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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Large-scale application of free energy perturbation calculations for antibody design

Abstract Alchemical free energy perturbation (FEP) is a rigorous and powerful technique to calculate the free energy difference between distinct chemical systems. Here we report our implementation of automated large-scale FEP calculations, using the Amber software package, to facilitate antibody design and evaluation. In combination with Hamiltonian replica exchange, our FEP simulations aim to predict the effect of mutations on both the binding affinity and the structural stability. Importantly, we incorporate multiple strategies to faithfully estimate the statistical uncertainties in the FEP results. As a case study, we apply our protocols to systematically evaluate variants of the m396 antibody for their conformational stability and their binding affinity to the spike proteins of SARS-CoV-1 and SARS-CoV-2. By properly adjusting relevant parameters, the particle collapse problems in the FEP simulations are avoided. Furthermore, large statistical errors in a small fraction of the FEP calculations are effectively reduced by extending the sampling, such that acceptable statistical uncertainties are achieved for the vast majority of the cases with a modest total computational cost. Finally, our predicted conformational stability for the m396 variants is qualitatively consistent with the experimentally measured melting temperatures. Our work thus demonstrates the applicability of FEP in computational antibody design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The genotype-phenotype landscape of an allosteric protein

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli , LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 10 5 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A single amino acid change led to structural and functional differentiation of PvHd1 to control flowering in switchgrass

Abstract Switchgrass, a forage and bioenergy crop, occurs as two main ecotypes with different but overlapping ranges of adaptation. The two ecotypes differ in a range of characteristics, including flowering time. Flowering time determines the duration of vegetative development and therefore biomass accumulation, a key trait in bioenergy crops. No causal variants for flowering time differences between switchgrass ecotypes have, as yet, been identified. In this study, we mapped a robust flowering time quantitative trait locus (QTL) on chromosome 4K in a biparental F2 population and characterized the flowering-associated transcription factor gene PvHd1, an ortholog of CONSTANS in Arabidopsis and Heading date 1 in rice, as the underlying causal gene. Protein modeling predicted that a serine to glycine substitution at position 35 (p.S35G) in B-Box domain 1 greatly altered the global structure of the PvHd1 protein. The predicted variation in protein compactness was supported in vitro by a 4 °C shift in denaturation temperature. Overexpressing the PvHd1-p.35S allele in a late-flowering CONSTANS-null Arabidopsis mutant rescued earlier flowering, whereas PvHd1-p.35G had a reduced ability to promote flowering, demonstrating that the structural variation led to functional divergence. Our findings provide us with a tool to manipulate the timing of floral transition in switchgrass cultivars and, potentially, expand their cultivation range.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Phenotypic effects of changes in the FTVTxK region of an Arabidopsis secondary wall cellulose synthase compared with results from analogous mutations in other isoforms

Abstract Understanding protein structure and function relationships in cellulose synthase (CesA), including divergent isomers, is an important goal. Here, we report results from mutant complementation assays that tested the ability of sequence variants of AtCesA7, a secondary wall CesA of Arabidopsis thaliana , to rescue the collapsed vessels, short stems, and low cellulose content of the irx3‐1 AtCesA7 null mutant. We tested a catalytic null mutation and seven missense or small domain changes in and near the AtCesA7 FTVTSK motif, which lies near the catalytic domain and may, analogously to bacterial CesA, exist within a substrate “gating loop.” A low‐to‐high gradient of rescue occurred, and even inactive AtCesA7 had a small positive effect on stem cellulose content but not stem elongation. Overall, secondary wall cellulose content and stem length were moderately correlated, but the results were consistent with threshold amounts of cellulose supporting particular developmental processes. Vibrational sum frequency generation microscopy allowed tissue‐specific analysis of cellulose content in stem xylem and interfascicular fibers, revealing subtle differences between selected genotypes that correlated with the extent of rescue of the collapsing xylem phenotype. Similar tests on PpCesA5 from the moss Physcomitrium (formerly Physcomitrella ) patens helped us to synergize the AtCesA7 results with prior results on AtCesA1 and PpCesA5. The cumulative results show that the FTVTxK region is important for the function of an angiosperm secondary wall CesA as well as widely divergent primary wall CesAs, while differences in complementation results between isomers may reflect functional differences that can be explored in further work.

