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Results for “conformational ensembles”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An RNA aptamer exploits exosite-dependent allostery to achieve specific inhibition of coagulation factor IXa

Hemostasis relies on a reaction network of serine proteases and their cofactors to form a blood clot. Coagulation factor IXa (protease) plays an essential role in hemostasis as evident from the bleeding disease associated with its absence. RNA aptamers specifically targeting individual coagulation factors have potential as anticoagulants and as probes of the relationship between structure and function. Here, we report X-ray structures of human factor IXa without a ligand bound to the active site either in the apo-form or in complex with an inhibitory aptamer specific for factor IXa. The aptamer binds to an exosite in the catalytic domain and allosterically distorts the active site. Our studies reveal a conformational ensemble of IXa states, wherein large movements of Trp 215 near the active site drive functional transitions between the closed (aptamer-bound), latent (apo), and open (substrate-bound) states. The latent state of the apo-enzyme may bear on the uniquely poor catalytic activity of IXa compared to other coagulation proteases. The exosite, to which the aptamer binds, has been implicated in binding VIIIa and heparin, both of which regulate IXa function. Our findings reveal the importance of exosite-driven allosteric modulation of IXa function and new strategies to rebalance hemostasis for therapeutic gain.

Science & Technology - Other Topics↗
DOE OSTI2024

Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG 1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~200 anti-GCGR IgG 1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2–10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Comparative analysis of KRAS4a and KRAS4b splice variants reveals distinctive structural and functional properties

KRAS, the most frequently mutated oncogene in human cancer, produces two isoforms, KRAS4a and KRAS4b, through alternative splicing. These isoforms differ in exon 4, which encodes the final 15 residues of the G-domain and hypervariable regions (HVRs), vital for trafficking and membrane localization. While KRAS4b has been extensively studied, KRAS4a has been largely overlooked. Our multidisciplinary study compared the structural and functional characteristics of KRAS4a and KRAS4b, revealing distinct structural properties and thermal stability. Position 151 influences KRAS4a’s thermal stability, while position 153 affects binding to RAF1 CRD protein. Nuclear magnetic resonance analysis identified localized structural differences near sequence variations and provided a solution-state conformational ensemble. Notably,KRAS4aexhibits substantial transcript abundance in bile ducts, liver, and stomach, with transcript levels approachingKRAS4bin the colon and rectum. Functional disparities were observed in full-length KRAS variants, highlighting the impact of HVR variations on interaction with trafficking proteins and downstream effectors like RAF and PI3K within cells.

Science & Technology - Other Topics↗
DOE OSTI2025

Conformational heterogeneity in the dGsw purine riboswitch: role of Mg²⁺ and 2’-dG in aptamer folding

Recent advancements in RNA structural biology have focused on unraveling the complexities of non-coding mRNA elements like riboswitches. These cis-acting regulatory regions undergo structural changes in response to specific cellular metabolites, leading to up or downregulation of downstream genes. The purine riboswitch family regulates many prokaryotic genes involved in purine degradation and biosynthesis. They feature an aptamer domain organized around a 3-way helical junction, where ligand encapsulation occurs at the junctional core. In our study, we chemically probed the aptamer domain of the 2’-dG-sensing purine riboswitch from Mesoplasma florum (dGsw) under various solution conditions to understand how Mg²⁺ and 2’-dG influence riboswitch folding. Here, we find that efficient 2’-dG binding strongly depends on Mg²⁺, indicating that Mg²⁺ is essential for priming dGsw for ligand interactions. We identified a previously undescribed sequence in the 5’ tail of dGsw that is complementary to a conserved helix. The inclusion of this region in a construct led to intramolecular competition between the alternate helix, Palt, and P1. Mutational analysis confirmed that 5’ flanking end of the aptamer domain forms an alternate helix in the absence of ligand. Molecular dynamics simulations revealed that this alternative conformation is stable. This helix may, therefore, facilitate the formation of an anti-terminator helix by opening the 3-way junction surrounding the 2’-dG binding site. Our study further establishes the importance of a closed terminal P1 helix conformation for metabolite binding and suggests that the delicate interplay between P1 and Palt may fine-tune downstream gene regulation. These insights offer a new perspective on riboswitch structure and enhance our understanding of the role that a conformational ensemble plays in riboswitch activity and regulation.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Reversible domain closure modulates GlnBP ligand binding affinity

