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At least 127 records · Page 7

Structural insights into the assembly and the function of the plant oxidative phosphorylation system

One of the key functions of mitochondria is the production of ATP to support cellular metabolism and growth. The last step of mitochondrial ATP synthesis is performed by the oxidative phosphorylation (OXPHOS) system, an ensemble of protein complexes embedded in the inner mitochondrial membrane. In the last 25 yr, many structures of OXPHOS complexes and supercomplexes have been resolved in yeast, mammals, and bacteria. However, structures of plant OXPHOS enzymes only became available very recently. In this review, we highlight the plant-specific features revealed by the recent structures and discuss how they advance our understanding of the function and assembly of plant OXPHOS complexes. Here we also propose new hypotheses to be tested and discuss older findings to be re-evaluated. Further biochemical and structural work on the plant OXPHOS system will lead to a deeper understanding of plant respiration and its regulation, with significant agricultural, environmental, and societal implications.

59 BASIC BIOLOGICAL SCIENCES↗

Unveiling phase evolution of complex oxides toward precise solid-state synthesis

The precise synthesis of high-purity materials is crucial in accelerating materials discovery. However, the lack of theoretical understanding and practical guidance poses challenges, particularly for materials with compositional and structural complexity. Here, we propose a feasible principle toward synthesizing complex inorganic solids. This principle involves the introduction of an inducer that induces crucial intermediates, which in turn guide the synthesis pathway toward the target materials through structural templating, named inducer-facilitated assembly through structural templating (i-FAST). We validate this principle with three distinct oxides: garnet Li6.5La3Zr1.5Ta0.5O12, perovskite BaCo0.8Sn0.2O3, and pyrochlore Gd1.5La0.5Zr2O7. This structural templating approach enables synthesis along predesigned pathways, forming intermediates that are thermodynamically favored for prior formation and kinetically preferred for the final product, resulting in precisely synthesizing high-purity target materials. This study not only represents a substantial advancement in comprehending the interplay between thermodynamics/kinetics and phase evolution in complex solid synthesis but also provides an effective strategy for guiding exploratory solid-state synthesis.

Yang, Lin↗

Apex hydrogen bonds in dendron assemblies modulate close-packed mesocrystal structures

The close-packed mesocrystal structures from soft-matter assemblies have recently received attention due to their structural similarity to atomic crystals, displaying various sphere-packing Frank–Kasper (FK) and quasicrystal structures. Herein, diverse mesocrystal structures are explored in second-generation dendrons (G2-X) designed with identical wedges, in which the terminal functionalities X = CONH 2 and CH 2 NH 2 represent two levels of the strong and weak hydrogen-bonding apexes, respectively. The cohesive interactions at the core apex, referred to as the core interactions, are effectively modulated by forming heterogeneous hydrogen bonds between these two functional units. For the dendron assemblies compositionally close to each pure component of G2-CONH 2 and G2-CH 2 NH 2 , their own FK A15 and C14 phases dominate other phases, respectively. We show the existence of the wide-range FK σ including the dodecagonal quasicrystal (DDQC) phases from the dendron mixtures between G2-CONH 2 and G2-CH 2 NH 2 , providing an experimental phase sequence of A15–σ–DDQC–C14 as the core interactions are alleviated. Intriguingly, the temperature dependence of particle sizes shows that the high plateau values of particle sizes are maintained equivalently until each threshold temperature (T th ), followed by a prompt decrease above the T th . A decrease in T th by alleviating the core interactions and its composition dependence suggest that the more size-dispersed particles, the more susceptibility to chain exchange with increasing temperature. Here our results on the formation of supramolecular dendron assemblies provide a guide to understand the core-interaction-dependent mesocrystal structures toward the fundamental principle underlying the temperature dependence of their particle sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural asymmetry governs the assembly and GTPase activity of McrBC restriction complexes

Abstract McrBC complexes are motor-driven nucleases functioning in bacterial self-defense by cleaving foreign DNA. The GTP-specific AAA + protein McrB powers translocation along DNA and its hydrolysis activity is stimulated by its partner nuclease McrC. Here, we report cryo-EM structures of Thermococcus gammatolerans McrB and McrBC, and E. coli McrBC. The McrB hexamers, containing the necessary catalytic machinery for basal GTP hydrolysis, are intrinsically asymmetric. This asymmetry directs McrC binding so that it engages a single active site, where it then uses an arginine/lysine-mediated hydrogen-bonding network to reposition the asparagine in the McrB signature motif for optimal catalytic function. While the two McrBC complexes use different DNA-binding domains, these contribute to the same general GTP-recognition mechanism employed by all G proteins. Asymmetry also induces distinct inter-subunit interactions around the ring, suggesting a coordinated and directional GTP-hydrolysis cycle. Our data provide insights into the conserved molecular mechanisms governing McrB family AAA + motors.

59 BASIC BIOLOGICAL SCIENCES↗

Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.

Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.

