Advances in integrative structural biology: Towards understanding protein complexes in their cellular context
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On-orbit system identification (ID) of large space systems is essential for various reasons. For example, the complex composite structure of such systems cannot be ground-tested; their structural dynamic characteristics must be known accurately in order to accomplish active control. Furthermore, such capability can be used to characterize/identify various disturbances. The identification process is consisted of four principal elements: (1) modeling, (2) the estimation algorithm, (3) input system, and (4) measurement system. These elements are highly correlated and all togerher determine the success of the identification problem. Accurate modeling of large space systems is the most important element of the identification process. Large flexible structures are non-linear and infinite dimensional systems with highly coupled parameters and low frequency packed modes. In addition, these systems are subject to stochastic and time-varying disturbances, they have structural parameters which can vary due to on-orbit assembly deployment, and operations. These systems are generally; however, represented by constant coefficient, finite order differential equations. The non-linearities, coupling and noise effects are also often neglected. Moreover, identification experiment designs which lead to highly complex optimization problems usually require the simultaneous choice of ID algorithm, sensor, and actuator type and placement. On-orbit bandwidth and power restrictions on excitation, limited data window, and restrictions on sensor/actuator type, placement and number, has led to practical questions of implementations.
In this study, we present a novel orientation discretization approach based on the rhombic triacontahedron for Monte Carlo simulations of semiflexible polymer chains, aiming at enhancing structural analysis through rheo-small-angle scattering (rheo-SAS). Our approach provides a more accurate representation of the geometric features of semiflexible chains under deformation, surpassing the capabilities of traditional lattice structures. Validation against the Kratky–Porod chain system demonstrated superior consistency, underscoring its potential to significantly improve the precision of uncovering geometric details from rheo-SAS data. Further, this approach opens new avenues for investigating the conformations of semiflexible polymers and mechanically induced phase transitions in more complex polymer structures, offering deeper insights into their behavior under various conditions.
The electronic structure, interatomic bonding, and mechanical properties of two supercell models of Ni-based superalloys are calculated using ab initio density functional theory methods. The alloys, Haynes282 and Inconel740, are face-centered cubic lattices with 864 atoms and eleven elements. These multi-component alloys have very complex electronic structure, bonding and partial-charge distributions depending on the composition and strength of the local bonding environment. We employ the novel concept of total bond order density (TBOD) and its partial components (PBOD) to ascertain the internal cohesion that controls the intricate balance between the propensity of metallic bonding between Ni, Cr and Co, and the strong bonds with C and Al. We find Inconel740 has slightly stronger mechanical properties than Haynes282. Both Inconel740 and Haynes282 show ductile natures based on Poisson’s ratio. Poisson’s ratio shows marginal correlation with the TBOD. Comparison with more conventional high entropy alloys with equal components are discussed.
New frequency response measurement procedures, on-line modal tuning techniques, and off-line modal identification algorithms are developed and applied to the modal identification of the Advanced Structures/Controls Integrated Experiment (ASCIE), a generic segmented optics telescope test-bed representative of future complex space structures. The frequency response measurement procedure uses all the actuators simultaneously to excite the structure and all the sensors to measure the structural response so that all the transfer functions are measured simultaneously. Structural responses to sinusoidal excitations are measured and analyzed to calculate spectral responses. The spectral responses in turn are analyzed as the spectral data become available and, which is new, the results are used to maintain high quality measurements. Data acquisition, processing, and checking procedures are fully automated. As the acquisition of the frequency response progresses, an on-line algorithm keeps track of the actuator force distribution that maximizes the structural response to automatically tune to a structural mode when approaching a resonant frequency. This tuning is insensitive to delays, ill-conditioning, and nonproportional damping. Experimental results show that is useful for modal surveys even in high modal density regions. For thorough modeling, a constructive procedure is proposed to identify the dynamics of a complex system from its frequency response with the minimization of a least-squares cost function as a desirable objective. This procedure relies on off-line modal separation algorithms to extract modal information and on least-squares parameter subset optimization to combine the modal results and globally fit the modal parameters to the measured data. The modal separation algorithms resolved modal density of 5 modes/Hz in the ASCIE experiment. They promise to be useful in many challenging applications.
