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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
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 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 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↗
DOE OSTI2020

Stochastic DC optimal power flow with reserve saturation

We propose an optimization framework for stochastic optimal power flow with uncertain loads and renewable generator capacity. Our model follows previous work in assuming that generator outputs respond to load imbalances according to an affine control policy, but introduces a model of saturation of generator reserves by assuming that when a generator’s target level hits its limit, it abandons the affine policy and produces at that limit. This is a particularly interesting feature in models where wind power plants, which have uncertain upper generation limits, are scheduled to provide reserves to balance load fluctuations. Here, the resulting model is a nonsmooth nonconvex two-stage stochastic program, and we use a stochastic approximation method to find stationary solutions to a smooth approximation. Computational results on 6-bus and 118-bus test instances demonstrate that by considering the effects of saturation, our model can yield solutions with lower expected generation costs (at the same target line violation probability level) than those obtained from a model that enforces the affine policy to stay within generator limits with high probability.

17 WIND ENERGY↗
DOE OSTI2021

The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer

Aptamers are short, single-stranded DNA or RNA oligonucleotide molecules that function as synthetic analogs of antibodies and bind to a target molecule with high specificity. Aptamer affinity entirely depends on its tertiary structure and charge distribution. Therefore, length and structure optimization are essential for increasing aptamer specificity and affinity. Here, we present a general optimization procedure for finding the most populated atomistic structures of DNA aptamers. Based on the existed aptamer LC-18 for lung adenocarcinoma, a new truncated LC-18 (LC-18t) aptamer LC-18t was developed. A three-dimensional (3D) shape of LC-18t was reported based on small-angle X-ray scattering (SAXS) experiments and molecular modeling by fragment molecular orbital or molecular dynamic methods. Molecular simulations revealed an ensemble of possible aptamer conformations in solution that were in close agreement with measured SAXS data. The aptamer LC-18t had stronger binding to cancerous cells in lung tumor tissues and shared the binding site with the original larger aptamer. The suggested approach reveals 3D shapes of aptamers and helps in designing better affinity probes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Designing clay-polymer nanocomposite sorbents for water treatment: A review and meta-analysis of the past decade

Clay-polymer nanocomposites (CPNs) have been studied for two decades as sorbents for water pollutants, but their applicability remains limited. Our aim in this review is to present the latest progress in CPN research using a meta-analysis approach and identify key steps necessary to bridge the gap between basic research and CPN application. Based on results extracted from 99 research articles on CPNs and 8 review articles on other widely studies sorbents, CPNs had higher adsorption capacities for several inorganic and organic pollutant classes (including heavy metals, oxyanions, and dyes, n = 308 observations). We applied principal component analysis, analysis of variance, and multiple linear regressions to test how CPN and pollutant properties correlated with Langmuir adsorption model coefficients. While adsorption was, surprisingly, not influenced by mineral properties, it was influenced by CPN fabrication method, polymer functional groups, and pollutant properties. For example, among the pollutant classes, heavy metals had the highest adsorption capacity but the lowest adsorption affinity. Conversely, dyes had high adsorption affinities, as reflected by the linear correlation between adsorption affinity and pollutant molecular weight. Scaling from ‘basic research’ to ‘technological application’ requires testing CPN performance in real water, application in columns, comparison to commercial sorbents, regeneration, and cost evaluation. However, our survey indicates that of the 158 observations, only 20 compared the CPN's performance to that of a commercial sorbent. We anticipate that this review will promote the design of smart and functional CPNs, which can then evolve into an effective water treatment technology.

42 ENGINEERING↗
DOE OSTI2021

Dynamics-Based Peptide–MHC Binding Optimization by a Convolutional Variational Autoencoder: A Use-Case Model for CASTELO

An unsolved challenge in the development of antigen-specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen–major histocompatibility complex (MHC) binding is paramount toward achieving this goal. Here, we apply CASTELO, a combined machine learning-molecular dynamics (ML-MD) approach, to identify per-residue antigen binding contributions and then design novel antigens of increased MHC-II binding affinity for a type 1 diabetes-implicated system. We build upon a small-molecule lead optimization algorithm by training a convolutional variational autoencoder (CVAE) on MD trajectories of 48 different systems across four antigens and four HLA serotypes. We develop several new machine learning metrics including a structure-based anchor residue classification model as well as cluster comparison scores. ML-MD predictions agree well with experimental binding results and free energy perturbation-predicted binding affinities. Moreover, ML-MD metrics are independent of traditional MD stability metrics such as contact area and root-mean-square fluctuations (RMSF), which do not reflect binding affinity data. Finally, our work supports the role of structure-based deep learning techniques in antigen-specific immunotherapy design.

