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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Foldy: An open-source web application for interactive protein structure analysis

Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock. In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Control over Conformational Landscapes of Polypeptoids by Monomer Sequence Patterning

The ability to program chain conformation and structure through control over the monomer sequence of synthetic polymers has broad implications for next-generation material design. While related problems of protein-folding and de novo design have generated accurate predictions of 3D folded chain structures, generalization to synthetic polymers remains intractable due to the requirement of large structural databases and the intrinsically disordered nature of polymer building blocks. In this work, polypeptoids, a class of peptidomimetic synthetic polymers, are utilized to build a general workflow for the study of relationships between monomer sequence and dynamic 3D chain structure in solution. Furthermore, this work demonstrates how control over the monomer sequence can alter the conformational landscape of synthetic polymers to deviate dramatically from classical chain statistics. Specifically, the distribution of end-to-end distances, as measured by double electron-electron resonance spectroscopy in dilute solvent, is systematically skewed towards shorter distances with an increasing number of hydrophobes and further refined by hydrophobe arrangement in amphiphilic polypeptoid chains.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optimizing the Design of Diatom Biosilica-Targeted Fusion Proteins in Biosensor Construction for Bacillus anthracis Detection

In vivo functionalization of diatom biosilica frustules by genetic manipulation requires careful consideration of the overall structure and function of complex fusion proteins. Although we previously had transformed Thalassiosira pseudonana with constructs containing a single domain antibody (sdAb) raised against the Bacillus anthracis Sterne strain, which detected an epitope of the surface layer protein EA1 accessible in lysed spores, we initially were unsuccessful with constructs encoding a similar sdAb that detected an epitope of EA1 accessible in intact spores and vegetative cells. This discrepancy limited the usefulness of the system as an environmental biosensor for B. anthracis. We surmised that to create functional biosilica-localized biosensors with certain constructs, the biosilica targeting and protein trafficking functions of the biosilica-targeting peptide Sil3T8 had to be uncoupled. We found that retaining the ER trafficking sequence at the N-terminus and relocating the Sil3T8 targeting peptide to the C-terminus of the fusion protein resulted in successful detection of EA1 with both sdAbs. Homology modeling of antigen binding by the two sdAbs supported the hypothesis that the rescue of antigen binding in the previously dysfunctional sdAb was due to removal of steric hindrances between the antigen binding loops and the diatom biosilica for that particular sdAb.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Design of Broadly Cross-Reactive M Protein–Based Group A Streptococcal Vaccines

Group A streptococcal infections are a significant cause of global morbidity and mortality. A leading vaccine candidate is the surface M protein, a major virulence determinant and protective Ag. An obstacle to the development of M protein–based vaccines is the >200 different M types defined by the N-terminal sequences that contain protective epitopes. Despite sequence variability, M proteins share coiled-coil structural motifs that bind host proteins required for virulence. In this study, we exploit this potential Achilles heel of conserved structure to predict cross-reactive M peptides that could serve as broadly protective vaccine Ags. Combining sequences with structural predictions, six heterologous M peptides in a sequence-related cluster were predicted to elicit cross-reactive Abs with the remaining five nonvaccine M types in the cluster. The six-valent vaccine elicited Abs in rabbits that reacted with all 11 M peptides in the cluster and functional opsonic Abs against vaccine and nonvaccine M types in the cluster. We next immunized mice with four sequence-unrelated M peptides predicted to contain different coiled-coil propensities and tested the antisera for cross-reactivity against 41 heterologous M peptides. Based on these results, we developed an improved algorithm to select cross-reactive peptide pairs using additional parameters of coiled-coil length and propensity. The revised algorithm accurately predicted cross-reactive Ab binding, improving the Matthews correlation coefficient from 0.42 to 0.74. These results form the basis for selecting the minimum number of N-terminal M peptides to include in potentially broadly efficacious multivalent vaccines that could impact the overall global burden of group A streptococcal diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Tubulin Double Helix: Lateral and Longitudinal Curvature Changes of Tubulin Protofilament

By virtue of their native structures, tubulin dimers are protein building blocks that are naturally pre-programmed to assemble into cytoskeletal polymers known as microtubules (MTs). Here we demonstrate polycation-directed (i.e. electrostatically tunable) assembly of tubulins through tubulin protofilament conformational changes in the longitudinal and lateral directions, creating novel tubulin double helices and various tubular architectures. Synchrotron small angle X-ray scattering and transmission electron microscopy reveal a remarkable range of nanoscale assembly structures: single- and double-layered double-helix tubulin tubules. The phase transitions from MTs into the new assemblies are dependent on the size and concentration of polycations. Two characteristic scales that determine the number of observed phases are the size of polycation compared to the size of tubulin (≈4 nm) and MT diameter (≈25 nm). This work suggests the feasibility of “programmable breakdown” of protein nanotubes, tearing MTs into double-stranded tubulins and building up previously undiscovered nanostructures, by using polycations with scissor- and glue-like properties. Importantly, we define a new role of tubulins as two-dimensionally shape-controllable building blocks for novel supramolecular architectures. Furthermore, these findings provide insight into the design of protein-based functional materials, for example, as metallization templates for nanoscale electronic devices, kinesin motor-driving molecular screws, and anticancer drug delivery vehicles.

