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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Supercharging simulation-based inference for Bayesian optimal experimental design

Abstract Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG maximization and show that a simple multi-start parallel gradient ascent procedure can substantially improve reliability and performance. With these innovations, our SBI-based BOED methods are able to match or outperform by up to 22% existing state-of-the-art approaches across standard BOED benchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

Our study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and takes account of the over dispersion in the data that leads to a superior data fitting. But, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Moreover, the correlations among the latent effects of different severity levels are found significant in both datasets that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Design of a Multi-Chemistry Battery Pack System for Behind-the-Meter Storage Applications

Battery management systems (BMS) are essential for a battery pack's safe operation and longevity. This paper presents an active balancing method-based BMS for different cell chemistry structures to be used in behind-the-meter storage (BTMS) applications. The proposed system utilizes modular isolated dual active bridge (DAB) DC/DC converters to actively balance the battery pack through a low voltage (LV) bus. A supervisory controller monitors all the cell voltage, current, and state of charge (SOC) values. Based on the estimation of the SOCs, reference currents for the DAB converters are generated by the supervisory controller. Detailed modeling and the control approach of the modular DAB converters are presented in the paper. Moreover, the control strategy of the supervisory control is also analyzed. The proposed method and structure can be extended to any combination of the number of cells to design the battery pack. Simulation results are provided for a system consisting of three cells in parallel to form a cell block and three cell blocks in series to form the battery module. Experimental results are provided for three modular DAB converters operating with a LiFeMnPO4 prismatic cell with 3.2V, 20Ah rated values.

battery management systems↗
DOE OSTI2016

Collaborative Project: Building improved optimized parameter estimation algorithms to improve methane and nitrogen fluxes in a climate model

Soils in natural and managed ecosystems and wetlands are well known sources of methane, nitrous oxides, and reactive nitrogen gases, but the magnitudes of gas flux to the atmosphere are still poorly constrained. Thus, the reasons for the large increases in atmospheric concentrations of methane and nitrous oxide since the preindustrial time period are not well understood. The low atmospheric concentrations of methane and nitrous oxide, despite being more potent greenhouse gases than carbon dioxide, complicate empirical studies to provide explanations. In addition to climate concerns, the emissions of reactive nitrogen gases from soils are important to the changing nitrogen balance in the earth system, subject to human management, and may change substantially in the future. Thus improved modeling of the emission fluxes of these species from the land surface is important. Currently, there are emission modules for methane and some nitrogen species in the Community Earth System Model’s Community Land Model (CLM-ME/N); however, there are large uncertainties and problems in the simulations, resulting in coarse estimates. In this proposal, we seek to improve these emission modules by combining state-of-the-art process modules for emissions, available data, and new optimization methods. In earth science problems, we often have substantial data and knowledge of processes in disparate systems, and thus we need to combine data and a general process level understanding into a model for projections of future climate that are as accurate as possible. The best methodologies for optimization of parameters in earth system models are still being developed. In this proposal we will develop and apply surrogate algorithms that a) were especially developed for computationally expensive simulations like CLM-ME/N models; b) were (in the earlier surrogate optimization Stochastic RBF) demonstrated to perform very well on computationally expensive complex partial differential equations in earth science with limited numbers of simulations; and, c) will be (as part of the proposed research) significantly improved both by adding asynchronous parallelism, early truncation of unsuccessful simulations, and the improvement of both serial and parallel performance by the use of derivative and sensitivity information from global and local surrogate approximations S(x) . The algorithm development and testing will be focused on the CLM-ME/N model application, but the methods are general and are expected to also perform well on optimization for parameter estimation of other climate models and other classes of continuous multimodal optimization problems arising from complex simulation models. In addition, this proposal will compile available datasets of emissions of methane, nitrous oxides and reactive nitrogen species and develop protocols for site level comparisons with the CLM-ME/N. Once the model parameters are optimized against site level data, the model will be simulated at the global level and compared to atmospheric concentration measurements for the current climate, and future emissions will be estimated using climate change as simulated by the CESM. This proposal combines experts in earth system modeling, optimization, computer science, and process level understanding of soil gas emissions in an interdisciplinary team in order to improve the modeling of methane and nitrogen gas emissions. This proposal thus meets the requirements of the SciDAC RFP, by integrating state-of-the-art computer science and earth system to build an improved earth system model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The hydrogen tunneling splitting in malonaldehyde: A full-dimensional time-independent quantum mechanical method

