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At least 775 records · Page 43

Structure of metallochaperone in complex with the cobalamin-binding domain of its target mutase provides insight into cofactor delivery

G-protein metallochaperone MeaB in bacteria [methylmalonic aciduria type A (MMAA) in humans] is responsible for facilitating the delivery of adenosylcobalamin (AdoCbl) to methylmalonyl-CoA mutase (MCM), the only AdoCbl-dependent enzyme in humans. Genetic defects in the switch III region of MMAA lead to the genetic disorder methylmalonic aciduria in which the body is unable to process certain lipids. Here, we present a crystal structure of Methylobacterium extorquens MeaB bound to a nonhydrolyzable guanosine triphosphate (GTP) analog guanosine-5'-[(β,γ)-methyleno]triphosphate (GMPPCP) with the Cbl-binding domain of its target mutase enzyme (MeMCM cbl ). This structure provides an explanation for the stimulation of the GTP hydrolyase activity of MeaB afforded by target protein binding. We find that upon MCM cbl association, one protomer of the MeaB dimer rotates ~180°, such that the inactive state of MeaB is converted to an active state in which the nucleotide substrate is now surrounded by catalytic residues. Importantly, it is the switch III region that undergoes the largest change, rearranging to make direct contacts with the terminal phosphate of GMPPCP. These structural data additionally provide insights into the molecular basis by which this metallochaperone contributes to AdoCbl delivery without directly binding the cofactor. Our data suggest a model in which GTP-bound MeaB stabilizes a conformation of MCM that is open for AdoCbl insertion, and GTP hydrolysis, as signaled by switch III residues, allows MCM to close and trap its cofactor. Substitutions of switch III residues destabilize the active state of MeaB through loss of protein:nucleotide and protein:protein interactions at the dimer interface, thus uncoupling GTP hydrolysis from AdoCbl delivery.

59 BASIC BIOLOGICAL SCIENCES↗

Structure of Layers Formed by [2-(3,6-Disubstituted-9 H -carbazol-9-yl)ethyl]phosphonic Acids on Metal Oxides

[2-(9 H -Carbazol-9-yl)ethyl]phosphonic acid (2PACz) and its derivatives are being used extensively as hole-transport layers in organic and perovskite solar cells due to their ability to modify electrode work function, surface wettability, and in some cases, to improve active-layer adhesion, while minimizing interfacial energy losses. The orientation and coverage of surface modifiers significantly impact these functional properties; however, the detailed structure and packing in these overlayers are challenging to investigate, leading to a lack of understanding of how this structure and packing influence performance and limiting the ability to rationally design molecular modifiers. Here, we investigate monolayers of 2-(9 H -carbazol-9-yl)ethyl phosphonic acid derivatives (from here on referred to as X-2PACz) on indium tin oxide (ITO) and alpha phase aluminum oxide (α-Al 2 O 3 ) using a combination of X-ray photoelectron spectroscopy (XPS), near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, and X-ray reflectivity (XRR). By correlating elemental ratios, molecular orientation, and electron density profiles, we directly quantify surface coverage, layer thickness, and molecular tilt across a series of chemically related monolayers. We find that 2PACz and the X-2PACz derivatives form dense monolayers on α-Al 2 O 3 and ITO, with similar surface coverages on either substrate that are inversely proportional to molecular steric bulk. These surface coverage results indicate that X-2PACz is sterically limited in its monolayer surface packing density, as opposed to site limited. Despite surface packing density differences between molecules, the NEXAFS data show a constant average molecular orientation of 61° to 65° between the plane of the carbazole and the substrate for all the molecules on both substrates. These results increase our general understanding of 2PACz derivatives as they become increasingly useful in high performance solar cells.

NEXAFS↗

Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

97 MATHEMATICS AND COMPUTING↗

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗

Argon equation of state data to 1 TPa: Shock compression experiments and simulations

Argon is the most abundant noble gas on Earth and its noble, atomic fluid nature makes it an excellent candidate for comparison of experiment and theory at extreme conditions. For this study, we performed a combined computational and experimental study on shock compressed cryogenic liquid argon. Using Sandia's Z machine, we shock compressed liquid argon to 600 GPa and reshock states up to 950 GPa. Laser shock experiments at the Omega Laser facility extend the principal Hugoniot to 1000 GPa and provided temperature data along the principal Hugoniot. The plate impact experiments and laser shock experiments used well-characterized impedance matching standards and demonstrate consistent results between the two platforms over a common range. Density functional theory based molecular dynamics simulations provided additional data on the Hugoniot to 600 GPa. The combined experimental data and simulation results provide constraints on the development of new equation of state models at extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Infrared and Raman spectroscopic studies of structural variations in minerals from Apollo 11, 12, 14 and 15 samples, volume 3