2D shape‐control↗
DOE OSTI2025

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗
DOE OSTI2021

Binding mechanism and binding free energy of amino acids and citrate to hydroxyapatite surfaces as a function of crystallographic facet, pH, and electrolytes

Hydroxyapatite (HAP) is the major mineral phase in bone and teeth. The interaction of individual amino acids and citrate ions with different crystallographic HAP surfaces has remained uncertain for decades, creating a knowledge gap to rationally design interactions with peptides, proteins, and drugs. In this contribution, we quantify the binding mechanisms and binding free energies of the 20 end-capped natural amino acids and citrate ions on the basal (001) and prismatic (010)/(020) planes of hydroxyapatite at pH values of 7 and 5 for the first time at the molecular scale. We utilized over 1500 steered molecular dynamics simulations with highly accurate potentials that reproduce surface and hydration energies of (hkl) hydroxyapatite surfaces at different pH values. Charged residues demonstrate a much higher affinity to HAP than charge-neutral species due to the formation of superficial ion pairs and ease of penetration into layers of water molecules on the mineral surface. Binding free energies range from 0 to -60 kJ/mol and were determined with ~10% uncertainty. The highest affinity was found for citrate, followed by Asp(-) and Glu(-), and followed after a gap by Arg(+), Lys(+), as well as by His(+) at pH 5. The (hkl)-specific area density of calcium ions, the protonation state of phosphate ions, and subsurface directional order of the ions in HAP lead to surface-specific binding patterns. Amino acids without ionic side groups exhibit weak binding, between -3 and 0 kJ/mol, due to difficulties to penetrate the first layer of water molecules on the apatite surfaces. We explain recognition processes that remained elusive in experiments, in prior simulations, discuss agreement with available data, and reconcile conflicting interpretations. In conclusion, the findings can serve as useful input for the design of peptides, proteins, and drug molecules for the modification of bone and teeth-related materials, as well as control of apatite mineralization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Aerobic Respiration and Its Regulation in the Metal Reducer Shewanella oneidensis

Shewanella oneidensis MR-1 is a facultative anaerobe known for its ability to reduce metal oxides. Anaerobic respiration, especially metal reduction, has been the subject of extensive research. In contrast, S. oneidensis aerobic respiration has received less attention. S. oneidensis expresses cbb3- and aa3-type cytochrome c oxidases and a bd-type quinol oxidase. The aa3-type oxidase, which in other bacteria is the major oxygen reductase under oxygen replete conditions, does not appear to contribute to aerobic respiration and growth in S. oneidensis. Our results indicated that although the aa3-type oxidase does not play a role in aerobic growth on lactate, the preferred carbon source for S. oneidensis, it is involved in growth on pyruvate or acetate. These results highlight the importance of testing multiple carbon and energy sources when attempting to identify enzyme activities and mutant phenotypes. Several regulatory proteins contribute to the regulation of aerobic growth in S. oneidensis including CRP and ArcA. The 3',5'-cAMP phosphodiesterase (CpdA) appears to play a more significant role in aerobic growth than either CRP or ArcA, yet the deficiency does not appear to be the result of reduced oxidase genes expression. Interestingly, the ΔcpdA mutant was more deficient in aerobic respiration with several carbon sources tested compared to Δcrp, which was moderately deficient only in the presence of lactate. To identify the reason for ΔcpdA aerobic growth deficiency, we isolated a suppressor mutant with transposon insertion in SO_3550. Inactivation of this gene, which encodes an anti-sigma factor, restored aerobic growth in the cpdA mutant to wild-type levels. Inactivation of SO_3550 in wild-type cells, however, did not affect aerobic growth. The S. oneidensis genome encodes two additional CRP-like proteins that we designated CrpB and CrpC. Mutants that lack crpB and crpC were deficient in aerobic growth, but this deficiency was not due to the loss of oxidase gene expression.