Chinnam, Naga Babu↗

Sequence Programmable Order–Disorder Transitions in Supramolecular Assembly of Peptide Nanofibers

Protein–protein interactions determine the assembly of complexes that are responsible for numerous key biological processes. The assembly of many natural protein complexes is mediated by post-translational structural changes and environmental stimuli. In this study, we show that incorporation of adjacent lysine residues results in the pH-tunable stability of peptide secondary structure and assembly, allowing for the incorporation of complementary order-inducing motifs. The strategic placement of cysteine pairs in the same peptide sequence results in redox-dependent disulfide staple formation, inducing a transition from random coil to β-sheet conformation and subsequent supramolecular nanofiber assembly from otherwise disordered peptide monomers. Spectroscopic, imaging, molecular dynamics, and kinetic studies highlight the critical role of sequence motif location, oligomerization, and the competitive interplay between intra- and interpeptide disulfide bonding in determining assembly outcomes. We extend this approach to demonstrate phosphorylation-dependent assembly from the design of the same parent peptide sequence, suggesting a general approach to the design of diverse stimulus-responsive peptide sequences for supramolecular assembly. Furthermore, these findings also provide a framework for investigating sequence-dependent pathways in amyloid fiber formation with potential implications for neurodegenerative disease research.

Disulfides↗

Structural insight on assembly-line catalysis in terpene biosynthesis

Fusicoccadiene synthase from Phomopsis amygdali (PaFS) is a unique bifunctional terpenoid synthase that catalyzes the first two steps in the biosynthesis of the diterpene glycoside Fusicoccin A, a mediator of 14-3-3 protein interactions. The prenyltransferase domain of PaFS generates geranylgeranyl diphosphate, which the cyclase domain then utilizes to generate fusicoccadiene, the tricyclic hydrocarbon skeleton of Fusicoccin A. Here, we use cryo-electron microscopy to show that the structure of full-length PaFS consists of a central octameric core of prenyltransferase domains, with the eight cyclase domains radiating outward via flexible linker segments in variable splayed-out positions. Cryo-electron microscopy and chemical crosslinking experiments additionally show that compact conformations can be achieved in which cyclase domains are more closely associated with the prenyltransferase core. This structural analysis provides a framework for understanding substrate channeling, since most of the geranylgeranyl diphosphate generated by the prenyltransferase domains remains on the enzyme for cyclization to form fusicoccadiene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing the self-assembly of conjugated polymers and small molecules through structurally programmed non-covalent control

Organic conjugated polymers and oligomers are key electronic materials for applications such as transistors, photovoltaics, and light emitting devices due to their potential for solution processability, mechanical flexibility, and precise structure-based tuning compared to inorganic materials. In dilute environments, the optoelectronic properties of conjugated polymers are largely governed by their constitutional structure and, to a lesser degree, their solution-state intramolecular configuration. In the solid state, intramolecular conformation and intermolecular electronic coupling impact these properties substantially, especially in relation to device performance. Therefore, an increasingly important area of research concerning conjugated materials is developing design strategies aimed at optimizing the solid-state packing for electronic applications. Programming solid-state packing arrangements through discrete non-covalent interactions is an emerging strategy within the context of conjugated polymers. This review focuses on the use of the two most prevalent discrete and directional interactions used to dictate the self-assembly of conjugated polymers and oligomers—hydrogen bonds and chalcogen bonds. Further, we also discuss how these design motifs can imbue conjugated materials with appealing physical properties while simultaneously retaining or improving electronic capabilities.

36 MATERIALS SCIENCE↗

Structural plasticity enables evolution and innovation of RuBisCO assemblies

Oligomerization is a core structural feature that defines the form and function of many proteins. Most proteins form molecular complexes; however, there remains a dearth of diversity-driven structural studies investigating the evolutionary trajectory of these assemblies. Ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO) is one such enzyme that adopts multiple assemblies, although the origins and distribution of its different oligomeric states remain cryptic. Here, we retrace the evolution of ancestral and extant form II RuBisCOs, revealing a complex and diverse history of oligomerization. We structurally characterize a newly discovered tetrameric RuBisCO, elucidating how solvent-exposed surfaces can readily adopt new interactions to interconvert or give rise to new oligomeric states. We further use these principles to engineer and demonstrate how changes in oligomerization can be mediated by relatively few mutations. Our findings yield insight into how structural plasticity may give rise to new oligomeric states.