The accurate time-independent quantum dynamics calculations on the ground-state tunneling splitting of malonaldehyde in full dimensionality are reported for the first time. This is achieved with an efficient method developed by us. In our method, the basis functions are customized for the hydrogen transfer process which has the effect of greatly reducing the size of the final Hamiltonian matrix, and the Lanczos method and parallel strategy are used to further overcome the memory and central processing unit time bottlenecks. The obtained ground-state tunneling splitting of 24.5 cm{sup −1} is in excellent agreement with the benchmark value of 23.8 cm{sup −1} computed with the full-dimensional, multi-configurational time-dependent Hartree approach on the same potential energy surface, and we estimate that our reported value has an uncertainty of less than 0.5 cm{sup −1}. Moreover, the role of various vibrational modes strongly coupled to the hydrogen transfer process is revealed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Ferromagnetic and paramagnetic magnetization of implanted GaN:Ho,Tb,Sm,Tm films

The SQUID magnetic measurements were performed on the GaN films prepared by metal-organic vapour phase epitaxy and implanted by Tb{sup 3+}, Tm{sup 3+}, Sm{sup 3+}, and Ho{sup 3+} ions. The sapphire substrate was checked by the electron paramagnetic resonance method which showed a content of Cr{sup 3+} and Fe{sup 3+} impurities. The samples 5 × 5 mm{sup 2} were positioned in the classical straws and within an estimated accuracy of 10{sup −6 }emu, no ferromagnetic moment was detected in the temperature region of 2–300 K. The paramagnetic magnetization was studied for parallel and perpendicular orientation. In the case of GaN:Tb sample, at T = 2 K, a pronounced anisotropy with the easy axis perpendicular to the film was observed which can be explained by the lowest quasi-doublet state of the non-Kramers Tb{sup 3+} ion. The Weiss temperature deduced from the susceptibility data using the Curie-Weiss (C-W) law was found to depend substantially on the magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Tuning Shinkarev’s Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ferrari, Nicholas [Louisiana State Univ., Baton Ro↗
DOE OSTI2022

Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization

The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.

58 GEOSCIENCES↗
DOE OSTI2019

Applying Machine Learning to Understand Write Performance of Large-scale Parallel Filesystems

In high-performance computing (HPC), I/O performance prediction offers the potential to improve the efficiency of scientific computing. In particular, accurate prediction can make runtime estimates more precise, guide users toward optimal checkpoint strategies, and better inform facility provisioning and scheduling policies. HPC I/O performance is notoriously difficult to predict and model, however, in large part because of inherent variability and a lack of transparency in the behaviors of constituent storage system components. In this work we seek to advance the state of the art in HPC I/O performance prediction by (1) modeling the mean performance to address high variability, (2) deriving model features from write patterns, system architecture and system configurations, and (3) employing Lasso regression model to improve model accuracy. We demonstrate the efficacy of our approach by applying it to a crucial subset of common HPC I/O motifs, namely, file-per-process checkpoint write workloads. We conduct experiments on two distinct production HPC platforms—Titan at the Oak Ridge Leadership Computing Facility and Cetus at the Argonne Leadership Computing Facility—to train and evaluate our models. We find that we can attain ≤ 30% relative error for 92.79% and 99.64% of the samples in our test set on these platforms, respectively.

Xie, Bing↗
DOE OSTI2014

Use of system code to estimate equilibrium tritium inventory in fusion DT machines, such as ARIES-AT and components testing facilities

ITER is under construction and will begin operation in 2020. This is the first 500 MWfusion class DT device, and since it is not going to breed tritium, it will consume most of the limited supply of tritium resources in the world. Yet, in parallel, DT fusion nuclear component testing machines will be needed to provide technical data for the design of DEMO. It becomes necessary to estimate the tritium burn-up fraction and corresponding initial tritium inventory and the doubling time of these machines for the planning of future supply and utilization of tritium. With the use of a system code, tritium burn-up fraction and initial tritium inventory for steady state DT machines can be estimated. Estimated tritium burn-up fractions of FNSF-AT, CFETR-R and ARIES-AT are in the range of 1–2.8%. Corresponding total equilibrium tritium inventories of the plasma flow and tritium processing system, and with the DCLL blanket option are 7.6 kg, 6.1 kg, and 5.2 kg for ARIES-AT, CFETR-R and FNSF-AT, respectively.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Transient and Steady-State Inverse Problems in Sierra/Aria