Glutamine binding protein (GlnBP) is an Escherichia Coli periplasmic binding protein, which binds and carries glutamine to the inner membrane ATP-binding cassette (ABC) transporter. GlnBP binds the ligand with affinity around 0.1μM measured by isothermal titration calorimetry (ITC) and ligand binding stabilizes protein structure shown by its increase in thermodynamic stability. However, the molecular determinant of GlnBP ligand binding is not known. Electrostatic and hydrophobic interaction between GlnBP and glutamine are critical factors. We propose that the freedome of closure movement is also vital for ligand binding. In order to approve this hypothesis, we generate a series of mutants with different linker length that has different magnitude of domain closure. Mutants show different ligand binding affinity, which indicates that the propensity of domain closure determines the ligand binding affinity. Ligand binding triggers gradual ensemble conformational change. Structural changes upon ligand binding are monitored by combination of small angle x-ray scattering (SAXS) and NMR spectroscopy. Detailed structure characterization of GlnBP contributes to a better understanding of ligand binding and provides the structural basis for biosensor design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗
DOE OSTI2023

Molecular-dynamics simulation methods for macromolecular crystallography

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein–solvent interface. To address this limitation, a set of MD–MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Approximate CFTs and random tensor models

Abstract A key issue in both the field of quantum chaos and quantum gravity is an effective description of chaotic conformal field theories (CFTs), that is CFTs that have a quantum ergodic limit. We develop a framework incorporating the constraints of conformal symmetry and locality, allowing the definition of ensembles of ‘CFT data’. These ensembles take on the same role as the ensembles of random Hamiltonians in more conventional quantum ergodic phases of many-body quantum systems. To describe individual members of the ensembles, we introduce the notion of approximate CFT, defined as a collection of ‘CFT data’ satisfying the usual CFT constraints approximately, i.e. up to small deviations. We show that they generically exist by providing concrete examples. Ensembles of approximate CFTs are very natural in holography, as every member of the ensemble is indistinguishable from a true CFT for low-energy probes that only have access to information from semi-classical gravity. To specify these ensembles, we impose successively higher moments of the CFT constraints. Lastly, we propose a theory of pure gravity in AdS 3 as a random matrix/tensor model implementing approximate CFT constraints. This tensor model is the maximum ignorance ensemble compatible with conformal symmetry, crossing invariance, and a primary gap to the black-hole threshold. The resulting theory is a random matrix/tensor model governed by the Virasoro 6j-symbol.

Physics↗
DOE OSTI2026

Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model

Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galaxy property estimation. However, point predictions alone are insufficient for scientific inference; reliable uncertainty quantification (UQ) is essential. We compare seven UQ methods on galaxy property regression using frozen AION-1 foundation-model embeddings, predicting redshift, stellar mass, stellar-population age, gas-phase metallicity, and specific star-formation rate, from Legacy Survey photometry/imaging and DESI spectra, with PROVABGS-derived labels. Distribution-free conformal methods achieve marginal coverage within $\sim$1 pp of the nominal 90% across all properties, while non-conformal baselines (Deep Ensembles, MC~Dropout) fail to calibrate reliably. Among conformal approaches, Conformalized Quantile Regression (CQR) delivers the best coverage in the bin with the poorest model predictions. More importantly, only the Locally Valid and Discriminative (LVD) framework -- particularly when operating on AION-1 embeddings -- also provides finite-sample \emph{local validity}, producing intervals that adapt to each galaxy's local prediction difficulty rather than relying on marginal guarantees alone. These results establish conformal prediction, and LVD in particular, as the preferred UQ framework for uncertainty-aware inference on foundation-model embeddings in astrophysics.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
DOE OSTI2024

Evaluating the Importance of Conformers for Understanding the Vacuum-Ultraviolet Spectra of Oxiranes: Experiment and Theory

