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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecular architecture and functional dynamics of the pre-incision complex in nucleotide excision repair

Nucleotide excision repair (NER) is vital for genome integrity. Yet, our understanding of the complex NER protein machinery remains incomplete. Combining cryo-EM and XL-MS data with AlphaFold2 predictions, we build an integrative model of the NER pre-incision complex(PInC). Here TFIIH serves as a molecular ruler, defining the DNA bubble size and precisely positioning the XPG and XPF nucleases for incision. Using simulations and graph theoretical analyses, we unveil PInC’s assembly, global motions, and partitioning into dynamic communities. Remarkably, XPG caps XPD’s DNA-binding groove and bridges both junctions of the DNA bubble, suggesting a novel coordination mechanism of PInC’s dual incision. XPA rigging interlaces XPF/ERCC1 with RPA, XPD, XPB, and 5' ssDNA, exposing XPA’s crucial role in licensing the XPF/ERCC1 incision. Mapping disease mutations onto our models reveals clustering into distinct mechanistic classes, elucidating xeroderma pigmentosum and Cockayne syndrome disease etiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Functional anatomy of zinc finger antiviral protein complexes

Abstract ZAP is an antiviral protein that binds to and depletes viral RNA, which is often distinguished from vertebrate host RNA by its elevated CpG content. Two ZAP cofactors, TRIM25 and KHNYN, have activities that are poorly understood. Here, we show that functional interactions between ZAP, TRIM25 and KHNYN involve multiple domains of each protein, and that the ability of TRIM25 to multimerize via its RING domain augments ZAP activity and specificity. We show that KHNYN is an active nuclease that acts in a partly redundant manner with its homolog N4BP1. The ZAP N-terminal RNA binding domain constitutes a minimal core that is essential for antiviral complex activity, and we present a crystal structure of this domain that reveals contacts with the functionally required KHNYN C-terminal domain. These contacts are remote from the ZAP CpG binding site and would not interfere with RNA binding. Based on our dissection of ZAP, TRIM25 and KHNYN functional anatomy, we could design artificial chimeric antiviral proteins that reconstitute the antiviral function of the intact authentic proteins, but in the absence of protein domains that are otherwise required for activity. Together, these results suggest a model for the RNA recognition and action of ZAP-containing antiviral protein complexes.

Science & Technology - Other Topics↗
DOE OSTI2025

Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide

Understanding how local distortions determine the functional properties of high entropy materials, containing five or more elements at the same crystallographic site, is an open challenge. We address this for a compositionally complex spinel oxide (Mn 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )Cr 2 O 4 (A 5 Cr 2 O 4 ). By comparatively examining extended X-ray absorption fine structure on A 5 Cr 2 O 4 and its parent counterparts, ACr 2 O 4 , along with density functional theory calculations for multiple configurations, we find that the element-specific distortions go beyond the first neighbor. Specifically, the strong Jahn-Teller distortion present in CuCr 2 O 4 is found to be completely suppressed in A 5 Cr 2 O 4 even locally. Instead, there is a broad distribution of Cu-O and Cu-Cr bond distances, while other A-O distances acquire certain specific values. This study demonstrates the additional flexibility of a cationic sublattice in maintaining a uniform long-range structure, in contrast to previous reports showing only the accommodative anionic sublattice. The mean-field magnetic interactions of A 5 Cr 2 O 4 exhibit a striking resemblance to those of NiCr 2 O 4 , despite the presence of multiple magnetic ions and variable bond lengths. This originates from the comparability of bond lengths around Cr in both materials. Our study paves the way for a deeper understanding of the impact of local structural distortions on the physical properties of compositionally complex quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

Abstract This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases ofd-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupieddstates near the Fermi level, we determine that the large, sharpddensity of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.