Inverse problems arise in a wide range of applications, whenever unknown model parameters cannot be measured directly. Instead, the unknown parameters are estimated using experimental data and forward simulations. Thermal inverse problems, such as material characterization problems, are often large-scale and transient. Therefore, they require intrusive adjoint-based gradient implementations in order to be solved efficiently. The capability to solve large-scale transient thermal inverse problems using an adjoint-based approach was recently implemented in SNL Sierra Mechanics, a massively parallel capable multiphysics code suite. This report outlines the theory, optimization formulation, and path taken to implement thermal inverse capabilities in Sierra within a unit test framework. The capability utilizes Sierra/Aria and Sierra/Fuego data structures, the Rapid Optimization Library, and an interface to the Sierra/InverseOpt library. The existing Sierra/Aria time integrator is leveraged to implement a time-dependent adjoint solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Oxygen transport properties estimation by DSMC-CT simulations

Coupling DSMC simulations with classical trajectories calculations is emerging as a powerful tool to improve predictive capabilities of computational rarefied gas dynamics. The considerable increase of computational effort outlined in the early application of the method (Koura,1997) can be compensated by running simulations on massively parallel computers. In particular, GPU acceleration has been found quite effective in reducing computing time (Ferrigni,2012; Norman et al.,2013) of DSMC-CT simulations. The aim of the present work is to study rarefied Oxygen flows by modeling binary collisions through an accurate potential energy surface, obtained by molecular beams scattering (Aquilanti, et al.,1999). The accuracy of the method is assessed by calculating molecular Oxygen shear viscosity and heat conductivity following three different DSMC-CT simulation methods. In the first one, transport properties are obtained from DSMC-CT simulations of spontaneous fluctuation of an equilibrium state (Bruno et al, Phys. Fluids, 23, 093104, 2011). In the second method, the collision trajectory calculation is incorporated in a Monte Carlo integration procedure to evaluate the Taxman’s expressions for the transport properties of polyatomic gases (Taxman,1959). In the third, non-equilibrium zero and one-dimensional rarefied gas dynamic simulations are adopted and the transport properties are computed from the non-equilibrium fluxes of momentum and energy. The three methods provide close values of the transport properties, their estimated statistical error not exceeding 3%. The experimental values are slightly underestimated, the percentage deviation being, again, few percent.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Adsorbent Alkali Conditioning for Uranium Adsorption from Seawater. Adsorbent Performance and Technology Cost Evaluation