Vacuum-ultraviolet (VUV) absorption spectroscopy enables electronic transitions that offer the unambiguous identification of molecules. As target molecules become more complex, multifunctional species present a great challenge to both experimental and computational spectroscopy. This research reports both experimental and theoretical studies of oxiranes. Computationally, the nuclear ensemble approach has been used to accurately predict experimental spectra for a variety of molecules. However, this approach incurs great computational cost, as ensembles generally consist of thousands of geometries. The present study aims to drastically reduce the ensemble by evaluating the significance of the conformers to the predicted spectra. This approach was applied to 11 substituted oxiranes using the Conformer Rotamer Ensemble Sampling Tool (CREST) of Grimme to generate an ensemble of unique conformers determined by their Boltzmann populations. Five TD-DFT functionals (BMK, CAM-B3LYP, M06-2X, MN15, ωB97X-D) and EOM-CCSD were used to simulate the spectrum of each substituted oxirane ensemble. Computed spectra were then compared to the experiment using both qualitative and quantitative metrics. Based on these metrics, it was observed that certain conformers may not be necessary to characterize this set of oxiranes despite the temperature (323 K) of the experiment. A single conformer can then be used with TD-DFT and EOM-CCSD to replicate the experimental spectra of these medium-sized combustion species.

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

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations

Abstract Motivation Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. Results We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. Availability and implementation It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Du, Lin (ORCID:0009000289869812)↗
DOE OSTI2025

Wormholes with ends of the world

We study classical wormhole solutions in 3D gravity with end-of-the-world (EOW) branes, conical defects, kinks, and punctures. These solutions compute statistical averages of an ensemble of boundary conformal field theories (BCFTs) related to universal asymptotics of OPE data extracted from the 2D conformal bootstrap. Conical defects connect BCFT bulk operators; branes join BCFT boundary intervals with identical boundary conditions; kinks (1D defects along branes) link BCFT boundary operators; and punctures (0D defects) are endpoints where conical defects terminate on branes. We provide evidence for a correspondence between the gravity theory and the ensemble. In particular, the agreement of the g-function dependence results from an underlying topological aspect of the on-shell EOW brane action, from which a BCFT analog of the Schlenker-Witten theorem also follows.

AdS-CFT Correspondence↗
DOE OSTI2023

Chain trajectories, domain shapes, and terminal boundaries in block copolymers

The packing geometry of macromolecules in complex mesophases is of key importance to self-organization in synthetic and biological soft materials. While approximate or heuristic models rely on often-untested assumptions about how flexible molecules “fit in” to distinct locations of complex assemblies, physical assemblies derive from ensembles of fluctuating conformations, obscuring the connection between mesophase geometry and the underlying arrangements. Here, we present an approach to extract and analyze features of molecular packing in diblock block copolymer (BCP) melts, a prototypical soft matter system, based on the statistical description of chain conformations in self-consistent field (SCF) theory. We show how average BCP chain trajectories in ordered morphologies can be analyzed from the SCF-derived orientational order parameter of chain segments. We use these extracted trajectories to analyze the features of local packing geometry, including chain bending and tilt, as well as the terminal boundaries that delineate distinct domains in ordered BCP morphologies. In conclusion, we illustrate this analysis by focusing on measurable features of packing frustration in 2D (columnar) and 3D (spherical and bicontinuous) morphologies, notably establishing an explicit link between chain conformations in complex morphologies and their medial geometry.

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

Using Multiple Isotope-Labeled Infrared Spectra for the Structural Characterization of an Intrinsically Disordered Peptide

Intrinsically disordered proteins (IDPs) rapidly interconvert between conformers, requiring an ensemble description. This complicates their experimental characterization, and force field limitations pose challenges for their simulation. Here, in this work, we use isotope-labeled and unlabeled infrared (IR) spectra to reweight simulated ensembles of the elastin-like peptide GVGVPGVG, a paradigmatic disordered peptide. By comparing the results obtained with different spectra, we explicitly show that the weights are underdetermined by the ensemble averaged data. We identify which labels and frequency regions maximize structural information while minimizing sensitivity to simulation error and show that these regions report on whether the peptide makes specific interactions. Our work shows the importance of incorporating simulations and simulated spectra at the planning stages of isotope-labeled IR experiments and more generally provides a framework for interpreting IR data for IDPs.

