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NASA NTRS1989

Controlled method of reducing electrophoretic mobility of various substances

A method of reducing electrophoretic mobility of macromolecules, particles, cells, and the like is provided. The method comprises interacting the particles or cells with a polymer-linked affinity compound composed of: a hydrophilic neutral polymer such as polyethylene glycol, and an affinity component consisting of a hydrophobic compound such as a fatty acid ester, an immunocompound such as an antibody or active fragment thereof or simular macromolecule, or other ligands. The reduction of electrophoretic mobility achieved is directly proportional to the concentration of the polymer-linked affinity compound employed, and the mobility reduction obtainable is up to 100 percent for particular particles and cells. The present invention is advantageous in that analytical electrophoretic separation can not be achieved for macromolecules, particles, and cells whose native surface charge structure had prevented them from being separated by normal electrophoretic means. Depending on the affinity component utilized, separation can be achieved on the basis of specific/irreversible, specific/reversible, semi-specific/reversible, relatively nonspecific/reversible, or relatively nonspecific/irreversible ligand-substance interactions. The present method is also advantageous in that it can be used in a variety of standard laboratory electrophoresis equipment.

Vanalstine, James M.↗

NASA NTRS1994

Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data

Many analysis algorithms for high-dimensional remote sensing data require that the remotely sensed radiance spectra be transformed to approximate reflectance to allow comparison with a library of laboratory reflectance spectra. In maximum likelihood classification, however, the remotely sensed spectra are compared to training samples, thus a transformation to reflectance may or may not be helpful. The effect of several radiance-to-reflectance transformations on maximum likelihood classification accuracy is investigated in this paper. We show that the empirical line approach, LOWTRAN7, flat-field correction, single spectrum method, and internal average reflectance are all non-singular affine transformations, and that non-singular affine transformations have no effect on discriminant analysis feature extraction and maximum likelihood classification accuracy. (An affine transformation is a linear transformation with an optional offset.) Since the Atmosphere Removal Program (ATREM) and the log residue method are not affine transformations, experiments with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were conducted to determine the effect of these transformations on maximum likelihood classification accuracy. The average classification accuracy of the data transformed by ATREM and the log residue method was slightly less than the accuracy of the original radiance data. Since the radiance-to-reflectance transformations allow direct comparison of remotely sensed spectra with laboratory reflectance spectra, they can be quite useful in labeling the training samples required by maximum likelihood classification, but these transformations have only a slight effect or no effect at all on discriminant analysis and maximum likelihood classification accuracy.

Hoffbeck, Joseph P.↗

NASA NTRS2000

Over-Expression, Purification and Crystallization of Human Dihydrolipoamide Dehydrogenase

Dehydrolipoamide dehydrogenase (E3; dihydrolipoan-tide:NAD+ oxidoreductase, EC 1.8.1.4) is a common catalytic component found in pyruvate dehydrogenase complex, alpha-ketoglutarate dehydrogenase complex, and branched-chain cc-keto acid dehydrogenase complex. E3 is also a component (referred to as L protein) of the glycine cleavage system in bacterial metabolism (2). Active E3 forms a homodimer with four distinctive subdomain structures (FAD binding, NAD+ binding, central and interface domains) with non-covalently but tightly bound FAD in the holoenzyme. Deduced amino acids from cloned full-length human E3 gene showed a total of 509 amino acids with a leader sequence (N-terminal 35 amino acids) that is excised (mature form) during transportation of expressed E3 into mitochondria membrane. So far, three-dimensional structure of human E3 has not been reported. Our effort to achieve the elucidation of the X-ray crystal structure of human E3 will be presented. Recombinant pPROEX-1 expression vector (from GIBCO BRL Life Technologies) having the human E3 gene without leader sequence was constructed by Polymerase Chain Reaction (PCR) and subsequent ligation, and cloned in E.coli XL1-Blue by transformation. Since pPROEX-1 vector has an internal His-tag (six histidine peptide) located at the upstream region of a multicloning site, one-step affinity purification of E3 using nickelnitriloacetic acid (Ni-NTA) agarose resin, which has a strong affinity to His-tag, was feasible. Also a seven-amino-acid spacer peptide and a recombinant tobacco etch virus protease recognition site (seven amino acids peptide) found between His-tag and first amino acid of expressed E3 facilitated the cleavage of His-tag from E3 after the affinity purification. By IPTG induction, ca. 15 mg of human E3 (mature form) was obtained from 1L LB culture with overnight incubation at 25C. Over 98% of purity of E3 from one-step Ni-NTA agarose affinity purification was confirmed by SDS-PAGE analysis. For crystallization, E3 samples were prepared with and without His-tag. To minimize the aggregation of E3, apo- and holo- forms of E3s were tested, as well as a mutated E3. Dynamic light scattering measurements revealed that the E3 preparations without His-tag and substrate are highly monodispersive with regard to homodimers. Consequent crystallization trials of this E3 preparation led to single crystals of E3 grown by the vapor diffusion method. Crystals were obtained within a few days from solution containing poly (ethylene glycol) monomethyl ether 5000 as a precipitant. Autoindexing and integration of the X-ray diffraction data showed that E3 crystals belong to an orthorhombic system with unit cell parameters a-- 123. 1, b= 165.3 and c=214.3A. Further optimization of protein preparation and crystallization experiments for the structural determination will be discussed.

