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DOE OSTI2026

Phosphoserine Charge State Drives Ion Condensation and Spatial Polyamine Presentation in Multirepeat Silaffin

Diatom silaffins direct silica biomineralization through heavily post-translationally modified repeat domains, yet how these modifications reshape the multirepeat conformational ensemble remains unknown. We report all-atom MD simulations of a 195-residue construct spanning repeats R1–R7 of Sil1p from Cylindrotheca fusiformis, carrying the full complement of native PTMs: phosphoserine (pSer), long-chain polyamines (LCPA), dimethyllysine (MLY), and trimethylhydroxylysine phosphate (TPL). We simulated three variants (Native, P1/singly deprotonated phosphate, and P2/doubly deprotonated phosphate) at two NaCl concentrations in triplicate for 500 ns each. All systems disorder from the AlphaFold 3 starting structure. Phosphate charge state, not ionic strength, is the dominant control of ensemble compaction and ion organization. Doubly deprotonated phosphate organizes an extensive Na + condensation shell (∼100 ions, 20% of box Na + ) and a heterogeneous bridging network that integrates both pSer and TPL phosphate groups. The resulting ensemble is compact with LCPA side chains exhibiting above-median solvent accessibility in 84% of simulation frames in P2 at 300 mM. This is higher than any other condition we simulated and indicates that polyamine groups are preferentially surface-presented in the most compact, ion-organized state. A charge-neutralization control confirms that this compact state is a structured intermediate maintained by the bridging network, not a simple collapsed globule. Here, this repeat-scale spatial organization is not captured by single-repeat peptide studies. Understanding the dynamics, mechanism, and spatial organization of PTM-rich silaffin at the repeat scale is a step closer to hierarchical biomimetic materials beyond simple silica morphologies.

Amines↗

DOE OSTI2015

A composite approach towards a complete model of the myosin rod

Sarcomeric myosins have the remarkable ability to form regular bipolar thick filaments that, together with actin thin filaments, constitute the fundamental contractile unit of skeletal and cardiac muscle. This has been established for over 50 years and yet a molecular model for the thick filament has not been attained. In part this is due to the lack of a detailed molecular model for the coiled–coil that constitutes the myosin rod. The ability to self–assemble resides in the C–terminal section of myosin known as light meromyosin (LMM) which exhibits strong salt–dependent aggregation that has inhibited structural studies. Here we evaluate the feasibility of generating a complete model for the myosin rod by combining overlapping structures of five sections of coiled–coil covering 164 amino acid residues which constitute 20% of LMM. Each section contains ~7–9 heptads of myosin. The problem of aggregation was overcome by incorporating the globular folding domains, Gp7 and Xrcc4 which enhance crystallization. The effect of these domains on the stability and conformation of the myosin rod was examined through biophysical studies and overlapping structures. In addition, a computational approach was developed to combine the sections into a contiguous model. The structures were aligned, trimmed to form a contiguous model, and simulated for >700 ns to remove the discontinuities and achieve an equilibrated conformation that represents the native state. As a result, this experimental and computational strategy lays the foundation for building a model for the entire myosin rod.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Evaluation of native Earth system model output with ESMValTool v2.6.0

Earth system models (ESMs) are state-of-the-art climate models that allow numerical simulations of the past, present-day, and future climate. To extend our understanding of the Earth system and improve climate change projections, the complexity of ESMs heavily increased over the last decades. As a consequence, the amount and volume of data provided by ESMs has increased considerably. Innovative tools for a comprehensive model evaluation and analysis are required to assess the performance of these increasingly complex ESMs against observations or reanalyses. One of these tools is the Earth System Model Evaluation Tool (ESMValTool), a community diagnostic and performance metrics tool for the evaluation of ESMs. Input data for ESMValTool needs to be formatted according to the CMOR (Climate Model Output Rewriter) standard, a process that is usually referred to as “CMORization”. While this is a quasi-standard for large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP), this complicates the application of ESMValTool to non-CMOR-compliant climate model output. In this paper, we describe an extension of ESMValTool introduced in v2.6.0 that allows seamless reading and processing of “native” climate model output, i.e., operational output produced by running the climate model through the standard workflow of the corresponding modeling institute. This is achieved by an extension of ESMValTool's preprocessing pipeline that performs a CMOR-like reformatting of the native model output during runtime. Thus, the rich collection of diagnostics provided by ESMValTool is now fully available for these models. For models that use unstructured grids, a further preprocessing step required to apply many common diagnostics is regridding to a regular latitude–longitude grid. Extensions to ESMValTool's regridding functions described here allow for more flexible interpolation schemes that can be used on unstructured grids. Currently, ESMValTool supports nearest-neighbor, bilinear, and first-order conservative regridding from unstructured grids to regular grids. Example applications of this new native model support are the evaluation of new model setups against predecessor versions, assessing of the performance of different simulations against observations, CMORization of native model data for contributions to model intercomparison projects, and monitoring of running climate model simulations. For the latter, new general-purpose diagnostics have been added to ESMValTool that are able to plot a wide range of variable types. Currently, five climate models are supported: CESM2 (experimental; at the moment, only surface variables are available), EC-Earth3, EMAC, ICON, and IPSL-CM6. As the framework for the CMOR-like reformatting of native model output described here is implemented in a general way, support for other climate models can be easily added.

