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DOE OSTI2024

Activation of polycystin-1 signaling by binding of stalk-derived peptide agonists

Polycystin-1 (PC1) is the protein product of thePKD1gene whose mutation causes autosomal dominant Polycystic Kidney Disease (ADPKD). PC1 is an atypical G protein-coupled receptor (GPCR) with an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal and membrane-embedded C-terminal (CTF) fragments. Recently, activation of PC1 CTF signaling was shown to be regulated by a stalk tethered agonist (TA), resembling the mechanism observed for adhesion GPCRs. Here, synthetic peptides of the first 9- (p9), 17- (p17), and 21-residues (p21) of the PC1 stalk TA were shown to re-activate signaling by a stalkless CTF mutant in human cell culture assays. Novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) simulations elucidated binding conformations of p9, p17, and p21 and revealed multiple specific binding regions to the stalkless CTF. Peptide agonists binding to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of stalk TA-mediated PC1 CTF activation. Additional sequence coevolution analyses showed the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. These insights into the structural dynamic mechanism of PC1 activation by TA peptide agonists provide an in-depth understanding that will facilitate the development of therapeutics targeting PC1 for ADPKD treatment.

Life Sciences & Biomedicine - Other Topics↗

DOE OSTI2021

Fabricating structured particles through rapid hardening and tailored collection methods

Fabrication of functional polymer-based particles by crosslinking UV-curable polymer drops in mid-air and collecting crosslinked particles in a solid container, a liquid suspension, or an air flow. The particles can contain different phases in the form or layered structures that contain one to multiple cores, or structures that are blended with dissolved or emulsified smaller domains. A curing system produces ultraviolet rays that are directed onto the particles in the jet stream from one side. A reflector positioned on other side of the jet stream reflects the ultraviolet rays back onto the particles in the jet stream.

Ye, Congwang↗

DOE OSTI2023

Fabricating structured particles through rapid hardening and tailored collection methods

Ye, Congwang↗

DOE OSTI2023

Ultrahigh-Capacity Rocksalt Cathodes Enabled by Cycling-Activated Structural Changes

Mn-redox-based oxides and oxyfluorides are considered the most promising earth-abundant high-energy cathode materials for next-generation lithium-ion batteries. While high capacities are obtained in high-Mn content cathodes such as Li- and Mn-rich layered and spinel-type materials, local structure changes and structural distortions ( often lead to voltage fade, capacity decay, and impedance rise, resulting in unacceptable electrochemical performance upon cycling. In the present study, structural transformations that exploit the high capacity of Mn-rich oxyfluorides while enabling stable cycling, in stark contrast to commonly observed structural changes that result in rapid performance degradation, are reported. Here, it is shown that upon cycling of a cation-disordered rocksalt (DRX) cathode (Li 1.1 Mn 0.8 Ti 0.1 O 1.9 F 0.1 , an ultrahigh capacity of ≈320 mAh g –1 (energy density of ≈900 Wh kg –1 ) can be obtained through dynamic structural rearrangements upon cycling , along with a unique voltage profile evolution and capacity rise. At high voltage, the presence of Mn 4+ and Li + vacancies promotes local cation ordering, leading to the formation of domains of a “δ phase” within the disordered framework. On deep discharge, Mn 4+ reduction, along with Li + insertion transform the structure to a partially ordered DRX phase with a β'-LiFeO 2 -type arrangement. At the nanoscale, domains of the in situ formed phases are randomly oriented, allowing highly reversible structural changes and stable electrochemical cycling. These new insights not only help explain the superior electrochemical performance of high-Mn DRXbut also provide guidance for the future development of Mn-based, high-energy density oxide, and oxyfluoride cathode materials.