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

Discovery of Multiple Light-Harvesting States of the Photosynthetic Protein PE545

Cryptophytes are photosynthetic microalga that flourish in a remarkable diversity of natural environments by using pigment-containing proteins with absorption maxima tuned to each ecological niche. While this diversity in the absorption has been well established, the subsequent photophysics is highly sensitive to the local protein environment and so may exhibit similar variation. Thermal fluctuations of the protein conformation are expected to introduce photophysical heterogeneity of the pigments that may have evolved important functional properties in a manner similar to that of the absorption. However, such heterogeneity is averaged out in ensemble measurements and, therefore, has not yet been probed. Here, we report single-molecule measurements of phycoerythrin 545 (PE545), the prototypical cryptophyte antenna protein, in its native dimeric form. A conformational ensemble was resolved consisting of distinct photophysical states with different light-harvesting properties. Proteins that did not quench, partially quenched, or fully quenched absorbed light were observed. Light intensity increased the quenched-state population of the dimer, potentially as a mechanism to deal with the extreme light intensities found in aqueous environments. Cross-linking, which mimics local interactions, introduces this light-dependent functionality while also suppressing other conformational dynamics. The cellular organization can, therefore, actively modulate the protein conformation and dynamics, selecting for distinct levels of light harvesting. Furthermore, the complex conformational equilibrium provides an additional mechanism for cryptophytes and likely other photosynthetic organisms to optimize solar energy capture and conversion.

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

Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?

Machine learning (ML) has been leveraged to tackle a diverse range of tasks in almost all branches of nuclear engineering. Many of the successes in ML applications can be attributed to the recent performance breakthroughs in deep learning, the growing availability of computational power, data, and easy-to-use ML libraries. However, these empirical successes have often outpaced our formal understanding of the ML algorithms. An important but under-rated area is uncertainty quantification (UQ) of ML. ML-based models are subject to approximation uncertainty when they are used to make predictions, due to sources including but not limited to, data noise, data coverage, extrapolation, imperfect model architecture and the stochastic training process. The goal of this paper is to clearly explain and illustrate the importance of UQ of ML. We will elucidate the differences in the basic concepts of UQ of physics-based models and data-driven ML models. Various sources of uncertainties in physical modeling and data-driven modeling will be discussed, demonstrated, and compared. We will also present and demonstrate a few techniques to quantify the ML prediction uncertainties, including Monte Carlo dropout, deep ensemble, Bayesian neural networks, Gaussian Processes and conformal prediction. Lastly, we will discuss the need for building a verification, validation and UQ framework to establish ML credibility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Mapping Composition Evolution through Synthesis, Purification, and Depolymerization of Random Heteropolymers

Random heteropolymers (RHPs) consisting of three or more comonomers have been routinely used to synthesize functional materials. While increasing the monomer variety diversifies the side-chain chemistry, this substantially expands the sequence space and leads to ensemble-level sequence heterogeneity. Most studies have relied on monomer composition and simulated sequences to design RHPs, but the questions remain unanswered regarding heterogeneities within each RHP ensemble and how closely these simulated sequences reflect the experimental outcomes. Here, we quantitatively mapped out the evolution of monomer compositions in four-monomer-based RHPs throughout a design-synthesis-purification-depolymerization process. By adopting a Jaacks method, we first determined 12 reactivity ratios directly from quaternary methacrylate RAFT copolymerization experiments to account for the influences of competitive monomer addition and the reversible activation/deactivation equilibria. The reliability of in silico analysis was affirmed by a quantitative agreement (<4% difference) between the simulated RHP compositions and the experimental results. Furthermore, we mapped out the conformation distribution within each ensemble in different solvents as a function of monomer chemistry, composition, and segmental characteristics via high-throughput computation based on self-consistent field theory (SCFT). These comprehensive studies confirmed monomer composition as a viable design parameter to engineer RHP-based functional materials as long as the reactivity ratios are accurately determined and the livingness of RHP synthesis is ensured.

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

Reaching percolation and conformal limits in neutron stars

Generating an ensemble of equations of state that fulfill multimessenger constraints, we statistically determine the properties of dense matter found inside neutron stars (NSs). We calculate the speed of sound and trace anomaly and demonstrate that they are driven towards their conformal values at the center of maximally massive NSs. The local peak of the speed of sound is shown to be located at values of the energy and particle densities, which are consistent with deconfinement and percolation conditions in QCD matter. Here, we also analyze fluctuations of the net-baryon number density in the context of possible remnants of critical behavior. We find that the global maxima of the variance of these fluctuations emerge at densities beyond those found in the interiors of NSs.

79 ASTRONOMY AND ASTROPHYSICS↗