Integrated heterostructures exhibiting nanocolumnar morphology of the In{sub x}Ga{sub 1 – x}N/Si(111) film are grown on a single-crystal silicon substrate (c-Si(111)) and a substrate with a nanoporous buffer sublayer (por-Si) by molecular-beam epitaxy with the plasma activation of nitrogen. Using a complex of structural and microscopic methods of analysis, it is shown that the growth of In{sub x}Ga{sub 1 – x}N nanocolumns on a nanoporous buffer layer offers a number of advantages over growth on c-Si. The por-Si substrate predetermines the preferential orientation of the growth of In{sub x}Ga{sub 1 – x}N nanocolumns closer to the Si(111) orientation direction and makes it possible to produce In{sub x}Ga{sub 1 – x}N nanocolumns with a higher degree of crystallographic uniformity and with a nanocolumn lateral size of ~40 nm unified over the entire surface. The growth of In{sub x}Ga{sub 1 – x}N nanocolumns on a por-Si layer yields a decrease in the strain components ε{sub xx} and ε{sub zz} and in the density of edge and screw dislocations compared to the corresponding parameters for In{sub x}Ga{sub 1 – x}N nanocolumns grown on c-Si. The In{sub x}Ga{sub 1 – x}N nanocolumnar layer fabricated on por-Si exhibits a 20% higher charge-carrier concentration compared to the layer grown on c-Si as well as a higher intensity of the photoluminescence quantum yield (+25%).
Here we used machine learning (ML) to accurately predict eigenvalues of the hybrid HSE06 functional using eigenvalues computed by the less computationally expensive PBE functional and associated electronic features based on the k-point resolved atomic band character. The ML model was trained by using eigenvalues from only one k-point for each of the 168 compounds in the training set. The HSE06 eigenvalues across all k-points were then predicted for a separate set of 169 compounds with a mean absolute error (MAE) of 0.13 eV, representing a significant improvement over the error of PBE-computed eigenvalues relative to that of HSE06 (MAE = 0.96 eV). These accurately predicted eigenvalues result in remarkably accurate predictions for the band structures, projected density of states, and band gaps, even though the model was not explicitly trained on these other properties. Finally, we demonstrate that our ML model has a similar accuracy for both ternary and quaternary compounds well outside the initial training set and on systems with 112 and 160 atoms, demonstrating its potential to rapidly predict HSE06-quality electronic structures of complex materials that are practically unfeasible for HSE06.
We report two new rare-earth (R) ternary intermetallic compounds—Ho 2 Ni 0.8 T 1.2 with T = Si and Ge—that correspond to the R 5 Ni 2 T 3 phase earlier reported to form in Dy–Ni–T and Ho–Ni–T ternary systems. The compounds crystallize in a filled version of the orthorhombic Zr 2 Ni 1–x P-type structure with x = 0.52; their stoichiometry, determined from both single-crystal and powder X-ray diffraction data, is centered on Ho 2 Ni 0.8 T 1.2 with a narrow solid solubility range for the silicide, while the germanide appears to be a line phase. In addition to R = Dy and Ho, R 2 Ni 0.8 T 1.2 compounds also form for R = Y and Tb, representing the first examples of rare-earth-based compounds adopting the Zr 2 Ni 1–x P structural prototype. Bulk magnetization data reveal the main transitions of the ferrimagnetic or ferromagnetic type at TC = 38 K for Ho 2 Ni 0.8 Si 1.2 and TC = 37 K for Ho 2 Ni 0.8 Ge 1.2 , which are followed by subsequent magnetic reordering at lower temperatures. Neutron diffraction shows complex magnetic structures below T C with both ferromagnetic and antiferromagnetic components and magnetic propagation vector κ 1 = [0, 0, 0]. Below T N ≅ 24 K (22 K) for the silicide (germanide), an additional antiferromagnetic coupling following an incommensurate magnetic propagation vector κ 2 = [κ x , 0, 0] appears to coexist with the first magnetic structure.