25 ENERGY STORAGE↗

DOE OSTI2022

Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom–atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Cognitive aging outcomes are related to both tau pathology and maintenance of cingulate cortex structure

Abstract INTRODUCTION Successful cognitive aging is related to both maintaining brain structure and avoiding Alzheimer's disease (AD) pathology, but how these factors interplay is unclear. METHODS A total of 109 cognitively normal older adults (70+ years old) underwent amyloid beta (Aβ) and tau positron emission tomography (PET) imaging, structural magnetic resonance imaging (MRI), and cognitive testing. Cognitive aging was quantified using the cognitive age gap (CAG), subtracting chronological age from predicted cognitive age. RESULTS Lower CAG (younger cognitive age) was related to slower decline in episodic memory, multi‐domain cognition, and atrophy of the midcingulate cortex (MCC). Lower entorhinal cortical tau was linked to slower decline in episodic memory, multi‐domain cognition, and hippocampal atrophy. DISCUSSION These results suggest that aging outcomes may be influenced by two independent pathways: one associated with tau accumulation, affecting primarily memory and hippocampal atrophy, and another involving tau‐independent structural preservation of the MCC, benefiting multi‐domain cognition over time. Highlights Younger cognitive age (lower cognitive age gap [CAG]) is related to slower cognitive decline. Lower CAG is linked to slower midcingulate cortex (MCC) atrophy. Reduced tau in the entorhinal cortex is related to less hippocampal atrophy and cognitive decline. Structural preservation of the MCC benefits multi‐domain cognition over time. Two independent pathways influence cognitive aging: tau accumulation and MCC preservation.

Neurosciences & Neurology↗

DOE OSTI2022

Voronoi Meshing to Accurately Capture Geological Structure in Subsurface Simulations

Mesh generation lies at the interface of geological modeling and reservoir simulation. Highly skewed or very small grid cells may be necessary to accurately capture the geometry of geological features, but the resulting poorly scaled or small grid cells can have a substantial negative impact on simulator accuracy and speed. One way to minimize numerical errors caused by gridding complex structures is to simulate on high-quality Voronoi meshes, which reduce grid orientation effects in fluid flow. This work presents a complete methodology to create Voronoi simulation grids, model fluid flow in complex geological systems, and visualize the results. A recently developed Voronoi meshing method that can automatically generate provably good unstructured meshes that conform to input surfaces creating closed volumes is used. Initially an analytical benchmark simulation is presented to validate the quality of the meshes and simulation results and demonstrate the superiority of simulation results using Voronoi meshes over flexed-hexahedral meshes on a domain with internal features. Next, meshes are created for test structures representing four of the most common geological features in the subsurface: layering, pinch-out, an interior lens that tapers to zero thickness on all sides and a fault with offset. Two benchmark flow simulations are run for each test structure. Finally, a realistic geological example for CO 2 injection into an anticline is simulated. Three realizations of the Voronoi mesh at the same resolution are generated for the simulations. Each mesh is highly refined near the injection wells and coarse in areas of less interest. These three meshes are used to model the CO 2 plume in the subsurface as it migrates to the top of the structure and then fills downward. Simulations on the meshes with randomly generated elements inside the input volumes each give slightly different fingering patterns for the viscous-unstable buoyant gas flow. The results presented in this work show a promising step towards utilizing fully automated Voronoi meshing for subsurface flow simulations in complex geology.

58 GEOSCIENCES↗

DOE OSTI2020

TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graph analytics has emerged as an important tool in the analysis of large scale data from diverse application domains such as social networks, cyber security and bioinformatics. Counting the number of triangles in a graph is a fundamental kernel with several applications such as detecting the community structure of a graph or in identifying important vertices in a graph. The ubiquity of massive datasets is driving the need to scale graph analytics on parallel systems. However, numerous challenges exist in efficiently parallelizing graph algorithms, especially on distributed-memory systems. Irregular memory accesses and communication patterns, low computation to communication ratios, and the need for frequent synchronization are some of the leading challenges. In this paper, we present TriC, our distributed-memory implementation of triangle counting in graphs using the Message Passing Interface (MPI), as a submission to the 2020 GraphChallenge competition. Using a set of synthetic and real-world inputs from the challenge, we demonstrate a speedup of up to 90x relative to previous work on 32 processor-cores of a NERSC Cori node. We also provide details from distributed runs with up to8192 processes along with strong scaling results. The observations presented in this work provide an understanding of the system-level bottlenecks at scale that specifically impact sparse-irregular workloads and will therefore benefit other efforts to parallelize graph algorithms.

