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At least 163 records · Page 9

Using geometric simulation software ‘GASP’ to model conformational flexibility in a family of zinc metal–organic frameworks

Here, a new tripodal tricarboxylic acid ligand, 4,4'-(4'-(4'-carboxy-[1,1'-biphenyl]-4-yl)-[2,2':6',2''-terpyridine]-5,5''-diyl)-dibenzoic acid (H 3 cbt ), was synthesised using a three-step convergent strategy. Subsequent reactions with zinc( II ) nitrate hexahydrate yielded three metal–organic frameworks (MOFs). The three MOFs, [Zn(H cbt )]·4DMF ( 1 ), [Zn(H cbt )]·4DMSO·1.5H 2 O·DMF ( 2 ), and [Zn(H cbt )]·2DMF·3H 2 O ( 3 ), each adopt flexible interdigitated 2D net topologies. Framework 1 has DMF-filled channels that retain porosity upon desolvation, with a measured BET surface area of 248 m 2 g -1 . Framework 2 possesses larger DMSO-containing channels that collapse upon desolvation, resulting in near-equivalent porosity values to framework 1 . In silico calculations and topological considerations determined using the geometric simulation software GASP dictate that framework 2 can feasibly alter conformation to approximate 1 , but cannot perfectly replicate the interdigitated motif. Framework 3 formed when wet solvents were used to synthesise 1 . Interestingly, the interdigitated structure of 3 contains a unique carboxylate binding mode that precludes its subsequent adoption by either 1 or 2 upon their exposure to water. This diverse array of structural considerations recommends this MOF family for modelling using GASP. Interrogating frameworks 1–3 using this software provided insights that justified experimentally observed conformational trends, as well as barriers to interconversion between members of this MOF family. In a broader sense, this work demonstrates the wider applicability of GASP software to modelling structural changes within flexible MOF materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Net Electronic Charge as an Effective Electronic Descriptor for Oxygen Release and Transport Properties of SrFeO 3 -based Oxygen Sorbents

Perovskite oxides, as oxygen sorbents, exhibit excellent potential in thermochemical redox applications such as chemical looping air separation (CLAS), resulting from their excellent redox properties and high tunability. The structural and compositional flexibility of perovskites, while making these mixed oxides highly versatile, also poses challenges for their design and optimization. Moreover, the elevated operating temperature and dynamic oxygen partial pressure swings during redox processes add additional complications for oxygen sorbent design. From a fundamental standpoint, finding simple yet effective descriptors for the effect of cation substitutions on oxygen sorbents’ redox and oxygen transport properties are of significant importance for rational optimization of perovskite-based oxygen sorbents. In the present study, a series of A/B-site-doped SrFeO 3-δ perovskites are investigated using density functional theory (DFT) + U simulations. From these simulations, an effective electronic structural descriptor, the net electronic charge (Δe) of oxygen anions, is extracted based on its excellent correlations with vacancy formation energy, experimentally derived oxygen capacity, and oxygen vacancy migration barrier. Overall, these findings provide an effective tool to correlate the oxygen sorbents’ redox performances with a simple yet physically meaningful descriptor for rational design and optimization of perovskites in the context of CLAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser-assisted high-energy proton pulse extraction for feasibility study of co-located muon source at the SNS

Here, we have experimentally demonstrated the first non-intrusive 1-GeV proton beam extraction for the generation of muons with a temporal structure optimized for Muon Spin Relaxation/Rotation/Resonance (μSR) applications. The proton pulses are extracted based on the laser neutralization of 1 GeV hydrogen ion (H - ) beam in the high energy beam transport of the Spallation Neutron Source (SNS) accelerator. The maximum flux of the extracted proton beam based on laser neutralization causes only 0.2% reduction of the total proton beam used for neutron production, a marked difference from the 20% reduction at other co-located muon and neutron facilities, and thus the proposed method will result in negligible impact on the SNS operation. This paper describes the development of a fiber/solid-state hybrid laser system that has high flexibility of pulse structure and output power, initial experiments on laser neutralization of beam and separation of H 0 beam from the existing SNS accelerator beam line, conversion of H 0 to proton at the SNS linac dump, and measurement results of 30 ns/50 kHz proton pulses. This system conclusively demonstrates the feasibility of laser-based proton beam extraction to power a world-leading μSR facility at the SNS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Progress in Understanding the Origins of Excellent Corrosion Resistance in Metallic Alloys: From Binary Polycrystalline Alloys to Metallic Glasses and High Entropy Alloys