Burris, Jason N.↗
DOE OSTI2023

Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models

Here, we construct a data set of metal–organic framework (MOF) linkers and employ a fine-tuned GPT assistant to propose MOF linker designs by mutating and modifying the existing linker structures. This strategy allows the GPT model to learn the intricate language of chemistry in molecular representations, thereby achieving an enhanced accuracy in generating linker structures compared with its base models. Aiming to highlight the significance of linker design strategies in advancing the discovery of water-harvesting MOFs, we conducted a systematic MOF variant expansion upon state-of-the-art MOF-303 utilizing a multidimensional approach that integrates linker extension with multivariate tuning strategies. We synthesized a series of isoreticular aluminum MOFs, termed Long-Arm MOFs (LAMOF-1 to LAMOF-10), featuring linkers that bear various combinations of heteroatoms in their five-membered ring moiety, replacing pyrazole with either thiophene, furan, or thiazole rings or a combination of two. Beyond their consistent and robust architecture, as demonstrated by permanent porosity and thermal stability, the LAMOF series offers a generalizable synthesis strategy. Importantly, these 10 LAMOFs establish new benchmarks for water uptake (up to 0.64 g g –1 ) and operational humidity ranges (between 13 and 53%), thereby expanding the diversity of water-harvesting MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantum machine learning for chemistry and physics

Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.

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

Combining variational autoencoders and physical bias for improved microscopy data analysis *

Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as electron energy loss spectroscopy or 4D scanning transmission electron microscope, that contain information on a wide range of structural, physical, and chemical properties of materials. To extract valuable insights from these data, it is crucial to identify physically separate regions in the data, such as phases, ferroic variants, and boundaries between them. In order to derive an easily interpretable feature analysis, combining with well-defined boundaries in a principled and unsupervised manner, here we present a physics augmented machine learning method which combines the capability of variational autoencoders to disentangle factors of variability within the data and the physics driven loss function that seeks to minimize the total length of the discontinuities in images corresponding to latent representations. Our method is applied to various materials, including NiO-LSMO, BiFeO 3 , and graphene. The results demonstrate the effectiveness of our approach in extracting meaningful information from large volumes of imaging data. The customized codes of the required functions and classes to develop phyVAE is available at https://github.com/arpanbiswas52/phy-VAE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Advanced Structured Adsorbent Architectures for Transformative Carbon Dioxide Capture Performance (Final Report)

Svante is a world leader at using solid sorbents for low-cost Carbon Dioxide (CO 2 ) capture, a technology which is recognized as critical in meeting the dual mandates of energy security/reliability and the mitigation of man-made CO 2 emissions. Svante has been developing proprietary adsorbent material compositions, forming them into structured laminates, developing and optimizing process cycles, and system design for efficient capture of CO 2 from post-combustion flue gases of thermal power plants and industrial facilities. The deployment of first-generation CO 2 capture technology has been significantly hampered by high costs and energy penalties, among other barriers. Second generation CO 2 capture technologies (including the Mark I variant of Svante’s Veloxotherm™ adsorption-based technology), utilizing single adsorbent architecture, show promise for reducing the barriers to deploying CO 2 capture plants in commercially meaningful numbers. The objective of this project was to evaluate the Recipient’s transformational (Mark-II) VeloxoTherm™ Technology via the development and bench-scale testing of an advanced structured adsorbent, including novel Bi-layer, laminated adsorbent structures and segmented beds. Svante selected, synthesized, and characterized tailored solid adsorbents for computational modeling, advanced structured adsorbent development, process simulations, and dynamic bench scale (~1-10 kg/day CO 2 captured) testing using an existing single-bed VeloxoTherm™ Station (VTS) coupled with a natural gas-fired boiler. Segmented beds used the in-house, multi-bed Process Demonstration Unit (PDU) to demonstrate key performance indicators (KPIs), such as recovery, product purity, regeneration energy, and the integrated system's productivity in lifetime analysis. Segmented beds were used at a 1 tonne per day (TPD) unit at an industrial site to provide bench-scale validation of performance in an industrial setting. Svante was developing and optimizing the post-combustion CO 2 adsorption technology architectures, including the Bi-layer and segmented laminated adsorbent structure design, integrated rapid cycle temperature swing adsorption (RC-TSA) cycle, flow path architecture, and adsorbent bed construction and packaging (including gas porting) to progress towards achievement of DOE’s Transformational CO 2 Capture goals of 95% CO 2 purity and a cost of electricity at least 30% lower than a supercritical Pulverized Coal (PC) power plant with CO 2 capture, or approximately $30 per tonne of CO 2 captured ready for demonstration by 2030. The main requirements to reach the DOE target cost of carbon capture below $30/MT using Rapid-Cycling Temperature Swing Adsorption (RC-TSA) are as follows: (1) Increased capacity at different CO 2 concentrations, (2) Increased sorbents cycle life, (3) Increased O 2 resistance, and (4) Decreased steam requirement to extract 1 kg of CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2005