Halappanavar, Mahantesh↗

DOE OSTI2025

Ion-selective conformational stabilization of a disordered repeats-in-toxin protein domain

Ion-binding intrinsically disordered proteins (IDPs) recruit and bind to specific metal ions to perform critical biological functions. In proteins where ion binding and structural transitions are coupled, interactions with off-target toxic metals can dramatically disrupt protein structure and function, exemplified by lead and mercury poisoning. Understanding the complex mechanisms underlying how IDPs exclude or allow binding to different ionic species is crucial for addressing the origins of metal toxicity in biological systems. Here, we elucidate mechanisms of ion selectivity in an IDP that adopts a structure upon Ca 2+ binding. We probed ion-induced conformational changes of a repeats-in-toxin (RTX) protein domain in the presence of different ion ligands—Mg 2+ , Ca 2+ , Sr 2+ , and Ba 2+ —with chemical similarities but drastically different ionic radii. RTX adopts ion-selective conformations measured by x-ray crystallography, small-angle x-ray scattering, and circular dichroism. High-resolution x-ray structures reveal that Sr 2+ induces a nearly identical RTX structure as natively binding Ca 2+ , enabled by the intrinsic flexibility and disorder of the protein. Small-angle x-ray scattering and circular dichroism indicate that smaller Mg 2+ does not induce a significant conformational change in RTX, whereas larger Ba 2+ induces a partially folded structure. These results highlight the importance of geometric constraints imposed by protein structure in determining metal ion selectivity, yielding insights into how off-target ion binding may result in protein misfolding and malfunction.

Gudinas, Alana P. [Stanford Univ., CA (United Stat↗

DOE OSTI2021

Correlating 3D Surface Atomic Structure and Catalytic Activities of Pt Nanocrystals

Active sites and catalytic activity of heterogeneous catalysts is determined by their surface atomic structures. However, probing the surface structure at an atomic resolution is difficult, especially for solution ensembles of catalytic nanocrystals, which consist of heterogeneous particles with irregular shapes and surfaces. In this study, we constructed 3D maps of the coordination number (CN) and generalized CN ($\bar{C}\bar{N}$) for individual surface atoms of sub-3 nm Pt nanocrystals. Our results reveal that the synthesized Pt nanocrystals are enclosed by islands of atoms with nonuniform shapes that lead to complex surface structures, including a high ratio of low-coordination surface atoms, reduced domain size of low-index facets, and various types of exposed high-index facets. 3D maps of $\bar{C}\bar{N}$ are directly correlated to catalytic activities assigned to individual surface atoms with distinct local coordination structures, which explains the origin of high catalytic performance of small Pt nanocrystals in important reactions such as oxygen reduction reactions and CO electro-oxidation.

3D atomic structure↗

DOE OSTI2021

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Structure of Pseudomonas aeruginosa spermidine dehydrogenase: a polyamine oxidase with a novel heme‐binding fold

The opportunistic pathogen Pseudomonas aeruginosa can utilize polyamines (including putrescine, cadaverine, 4‐aminobutyrate, spermidine, and spermine) as its sole source of carbon and nitrogen. Spermidine dehydrogenase (SpdH) is a component of one of the two polyamine utilization pathways identified in P . aeruginosa , but little is known about its structure and function. Here, we report the first crystal structure of SpdH from P . aeruginosa to 1.85 Å resolution. The resulting core structure confirms that SpdH belongs to the polyamine oxidase (PAO) family with flavin‐binding and substrate‐binding domains. A unique N‐terminal extension wraps around the flavin‐binding domain of SpdH and is required for heme binding, placing a heme cofactor in close proximity to the FAD cofactor. Structural and mutational analysis reveals that residues in the putative active site at the re side of the FAD isoalloxazine ring form part of the catalytic machinery. PaSpdH features an unusual active site and lacks the conserved lysine that forms part of a lysine–water–flavin N5 atom interaction in other PAO enzymes characterized to date. Mutational analysis further confirms that heme is required for catalytic activity. This work provides an important starting point for understanding the role of SpdH, which occurs universally in P . aeruginosa strains, in polyamine metabolism.