Here in this paper, an approach for 3D plasma structure diagnostics using tomographic optical emission spectroscopy (Tomo-OES) of a nanosecond pulsed atmospheric pressure plasma jet (APPJ) is presented. In contrast to the well-known Abel inversion, Tomo-OES does not require cylindrical symmetry to recover 3D distributions of plasma light emission. Instead, many 2D angular projections are measured with intensified cameras and the multiplicative algebraic reconstruction technique is used to recover the 3D distribution of light emission. This approach solves the line-of-sight integration problem inherent to optical diagnostics, allowing recovery of localized OES information within the plasma that can be used to better infer plasma parameters within complex plasma structures. Here, Tomo-OES was applied to investigate an APPJ operated with helium in ambient air and impinging on planar and structured dielectric surfaces. Surface charging caused the guided streamer from the APPJ to transition to a surface ionization wave (SIW) that propagated along the surface. The SIW experienced variable geometrical and electrical material properties as it propagated, leading to 3D configurations that were non-symmetric and spatially complex. Light emission from He, N$_2^+$, and N2 were imaged at ten angular projections and the respective time-resolved 3D emission distributions in the plasma were then reconstructed. The spatial resolution of each tomographic reconstruction was 7.4 µm and the temporal resolution was 5 ns, sufficient to observe the guided streamer and the effects of the structured surface on the SIW. Emission from He showed the core of the jet and emission from N$_2^+$ and N2 indicated effects of entrainment of ambient air. Penning ionization of N2 created a ring or outer layer of N$_2^+$ that spatially converged to form the 'plasma bullet' or spatially diverged across a surface as part of a SIW. The SIW entered trenches of size 150 µm, leading to decreases in plasma light emission in regions above the trenches. The plasma light emission was higher in some regions with trenches, possibly due to effects of field enhancement.
In semiconductor physics, the Urbach rule describes an exponential dependence of the UV-Vis absorption coefficient on photon energy at the band edge. The rule is so ubiquitously applied that a single common mechanism, variability in the local potential, is generally considered to be the cause of exponential band edges. Variability in the local potential may be caused by alloy inhomogeneity, structural defects, impurities, thermal excitation, or any other mechanism that interrupts ideal crystallinity and creates disorder. A crucial point of the Urbach rule is its development for band edges which approach linearity when plotted on a logarithmic scale. The rule was not developed in the context of nonlinear band edges with complex fine structure. Even so, this model has been applied extensively to band edges with such features. Using differential analysis and deconvolution, we develop an analytical technique capable of separating the components responsible for the fine structure observed. This approach reduces challenging signal-artifact convolution problems to a simple linear combination. Furthermore, we develop a model that can be applied to the nonlinear band-edge signals extracted. In this work, we show that in the limiting case of linearity, our model is consistent with and produces the same results as the linear Urbach model. Our model is capable of bypassing “tailing” as an indirect measure of the spread in the local potential and gives a direct measure of this quantity.
Bis(trifluoromethanesulfonimide) or TFSI is widely used as a counter anion in electrolyte design due to its structural flexibility and chemical stability. Here we studied the conformational variations and associated dynamics of TFSI in adduct of Mg(TFSI) 2 with dimethoxyethane (DME), a solvate crystalline material using solid-state 1 H and 19 F NMR. TFSI molecular motion in this solvate structure falls within the timescale of the 19 F NMR experiment, yielding spectroscopic signatures for unique TFSI conformers under the coordination environment of Mg 2+ cation. Within the temperature range of -5 to 82 °C, we observe nine distinct TFSI sites in both crystalline and disordered regions using 19 F NMR, reflecting complexity of structural and dynamics of TFS1 anions within solvate structure. The four distinguishable sites in the disordered region for the two CF 3 groups of the same TFSI molecule are identified using chemical shift analysis. The exchange rate constants from site to site are calculated through variable temperature 19 F NMR and two-dimensional (2D) exchange spectroscopy (EXSY) experiments, along with respective activation enthalpies using Eyring's formulation. The flip rate of CF 3 around the S-C bond is estimated as ~ 15 s -1 at 8 °C with ΔH ≠ ~ 22 kJ/mol, but the rotation of the entire TFSI is 4.8 s -1 at 8 °C with a significantly greater ΔH ≠ = 98 ± 10 kJ/mol. Furthermore, the slow conversion of trans to cis conformers at a lower temperature (T ≤ 1 °C) in the crystalline region is monitored, with a conversion rate of ~ 2 x 10 -5 s -1 at -5 °C. Density functional theory (DFT)-based calculations were performed to support further the assignment of experimental chemical shifts, and the activation energy E a = 21.1 kJ/mol obtained for the cis to trans transition is consistent with experimental values. The combined set of 19 F and 1 H under both one-dimensional (1D) and 2D NMR methods demonstrated here can be further used for examining electrode-electrolyte interfaces to probe the motions of various constituents that can enable detailed studies of interfacial processes and dynamics. Ultimately, such studies will aid in the design and discovery of interfacial constructs in which directed defect chemistry, chemical moiety distribution, and nanostructure are employed to drive efficient charge transport.