Chemistry↗
DOE OSTI2026

Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Variational quantum eigensolver with reduced circuit complexity

Abstract The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenstates of a given Hamiltonian on noisy intermediate-scale quantum devices (NISQ). The practical realization is limited by the complexity of quantum circuits. Here we present an approach to reduce quantum circuit complexity in VQE for electronic structure calculations. Our ClusterVQE algorithm splits the initial qubit space into clusters which are further distributed on individual (shallower) quantum circuits. The clusters are obtained based on mutual information reflecting maximal entanglement between qubits, whereas inter-cluster correlation is taken into account via a new “dressed” Hamiltonian. ClusterVQE therefore allows exact simulation of the problem by using fewer qubits and shallower circuit depth at the cost of additional classical resources, making it a potential leader for quantum chemistry simulations on NISQ devices. Proof-of-principle demonstrations are presented for several molecular systems based on quantum simulators as well as IBM quantum devices.

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

Ramification of complex magnetism in Nd 2 Ir 2 O 7 observed by Raman scattering spectroscopy

Using Raman scattering spectroscopy, we uncover a complex magnetic behavior of Nd2Ir2O7, which stands out among magnetic pyrochlores by the lowest temperature of the all-in-all-out (AIAO) Ir moments ordering (${T}_{{\rm{Ir}}}^{{\rm{N}}} = 33$ K) and the highest temperature at which AIAO order of rare-earth Nd ions is detected (${T}_{{\rm{Nd}}}^{{\rm{* }}}$ = 15 K). Detected magnetic Raman scattering and calculations of expected response allow us to demonstrate that the ordering of Ir magnetic moments is accompanied by an appearance of one-magnon Raman modes at 26.3 and 29.6 meV compatible with the AIAO order and allowing to estimate the energies of Ir-Ir interactions. An additional two-magnon excitation of the AIAO Nd order at around 33 meV appears in the spectra below the ordering temperature of Nd moments ${T}_{{\rm{Nd}}}^{{\rm{* }}}$ = 15 K. In the temperature range between 15 K and 33 K we observe a broad mode, which demonstrates strong temperature dependence and shifts on cooling below 20 K from 14 meV to higher frequencies, and disappears at 5 K, when two-magnon excitation of Nd moments becomes prominent. We suggest an interpretation of this excitation in terms of continuum arising from collective fluctuations of Nd moments above the transition. This complex behavior emerges from the interplay of strong spin-orbit coupling, electronic correlations, and geometric frustration on two magnetic pyrochlore sublattices of Nd and Ir ions.

magnetic properties and materials↗
DOE OSTI2025

A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modelling and screening. When applied to a dataset from patients with idiopathic pulmonary fibrosis, UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation using proteomics reveals the accuracy of UNAGI’s cellular dynamics analysis, and the use of the fibrotic cocktail-treated human precision-cut lung slices confirms UNAGI’s predictions that nifedipine, an antihypertensive drug, may have anti-fibrotic effects on human tissues. UNAGI’s versatility extends to other diseases, including COVID, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond idiopathic pulmonary fibrosis, amplifying its use in the quest for therapeutic solutions across diverse pathological landscapes.

Neural Network↗
DOE OSTI2023

Isolation of a californium(II) crown–ether complex

The actinides, from californium to nobelium (Z = 98–102), are known to have an accessible +2 oxidation state. Understanding the origin of this chemical behaviour requires characterizing Cf II materials, but investigations are hampered by the fact that they have remained dificult to isolate. This partly arises from the intrinsic challenges of manipulating this unstable element, as well as a lack of suitable reductants that do not reduce Cf III to Cf°. Here we show that a Cf II crown–ether complex, Cf(18-crown-6)I 2 , can be prepared using an Al/Hg amalgam as a reductant. Spectroscopic evidence shows that Cf III can be quantitatively reduced to Cf II , and rapid radiolytic re-oxidation in solution yields co-crystallized mixtures of Cf II and Cf III complexes without the Al/Hg amalgam. Furthermore, quantum-chemical calculations show that the Cf– ligand interactions are highly ionic and that 5f/6d mixing is absent, resulting in weak 5f→5f transitions and an absorption spectrum dominated by 5f→6d transitions.

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

Geometrically frustrated interactions drive structural complexity in amorphous calcium carbonate

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca∙∙∙Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca 2+ -ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca 2+ ions.