Che, Shiyou↗

DOE OSTI2020

Shear-induced polydomain structures of nematic lyotropic chromonic liquid crystal disodium cromoglycate

Lyotropic chromonic liquid crystals (LCLCs) represent aqueous dispersions of organic disk-like molecules that form cylindrical aggregates. Despite the growing interest in these materials, their flow behavior is poorly understood. Here, we explore the effect of shear on dynamic structures of the nematic LCLC, formed by 14 wt% water dispersion of disodium cromoglycate (DSCG). We employ in situ polarizing optical microscopy (POM) and small-angle and wide-angle X-ray scattering (SAXS/WAXS) to obtain independent and complementary information on the director structures over a wide range of shear rates. The DSCG nematic shows a shear-thinning behavior with two shear-thinning regions (Region I at $\dot{\gamma}$ < 1 s -1 and Region III at $\dot{\gamma}$ > 10 s -1 ) separated by a pseudo-Newtonian Region II (1 s-1 < $\dot{\gamma}$ < 10 s -1 ). The material is of a tumbling type. In Region I, $\dot{\gamma}$ < 1 s -1 , the director realigns along the vorticity axis. An increase of [small gamma, Greek, dot above] above 1 s -1 triggers nucleation of disclination loops. The disclinations introduce patches of the director that deviates from the vorticity direction and form a polydomain texture. Extension of the domains along the flow and along the vorticity direction decreases with the increase of the shear rate to 10 s -1 . Above 10 s -1 , the domains begin to elongate along the flow. At $\dot{\gamma}$ > 100 s -1 , the texture evolves into periodic stripes in which the director is predominantly along the flow with left and right tilts. The period of stripes decreases with an increase of $\dot{\gamma}$. The shear-induced transformations are explained by the balance of the elastic and viscous energies. In particular, nucleation of disclinations is associated with an increase of the elastic energy at the walls separating nonsingular domains with different director tilts. The uncovered shear-induced structural effects would be of importance in the further development of LCLC applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Superlattice reflection signatures of the insulator–metal transition in V 3 O 5 thin films

Nanoelectronic systems that are inspired by the brain are increasingly looking to insulator–metal transition (IMT) materials as they can mimic the response characteristics of neurons to temperature changes so that these can be used in robotic and computational applications. V 3 O 5 has an insulator–metal transition at ∼430 or ∼80 K higher than VO 2 and provides a unique high-temperature opportunity for these types of applications. Here, in this work, we track the structural evolution of V 3 O 5 thin films across the IMT through conventional selected-area electron diffraction (SAED) and four-dimensional scanning TEM (4D-STEM), correlated with temperature-dependent resistance measurements. SAED patterns show reversible evidence of superlattice reflections associated with the IMT—present below T IMT and absent above it—consistent with the accompanying drop in resistance. At room temperature, nanobeam electron diffraction patterns further reveal three local configurations: (i) type I regions with clean patterns lacking superlattice reflections and spot splitting; (ii) type II regions exhibiting rows of superlattice reflections and split spots indicative of crystallographic variants; and (iii) type III regions with negligible superlattice reflections but larger spot splitting suggestive of overlapping domains of insulating and conducting phases likely driven by local lattice distortions. Upon heating, the superlattice reflections disappear between 413 and 453 K, concurrent with the resistance drop at T IMT , consistent with the emergence of a conducting phase. The overall diffraction geometry remains essentially unchanged up to 573 K, implying that relative domain orientations persist through the transition. These observations reveal nanoscale structural heterogeneity in V 3 O 5 thin films across the IMT and inform operation in regimes where mixed-phase textures are expected. A plausible indexing framework rationalizing the observed geometries is presented in the Discussion section, alongside its limitations and alternative interpretations.