Hong, Y. S.↗

NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗

NASA NTRS2015

Thioaptamer Diagnostic System (TDS)

AM Biotechnologies, LLC, in partnership with Sandia National Laboratories, has developed a diagnostic device that quickly detects sampled biomarkers. The TDS quickly quantifies clinically relevant biomarkers using only microliters of a single sample. The system combines ambient-stable, long shelf-life affinity assays with handheld, microfluidic gel electrophoresis affinity assay quantification technology. The TDS is easy to use, operates in microgravity, and permits simultaneous quantification of 32 biomarkers. In Phase I of the project, the partners demonstrated that a thioaptamer assay used in the microfluidic instrument could quantify a specific biomarker in serum in the low nanomolar range. The team also identified novel affinity agents to bone-specific alkaline phosphatase (BAP) and demonstrated their ability to detect BAP with the microfluidic instrument. In Phase II, AM Biotech expanded the number of ambient affinity agents and demonstrated a TDS prototype. In the long term, the clinical version of the TDS will provide a robust, flight-tested diagnostic capability for space exploration missions.

Yang, Xianbin↗

DOE OSTI2021

Characterization of protein–ligand binding interactions of enoyl-ACP reductase ( FabI ) by native MS reveals allosteric effects of coenzymes and the inhibitor triclosan

The enzyme enoyl-ACP reductase (also called FabI in bacteria) is an essential member of the fatty acid synthase II pathway in plants and bacteria. This enzyme is the target of the antibacterial drug triclosan and has been the subject of extensive studies for the past 20 years. Despite the large number of reports describing the biochemistry of this enzyme, there have been no studies that provided direct observation of the protein and its various ligands. In this paper we describe the use of native MS to characterize the protein–ligand interactions of FabI with its coenzymes NAD + and NADH and with the inhibitor triclosan. Measurements of the gas-phase affinities of the enzyme for these ligands yielded values that are in close agreement with solution-phase affinity measurements. Additionally, FabI is a homotetramer and we were able to measure the affinity of each subunit for each coenzyme, which revealed that both coenzymes exhibit a positive homotropic allosteric effect. An allosteric effect was also observed in association with the inhibitor triclosan. These observations provide new insights into this well-studied enzyme and suggest that there may still be gaps in the existing mechanistic models that explain FabI inhibition.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗

DOE OSTI2022

Moving the needle: Employing deep reinforcement learning to push the boundaries of coarse-grained vaccine models

Highly mutable infectious disease pathogens (hm-IDPs) such as HIV and influenza evolve faster than the human immune system can contain them, allowing them to circumvent traditional vaccination approaches and causing over one million deaths annually. Agent-based models can be used to simulate the complex interactions that occur between immune cells and hm-IDP-like proteins (antigens) during affinity maturation—the process by which antibodies evolve. Compared to existing experimental approaches, agent-based models offer a safe, low-cost, and rapid route to study the immune response to vaccines spanning a wide range of design variables. However, the highly stochastic nature of affinity maturation and vast sequence space of hm-IDPs render brute force searches intractable for exploring all pertinent vaccine design variables and the subset of immunization protocols encompassed therein. To address this challenge, we employed deep reinforcement learning to drive a recently developed agent-based model of affinity maturation to focus sampling on immunization protocols with greater potential to improve the chosen metrics of protection, namely the broadly neutralizing antibody (bnAb) titers or fraction of bnAbs produced. Using this approach, we were able to coarse-grain a wide range of vaccine design variables and explore the relevant design space. Our work offers new testable insights into how vaccines should be formulated to maximize protective immune responses to hm-IDPs and how they can be minimally tailored to account for major sources of heterogeneity in human immune responses and various socioeconomic factors. Our results indicate that the first 3 to 5 immunizations, depending on the metric of protection, should be specially tailored to achieve a robust protective immune response, but that beyond this point further immunizations require only subtle changes in formulation to sustain a durable bnAb response.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Amino‐Functionalised Hybrid Ultramicroporous Materials that Enable Single‐Step Ethylene Purification from a Ternary Mixture