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

Persistence of soil organic carbon caused by functional complexity

Soil organic carbon management has the potential to aid climate change mitigation through drawdown of atmospheric carbon dioxide. To be effective, such management must account for processes influencing carbon storage and re-emission at different space and time scales. Achieving this requires a conceptual advance in our understanding to link carbon dynamics from the scales at which processes occur to the scales at which decisions are made. Here, we propose that soil carbon persistence can be understood through the lens of decomposers as a result of functional complexity derived from the interplay between spatial and temporal variation of molecular diversity and composition. For example, co-location alone can determine whether a molecule is decomposed, with rapid changes in moisture leading to transport of organic matter and constraining the fitness of the microbial community, while greater molecular diversity may increase the metabolic demand of, and thus potentially limit, decomposition. This conceptual shift accounts for emergent behaviour of the microbial community and would enable soil carbon changes to be predicted without invoking recalcitrant carbon forms that have not been observed experimentally. Finally, functional complexity as a driver of soil carbon persistence suggests soil management should be based on constant care rather than one-time action to lock away carbon in soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Rapid loss of complex polymers and pyrogenic carbon in subsoils under whole-soil warming

Subsoils contain more than half of soil organic carbon (SOC) and are expected to experience rapid warming in the coming decades. Yet our understanding of the stability of this vast carbon pool under global warming is uncertain. In particular, the fate of complex molecular structures (polymers) remains debated. Here we show that 4.5 years of whole-soil warming (+4 °C) resulted in less polymeric SOC (sum of specific polymers contributing to SOC) in the warmed subsoil (20–90 cm) relative to control, with no detectable change in topsoil. Warming stimulated the subsoil loss of lignin phenols (–17 ± 0%) derived from woody plant biomass, hydrolysable lipids cutin and suberin, derived from leaf and woody plant biomass (–28 ± 3%), and pyrogenic carbon (–37 ± 8%) produced during incomplete combustion. Given that these compounds have been proposed for long-term carbon sequestration, it is notable that they were rapidly lost in warmed soils. We conclude that complex polymeric carbon in subsoil is vulnerable to decomposition and propose that molecular structure alone may not protect compounds from degradation under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Resolving complex intralayer transition motifs in high-Ni-content layered cathode materials for lithium-ion batteries

High-Ni-content layered materials are promising cathodes for next-generation lithium-ion batteries. However, investigating the atomic configurations of the delithiation-induced complex phase boundaries and their transitions remains challenging. Here, in this study, by using deep-learning-aided super-resolution electron microscopy, we resolve the intralayer transition motifs at complex phase boundaries in high-Ni cathodes. We reveal that an O3 → O1 transformation driven by delithiation leads to the formation of two types of O1–O3 interface, the continuous- and abrupt-transition interfaces. The interfacial misfit is accommodated by a continuous shear-transition zone and an abrupt structural unit, respectively. Atomic-scale simulations show that uneven in-plane Li+ distribution contributes to the formation of both types of interface, and the abrupt transition is energetically more favourable in a delithiated state where O1 is dominant, or when there is an uneven in-plane Li + distribution in a delithiated O3 lattice. Moreover, a twin-like motif that introduces structural units analogous to the abrupt-type O1–O3 interface is also uncovered. The structural transition motifs resolved in this study provide further understanding of shear-induced phase transformations and phase boundaries in high-Ni layered cathodes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Single-photon absorption and emission from a natural photosynthetic complex

Photosynthesis is generally assumed to be initiated by a single photon from the Sun, which, as a weak light source, delivers at most a few tens of photons per nanometre squared per second within a chlorophyll absorption band1. Yet much experimental and theoretical work over the past 40 years has explored the events during photosynthesis subsequent to absorption of light from intense, ultrashort laser pulses. Here, we use single photons to excite under ambient conditions the light-harvesting 2 (LH2) complex of the purple bacterium Rhodobacter sphaeroides, comprising B800 and B850 rings that contain 9 and 18 bacteriochlorophyll molecules, respectively. Excitation of the B800 ring leads to electronic energy transfer to the B850 ring in approximately 0.7 ps, followed by rapid B850-to-B850 energy transfer on an approximately 100-fs timescale and light emission at 850–875 nm. Using a heralded single photon source20,21 along with coincidence counting, we establish time correlation functions for B800 excitation and B850 fluorescence emission and demonstrate that both events involve single photons. We also find that the probability distribution of the number of heralds per detected fluorescence photon supports the view that a single photon can upon absorption drive the subsequent energy transfer and fluorescence emission and hence, by extension, the primary charge separation of photosynthesis. An analytical stochastic model and a Monte Carlo numerical model capture the data, further confirming that absorption of single photons is correlated with emission of single photons in a natural light-harvesting complex.