Some of the factors responsible for good corrosion resistance of select polycrystalline and emerging alloys in chloride solutions are discussed with a goal of providing some perspectives on the current status and future directions. Traditional metallic glass alloys, single phase high entropy alloys (HEAs), early metallic glasses, and high entropy metallic glasses are all emerging corrosion-resistant alloys (CRAs) that utilize traditional strategies for improved corrosion resistance as well as take advantage of some other novel beneficial attributes. These materials enjoy many degrees of freedom as far as choice of both composition and structure, providing great flexibility in the pursuit of superior corrosion resistance. The new materials depart from classical solvent-solute type polycrystalline binary or ternary alloys. Thus, such emerging materials provide significant opportunities to achieve even greater improvements in corrosion resistance in harsh environments. Several examples of the unique corrosion properties of selected materials in the context of modern theories of corrosion are discussed herein. Discussion is restricted to solid-solution binary or ternary polycrystalline alloys, several metallic glass alloys, and single phase HEAs. A common feature of many CRAs is that composition and microstructure often affect both passivity and resistance to localized corrosion that can be divided into initiation, stabilization, and propagation stages. Enormous complexities in protective oxide structures and chemistries and the large number of combinatorial possibilities in newer materials such as HEAs preclude trial-and-error approaches and perhaps even combinatorial experimental design. Computational materials methodologies will be required in the search for new corrosion-resistant alloys in these material classes. The search must consider the best scientific insights available regarding how major and minor alloy additions, as well as various microstructural attributes, contribute to corrosion mitigation. Additional scientific insights, as they emerge, will enable choices beyond the reliance on high concentrations of alloying elements that are known to affect passivity breakdown and pit stabilization. A challenge is to connect the “basic attributes” of an alloy with its properties. The strength of this connection will likely require new scientific principles enabling deep multiphysics insights in order to link feature(s) such as composition and metallurgical phases to the desired corrosion properties. Application of data informatics will likely also play a role given the plethora of variables that are important in corrosion and the difficulty in assessing all relationships. Here, the opportunity exists to accelerate the design of emerging materials for high corrosion resistance.

36 MATERIALS SCIENCE↗

Effect of frequency and applied voltage of an atmospheric-pressure dielectric-barrier discharge on breakdown and hydroxyl-radical generation with a liquid electrode

This work examines the effect of the frequency and peak applied voltage on hydroxyl-radical generation in a dielectric-barrier plasma discharge between a metallic needle electrode and one electrode covered with dielectric. The authors examine a system that can expose up to 96 liquid samples in an automated fashion without human intervention beyond setting the initial software configuration. Then, hydroxylradical concentration, measured through coumarin fluorescence, was measured for 5 s plasma exposures generated under different highvoltage conditions with frequencies from 2 to 16 kHz and amplitudes from 4 to 9 kV. Their results show that an increase in frequency and/or applied voltage, within the range prescribed above and the limits of the high-voltage power supply, can yield up to a 150% increase in fluorescence with an equivalent hydroxyl-radical increase. Applications using typical previous methods, such as the Fenton Reaction, are limited in that they continuously generate hydroxyl radicals over millisecond and longer intervals. These results establish the electrical parameters that can now be applied to polymers, like proteins, which show three dimensional structures that are flexible and fluctuate on a microsecond and nanosecond time scale, with hydroxyl-radical generation on this time scale using this device. Additionally, plasma exposures may be optimized for a great variety of proteins, devices and techniques, where hydroxyl-radical generation is of utmost importance, reducing exposure time and potential subjection of samples to harmful side effects.

42 ENGINEERING↗

Structures of monomeric and dimeric PRC2:EZH1 reveal flexible modules involved in chromatin compaction

Polycomb repressive complex 2 (PRC2) is a histone methyltransferase critical for maintaining gene silencing during eukaryotic development. In mammals, PRC2 activity is regulated in part by the selective incorporation of one of two paralogs of the catalytic subunit, EZH1 or EZH2. Each of these enzymes has specialized biological functions that may be partially explained by differences in the multivalent interactions they mediate with chromatin. Here, we present two cryo-EM structures of PRC2:EZH1, one as a monomer and a second one as a dimer bound to a nucleosome. When bound to nucleosome substrate, the PRC2:EZH1 dimer undergoes a dramatic conformational change. We demonstrate that mutation of a divergent EZH1/2 loop abrogates the nucleosome-binding and methyltransferase activities of PRC2:EZH1. Finally, we show that PRC2:EZH1 dimers are more effective than monomers at promoting chromatin compaction, and the divergent EZH1/2 loop is essential for this function, thereby tying together the methyltransferase, nucleosome-binding, and chromatin-compaction activities of PRC2:EZH1. We speculate that the conformational flexibility and the ability to dimerize enable PRC2 to act on the varied chromatin substrates it encounters in the cell.