Microporous materials include a large group of solids of varying chemical composition as well as porosity. These materials are characterized by channels and cavities of molecular dimensions. The framework structure is made up of interconnecting T-O-T' bonds, where T and T' can be Si, Al, P, Ga, Fe, Co, Zn, B and a host of other elements. Materials with Si-O-Al bonding in the framework are called zeolites and are extensively used in many applications. Ion-exchange properties of these materials are exploited in the consumer and environmental industries. Chemical and petroleum industries use zeolites as catalysts in hydrocarbon transform ations. Synthesis of new microporous frameworks has led to the development of new technologies, and thus considerable effort worldwide is expended in their discovery. Microporous materials are typically made under hydrothermal conditions. Influence of nature of starting reactants, structure directing agents, pH, temperature, and aging all have profound influence on the synthesis process. This is primarily because the most interesting open frameworks are not necessarily the stable structures in the reaction medium. Thus, the discovery of new frameworks is often tied to finding the right composition and synthesis conditions that allow for kinetic stabilization of the structure. This complexity of the synthesis process and limited understanding of it has made it difficult to develop directed is of microporous materials and most advances in this field have been made by trial and error. The basic issues in crystal growth of these materials include: (1) Nature of the nucleation process; (2) Molecular structure and assembly of nuclei; (3) Growth of nuclei into crystals; (4) Morphology control; and (5) Transformation of frameworks into other structures. The NASA-funded research described in this paper focuses on all the above issues and has been described in several publications. We present the highlights of our program, especially with the focus on possible experiments in microgravity.
Most nuclear waste disposal options include compacted bentonite, predominately consisting of montmorillonite clay, as part of a barrier system to minimize contaminant mobility. Uranium (U) is the primary element in spent nuclear fuel, and a potential contaminant of water resources. Uranium sorption onto clay and its slow diffusive transport away from waste canisters are expected to limit U(VI) mobility in these systems. However, their prediction is complicated by the complex mineralogical structure of montmorillonite clay, leading to two types of surface sites and clay porosities, and by the dependence of U(VI) solution speciation on chemical conditions. For instance, depending on pH and ionic strength, U(VI) may sorb onto montmorillonite due to weak ion exchange reactions or the formation of stable surface complexes. Furthermore, at the high degrees of clay compaction expected in future barrier systems, the ability of U(VI) species to access small, highly negatively charged interlayer spaces may ultimately control diffusive fluxes. In this modeling study, we investigate how the charge of U(VI) solution species affects U(VI) sorption and diffusion behavior. For this purpose, we simplified complex chemical solution speciation diagrams to charge speciation diagrams. Furthermore, we coupled an existing U(VI) sorption model (in PHREEQC) with U(VI) diffusion calculations (in GLE) to simulate U(VI) mobility in lab-scale through-diffusion experiments over various chemical conditions. Our results suggest that there are two important parameters that govern U(VI) diffusion in these systems. Uranium(VI) surface complexation on clay edge surfaces leads to contaminant retardation, while the access of U(VI) solution species to diffuse layers in clay interlayer spaces controls diffusive fluxes. Hence on the field scale, these parameters will determine how early a plume may cross site boundaries and pose risks to drinking water resources, and the levels of U(VI) concentrations to be expected in contaminated waters.