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 OSTI2021

Designed, highly expressing, thermostable dengue virus 2 envelope protein dimers elicit quaternary epitope antibodies

Dengue virus (DENV) is a worldwide health burden, and a safe vaccine is needed. Neutralizing antibodies bind to quaternary epitopes on DENV envelope (E) protein homodimers. However, recombinantly expressed soluble E proteins are monomers under vaccination conditions and do not present these quaternary epitopes, partly explaining their limited success as vaccine antigens. Using molecular modeling, we found DENV2 E protein mutations that induce dimerization at low concentrations (<100 pM) and enhance production yield by more than 50-fold. Cross-dimer epitope antibodies bind to the stabilized dimers, and a crystal structure resembles the wild-type (WT) E protein bound to a dimer epitope antibody. Mice immunized with the stabilized dimers developed antibodies that bind to E dimers and not monomers and elicited higher levels of DENV2-neutralizing antibodies compared to mice immunized with WT E antigen. Our findings demonstrate the feasibility of using structure-based design to produce subunit vaccines for dengue and other flaviviruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Mimicking Natural Photosynthesis: Designing Ultrafast Photosensitized Electron Transfer into Multiheme Cytochrome Protein Nanowires

Efficient nanomaterials for artificial photosynthesis require fast and robust unidirectional electron transfer (ET) from photosensitizers through charge-separation and accumulation units to redox-active catalytic sites. We explored the ultrafast time-scale limits of photo-induced charge transfer between a Ru(II)tris(bipyridine) derivative photosensitizer and PpcA, a 3-heme c-type cytochrome serving as a nanoscale biological wire. Four covalent attachment sites (K28C, K29C, K52C, and G53C) were engineered in PpcA enabling site-specific covalent labeling with expected donor-acceptor (DA) distances of 4–8 Å. X-ray scattering results demonstrated that mutations and chemical labeling did not disrupt the structure of the proteins. Time-resolved spectroscopy revealed three orders of magnitude difference in charge transfer rates for the systems with otherwise similar DA distances and the same number of covalent bonds separating donors and acceptors. All-atom molecular dynamics simulations provided additional insight into the structure-function requirements for ultrafast charge transfer and the requirement of van der Waals contact between aromatic atoms of photosensitizers and hemes in order to observe sub-nanosecond ET. This work demonstrates opportunities to utilize multi-heme c-cytochromes as frameworks for designing ultrafast light-driven ET into charge-accumulating biohybrid model systems, and ultimately for mimicking the photosynthetic paradigm of efficiently coupling ultrafast, light-driven electron transfer chemistry to multi-step catalysis within small, experimentally versatile photosynthetic biohybrid assemblies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Substrate multiplexed protein engineering facilitates promiscuous biocatalytic synthesis

Enzymes with high activity are readily produced through protein engineering, but intentionally and efficiently engineering enzymes for an expanded substrate scope is a contemporary challenge. One approach to address this challenge is Substrate Multiplexed Screening (SUMS), where enzyme activity is measured on competing substrates. SUMS has long been used to rigorously quantitate native enzyme specificity, primarily for in vivo settings. SUMS has more recently found sporadic use as a protein engineering approach but has not been widely adopted by the field, despite its potential utility. Here, we develop principles of how to design and interpret SUMS assays to guide protein engineering. This rich information enables improving activity with multiple substrates simultaneously, identifies enzyme variants with altered scope, and indicates potential mutational hot-spots as sites for further engineering. These advances leverage common laboratory equipment and represent a highly accessible and customizable method for enzyme engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Strategies for designing biocatalysts with new functions

Enzymes can be optimized to accelerate chemical transformations via a range of methods. In this review, we showcase how protein engineering and computational design techniques can be interfaced to develop highly efficient and selective biocatalysts.

09 BIOMASS FUELS↗
DOE OSTI2023

Build Optimization Software Tools (BOOST) v2.0.0

Build Optimization Software Tools (BOOST) accelerate the design of DNA, RNA and protein sequences for their synthesis and assembly in an automated and scalable fashion. The BOOST Juggler automates the following two design tasks: - Reverse-Translation of protein sequences into DNA sequences - Codon Juggling of DNA sequences The BOOST Polisher provides the following design tasks: - The Verification of DNA sequences against DNA synthesis constraints - The Modification of DNA sequences in case they violate any DNA synthesis constraint In addition, the BOOST Polisher can be instructed to verify and modify DNA sequences against sequence patterns, such as restriction sites. The BOOST Partitioner supports both Gibson/chewback and Yeast assembly (also known as Transformation-Associated Recombination, or TAR) methods when performing the decomposition of large sequences that exceed the maximum length of DNA synthesis into synthesizable building blocks. The Partitioner can be instructed to find building blocks with appropriate overlap sequences, making their assembly into the complete construct more efficient. BOOST Workflows enable, in a customized fashion, the execution of the Juggler, Polisher, and Partitioner tools on a batch of sequences.

Sharkey, Michael↗