59 BASIC BIOLOGICAL SCIENCES↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

Low-frequency and Moiré–Floquet engineering: A review

Highlights: • Review of theoretical and experimental advances in Floquet engineering. • Review of theories to derive effective Floquet Hamiltonians, with a focus on the low-frequency regime. • Review of the theoretical effects of light in Moiré materials. We review recent work on low-frequency Floquet engineering and its application to quantum materials driven by light, focusing on van der Waals systems hosting Moiré superlattices. These non-equilibrium systems combine the twist-angle sensitivity of the band structure with the flexibility of light drives. The frequency, amplitude, and polarization of light can be tuned in experimental setups, leading to platforms with on-demand properties. First, we review recent theoretical developments to derive effective Floquet Hamiltonians, emphasizing the low-frequency regime. We then review applications of some of these theories to study twisted graphene and transition metal dichalcogenide systems irradiated by light in free space and inside a waveguide. We study the changes induced in the quasienergies and steady-states, which can lead to topological transitions. Next, we consider van der Waals magnetic materials driven by low-frequency light pulses in resonance with the phonons. We discuss the phonon dynamics induced by the light and the resulting magnetic transitions from a Floquet perspective. We finish by outlining new directions for Moiré–Floquet engineering in the low-frequency regime and their relevance for technological applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Treatment of 1–4 Interactions in Force Fields for Molecular Dynamics Simulations

Traditional force fields commonly use a combination of bonded torsional terms and empirically scaled nonbonded interactions to capture 1-4 energies and forces of atoms separated by three bonds in a molecule. While this approach can yield accurate torsional energy barriers, it often leads to inaccurate forces and erroneous geometries and creates an interdependence between dihedral terms and nonbonded interactions, complicating parametrization and reducing transferability. Here, in this paper, we demonstrate that 1-4 interactions can be accurately modeled using only bonded coupling terms, eliminating the need for arbitrarily scaled nonbonded interactions altogether. Furthermore, by leveraging the automated parametrization capabilities of the Q-Force toolkit, we efficiently determine the necessary coupling terms without the need for manual adjustment. Our approach is first validated on a range of small molecule systems, encompassing both flexible and rigid structures, and shows a significant improvement in force field accuracy, obtaining subkcal/mol mean absolute error for every molecule tested. We further extend the bonded-only model for 1-4 interactions to Amber ff14sb, CHARMM36, and OPLS-AA force fields to reproduce ab initio gas and implicit solvent ϕ,ψ surfaces of alanine dipeptide.

Abdullah, Aalim S. [University of California, Berk↗

Efficient Mn 2+ Doping in Non-Stoichiometric Cesium Lead Bromide Perovskite Quantum Dots

Doping magnetic transition metal ions (e.g., Mn 2+ ) into colloidal quantum dots endows novel optical and magnetic properties to the host materials. CsPbBr 3 quantum dots (QDs) are emerging light-emitting materials with high structural and chemical flexibility in the visible spectral regime. However, efficiently doping Mn 2+ ions in CsPbBr 3 QDs remains challenging, especially when size confinement and ensemble uniformity are needed for understanding the underexplored exciton-dopant exchange interaction. Here, we introduce a doping mechanism based on electrostatic surface Mn 2+ adsorption that enables efficient Mn 2+ incorporation in strongly confined CsPbBr 3 QDs. The resultant QDs are found to have a Cs-deficient stoichiometry compared to their undoped counterparts. A redox reaction-based purification method was developed to remove Mn 2+ cations that are tightly adsorbed on the surface to determine the concentration of lattice-incorporated Mn 2+ . Our synthesis enables a Mn 2+ doping/alloying concentration of up to ∼44% with a Mn 2+ photoluminescence efficiency exceeding 90%. This allows for the determination of the intrinsic exciton-to-dopant energy transfer rate.