CD40 is a 48 kDa type I transmembrane protein that is constitutively expressed on hematopoietic cells such as dendritic cells, macrophages, and B cells. Engagement of CD40 by CD40L expressed on T cells results in the production of proinflammatory cytokines, induces T helper cell function, and promotes macrophage activation. The involvement of CD40 in chronic immune activation has resulted in CD40 being proposed as a therapeutic target for a range of chronic inflammatory diseases. CD40 antagonists are currently being explored for the treatment of autoimmune diseases and several anti-CD40 agonist mAbs have entered clinical development for oncological indications. To better understand the mode of action of anti-CD40 mAbs, we have determined the x-ray crystal structures of the ABBV-323 (anti-CD40 antagonist, ravagalimab) Fab alone, ABBV-323 Fab complexed to human CD40 and FAB516 (anti-CD40 agonist) complexed to human CD40. These three crystals structures 1) identify the conformational CD40 epitope for ABBV-323 recognition 2) illustrate conformational changes which occur in the CDRs of ABBV-323 Fab upon CD40 binding and 3) develop a structural hypothesis for an agonist/antagonist switch in the LCDR1 of this proprietary class of CD40 antibodies. The structure of ABBV-323 Fab demonstrates a unique method for antagonism by stabilizing the proposed functional antiparallel dimer for CD40 receptor via novel contacts to LCDR1, namely residue position R32 which is further supported by a closely related agonist antibody FAB516 which shows only monomeric recognition and no contacts with LCDR1 due to a mutation to L32 on LCDR1. These data provide a structural basis for the full antagonist activity of ABBV-323.
At sites of vascular damage, factor VIII (fVIII) is proteolytically activated by thrombin and binds to activated platelet surfaces with activated factor IX (fIXa) to form the intrinsic “tenase” complex. Previous structural and mutational studies of fVIII have identified the C1 and C2 domains in binding to negatively charged membrane surfaces through β-hairpin loops with solvent-exposed hydrophobic residues and a ring of positively charged basic residues. Several hemophilia A-associated mutations within the C domains are suggested to disrupt lipid binding, preventing formation of the intrinsic tenase complex. In this study, we devised a novel platform for generating recombinant C1, C2, and C1C2 domain constructs and performed mutagenesis of several charged residues proximal to the putative membrane binding region of each C domain. Binding measurements between phosphatidylserine (PS)-containing lipid membrane surfaces and fVIII C domains demonstrated an ionic strength dependence on membrane binding affinity. Mutations to basic residues adjacent to the surface-exposed hydrophobic regions of C1 and C2 differentially disrupted membrane binding, with abrogation of binding occurring for mutations to conserved arginine residues in the C1 (R2163) and C2 (R2320) domains. Lastly, we determined the X-ray crystal structure of the porcine fVIII C2 domain bound to o-phospho-L-serine, the polar headgroup of PS, which binds to a basic cleft and makes charge-charge contact with R2320. We conclude that basic clefts in the fVIII C domains bind to PS-containing membranes through conserved arginine residues via a C domain modularity, where each C domain possesses modest electrostatic-dependent affinity and tandem C domains are required for high affinity binding.
Ferrihydrite is one of the most important iron-containing minerals on Earth. Yet determination of its atomic-scale structure has been frustrated by its intrinsically poor crystallinity. The key difficulty is that physically-different models can appear consistent with the same experimental data. Using X-ray total scattering and a nancomposite reverse Monte Carlo approach, we evaluate the two principal contending models—one a multi-phase system without tetrahedral iron(III), and the other a single phase with tetrahedral iron(III). Our methodology is unique in considering explicitly the complex nanocomposite structure the material adopts: namely, crystalline domains embedded in a poorly-ordered matrix. The multi-phase model requires unphysical structural rearrangements to fit the data, whereas the single-phase model accounts for the data straightforwardly. Hence the latter provides the more accurate description of the short- and intermediate-range order of ferrihydrite. We discuss how this approach might allow experiment-driven (in)validation of complex models for important nanostructured phases beyond ferrihydrite.
Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.
Here, the magnetic structure, magnetoresistance (MR), and Hall effect of the noncentrosymmetric magnetic semimetal NdAlGe are investigated, revealing an unusual magnetic state and anomalous transport properties that are associated with the electronic structure of this compound. The magnetization and MR measurements are both highly anisotropic and indicate an Ising-like magnetic system. The magnetic structure is complex in that it involves two magnetic ordering vectors, including an incommensurate spin density wave and commensurate ferrimagnetic state in zero field. We have discovered a large anomalous Hall conductivity that reaches ≈430 Ω –1 cm –1 , implying that it originates from an intrinsic Berry curvature effect stemming from Weyl nodes found in the electronic structure. These electronic structure calculations indicate the presence of nested Fermi surface pockets with nesting wave vectors like the measured magnetic ordering wave vector and the presence of Weyl nodes in proximity to the Fermi surface. We associate the incommensurate magnetic structure with the large anomalous Hall response to be the result of the combination of Fermi surface nesting and the Berry curvature associated with Weyl nodes.