Infrared and Raman vibrational spectroscopic data, yielding direct information on molecular structure, were obtained for single grains ( 150 microns) of minerals, basalts, and glasses isolated from Apollo 11, 12, 14, and 15 rock and dust samples, and for grains in Apollo 14 polished butt samples. From the vibrational data, specification substitutions were determined for the predominant silicate minerals of plagioclase, pyroxene, and olivine. Unique spectral variations for grains of K-feldspar, orthopyroxene, pyroxenoid, and ilmenite were observed to exceed the ranges of terrestrial samples, and these variations may be correlatable with formation histories. Alpha-quartz was isolated as pure single grains, in granitic grains composited with sanidine, and in unique grains that were intimately mixed with varying amounts of glass. Accessory minerals of chromite and ulvospinel were isolated as pure grains and structurally characterized from their distinctive infrared spectra. Fundamental vibrations of the SiO4 tetrahedra in silicate minerals were used to classify bulk compositions in dust sieved fractions, basalt grains and glass particles, and to compare modal characteristics for maria, highland and rille samples. No hydrated minerals were found in any of the samples studied, indicating anhydrous formation conditions.

Estep, P. A.↗

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D

We report the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

59 BASIC BIOLOGICAL SCIENCES↗

Parallel Algorithms for Computing the Tensor-Train Decomposition

The tensor-train (TT) decomposition expresses a tensor in a data-sparse format used in molecular simulations, high-order correlation functions, and optimization. In this paper, we propose four parallelizable algorithms that compute the TT format from various tensor inputs: (1) Parallel-TTSVD for traditional format, (2) PSTT and its variants for streaming data, (3) Tucker2TT for Tucker format, and (4) TT-fADI for solutions of Sylvester tensor equations. We provide theoretical guarantees of accuracy, parallelization methods, scaling analysis, and numerical results. For example, for a d-dimension tensor in $\mathbb{R}$ $n\times∙∙∙$$\times$$n$ a two-sided sketching algorithm PSTT2 is shown to have a memory complexity of $O(n^{[d/2]})$, improving upon $O(n^{d—1})$ from previous algorithms.

97 MATHEMATICS AND COMPUTING↗

High‐Performance Fluorinated Fused‐Ring Electron Acceptor with 3D Stacking and Exciton/Charge Transport

Abstract A new fluorinated electron acceptor (FINIC) based on 6,6,12,12‐tetrakis(3‐fluoro‐4‐hexylphenyl)‐indacenobis(dithieno[3,2‐ b ;2 ′ ,3 ′ ‐ d ]thiophene) as the electron‐donating central core and 5,6‐difluoro‐3‐(1,1‐dicyanomethylene)‐1‐indanone as the electron‐deficient end groups is rationally designed and synthesized. FINIC shows similar absorption profile in dilute solution to the nonfluorinated analogue INIC. However, compared with INIC, FINIC film shows red‐shifted absorption, down‐shifted frontier molecular orbital energy levels, enhanced crystallinity, and more ordered molecular packing. Single‐crystal structure data show that FINIC molecules pack into closer 3D “network” motif through H‐bonding and π–π interaction, while INIC molecules pack into incompact “honeycomb” motif through only π–π stacking. Theoretical calculations reveal that FINIC has stronger electronic coupling and more molecular interactions than INIC. FINIC has higher electron mobilities in both horizontal and vertical directions than INIC. Moreover, FINIC and INIC support efficient 3D exciton transport. PBD‐SF/FINIC blend has a larger driving force for exciton splitting, more efficient charge transfer and photoinduced charge generation. Finally, the organic solar cells based on PBD‐SF/FINIC blend yield power conversion efficiency of 14.0%, far exceeding that of the PBD‐SF/INIC‐based devices (5.1%).

Dai, Shuixing↗

Insights on the dissolution of water in an albite melt at high pressures and temperatures from a direct structural analysis