25 ENERGY STORAGE↗

DOE OSTI2020

The bacterial copper resistance protein CopG contains a cysteine-bridged tetranuclear copper cluster

CopG is an uncharacterized protein ubiquitous in Gram-negative bacteria whose gene frequently occurs in clusters of copper resistance genes and can be recognized by the presence of a conserved CxCC motif. To investigate its contribution to copper resistance, here we undertook a structural and biochemical characterization of the CopG protein from Pseudomonas aeruginosa . Results from biochemical analyses of CopG purified under aerobic conditions indicate that it is a green copper-binding protein that displays absorbance maxima near 411, 581, and 721 nm and is monomeric in solution. Determination of the three-dimensional structure by X-ray crystallography revealed that CopG consists of a thioredoxin domain with a C-terminal extension that contributes to metal binding. We noted that adjacent to the CxCC motif is a cluster of four copper ions bridged by cysteine sulfur atoms. Structures of CopG in two oxidation states support the assignment of this protein as an oxidoreductase. On the basis of these structural and spectroscopic findings and also genetic evidence, we propose that CopG has a role in interconverting Cu(I) and Cu(II) to minimize toxic effects and facilitate export by the Cus RND transporter efflux system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Giant Nonlinear Optical Response via Coherent Stacking of In-Plane Ferroelectric Layers

Thin ferroelectric materials hold great promise for compact nonvolatile memory and nonlinear optical and optoelectronic devices. Herein, an ultrathin in-plane ferroelectric material that exhibits a giant nonlinear optical effect, group-IV monochalcogenide SnSe, is reported. Nanometer-scale ferroelectric domains with ≈90°/270° twin boundaries or ≈180° domain walls are revealed in physical-vapor-deposited SnSe by lateral piezoresponse force microscopy. Atomic structure characterization reveals both parallel and antiparallel stacking of neighboring van der Waals ferroelectric layers, leading to ferroelectric or antiferroelectric ordering. Ferroelectric domains exhibit giant nonlinear optical activity due to coherent enhancement of second-harmonic fields and the as-resulted second-harmonic generation was observed to be 100 times more intense than monolayer WS 2 . This work demonstrates in-plane ferroelectric ordering and giant nonlinear optical activity in SnSe, which paves the way for applications in on-chip nonlinear optical components and nonvolatile memory devices.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Molecular dissection of the glutamine synthetase-GlnR nitrogen regulatory circuitry in Gram-positive bacteria

How bacteria sense and respond to nitrogen levels are central questions in microbial physiology. In Gram-positive bacteria, nitrogen homeostasis is controlled by an operon encoding glutamine synthetase (GS), a dodecameric machine that assimilates ammonium into glutamine, and the GlnR repressor. GlnR detects nitrogen excess indirectly by binding glutamine-feedback-inhibited-GS (FBI-GS), which activates its transcription-repression function. The molecular mechanisms behind this regulatory circuitry, however, are unknown. Here we describe biochemical and structural analyses of GS and FBI-GS-GlnR complexes from pathogenic and non-pathogenic Gram-positive bacteria. The structures show FBI-GS binds the GlnR C-terminal domain within its active-site cavity, juxtaposing two GlnR monomers to form a DNA-binding-competent GlnR dimer. The FBI-GS-GlnR interaction stabilizes the inactive GS conformation. Strikingly, this interaction also favors a remarkable dodecamer to tetradecamer transition in some GS, breaking the paradigm that all bacterial GS are dodecamers. These data thus unveil unique structural mechanisms of transcription and enzymatic regulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Position Papers for the ASCR Workshop on the Science of Scientific-Software Development and Use

Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.

42 ENGINEERING↗