59 BASIC BIOLOGICAL SCIENCES↗

Oxides and Nitrides with Asymmetric Pore Structure from Block Copolymer Co–Assembly and Non–Solvent Induced Phase Separation

Materials combining an asymmetric pore structure with mesopores everywhere enable high surface area accessibility and fast transport, making them attractive for e.g., energy conversion and storage applications. Block copolymer (BCP)/inorganic precursor co-assembly combined with non-solvent induced phase separation (NIPS) provides a route to materials in which a mesoporous top surface layer merges into an asymmetric support with graded porosity along the film normal and mesopores throughout. Here, the co-assembly and non-solvent-induced phase separation (CNIPS) of poly(isoprene)-b-poly(styrene)-b-poly(4-vinylpyridine) (ISV) triblock terpolymer and titanium dioxide (TiO 2 ) sol-gel nanoparticlesare reported. Heat-treatment in air results in free-standing asymmetric porous TiO 2 . Further thermal processing in ammonia results in free-standing asymmetric porous titanium nitride (TiN). processing changes alter structural membrane characteristics is demonstrated. Changing the CNIPS evaporation time results in various membrane cross-sections ( finger-like to sponge-like). Further, oxide and nitride material composition, crystallinity, and porosity are tuned by varying thermal processing conditions. Finally, thermal processing condition effects are probed on phase-pure asymmetric nitride membrane behavior using cyclic voltammetry to elucidate their influence, e.g., on specific capacitance. Results provide further insights into improving asymmetric and porous materials for applications including energy conversion and storage, separation, and catalysis and motivate a further expansion of CNIPS to other (in)organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Not All Aggregates Are Made the Same: Distinct Structures of Solution Aggregates Drastically Modulate Assembly Pathways, Morphology, and Electronic Properties of Conjugated Polymers

Abstract Tuning structures of solution‐state aggregation and aggregation‐mediated assembly pathways of conjugated polymers is crucial for optimizing their solid‐state morphology and charge‐transport property. However, it remains challenging to unravel and control the exact structures of solution aggregates, let alone to modulate assembly pathways in a controlled fashion. Herein, aggregate structures of an isoindigo–bithiophene‐based polymer (PII‐2T) are modulated by tuning selectivity of the solvent toward the side chain versus the backbone, which leads to three distinct assembly pathways: direct crystallization from side‐chain‐associated amorphous aggregates, chiral liquid crystal (LC)‐mediated assembly from semicrystalline aggregates with side‐chain and backbone stacking, and random agglomeration from backbone‐stacked semicrystalline aggregates. Importantly, it is demonstrated that the amorphous solution aggregates, compared with semicrystalline ones, lead to significantly improved alignment and reduced paracrystalline disorder in the solid state due to direct crystallization during the meniscus‐guided coating process. Alignment quantified by the dichroic ratio is enhanced by up to 14‐fold, and the charge‐carrier mobility increases by a maximum of 20‐fold in films printed from amorphous aggregates compared to those from semicrystalline aggregates. This work shows that by tuning the precise structure of solution aggregates, the assembly pathways and the resulting thin‐film morphology and device properties can be drastically tuned.

36 MATERIALS SCIENCE↗

Rheological dynamics and structural characteristics of supramolecular assemblies of β-cyclodextrin and sulfonic surfactants

Cyclodextrins are highly functional compounds with a hydrophobic cavity capable of forming supramolecular inclusion complexes with various classes of molecules including surfactants. The resultant rich nanostructures and their dynamics are an interesting research problem in the area of soft condensed matter and related applications. In this paper, we report novel dynamical supramolecular assemblies based on the complexation of β-cyclodextrin with 3 different sulfonic surfactants, which are sodium hexadecylsulfate, sodium dodecylbenzenesulfonate, and myristyl sulfobetaine. It was observed that a β-cyclodextrin : surfactant/2 : 1 molar ratio was ideal for inducing axial growth and imparting large viscosities in the suspensions. Such complexation processes were accompanied by intriguing nanostructural phase behaviors and rheological properties that were very sensitive to the molecular architecture of sulfonic surfactants. The presence of an amino group in the head group of the surfactant allowed for large viscosities that reached 2.4 × 10 4 Pa s which exhibited gel-like behavior. In contrast, smaller viscosity values with a lower consistency index were observed when a bulky aromatic ring was present instead. DIC microscopy was used to visually probe the microstructure of the systems with respect to sulfonate molecular architecture. Additionally, surface tension measurements, and FTIR and NMR spectroscopies were used to gain insights into the nature of interactions that lead to the complexation and nanostructural characteristics. Finally, mechanics correlating the supramolecular morphologies to the rheological properties were proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MOOSE-Based Fast Reactor Core Bowing Capabilities: Coupled Structural Mechanics – Thermal Fluids Demonstration and Related Verification Efforts

Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. Verification and assessment efforts continued on the Multiphysics Object Oriented Simulation Environment (MOOSE) capabilities relevant for modeling thermo-mechanical core bowing behavior. IAEA Verification Problem 4, which was started in FY23, was further examined with MOOSE capabilities to rectify discrepancies observed in previous years when compared to IAEA benchmark participant data. Meshing and postprocessing capabilities in MOOSE were also advanced by other teams and utilized this year. A thermal fluids-structural mechanical coupling demonstration has performed on 7-assemblyand 19-assembly fast reactor assembly configurations using MOOSE. Subchannel capabilities are used to calculate coolant temperature, and heat conduction capabilities calculate duct wall temperature as well as heat transfer through the inter-assembly gap. Structural mechanical capabilities then deform the mesh, accounting for contact between assemblies, according to the temperature gradients calculated by the thermal solvers. Power distributions are imposed rather than calculated to demonstrate different deformations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