The water dissolution mechanism in silicate melts under high pressures is not well understood. Here we present the first direct structure investigation of a water-saturated albite melt to monitor the interactions between water and the network structure of silicate melt at the molecular level. In situ high-energy X-ray diffraction was carried out on the NaAlSi 3 O 8 -H 2 O system at 800 °C and 300 MPa, at the Advanced Photon Source synchrotron facility. The analysis of the X-ray diffraction data was augmented with classical Molecular Dynamics simulations of a hydrous albite melt, incorporating accurate water-based interactions. The results show that metal–oxygen bond breaking at the bridging sites occurs overwhelmingly at the Si site upon reaction with H 2 O, with subsequent Si–OH bond formation and negligible Al–OH formation. Furthermore, we see no evidence for the dissociation of the Al 3+ ion from the network structure upon breaking of the Si–O bond in the hydrous albite melt. The results also indicate that the Na + ion is an active participant in the modifications of the silicate network structure of the albite melt upon water dissolution at high P–T conditions. We do not find evidence for the Na + ion dissociating from the network structure upon depolymerization and subsequent formation of NaOH complexes. Instead, our results show that the Na + ion persists as a structure modifier with a shift away from Na–BO bonding to an increase in the extent of Na-NBO bonding, in parallel with pronounced depolymerization of the network. Our MD simulations show that the Si–O and Al–O bond lengths are expanded by about 6% in the hydrous albite melt compared to those of the dry melt at high P–T conditions. The changes in the network silicate structure of a hydrous albite melt at high pressure and temperature, as revealed in this study, must be considered in the advancement of water dissolution models of hydrous granitic (or alkali aluminosilicate) melts.

36 MATERIALS SCIENCE↗

Development of vestibular afferent projections into the hindbrain and their central targets

In contrast to most other sensory systems, hardly anything is known about the neuroanatomical development of central projections of primary vestibular neurons and how their second order target neurons develop. Recent data suggest that afferent projections may develop not unlike other sensory systems, forming first the overall projection by molecular means followed by an as yet unspecified phase of activity mediated refinement. The latter aspect has not been tested critically and most molecules that guide the initial projection are unknown.The molecular and topological origin of the vestibular and cochlear nucleus neurons is also only partially understood. Auditory and vestibular nuclei form from several rhombomeres and a given rhombomere can contribute to two or more auditory or vestibular nuclei. Rhombomere compartments develop as functional subdivisions from a single column that extends from the hindbrain to the spinal cord. Suggestions are provided for the molecular origin of these columns but data on specific mutants testing these proposals are not yet available. Overall, the functional significance of both overlapping and segregated projections are not yet fully experimentally explored in mammals. Such lack of details of the adult organization compromises future developmental analysis.

Review↗

PPI DataHub Project Data Package: S. elongatus PCC 7942 Limited Proteolysis and Thermal Proteome Profiling Structural Proteomics (JM-PB-DP3)

The purpose of this experiment was to investigate structural alterations in proteins involved in central carbon metabolism and photosynthetic electron transfer pathways in Synechococcus elongatus PCC 7942. Sample data was obtained from S. elongatus cell lysates using three complementary mass spectrometry (MS) techniques using limited proteolysis (LiP-MS), thermal proteome profiling (TPP-MS), and redox enrichment (Redox-MS) in evaluating alterations solvent accessibility and structural stability caused by light perturbation at the molecular level. Experimentally processed sample data for LiP and TPP proteomic datasets were derived from the same cell culture stock, prepared simultaneously in parallel, and acquired by mass spectrometry. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files, computed outputs, and supporting metadata materials. Experimental samples processed for LiP-MS label-free quantification (LFQ) or TPP-MS tandem mass tag (TMT) 10-plex were acquired using a Q-Exactive HF-X mass spectrometer and processed/compiled using either MSGF+ (v2024.03.26) or ​​​​PlexedPiper for proteome evaluation. Additional software supporting downstream proteomic analysis include FragPipe (v.4.0), MSFragger (v.22.1), and an adapted Microbial Isolate LiP Analysis Workflow (located at Zenodo). Processed proteomic data downloads include a sample naming key, normalized quantification results files, and processed protein annotated abundance files.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing the formation of ionic defects to study the ice Ih/XI transition with molecular dynamics simulations

Ice Ih, the common form of ice in the biosphere, contains proton disorder. Its proton-ordered counterpart, ice XI, is thermodynamically stable below 72 K. However, the formation of ice XI is kinetically hindered, and experimentally it is obtained by doping with KOH. Doping creates ionic defects that promote the migration of protons and the associated change in proton configuration. In this article, we mimic the effect of doping with a bias potential that enhances the formation of ionic defects in molecular dynamics simulations. The recombination of the ions thus formed proceeds through fast migration of the hydroxide along hydrogen bond loops, providing a physical and expedite way to change the proton configuration. Here, a key ingredient of this approach is a machine learning potential trained with density functional theory data and capable of modelling molecular dissociation. We exemplify the usefulness of this idea by studying the order-disorder transition using an appropriate order parameter that distinguishes the proton environments in ice Ih and XI. We calculate the changes in free energy, enthalpy, and entropy associated with the transition. Our estimated entropy agrees with experiment within the error bars of the calculation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Molecular Structure of Sphingomyelin in Fluid Phase Bilayers Determined by the Joint Analysis of Small-Angle Neutron and X-ray Scattering Data