Hidayatova, Lamia [Univ. of Oklahoma, Norman, OK (↗

Nucleon-pair truncation of the shell model for medium-heavy nuclei

Background: Establishing computationally tractable models of atomic nuclei is a long-time goal of nuclear structure physics. A flexible framework which easily includes excited states and many-body correlations is the configuration-interaction shell model (SM), but the exponential growth of the basis means one needs an efficient truncation scheme, ideally one that includes both deformation and pairing correlations. Purpose: Here, we propose an efficient truncation scheme of the SM: starting from a pair condensate variationally defined by Hartree-Fock single-particle states and the particle-number conserved Bardeen-Cooper-Schrieffer (NBCS) approximation, we carry out projection of states with good angular momentum. Methods: After generating Hartree-Fock single-particle states with Kramers degeneracy in a SM space, we optimize the pair amplitudes in the NBCS by minimizing the energy, and then use linear algebra projection (LAP) of states with good angular momentum. Both NBCS and LAP are computationally fast. Results: Our calculations yield good agreement with full configuration-interaction SM calculations for low-lying states of transitional and rotational nuclei with axially symmetric and triaxial deformation in medium- and heavy-mass regions: 44,46,48 Ti, 48,50 Cr, 52 Fe, 60,62,64 Zn, 66,68 Ge, 68 Se, and 108,110 Xe. We predict low-lying states of 112–114 Ba and 116–120 Ce, nuclei difficult to reach by large-scale SM calculations. Conclusions: Both pair correlation and the configuration mixing between different intrinsic states play a key role in reproducing collectivity and shape coexistence, demonstrating the utility of this truncation scheme of the SM to study transitional and deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cellulose assembles into helical bundles of uniform handedness in cell walls with abnormal pectin composition

Plant cells and organs grow into a remarkable diversity of shapes, as directed by cell walls composed primarily of polysaccharides such as cellulose and multiple structurally distinct pectins. The properties of the cell wall that allow for precise control of morphogenesis are distinct from those of the individual polysaccharide components. For example, cellulose, the primary determinant of cell morphology, is a chiral macromolecule that can self-assemble in vitro into larger-scale structures of consistent chirality, and yet most plant cells do not display consistent chirality in their growth. One interesting exception is the Arabidopsis thaliana rhm1 mutant, which has decreased levels of the pectin rhamnogalacturonan-I and causes conical petal epidermal cells to grow with a left-handed helical twist. Here, we show that in rhm1 the cellulose is bundled into large macrofibrils, unlike the evenly distributed microfibrils of the wild type. This cellulose bundling becomes increasingly severe over time, consistent with cellulose being synthesized normally and then self-associating into macrofibrils. We also show that in the wild type, cellulose is oriented transversely, whereas in rhm1 mutants, the cellulose forms right-handed helices that can account for the helical morphology of the petal cells. Furthermore, our results indicate that when the composition of pectin is altered, cellulose can form cellular-scale chiral structures in vivo, analogous to the helicoids formed in vitro by cellulose nano-crystals. We propose that an important emergent property of the interplay between rhamnogalacturonan-I and cellulose is to permit the assembly of nonbundled cellulose structures, providing plants flexibility to orient cellulose and direct morphogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Nanofabrication and inspection of fuel capsules for inertial confinement fusion

3D nanofabrication via Two-Photon Polymerization (TPP) provides a unique capability of flexibly fabricating complex structures over 1D-3D dimensions and µm-cm scales with resolutions below 100 nm. In the past years, the Laser-Assisted Nano Engineering (LANE) Group at the University of Nebraska-Lincoln (UNL) has been working closely with the Laboratory of Laser Energetics (LLE) in developing practical TPP approaches to fabricating various target structures for Inertial Confinement Fusion (ICF). At the same time, fuel capsules for ICF experiments should be inspected for surface and wall-embedded defects. Plastics materials [e.g., for example polystyrene (PS)] are the common materials used to make fuel capsules. However, during their manufacturing, capsules usually contain defects (vacuoles) embedded inside the shell walls, which may distort the implosion processes and influence the ICF performance of the capsules. The size of vacuoles is usually in a range from 100 to 2000 nm. Coherent anti-Stokes Raman scattering (CARS) microscope offers the capabilities of inspecting and characterizing the capsule defects. Furthermore, cryo-CARS microscopy was developed to explore how fuel isotope distributed inside target when icing that could not be diagnosed before.