Abstract Pyrazine‐linked hybrid ultramicroporous (pore size <7 Å) materials (HUMs) offer benchmark performance for trace carbon capture thanks to strong selectivity for CO 2 over small gas molecules, including light hydrocarbons. That the prototypal pyrazine‐linked HUMs are amenable to crystal engineering has enabled second generation HUMs to supersede the performance of the parent HUM, SIFSIX‐3‐Zn , mainly through substitution of the metal and/or the inorganic pillar. Herein, we report that two isostructural aminopyrazine‐linked HUMs, MFSIX‐17‐Ni (17=aminopyrazine; M=Si, Ti), which we had anticipated would offer even stronger affinity for CO 2 than their pyrazine analogs, unexpectedly exhibit reduced CO 2 affinity but enhanced C 2 H 2 affinity. MFSIX‐17‐Ni are consequently the first physisorbents that enable single‐step production of polymer‐grade ethylene (>99.95 % for SIFSIX‐17‐Ni ) from a ternary equimolar mixture of ethylene, acetylene and CO 2 thanks to coadsorption of the latter two gases. We attribute this performance to the very different binding sites in MFSIX‐17‐Ni versus SIFSIX‐3‐Zn .

Mukherjee, Soumya↗

DOE OSTI2025

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Abstract Lewis acids play a central role in a large variety of chemical transformations. The reactivity of the strongest Lewis acids is typically studied in the context of affinity towards hard bases, such as fluoride or oxygenous species. Carbocations can be viewed as soft Lewis acids, possessing significant affinity for softer bases, such as hydride. This work presents the ambient‐temperature isolation of salts of the perfluorotrityl cation ((C 6 F 5 ) 3 C + or F 15 Tr + ) in combination with halogenated carborane anions. The F 15 Tr + cation exhibits remarkable hydride affinity, illustrated by the observation of hydride abstraction from dihydrogen, and of the rapid abstraction of hydride from −CH 2 −groups in alkanes. Theoretical studies support the favorability of hydride abstraction from dihydrogen, and indicate that the hydride abstraction from alkanes proceeds via a concerted hydride transfer process that is sensitive to steric effects.

Leong, Derek W. [Department of Chemistry Texas A&a↗

DOE OSTI2021

Amino‐Functionalised Hybrid Ultramicroporous Materials that Enable Single‐Step Ethylene Purification from a Ternary Mixture

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Leong, Derek W. [Department of Chemistry Texas A&a↗

DOE OSTI2022

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Pyrrole‐Imine Macrocycle: Self‐Organizing Cross‐Reactive Anion Receptor and Sensor

Self-organizing macrocyclic receptor-sensors for phosphorus oxyanions, phosphates, and phosphonates comprising imine moieties were prepared by condensation of dipyrrolylmethane dicarbaldehyde with diethylene triamine. The incorporation of flexible ethylene moieties endows the macrocycle with unprecedented flexibility and ability to accommodate numerous phosphorus oxyanions from orthophosphate to large anions such as ATP or phosphonate glyphosate. The anion binding was elucidated by NMR titrations, low-temperature NMR, and NOESY NMR. The incorporation of dansyl fluorophore enables sensing of anions using the fluorescence signal, whereas the changes in fluorescence intensity, width of the fluorescence band, and position of the maxima are analyte-specific and useful in recognition and identification of eleven different P-oxyanions in water. The affinity (K assoc ) for Na + salts was H 2 PO 4 − ≈ Methylphosphonate > H 2 P 2 O 7 2− > Phenylphosphonate- > Glyphosate 2− > AMP 2− > ADP 2− > ATP 2− . Interestingly, phosphonates, including methylphosphonate and glyphosate anions, were also found to display a strong affinity (K assoc ∼10 6 M −1 ) while halides, nitrate, carbonates, or hydrogen sulfate did not show a significant affinity. The determined fluorescence spectral parameters were used to classify the 12 analytes (11 anions and water) using Linear Discriminant Analysis (LDA). Quantification was performed using LDA and Support Vector Machine (SVM), and the phosphonate concentrations in unknown samples were determined with an error of 3.5% or lower.