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

Coupled Interfacial and Bulk Kinetics Govern the Timescales of Multiphase Ozonolysis Reactions

Chemical transformations in aerosols impact the lifetime of particle phase species, the fate of atmospheric pollutants, and both climate- and health-relevant aerosol properties. Timescales for multiphase reactions of ozone in atmospheric aqueous phases are governed by coupled kinetic processes between the gas phase, the particle interface, and its bulk, which respond dynamically to reactive consumption of O 3 . However, models of atmospheric aerosol reactivity often do not account for the coupled nature of multiphase processes. Herein, to examine these dynamics, we use new and prior experimental observations of aqueous droplet reaction kinetics, including three systems with a range of surface affinities and ozonolysis rate coefficients ( trans -aconitic acid (C 6 H 6 O 6 ), maleic acid (C 4 H 4 O 4 ), and sodium nitrite (NaNO 2 )). Using literature rate coefficients and thermodynamic properties, we constrain a simple two-compartment stochastic kinetic model which resolves the interface from the particle bulk and represents O 3 partitioning, diffusion, and reaction as a coupled kinetic system. Our kinetic model accurately predicts decay kinetics across all three systems, demonstrating that both the thermodynamic properties of O 3 and the coupled kinetic and diffusion processes are key to making accurate predictions. An enhanced concentration of adsorbed O 3 , compared to gas and bulk phases is rapidly maintained and remains constant even as O 3 is consumed by reaction. Multiphase systems dynamically seek to achieve equilibrium in response to reactive O 3 loss, but this is hampered at solute concentrations relevant to aqueous aerosol by the rate of O 3 arrival in the bulk by diffusion. As a result, bulk-phase O 3 becomes depleted from its Henry's law solubility. This bulk-phase O 3 depletion limits reaction timescales for relatively slow-reacting organic solutes with low interfacial affinity (i.e., trans-aconitic and maleic acids, with k rxn ≈ 10 3 -10 4 M -1 s -1 ), which is in contrast to fast-reacting solutes with higher surface affinity (i.e., nitrite, with k rxn ≈ 10 5 M -1 s -1 ) where surface reactions strongly impact the observed decay kinetics.

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

Tuning the Electronic Properties of Graphane via Hydroxylation: An Ab Initio Study

The thermodynamic stability of hydroxylated graphane, that is, fully sp 3 graphene derivatives coordinated with -H and -OH groups, has been recently demonstrated by ab initio calculations. Within the density functional theory approach, we investigate the electronic property modifications of graphane by progressive hydroxylation, that is, by progressively substituting -H with -OH groups. When 50% of graphane is hydroxylated, the energy bandgap reaches its largest value of 6.68 eV. The electronic affinity of 0.8 eV for graphane can widely change in the 0.28–1.60 eV range depending on the geometric configuration. Hydroxylated graphane has two interfaces with vacuum, hence its electron affinity can be different on each interface with the formation of an intrinsic dipole perpendicular to the monolayer. We envisage the possibility of using hydroxylated graphane allotropes with tunable electronic affinity to serve as interfacial layers in 2D material-based heterojunctions.

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

Breaking the Brønsted–Evans–Polanyi Relation with Dual-Metal Sites

Linear scaling relationships impose inherent limitations on catalyst activity; the Brønsted−Evans−Polanyi (BEP) relation, which correlates activation and reaction energies, is a prominent example. Here we report a dual-metal site catalyst (DMSC) on ceria that breaks the BEP relation for C−C coupling of methyl intermediates an elementary step in methane coupling to form ethane. The DMSC structure on CeO 2 (111) was discovered by density-functional theory (DFT) structural exploration and confirmed to be stable via ab initio thermodynamics and ab initio molecular dynamics. Homonuclear and heteronuclear DMSCs of Ni, Pd, Pt, Fe, Ru, Os, Co, Rh, and Ir (45 pairs in total) were examined for methyl affinity and methyl−methyl coupling activation energy. We found that many heteronuclear DMSCs break the BEP linear scaling due to a mixed low-affinity/high-affinity coadsorption of the two methyl groups, decoupling the step responsible for the activation energy (E a ) at the low-affinity site from the overall reaction energy (ΔE) determined by both sites. This mechanism of breaking the BEP relationship via the DMSCs offers a catalyst design principle for C−C coupling reactions.

