73 +/- 6%), number of myoblast doublings prior to senescence in vitro (37 +/- 2), and myoblast doubling time (27 +/- 1 hr) were also not significantly different between the two patient groups. Fusion kinetics of the myoblasts were similar for the two groups after 20-22 doublings (74 +/- 2% myoblast fusion) when the biopsy samples had been expanded to 1 to 2 billion muscle cells, a number acceptable for human gene therapy use. The myoblasts from the two groups could be equally transduced ex vivo with replication-deficient retroviral expression vectors to secrete 0.5 to 2 microg of a foreign protein (recombinant human growth hormone, rhGH)/10(6) cells/day, and tissue engineered into human BAMs containing parallel arrays of differentiated, postmitotic myofibers. This work suggests that autologous human skeletal myoblasts from a potential patient population can be isolated, genetically modified to secrete foreign proteins, and tissue engineered into implantable living protein secretory devices for therapeutic use.

Non-NASA Center↗
DOE OSTI2026

Design-driven optimization of low-cost reagent formulations for reproducible and high-yielding cell-free gene expression

Access to recombinant proteins is vital in basic science and biotechnology research. Cell-free gene expression systems provide one approach to address this need, but widespread utilization remains limited by the cost, complexity, and inconsistency of current platforms. To address these limitations, we carry out a multi-dimensional definitive screening design to reduce the number of reagent components and remove costly secondary energy substrates. From 1,231 different reagent formulations, we discover a simple and reproducible system based on 12 components. The optimized reagent formulation can produce 2.4 ± 0.3 g/L of protein product at the 15-µL scale (~$\$60$/gprotein) and 3.7 ± 0.2 g/L (~$\$39$/gprotein) at the 4-mL scale with oxygen supplementation. This provides an average 95% reduction in cost over previous cell-free reagent formulations. We further show that the optimized reagent formulation can produce nucleoside triphosphates from nitrogenous bases and ribose and that it is robust to failure across batches of cell lysates, users/locations, and in the synthesis of more than 20 different proteins. For example, we demonstrate the production of fifteen therapeutically relevant products, including full-length aglycosylated monoclonal antibodies. We anticipate that our optimized reagent formulation will democratize the use of cell-free systems for protein manufacturing and synthetic biology applications.

Biologics↗
DOE OSTI2025

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗
DOE OSTI2024

A compact stem-loop DNA aptamer targets a uracil-binding pocket in the SARS-CoV-2 nucleocapsid RNA-binding domain

Abstract SARS-CoV-2 nucleocapsid (N) protein is a structural component of the virus with essential roles in the replication and packaging of the viral RNA genome. The N protein is also an important target of COVID-19 antigen tests and a promising vaccine candidate along with the spike protein. Here, we report a compact stem-loop DNA aptamer that binds tightly to the N-terminal RNA-binding domain of SARS-CoV-2 N protein. Crystallographic analysis shows that a hexanucleotide DNA motif (5′-TCGGAT-3′) of the aptamer fits into a positively charged concave surface of N-NTD and engages essential RNA-binding residues including Tyr109, which mediates a sequence-specific interaction in a uracil-binding pocket. Avid binding of the DNA aptamer allows isolation and sensitive detection of full-length N protein from crude cell lysates, demonstrating its selectivity and utility in biochemical applications. We further designed a chemically modified DNA aptamer and used it as a probe to examine the interaction of N-NTD with various RNA motifs, which revealed a strong preference for uridine-rich sequences. Our studies provide a high-affinity chemical probe for the SARS-CoV-2 N protein RNA-binding domain, which may be useful for diagnostic applications and investigating novel antiviral agents.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid

Structural biologists and the open-access Protein Data Bank (PDB) played decisive roles in combating the COVID-19 pandemic. Global biostructure data were turned into global knowledge, allowing scientists and engineers to understand the inner workings of coronaviruses and develop effective countermeasures. Two mRNA vaccines, initially designed with guidance from PDB structures of the SARS-CoV-1 and MERS-CoV spike proteins, prevented infections entirely or reduced the likelihood of morbidity and mortality for more than five billion individual recipients worldwide. Structure-guided drug discovery by Pfizer, Inc (facilitated by PDB structures), initiated in the 2000s in response to SARS-CoV-1 and resumed in 2020, yielded nirmatrelvir (the active ingredient of Paxlovid) -- a potent, orally-bioavailable inhibitor of the SARS-CoV-2 main protease. You've got to love the Protein Data Bank!

Burley, Stephen K.↗
DOE OSTI2025

Fragme∩t: An Open‐Source Framework for Multiscale Quantum Chemistry Based on Fragmentation

Fragment-based quantum chemistry offers a means to circumvent the nonlinear computational scaling of conventional electronic structure calculations, by partitioning a large calculation into smaller subsystems then considering the many-body interactions between them. Variants of this approach have been used to parameterize classical force fields and machine learning potentials, applications that benefit from interoperability between quantum chemistry codes. However, there is a dearth of software that provides interoperability yet is purpose-built to handle the combinatorial complexity of fragment-based calculations. To fill this void we introduce “Fragme∩t”, an open-source software application that provides a tool for community validation of fragment-based methods, a platform for developing new approximations, and a framework for analyzing many-body interactions. Fragme∩t includes algorithms for automatic fragment generation and structure modification, and for distance- and energy-based screening of the requisite subsystems. Checkpointing, database management, and parallelization are handled internally and results are archived in a portable database. Interfaces to various quantum chemistry engines are easy to write and exist already for Q-Chem, PySCF, xTB, Orca, CP2K, MRCC, Psi4, NWChem, GAMESS, and MOPAC. Applications reported here demonstrate parallel efficiencies around 96% on more than 1000 processors but also showcase that the code can handle large-scale protein fragmentation using only workstation hardware, all with a codebase that is designed to be usable by non-experts. Fragme∩t conforms to modern software engineering best practices and is built upon well established technologies including Python, SQLite, and Ray. The source code is available under the Apache 2.0 license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An elastin-like polymer targeting vascular endothelial growth factor receptor-1 reduces survival in serum-starved endothelial cells

Peptides often exhibit biological activity that depends on the context in which they are displayed and delivered. Understanding and controlling these contextual effects on peptide function is critical for designing targeted and responsive peptide-based biomaterials and therapeutics. Genetically engineered protein polymers such as elastin-like polypeptides (ELPs) can incorporate bioactive peptide motifs and are attractive candidates for biomaterials used in tissue engineering and targeted drug delivery. They also present an opportunity for investigating and modulating cell signaling pathways by presenting a peptide ligand in various defined chemical and physical environments. Vascular endothelial growth factor receptor-1 (VEGFR1) signaling plays important and complex roles in cell survival and angiogenesis, but polymeric materials that interact with this signaling axis are scarce. In this study, a novel genetically engineered elastin-like polymer that targets VEGFR1 is characterized. This polymer, termed R1B-ELP, binds to human endothelial cells in a manner dependent on its VEGFR1-targeting motif and, based on cell proliferation and cytotoxicity assays, demonstrates activity consistent with disrupting pro-survival signaling necessary for endothelial cell function under conditions of environmental stress. Notably, these findings indicate that ELP fusion alters the functional behavior of the targeting peptide. Modulators of VEGFR1 signaling have potential applications in basic studies of angiogenesis as well as in therapeutic applications targeting vascular or inflammatory diseases.

36 MATERIALS SCIENCE↗