anions↗

DOE OSTI2024

In Silico Screening of CO 2 –Dipeptide Interactions for Bioinspired Carbon Capture

Carbon capture, sequestration and utilization offers a viable solution for reducing the total amount of atmospheric CO 2 concentrations. On an industrial scale, amine-based solvents are extensively employed for CO 2 capture through chemisorption. Nevertheless, this method is marked by the high cost associated with solvent regeneration, high vapor pressure, and the corrosive and toxic attributes of by-products, such as nitrosamines. An alternative approach is the biomimicry of sustainable materials that have strong affinity and selectivity for CO 2 . Bioinspired approaches, such as those based on naturally occurring amino acids, have been proposed for direct air capture methodologies. In this study, we present a database consisting of 960 dipeptide molecular structures, composed of the 20 naturally occurring amino acids. Furthermore, those structures were analyzed with a novel computational workflow presented in this work that considers certain interaction sites that determine CO 2 affinity. Density functional theory (DFT) and symmetry-adapted perturbation theory (SAPT) computations were performed for the calculation of CO 2 interaction energies, which allowed to limit our search space to 400 unique dipeptide structures. Using this computational workflow, we provide statistical insights into dipeptides and their affinity for CO 2 binding, as well as design principles that can further enhance CO 2 capture through cooperative binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Screening a knowledge‐based library of low molecular weight compounds against the proline biosynthetic enzyme 1‐pyrroline‐5‐carboxylate 1 ( PYCR1)

Abstract Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H‐dependent reduction of Δ 1 ‐pyrroline‐5‐carboxylate toL‐proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of thePYCR1gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X‐ray crystallography and kinetic assays to determine affinity parameters. The library was counter‐screened against human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)‐tetrahydro‐2H‐pyran‐2‐carboxylic acid (70 μM) has higher affinity than the current best tool compoundN‐formyl‐l‐proline, is 30 times more specific for PYCR1 over human Δ 1 ‐pyrroline‐5‐carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure‐affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1‐hydroxyethane‐1‐sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed withl‐pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Biochemistry & Molecular Biology↗

DOE OSTI2022

New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering

We introduce a new phenomenological tool based on momentum region indicators to guide the analysis and interpretation of semi-inclusive deep-inelastic scattering measurements. The new tool, referred to as “affinity”, is devised to help visualize and quantify the proximity of any experimental kinematic bin to a particular hadron production region, such as that associated with transverse momentum dependent factorization. We apply the affinity estimator to existing HERMES and COMPASS data and expected data from Jefferson Lab and the future Electron-Ion Collider. We also provide an interactive notebook based on Machine Learning for fast evaluation of affinity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Resolving SPARC–HSA binding kinetics with an ultrasensitive photonic sensor based on bound states in the continuum

Secreted protein acidic and rich in cysteine (SPARC) is critical in cell-matrix interactions and tissue remodeling. It influences tumor progression through its affinity for human serum albumin (HSA) - the most abundant plasma protein, which also plays a crucial role in drug delivery. Strong molecular binding leads to a dissociation constant KD in the nanomolar range. Thus, determining KD requires detecting sub-nanomolar concentrations with ultrasensitive methods. This may be crucial for elucidating the nature of SPARC-HSA binding, as their interaction remains a subject of debate. Capturing these interactions accurately requires a platform capable of resolving rapid binding kinetics at extremely low analyte concentrations. In this work, we report on a microfluidics-integrated photonic nanostructure that supports bound states in the continuum (BICs) and is optimized for studying the fast kinetics of high-affinity protein-protein interactions. The unprecedented capability of detecting sub-nanomolar concentrations allows quantifying KD between SPARC and HSA beyond the state of the art. We leverage an all-dielectric photonic crystal slab (PhCS) sustaining two BIC branches arising from gapped Dirac cone dispersion. HSA is covalently immobilized on the PhCS bonded to a PDMS microfluidic chamber. SPARC dissociation is carried out using PBS buffer (pH 7.4), ensuring complete protein release through precise control of the flow rate and continuous spectral monitoring of the BICs. The measured KD=8.2±0.8 nM confirms the strong affinity of SPARC for HSA. This study highlights the potential of BIC-based sensing as a versatile tool for investigating protein interactions. These results also have implications for the optimization of drug delivery systems and cancer treatment strategies.

Albumin↗