Chen, Yiming [Vanderbilt Univ., Nashville, TN (Uni↗
DOE OSTI2024

Self-Assembled Bolaamphiphile-Based Organic Nanotubes as Efficient Cu(II) Ion Adsorbents

Self-assembled organic nanotubes (ONTs) have been actively examined for various applications such as chemical separations and catalysis owing to their well-defined tubular nanostructures with distinct chemical environments at the wall and internal/external surfaces. Adsorption of heavy metal ions onto ONTs plays an essential role in many of these applications, but it has rarely been assessed quantitatively. Herein, we investigated interactions between Cu 2+ and single-/quadruple-wall bolaamphiphile-based ONTs having inner carboxyl groups with different inner diameters, COOH-ONT 10nm and COOH-ONT 20nm . We first examined the effects of Cu 2+ on their nanotubular structures using SAXS, STEM, and AFM. COOH-ONT 10nm was stable in aqueous Cu 2+ solution in contrast to COOH-ONT 20nm owing to the presence of polyglycine-II-type hydrogen bonding networks within its wall. Subsequently, we studied the Cu 2+ adsorption behavior of COOH-ONT 10nm by monitoring the concentration of unbound Cu 2+ using linear sweep anodic stripping voltammetry. The Cu 2+ adsorption was quick, attributable to efficient Cu 2+ partitioning through the open ends of the ONT, followed by fast Cu 2+ diffusion in the uniform, relatively large nanochannel. More importantly, the Cu 2+ adsorption capacity and affinity of COOH-ONT 10nm were measured at different pH using the Langmuir adsorption model. The adsorption capacity was similar at the pH range examined, showing the participation of approximately 25% of the inner carboxyl groups in the adsorption. The adsorption affinity increased with pH, indicating the essential role of the deprotonated carboxyl groups in the Cu 2+ adsorption. Most interestingly, the Langmuir adsorption constant was significantly higher than those of previously reported synthetic adsorbents and planar monolayer based on carboxyl binding sites. The high Cu 2+ affinity of the ONT was attributable to the highly dense binding sites on the well-defined nanoscale concave structure of the inner channel. Furthermore, these results provide a valuable guideline to designing self-assembled nanomaterials for efficient chemical separations, detection, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Molecular-scale Insights into Cooperativity Switching of x TAB Adsorption on Gold Nanoparticles

Quantifying adsorption behaviors is crucial for various applications such as catalysis, separation, and sensing, yet it is generally challenging to access in solution. Here, we report a combined experimental and computational study of the adsorption behaviors of alkyl-trimethylammonium bromides (xTAB), a class of ligands important for colloidal nanoparticle stabilization and shape control, with various alkyl chain lengths x on Au nanoparticles. We use density functional theory (DFT) to calculate xTAB binding energies on Au{111} and Au{110} surfaces with standing-up and lying-down configurations, which provides insights into the adsorption affinity and cooperativity differences of xTAB on these two facets. We demonstrate the key role of van der Waals interactions in determining the xTAB adsorption behavior. These computational results predict and explain the experimental discovery of xTAB’s adsorption behavior switch from stronger affinity, negative cooperativity to weaker affinity, positive cooperativity when the concentration of xTAB increases in solution. We also show that in the standing-up configuration, bilayer adsorption may occur on both facets, which can lead to different differential binding energies and consequently adsorption crossover between the two facets when the ligand concentration increases. Our combined experimental and computational approaches demonstrate a paradigm for gaining molecular-scale insights into adsorbate–surface interactions.

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

Engineered pH-Sensitive Protein G/IgG Interaction

While natural protein–protein interactions have evolved to be induced by complex stimuli, rational design of interactions that can be switched-on-demand still remain challenging in the protein design world. Here, we demonstrate that a computationally redesigned natural interface for improved binding affinity could further be mutated to adopt a pH switchable interaction. The redesigned interface of Protein G/human IgG Fc domain (referred to as PrG/hIgG), when incorporated with histidine and glutamic acid on PrG (PrG-EHHE), showed a switch in binding affinity by 50-fold when the pH was altered from mild acidic to mild basic. The wild-type (WT) interface showed a negligible switch. The overall binding affinity under mild acidic pH for PrG-EHHE outperformed the wild-type PrG (PrG-WT) interaction. Overall, we find that the new reagent PrG-EHHE can be revolutionary in IgG purification, since the standard method of using an extreme acidic pH for elution can be circumvented.

59 BASIC BIOLOGICAL SCIENCES↗