58 GEOSCIENCES↗

DOE OSTI2022

Utah FORGE Phase 3 Native State Model: 2022 Update

This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. This data archive consists of 10 files, 4 of which are simulation input files and the remaining 6 are simulation output files. There is an included readme.txt file that contains details on each of the data files. The input files include meshes, FALCON code inputs, tabulated data of water properties, temperature values, and model boundaries. The output files include simulation outfiles and point data of modeled material properties.

15 GEOTHERMAL ENERGY↗

DOE OSTI2014

Distance Restraints from Crosslinking Mass Spectrometry: Mining a Molecular Dynamics Simulation Database to Evaluate Lysine-Lysine Distances

Integrative structural biology models the structures of protein complexes that are intractable by classical structural methods (because of extreme size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such method is chemical cross-linking mass spectrometry (XL-MS), in which cross-linked peptides, derived from a covalently cross-linked protein complex and identified by liquid chromatography-mass spectrometry, pinpoint protein residues close in three-dimensional space. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 Å long when fully extended. However, XL-MS studies on proteins of known structure frequently report cross-links that exceed this distance. Typically, a tolerance of ~3 Å is added to the theoretical maximum to account for this observation, with little justification for the value chosen. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of all protein folds, to investigate the change in lysine-lysine distances resulting from native-state dynamics on the time-scale of tens of nanoseconds. We conclude that observed cross-links are consistent with a protein structure if the distance between cross-linked lysine Nζ atoms is less than the cross-linker length plus 11.3 Å. For DSS or BS3, this corresponds to a Cα to Cα distance of 30.4 Å. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures, and indicates the appropriate values of an XLMS derived distance constraint to use in structural modeling.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Modeling soil CO<sub>2</sub> production and transport with dynamic source and diffusion terms: testing the steady-state assumption using DETECT v1.0

Abstract. The flux of CO2 from the soil to the atmosphere (soil respiration, Rsoil) is a major component of the global carbon (C) cycle. Methods to measure and model Rsoil, or partition it into different components, often rely on the assumption that soil CO2 concentrations and fluxes are in steady state, implying that Rsoil is equal to the rate at which CO2 is produced by soil microbial and root respiration. Recent research, however, questions the validity of this assumption. Thus, the aim of this work was two-fold: (1) to describe a non-steady state (NSS) soil CO2 transport and production model, DETECT, and (2) to use this model to evaluate the environmental conditions under which Rsoil and CO2 production are likely in NSS. The backbone of DETECT is a non-homogeneous, partial differential equation (PDE) that describes production and transport of soil CO2, which we solve numerically at fine spatial and temporal resolution (e.g., 0.01 m increments down to 1 m, every 6 h). Production of soil CO2 is simulated for every depth and time increment as the sum of root respiration and microbial decomposition of soil organic matter. Both of these factors can be driven by current and antecedent soil water content and temperature, which can also vary by time and depth. We also analytically solved the ordinary differential equation (ODE) corresponding to the steady-state (SS) solution to the PDE model. We applied the DETECT NSS and SS models to the six-month growing season period representative of a native grassland in Wyoming. Simulation experiments were conducted with both model versions to evaluate factors that could affect departure from SS, such as (1) varying soil texture; (2) shifting the timing or frequency of precipitation; and (3) with and without the environmental antecedent drivers. For a coarse-textured soil, Rsoil from the SS model closely matched that of the NSS model. However, in a fine-textured (clay) soil, growing season Rsoil was ∼ 3 % higher under the assumption of NSS (versus SS). These differences were exaggerated in clay soil at daily time scales whereby Rsoil under the SS assumption deviated from NSS by up to 35 % on average in the 10 days following a major precipitation event. Incorporation of antecedent drivers increased the magnitude of Rsoil by 15 to 37 % for coarse- and fine-textured soils, respectively. However, the responses of Rsoil to the timing of precipitation and antecedent drivers did not differ between SS and NSS assumptions. In summary, the assumption of SS conditions can be violated depending on soil type and soil moisture status, as affected by precipitation inputs. The DETECT model provides a framework for accommodating NSS conditions to better predict Rsoil and associated soil carbon cycling processes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Unfolding of Proteins: Thermal and Mechanical Unfolding