In this work, we have determined the fluid bilayer structure of palmitoyl sphingomyelin (PSM) and stearoyl sphingomyelin (SSM) by simultaneously analyzing small-angle neutron and X-ray scattering data. Using a newly developed scattering density profile (SDP) model for sphingomyelin lipids, we report structural parameters including the area per lipid, total bilayer thickness, and hydrocarbon thickness, in addition to lipid volumes determined by densitometry. Unconstrained all-atom simulations of PSM bilayers at 55 °C using the C36 CHARMM force field produced a lipid area of 56 Å 2 , a value that is 10% lower than the one determined experimentally by SDP analysis (61.9 Å2). Furthermore, scattering form factors calculated from the unconstrained simulations were in poor agreement with experimental form factors, even though segmental order parameter (S CD ) profiles calculated from the simulations were in relatively good agreement with S CD profiles obtained from NMR experiments. Conversely, constrained area simulations at 61.9 Å 2 resulted in good agreement between the simulation and experimental scattering form factors, but not with S CD profiles from NMR. We discuss possible reasons for the discrepancies between these two types of data that are frequently used as validation metrics for molecular dynamics force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data

Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Aerodynamics Database for Aerocapture of a Conceptual Morphable Entry System at Mars

An aerodynamics database for aerocapture of a conceptual morphable entry system at Mars was developed. The vehicle is envisioned to employ deflections of its geometry to modulate angle of attack and sideslip angle for trajectory control. Modified Newtonian methods were used to compute hypersonic continuum aerodynamics. Direct simulation Monte Carlo calculations were carried out to compute data in the rarefied transitional regime. Free-molecular theory was used to compute values in the free-molecular regime. A bridging function method was then used to bridge data from all three flow regimes together and produce a database that can be used for future trajectory simulations to assess the vehicle’s performance. The vehicle was found to have the control authority in hypersonic continuum to effect an 18 deg change in the trim angle of attack using a 10 deg deflection of the pitching control surfaces. Similarly, a 6 deg change in the trim sideslip angle could be achieved with a 5 deg deflection of the yawing control surfaces. Different configurations of the vehicle were found to be statically stable in pitch and yaw in the continuum regime, but unstable in the rarefied and free-molecular regimes.

aerocapture↗

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids

Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions of diffusion also should be possible for fluids in confined environments. The ability to quickly and accurately predict diffusion in porous materials would enable new discoveries and spur development in relevant technologies such as separations, catalysis, batteries, and subsurface applications. Here in this work, we apply artificial neural network (ANN) models to predict the simulated self-diffusion coefficients of real liquids in both bulk and pore environments. The training data sets were generated from molecular dynamics (MD) simulations of Lennard-Jones particles representing a diverse set of 14 molecules ranging from ammonia to dodecane over a range of liquid pressures and temperatures. Planar, cylindrical, and hexagonal pore models consisted of walls composed of carbon atoms. Our simple model for these liquids was primarily used to generate ANN training data, but the simulated self-diffusion coefficients of bulk liquids show excellent agreement with experimental diffusion coefficients. ANN models based on simple descriptors accurately reproduced the MD diffusion data for both bulk and confined liquids, including the trend of increased mobility in large pores relative to the corresponding bulk liquid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Addition of Short Polymer Chains Mechanically Reinforces Glassy Poly(2-vinylpyridine)–Silica Nanoparticle Nanocomposites

The addition of hard fillers to a polymer matrix is a well-known process for achieving mechanical reinforcement. With a decrease in the size of the fillers, the contribution from polymer–particle nanometer-sized interfaces become significant, and these interfaces affect the mechanical performance of polymer nanocomposites (PNCs) beyond the limits established for conventional composites. However, the molecular mechanisms underlying the improvement in the mechanical performance of glassy PNCs remain unresolved, necessitating a deeper understanding of the structure–property relationships in these intrinsically heterogeneous systems. In this effort, by using Brillouin light scattering (BLS) and dynamic mechanical analysis (DMA), we demonstrated that adding shorter chains to a PNC prepared with high molecular weight polymers significantly improved the mechanical properties of the PNC in the glassy state. The strongest enhancement of mechanical properties occurred at an optimum concentration of short chains. This is in contrast to behavior of the glass transition temperature of PNCs which shows a monotonic decrease with an increase in the concentration of shorter chains. Using experimental data and coarse-grained molecular dynamics (MD) simulations, we have identified the molecular mechanism leading to the observed non-monotonic changes in mechanical reinforcement. Here, this mechanism includes changes in the nanoscale organization at the interface, combined with chain stretching amplified by the addition of the short chains. Overall, our approach paves a simple, cost-effective pathway to fabricating glassy PNCs with significantly improved mechanical properties that will fill various practical needs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