Making Activated Carbon for Storing Gas

Solid disks of microporous activated carbon, produced by a method that enables optimization of pore structure, have been investigated as means of storing gas (especially hydrogen for use as a fuel) at relatively low pressure through adsorption on pore surfaces. For hydrogen and other gases of practical interest, a narrow distribution of pore sizes <2 nm is preferable. The present method is a variant of a previously patented method of cyclic chemisorption and desorption in which a piece of carbon is alternately (1) heated to the lower of two elevated temperatures in air or other oxidizing gas, causing the formation of stable carbon/oxygen surface complexes; then (2) heated to the higher of the two elevated temperatures in flowing helium or other inert gas, causing the desorption of the surface complexes in the form of carbon monoxide. In the present method, pore structure is optimized partly by heating to a temperature of 1,100 C during carbonization. Another aspect of the method exploits the finding that for each gas-storage pressure, gas-storage capacity can be maximized by burning off a specific proportion (typically between 10 and 20 weight percent) of the carbon during the cyclic chemisorption/desorption process.

Wojtowicz, Marek A.↗
DOE OSTI2024

Rapid DNA unwinding accelerates genome editing by engineered CRISPR-Cas9

Thermostable clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas9) enzymes could improve genome-editing efficiency and delivery due to extended protein lifetimes. However, initial experimentation demonstrated Geobacillus stearothermophilus Cas9 (GeoCas9) to be virtually inactive when used in cultured human cells. Laboratory-evolved variants of GeoCas9 overcome this natural limitation by acquiring mutations in the wedge (WED) domain that produce >100-fold-higher genome-editing levels. Cryoelectron microscopy (cryo-EM) structures of the wild-type and improved GeoCas9 (iGeoCas9) enzymes reveal extended contacts between the WED domain of iGeoCas9 and DNA substrates. Biochemical analysis shows that iGeoCas9 accelerates DNA unwinding to capture substrates under the magnesium-restricted conditions typical of mammalian but not bacterial cells. These findings enabled rational engineering of other Cas9 orthologs to enhance genome-editing levels, pointing to a general strategy for editing enzyme improvement. Together, these results uncover a new role for the Cas9 WED domain in DNA unwinding and demonstrate how accelerated target unwinding dramatically improves Cas9-induced genome-editing activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Understanding, inhibiting, and engineering membrane transporters with high-throughput mutational screens

Promiscuous membrane transporters play vital roles across domains of life, mediating the uptake and efflux of structurally and chemically diverse substrates. Although many transporter structures have been solved, the fundamental rules of polyspecific transport remain inscrutable. In recent years, high-throughput genetic screens have solidified as powerful tools for comprehensive, unbiased measurements of variant function and hypothesis generation, but have had infrequent application and limited impact in the transporter field. In this primer, we describe the principles of high-throughput screening methods available for studying polyspecific transporters and comment on the necessity and potential of high-throughput methods for deciphering these transporters in particular. We present several screening approaches which could provide a fundamental understanding of the molecular basis of function and promiscuity in transporters. Here, we further posit how this knowledge can be leveraged to design inhibitors that combat multidrug resistance and engineer transporters as needed tools for synthetic biology and biotechnology applications.

EPIs↗
DOE OSTI2023

Performance of hybrid Innegra-carbon fiber composites

Abstract In this work material synergy with high stiffness carbon fiber with ductile high strength polypropylene fiber (Innegra S), (referred to as Innegra, herein) have been evaluated in a range of laminate designs. Both woven and discontinuous carbon fiber have been considered. The discontinuous fibers are based on three-dimensional deposition (3DEP) (referred to as 3DEP, herein) carbon fiber preform process. Eleven (11) variants of Innegra-carbon fiber hybrid laminates were investigated for tensile, flexure, compression, in-plane shear and low velocity impact response. The effect of position of Innegra within the laminate was studied and found to influence strength and stiffness properties. In terms of overall trends, Innegra provides upward of 18% improvement in strain (ductility) to the composite and eliminates brittle fracture of carbon fiber. The moduli trends follow the proportionality of Innegra fiber to carbon fiber plies. However, the strength is controlled by the interface between Innegra and carbon fiber. The primary failure mode in tension and compression is via onset of debonding between Innegra and carbon fiber. The 3DEP carbon fiber constituents provided highest values of in-plane shear indicating that three-dimensional (3D) network of carbon fiber provides higher shear resistance. The Innegra intensive variants exhibited superior energy absorption under low velocity impact, at energy levels 15–60 J. This work provides insight for designers to incorporate Innegra and carbon fiber hybrids in composite structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

TDP-43 α-helical structure tunes liquid–liquid phase separation and function

Liquid–liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. The RNA-binding protein TDP-43 is present in several MLOs, undergoes LLPS, and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some ALS-associated mutations in TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes upon dimerization of TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix–helix interaction, which are removed in part by variants at these positions, including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase-separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a minigene assay. Therefore, the TDP-43 helical region serves as a short but uniquely tunable module where application of biophysical principles can precisely control assembly and function in cellular and synthetic biology applications of LLPS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Structure-based decoupling of the pro- and anti-inflammatory functions of interleukin-10