We have employed a Hamiltonian model based on a self-consistent Gaussian appoximation to examine the unfolding process of proteins in external - both mechanical and thermal - force elds. The motivation was to investigate the unfolding pathways of proteins by including only the essence of the important interactions of the native-state topology. Furthermore, if such a model can indeed correctly predict the physics of protein unfolding, it can complement more computationally expensive simulations and theoretical work. The self-consistent Gaussian approximation by Micheletti et al. has been incorporated in our model to make the model mathematically tractable by signi cantly reducing the computational cost. All thermodynamic properties and pair contact probabilities are calculated by simply evaluating the values of a series of Incomplete Gamma functions in an iterative manner. We have compared our results to previous molecular dynamics simulation and experimental data for the mechanical unfolding of the giant muscle protein Titin (1TIT). Our model, especially in light of its simplicity and excellent agreement with experiment and simulation, demonstrates the basic physical elements necessary to capture the mechanism of protein unfolding in an external force field.

Hur, Joe S.↗

DOE OSTI2026

Pulse control of superconducting cavity-based qudits with a Fock-state basis

Fock-basis-encoding qudits allow quantum gates to operate on multiple qudit levels simultaneously. This capability is advantageous for applications involving complex local gate operations, such as the digital quantum simulation of non-Abelian gauge theories. However, compiling unitary operations to native qudit gates remains a challenging task, often requiring substantial computational resources. In this work, we theoretically investigate the direct pulse control of a superconducting radio-frequency cavity coupled to an ancilla transmon for gate synthesis. We will discuss the improvements and limitations applicable to high Fock states. This work paves the way toward more efficient and robust qudit-gate synthesis.

Li, Andy C.Y. [Fermilab] (ORCID:0000000345423739)↗

DOE OSTI2026

Pulse control of superconducting cavity-based qudits with a Fock-state basis

Li, Andy C.Y. [Fermilab] (ORCID:0000000345423739)↗

DOE OSTI2019

Orientational Dynamics of Transition Dipoles and Exciton Relaxation in LH2 from Ultrafast Two-Dimensional Anisotropy

Light-harvesting complexes in photosynthetic organisms display fast and efficient energy transfer dynamics, which depend critically on the electronic structure of the coupled chromophores within the complexes and their interactions with their environment. We present ultrafast anisotropy dynamics, resolved in both time and frequency, of the transmembrane light-harvesting complex LH2 from Rhodobacter sphaeroides in its native membrane environment using polarization-controlled two-dimensional electronic spectroscopy. Time-dependent anisotropy obtained from both experiment and modified Redfield simulation reveals an orientational preference for excited state absorption and an ultrafast equilibration within the B850 band in LH2. This ultrafast equilibration is favorable for subsequent energy transfer toward the reaction center. Our results also show a dynamic difference in excited state absorption anisotropy between the directly excited B850 population and the population that is initially excited at 800 nm, suggesting absorption from B850 states to higher-lying excited states following energy transfer from B850*. Finally, these results give insight into the ultrafast dynamics of bacterial light harvesting and the excited state energy landscape of LH2 in the native membrane environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Advancing xEMU Lunar Dust Mitigation Devices

Fine, electrically charged, glass like dust particles caused significant damage to the Apollo EMU9 during lunar EVAs, identified as one of the greatest challenges to future exploration. Passive Lunar Dust Mitigation Devices (LDMD) were developed, within a SBIR Phase II, to prohibit this dust from interrupting venting space suit component operation. A Computational Fluid-Dynamics and Discrete Element Method (CFD-DEM) Simulation Tool was developed at the University of Colorado, Boulder to predict venting gas flow ability to self-clean adhered dust particles from LDMD surfaces. Lunar dust properties (i.e., adhesion and cohesion strengths) required to complete Simulation Tool analysis are relatively unknown due to considerable differences between the Earth and the Moon (i.e., gravity, humidity) and due to an absence of dust particles in their native state. Analytically determining gas flow velocity, density and direction within the fluid Boundary Layer, microns from LDMD surfaces presented a second challenge. Dusty Plasma Chamber testing is being performed at Auburn University, Auburn to observe electrostatically charged dust behavior as it adheres to LDMD prototypes and specific geometry and is then blown away by metered gas flow. Test articles were developed to offer insight into the impact of different flow geometries, surface roughness and dust removal within the gas Boundary-Layer. Observed dust behavior is currently being developed to support the CFD-DEM analysis. Many Simulation Tool analytical cases have been processed to support the intention of completing sensitivity studies to assess how different dust adherence values and Boundary Layer fluid properties impact LDMD self-cleaning effectivity.