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

Top-down mass spectrometry of native proteoforms and their complexes: a community study

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. Further, to address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Structure of the human SAGA coactivator complex

The SAGA complex is a regulatory hub involved in gene regulation, chromatin modification, DNA damage repair and signaling. While structures of yeast SAGA (ySAGA) have been reported, there are noteworthy functional and compositional differences for this complex in metazoans. Here we present the cryogenic-electron microscopy (cryo-EM) structure of human SAGA (hSAGA) and show how the arrangement of distinct structural elements results in a globally divergent organization from that of yeast, with a different interface tethering the core module to the TRRAP subunit, resulting in a dramatically altered geometry of functional elements and with the integration of a metazoan-specific splicing module. Our hSAGA structure reveals the presence of an inositol hexakisphosphate (InsP 6 ) binding site in TRRAP and an unusual property of its pseudo-(Ψ)PIKK. Finally, we map human disease mutations, thus providing the needed framework for structure-guided drug design of this important therapeutic target for human developmental diseases and cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The CNK–HYP scaffolding complex promotes RAF activation by enhancing KSR–MEK interaction

The RAS–MAPK pathway regulates cell proliferation, differentiation and survival, and its dysregulation is associated with cancer development. The pathway minimally comprises the small GTPase RAS and the kinases RAF, MEK and ERK. Activation of RAF by RAS is notoriously intricate and remains only partially understood. There are three RAF isoforms in mammals (ARAF, BRAF and CRAF) and two related pseudokinases (KSR1 and KSR2). RAS-mediated activation of RAF depends on an allosteric mechanism driven by the dimerization of its kinase domain. Recent work on human RAFs showed that MEK binding to KSR1 promotes KSR1–BRAF heterodimerization, which leads to the phosphorylation of free MEK molecules by BRAF. Similar findings were made with the single Drosophila RAF homolog. Here we show that the fly scaffold proteins CNK and HYP stabilize the KSR–MEK interaction, which in turn enhances RAF–KSR heterodimerization and RAF activation. The cryogenic electron microscopy structure of the minimal KSR–MEK–CNK–HYP complex reveals a ring-like arrangement of the CNK–HYP complex allowing CNK to simultaneously engage KSR and MEK, thus stabilizing the binary interaction. Together, these results illuminate how CNK contributes to RAF activation by stimulating the allosteric function of KSR and highlight the diversity of mechanisms impacting RAF dimerization as well as the regulatory potential of the KSR–MEK interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Three-dimensional imaging of mitochondrial cristae complexity using cryo-soft X-ray tomography

Mitochondria are dynamic organelles that change morphology to adapt to cellular energetic demands under both physiological and stress conditions. Cardiomyopathies and neuronal disorders are associated with structure-related dysfunction in mitochondria, but three-dimensional characterizations of the organelles are still lacking. In this study, we combined high-resolution imaging and 3D electron density information provided by cryo-soft X-ray tomography to characterize mitochondria cristae morphology isolated from murine. Using the linear attenuation coefficient, the mitochondria were identified (0.247 ± 0.04 µm -1 ) presenting average dimensions of 0.90 ± 0.20 µm in length and 0.63 ± 0.12 µm in width. The internal mitochondria structure was successfully identified by reaching up the limit of spatial resolution of 35 nm. The internal mitochondrial membranes invagination (cristae) complexity was calculated by the mitochondrial complexity index (MCI) providing quantitative and morphological information of mitochondria larger than 0.90 mm in length. The segmentation to visualize the cristae invaginations into the mitochondrial matrix was possible in mitochondria with MCI ≥ 7. Altogether, we demonstrated that the MCI is a valuable quantitative morphological parameter to evaluate cristae modelling and can be applied to compare healthy and disease state associated to mitochondria morphology.

3-D reconstruction↗