The Fuel Resources program of the Fuel Cycle Research and Development program of the Office of Nuclear Energy (NE) is focused on identifying and implementing actions to assure that nuclear fuel resources are available in the United States. An immense source of uranium is seawater, which contains an estimated amount of 4.5 billion tonnes of dissolved uranium. This unconventional resource can provide a price cap and ensure centuries of uranium supply for future nuclear energy production. NE initiated a multidisciplinary program with participants from national laboratories, universities, and research institutes to enable technical breakthroughs related to uranium recovery from seawater. The goal is to develop advanced adsorbents to reduce the seawater uranium recovery technology cost and uncertainties. Under this program, Oak Ridge National Laboratory (ORNL) has developed a new amidoxime-based adsorbent of high surface area, which tripled the uranium capacity of leading Japanese adsorbents. Parallel efforts have been focused on the optimization of the physicochemical and operating parameters used during the preparation of the adsorbent for deployment. A set of parameters that need to be optimized are related to the conditioning of the adsorbent with alkali solution, which is necessary prior to adsorbent deployment. Previous work indicated that alkali-conditioning parameters significantly affect the adsorbent performance. Initiated in 2014, this study had as a goal to determine optimal parameters such as base type and concentration, temperature, and duration of conditioning that maximize the uranium adsorption performance of amidoxime functionalized adsorbent, while keeping the cost of uranium production low. After base-treatment at various conditions, samples of adsorbent developed at ORNL were tested in this study with batch simulated seawater solution of 8-ppm uranium concentration, batch seawater spiked with uranium nitrate at 75-100 ppb uranium, and continuous-flow natural seawater at the Pacific Northwest National Laboratory (PNNL). Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, Scanning Electron Microscopy (SEM), and elemental analysis were used to characterize the adsorbent at different stages of adsorbent preparation and treatment. The study can be divided into two parts: (A) investigation of optimal parameters for KOH adsorbent conditioning and (B) investigation of other possible agents for alkali conditioning, including cost analysis on the basis of uranium production. In the first part of the study, tests with simulated seawater containing 8 ppm uranium showed that the uranium adsorption capacity increased with an increase in the KOH concentration and conditioning time and temperature at each of the KOH concentrations used. FTIR and solid state NMR studies indicated that KOH conditioning converts the amidoxime functional groups into more hydrophilic carboxylate. The longer the KOH conditioning time, up to three hours, the higher was the loading capacity from the simulated seawater solution which is composed of only uranyl, sodium, chloride, and carbonate ions. Marine testing with natural seawater, on the other hand, showed that the uranium adsorption capacity of the adsorbent increased with KOH conditioning temperature, and gradually decreased with increasing KOH conditioning time from one hour to three hours at 80 C. This behavior is due to the conversion of amidoxime to carboxylate. The carboxylate groups are needed to increase the hydrophilicity of the adsorbent; however, conversion of a significant amount of amidoxime to carboxylate leads to loss in selectivity toward uranyl ions. Thus, there is an optimum KOH conditioning time for each temperature at which an optimum ratio between amidoxime and carboxylate is reached. For the case of base conditioning with 0.44 M KOH at 80 C, the optimal conditioning time is 1 hour, with respect to the highest uranium loading capacity from natural seawater. Uptake of other metal ions such as V, Fe, and Cu follows the same trend as that of uranium. Also, the uptake of Ca, Mg, and Zn ions increased with increasing KOH conditioning time, probably due to formation of more carboxylates, which leads to conversion of uranium-selective binding sites to less selective sites. In the second part of the study, inorganic based reagents such as sodium hydroxide (NaOH), sodium carbonate (Na 2 CO 3 ), cesium hydroxide (CsOH), as well as organic based reagents such as ammonium hydroxide (AOH), tetramethylammonium hydroxide (TMAOH), tetraethylammonium hydroxide (TEAOH), triethylmethylammonium hydroxide (TEMAOH), tetrapropylammonium hydroxide (TPAOH) and tetrabutylammonium hydroxide (TBAOH), in addition to KOH, were used for alkaline conditioning. NaOH has emerged as a better reagent for alkaline conditioning of amidoxime-based adsorbent because of higher uranium uptake capacity, higher uranium uptake selectivity ...

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Grain in weakly ionized plasma in the presence of an external magnetic field: Charging by plasma currents and effective potential

The problem of grain screening is solved numerically for the case of weakly ionized plasma in the presence of an external magnetic field. The plasma dynamics is described within the drift-diffusion approximation under the assumption that the grain absorbs all encountered electrons and ions. We also assume that the plasma current through the grain surface is equal to zero in the stationary state. This condition is used to perform self-consistent calculations of the grain charge. The spatial distribution of the screened grain potential is studied and compared with the analytical estimates. It is shown that at the distances larger than the Debye length such potential has the Coulomb-like asymptotics with the effective charge dependent on the angle between the radius vector and the external magnetic field direction. The numerical solutions show that in the direction parallel to the external magnetic field the effective potential can have nonmonotonic behavior.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Magnetoresistive system with concentric ferromagnetic asymmetric nanorings

A structure consisting of two concentric asymmetric nanorings, each displaying vortex remanent states, is studied with micromagnetic calculations. By orienting in suitable directions, both the asymmetry of the rings and a uniform magnetic field, the vortices chiralities can be switched from parallel to antiparallel, obtaining in this way the analogue of the ferromagnetic and antiferromagnetic configurations found in bar magnets pairs. Conditions on the thickness of single rings to obtain vortex states, as well as formulas for their remanent magnetization are given. The concentric ring structure enables the creation of magnetoresistive systems comprising the qualities of magnetic nanorings, such as low stray fields and high stability. A possible application is as contacts in spin injection in semiconductors, and estimations obtained here of magnetoresistance change for a cylindrical spin injection based device show significant variations comparable to linear geometries.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Antiparallel interface coupling evidenced by negative rotatable anisotropy in IrMn/NiFe bilayers