Thomas J Stapleton↗

DOE OSTI2014

Wang-Landau density of states based study of the folding-unfolding transition in the mini-protein Trp-cage (TC5b)

We present the results of a high-statistics equilibrium study of the folding/unfolding transition for the 20-residue mini-protein Trp-cage (TC5b) in water. The ECEPP/3 force field is used and the interaction with water is treated by a solvent-accessible surface area method. A Wang-Landau type simulation is used to calculate the density of states and the conditional probabilities for the various values of the radius of gyration and the number of native contacts at fixed values of energy—along with a systematic check on their convergence. All thermodynamic quantities of interest are calculated from this information. The folding-unfolding transition corresponds to a peak in the temperature dependence of the computed specific heat. This is corroborated further by the structural signatures of folding in the distributions for radius of gyration and the number of native contacts as a function of temperature. The potentials of mean force are also calculated for these variables, both separately and jointly. A local free energy minimum, in addition to the global minimum, is found in a temperature range substantially below the folding temperature. The free energy at this second minimum is approximately 5 k{sub B}T higher than the value at the global minimum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2015

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗

DOE OSTI2017

Disorder enabled band structure engineering of a topological insulator surface

Three-dimensional topological insulators are bulk insulators with Z 2 topological electronic order that gives rise to conducting light-like surface states. These surface electrons are exceptionally resistant to localization by non-magnetic disorder, and have been adopted as the basis for a wide range of proposals to achieve new quasiparticle species and device functionality. Recent studies have yielded a surprise by showing that in spite of resisting localization, topological insulator surface electrons can be reshaped by defects into distinctive resonance states. Here we use numerical simulations and scanning tunnelling microscopy data to show that these resonance states have significance well beyond the localized regime usually associated with impurity bands. Lastly, at native densities in the model Bi 2 X 3 (X=Bi, Te) compounds, defect resonance states are predicted to generate a new quantum basis for an emergent electron gas that supports diffusive electrical transport.

36 MATERIALS SCIENCE↗

DOE OSTI2019

The dynamic conformational landscape of the protein methyltransferase SETD8

Elucidating the conformational heterogeneity of proteins is essential for understanding protein function and developing exogenous ligands. With the rapid development of experimental and computational methods, it is of great interest to integrate these approaches to illuminate the conformational landscapes of target proteins. SETD8 is a protein lysine methyltransferase (PKMT), which functions in vivo via the methylation of histone and nonhistone targets. Utilizing covalent inhibitors and depleting native ligands to trap hidden conformational states, we obtained diverse X-ray structures of SETD8. These structures were used to seed distributed atomistic molecular dynamics simulations that generated a total of six milliseconds of trajectory data. Markov state models, built via an automated machine learning approach and corroborated experimentally, reveal how slow conformational motions and conformational states are relevant to catalysis. These findings provide molecular insight on enzymatic catalysis and allosteric mechanisms of a PKMT via its detailed conformational landscape.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein’s structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Unlocking the unfolded structure of ubiquitin: Combining time-resolved x-ray solution scattering and molecular dynamics to generate unfolded ensembles

The unfolding dynamics of ubiquitin were studied using a combination of x-ray solution scattering (XSS) and molecular dynamics (MD) simulations. The kinetic analysis of the XSS ubiquitin signals showed that the protein unfolds through a two-state process, independent of the presence of destabilizing salts. In order to characterize the ensemble of unfolded states in atomic detail, the experimental XSS results were used as a constraint in the MD simulations through the incorporation of x-ray scattering derived potential to drive the folded ubiquitin structure toward sampling unfolded states consistent with the XSS signals. We detail how biased MD simulations provide insight into unfolded states that are otherwise difficult to resolve and underscore how experimental XSS data can be combined with MD to efficiently sample structures away from the native state. Our results indicate that ubiquitin samples unfolded in states with a high degree of loss in secondary structure yet without a collapse to a molten globule or fully solvated extended chain. Finally, we propose how using biased-MD can significantly decrease the computational time and resources required to sample experimentally relevant nonequilibrium states.

Chemistry↗