Interleukin-10 (IL-10) is an immunoregulatory cytokine with both anti-inflammatory and immunostimulatory properties and is frequently dysregulated in disease. We used a structure-based approach to deconvolute IL-10 pleiotropy by determining the structure of the IL-10 receptor (IL-10R) complex by cryo–electron microscopy at a resolution of 3.5 angstroms. The hexameric structure shows how IL-10 and IL-10Rα form a composite surface to engage the shared signaling receptor IL-10Rβ, enabling the design of partial agonists. IL-10 variants with a range of IL-10Rβ binding strengths uncovered substantial differences in response thresholds across immune cell populations, providing a means of manipulating IL-10 cell type selectivity. Some variants displayed myeloid-biased activity by suppressing macrophage activation without stimulating inflammatory CD8 + T cells, thereby uncoupling the major opposing functions of IL-10. These results provide a mechanistic blueprint for tuning the pleiotropic actions of IL-10.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Evolution in vitro: analysis of a lineage of ribozymes

Background: Catalytic RNAs, or ribozymes, possessing both a genotype and a phenotype, are ideal molecules for evolution experiments in vitro. A large, heterogeneous pool of RNAs can be subjected to multiple rounds of selection, amplification and mutation, leading to the development of variants that have some desired phenotype. Such experiments allow the investigator to correlate specific genetic changes with quantifiable alterations of the catalytic properties of the RNA. In addition, patterns of evolutionary change can be discerned through a detailed examination of the genotypic composition of the evolving RNA population. Results: Beginning with a pool of 10(13) variants of the Tetrahymena ribozyme, we carried out in vitro evolution experiments that led to the generation of ribozymes with the ability to cleave an RNA substrate in the presence of Ca2+ ions, an activity that does not exist for the wild-type molecule. Over the course of 12 generations, a seven-error variant emerged that has substantial Ca(2+)-dependent RNA-cleavage activity. Advantageous mutations increased in frequency in the population according to three distinct dynamics--logarithmic, linear and transient. Through a comparative analysis of 31 individual variants, we infer how certain mutations influence the catalytic properties of the ribozyme. Conclusions: In vitro evolution experiments make it possible to elucidate important aspects of both evolutionary biology and structural biochemistry on a reasonable short time scale.

Non-NASA Center↗
NASA NTRS1994

Inventing and improving ribozyme function: rational design versus iterative selection methods

Two major strategies for generating novel biological catalysts exist. One relies on our knowledge of biopolymer structure and function to aid in the 'rational design' of new enzymes. The other, often called 'irrational design', aims to generate new catalysts, in the absence of detailed physicochemical knowledge, by using selection methods to search a library of molecules for functional variants. Both strategies have been applied, with considerable success, to the remodeling of existing ribozymes and the development of ribozymes with novel catalytic function. The two strategies are by no means mutually exclusive, and are best applied in a complementary fashion to obtain ribozymes with the desired catalytic properties.

Review, Tutorial↗
DOE OSTI2023

Gating interactions steer loop conformational changes in the active site of the L1 metallo-β-lactamase

β-Lactam antibiotics are the most important and widely used antibacterial agents across the world. However, the widespread dissemination of β-lactamases among pathogenic bacteria limits the efficacy of β-lactam antibiotics. This has created a major public health crisis. The use of β-lactamase inhibitors has proven useful in restoring the activity of β-lactam antibiotics, yet, effective clinically approved inhibitors against class B metallo-β-lactamases are not available. L1, a class B3 enzyme expressed by Stenotrophomonas maltophilia , is a significant contributor to the β-lactam resistance displayed by this opportunistic pathogen. Structurally, L1 is a tetramer with two elongated loops, α3-β7 and β12-α5, present around the active site of each monomer. Residues in these two loops influence substrate/inhibitor binding. To study how the conformational changes of the elongated loops affect the active site in each monomer, enhanced sampling molecular dynamics simulations were performed, Markov State Models were built, and convolutional variational autoencoder-based deep learning was applied. The key identified residues (D150a, H151, P225, Y227, and R236) were mutated and the activity of the generated L1 variants was evaluated in cell-based experiments. The results demonstrate that there are extremely significant gating interactions between α3-β7 and β12-α5 loops. Taken together, the gating interactions with the conformational changes of the key residues play an important role in the structural remodeling of the active site. These observations offer insights into the potential for novel drug development exploiting these gating interactions.

59 BASIC BIOLOGICAL SCIENCES↗