Negative rotatable anisotropy is estimated via ferromagnetic resonance measurements in as-made, annealed, and ion-irradiated IrMn{sub 3}/Ni{sub 81}Fe{sub 19} bilayers. Opposite to previous observations, inverse correlation between rotatable anisotropy and coercivity is observed. The exchange-bias field, determined from hysteresis loop measurements, is higher than that obtained from ferromagnetic resonance for all samples. The results are discussed in terms of majority antiparallel coupling and magnetic-field-induced transitions from antiparallel to parallel states of uncompensated spins at ferromagnet/antiferromagnet interface. We affirm that an observation of negative rotatable anisotropy evidences antiparallel coupling even in systems presenting conventional exchange bias.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Editorial to the special issue on the 2015 TOUGH Symposium

This Special Issue of Transport in Porous Media features selected papers from the 2015 TOUGH Symposium, which took place on September 28–30, 2015, in Berkeley, California, USA. Such symposia are held every 3 years and are a forum where users of the TOUGH family of numerical simulators meet for an open exchange on the code applications and recent enhancements. The TOUGH codes (TOUGH is an acronym for Transport of Unsaturated Groundwater and Heat) were originally developed in the early 1980s for geothermal reservoir simulation by a team of researchers at the Lawrence Berkeley National Laboratory (LBNL) headed by Karsten Pruess (see http://esd.lbl.gov/TOUGH). The TOUGH codes have a modular structure in which different fluid components can be incorporated into the code by means of a replaceable equation of state (EOS) package. Since its first release, a variety of important EOS modules have been developed, enabling the modeling of volatile organic compounds, decay chains of multiple radionuclides, gas hydrates, tight and shale gas behavior, enhanced oil recovery, and supercritical water and CO 2 . Derivatives and descendants of the basic TOUGH code include coupled multi-phase flow and reactive chemical transport; coupled thermo-hydrologic-mechanical processes; inverse modeling for parameter estimation, sensitivity analysis, and uncertainty quantification; and parallelization for multi-core PCs, workstation clusters, and supercomputers. The TOUGH codes have been applied to a large variety of problems, including geothermal and petroleum reservoir engineering, nuclear waste and CO 2 geologic sequestration, subsurface environmental remediation, methane gas hydrate production, compressed air energy storage, and many other energy and environmental applications. Finally, the international TOUGH user community currently numbers almost 400 organizations (research laboratories, government agencies, private companies, universities, etc.) in over 60 countries.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

A Trichomonas vaginalis C2-XYPPX-repeat protein with a structured C2 domain displaying dampened flexibility upon binding calcium

C2 domains are ubiquitous membrane-binding modules of ∼130 residues in eukaryotes that are often associated with proteins involved in membrane trafficking and lipid modification. The genome of Trichomonas vaginalis, the most common, non-viral, sexually transmitted human pathogen, encodes eight genes that contain a N-terminal C2 module linked to a XYPPX-repeat domain of more than four XYPPX repeats (C2-XYPPX). While the function of the XYPPX-repeat domain remains unknown, its multiple association with C2 domains in T. vaginalis suggests it is important. Here, the C2 domain from one of these C2-XYPPX-repeat proteins, Tv-C2-1, was structurally and physically characterized using X-ray crystallography and NMR spectroscopy. The crystal structure for Tv-C2-1 shows that this domain shares a fold common to all C2 domains, a compact Greek-key motif composed of eight anti-parallel β-strands in the type-2 topology. An NMR chemical shift perturbation study with Ca 2+ showed that Tv-C2-1 bound two Ca 2+ atoms primarily via two loops (loop-1 and loop-3) on the predicted calcium binding face of the protein with K d s of 58.0 ± 0.1 μM and 232 ± 6 μM. Estimations of the overall rotational correlation time, τ c , in the apo (11.1 ns) and Ca 2+ -bound (9.2 ns) state suggests the protein becomes more compact upon Ca 2+ binding, consistent with a decrease in dynamics in loop-3 and marginally in loop-1 suggested by amide 15 N heteronuclear steady-state { 1 H}- 15 N NOEs. Showing Tv-C2-1 binds calcium and adopts a compact Greek-key motif structure, two primary features of C2 domains, suggests understanding the function of the XYPPX-repeat domain may be warranted.

NMR spectroscopy↗