36 MATERIALS SCIENCE↗

Deep learning-based spatio-temporal estimate of greenhouse gas emissions using satellite data

Accurate estimation of greenhouse gases (GHGs) emissions is very important for developing mitigation strategies to climate change by controlling and reducing GHG emissions. This project aims to develop multiple deep learning approaches to estimate anthropogenic greenhouse gas emissions using multiple types of satellite data. NO2 concentration is chosen as an example of GHGs to evaluate the proposed approach. Two sentinel satellites (sentinel-2 and sentinel-5P) provide multiscale observations of GHGs from 10-60m resolution (sentinel-2) to ~kilometer scale resolution (sentinel-5P). Among multiple deep learning (DL) architectures evaluated, two best DL models demonstrate that key features of spatio-temporal satellite data and additional information (e.g., observation times and/or coordinates of ground stations) can be extracted using convolutional neural networks and feed forward neural networks, respectively. In particular, irregular time series data from different NO 2 observation stations limit the flexibility of long short-term memory architecture, requiring zero-padding to fill in missing data. However, deep neural operator (DNO) architecture can stack time-series data as input, providing the flexibility of input structure without zero-padding. As a result, the DNO outperformed other deep learning architectures to account for time-varying features. Overall, temporal patterns with smooth seasonal variations were predicted very well, while frequent fluctuation patterns were not predicted well. In addition, uncertainty quantification using conformal inference method is performed to account for prediction ranges. Overall, this research will lead to a new groundwork for estimating greenhouse gas concentrations using multiple satellite data to enhance our capability of tracking the cause of climate change and developing mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

Modeling Disorder in Pyrochlores and Other Anion-Deficient Fluorite Structural Derivative Oxides

Their very flexible chemistry gives oxide materials a richness in functionality and wide technological application. A specific group of oxides that have a structure related to fluorite but with less oxygen, termed anion-deficient fluorite structural derivatives and with pyrochlores being the most notable example, has been shown to exhibit a diversity of useful properties. For example, the possibility to undergo a transition from an ordered to disordered state allows these oxides to have high radiation tolerance. Atomistic-scale calculations in the form of molecular dynamics (MD) and density functional theory (DFT) have been extensively used to understand what drives this order/disorder transition. Here we give a brief overview of how atomistic-scale calculations are utilized in modeling disorder in pyrochlores and other anion-deficient fluorite structural derivatives. We discuss the modeling process from simple point defects to completely disordered structures, the dynamics during the disordering process, and the use of mathematical models to generate ordered solid-solution configurations. We also attempt to identify the challenges in modeling short range order and discuss future directions to more comprehensive models of the disordered structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complex and Unusual Excited-State Relaxation Dynamics of 9,9′-Bifluorenylidene Revealed by Comprehensive Time-Resolved Spectroscopy and MRSF-TDDFT Calculations

Design of novel photochemical molecular motors often requires molecular building blocks that exhibit rather unusual photoactivity, for which conventional analyses of spectroscopic data can lead to conflicting interpretations. We here systematically investigated the excited-state relaxation dynamics of one such molecule, 9,9′-bifluorenylidene (BF), through comprehensive and complementary integration of ultrafast transient absorption (TA) and femtosecond stimulated Raman (FSRS) spectroscopies and first-principles mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT). TA and FSRS identified two sequentially formed transients following photoexcitation. The decay kinetics of the two intermediates differ in response to excitation wavelengths and the viscosity/polarity of solvents. MRSF-TDDFT calculations reveal a direct, barrierless internal-conversion pathway from the bright Franck−Condon state to a dark S1 minimum, where the excited-state population is transiently trapped, accounting for the first transient species observed in spectroscopic experiments. Further tracking down along the PES with MRSF-TDDFT mapped out two nonradiative relaxation pathways via conical intersections that connect the dark S 1 state to three configurations in the ground-state manifolds, within which a ring structure with a C8−C8′ bond and the vibrationally excited ground-state BF were identified from spectroscopic and kinetic data. The complexity of relaxation kinetics was attributed to the flexible torsional and twisting motions about the C9−C9′ bridge bond enabled by the diradical character of the S 1 state. These findings clarify unusual photoactive relaxation dynamics stemming from a novel correlation between structural flexibility and shifting electronic characteristics, and they demonstrate the importance of integrating spectroscopic and advanced electronic structure calculation studies for judicious clarification of complex, competing relaxation pathways of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural determination of a full-length plant cellulose synthase informed by experimental and in silico methods

Three-dimensional structure determination and prediction of proteins with intrinsically disordered regions, unstructured regions, conformational flexibility, and lacking homologous structures are challenging. We previously predicted and refined an in silico structure of a plant cellulose synthase from cotton (GhCESA1), and more recently, cryo-electron microscopy (cryo-EM) has resolved a majority of the lengths of two CESA structures from poplar (PttCESA8) and cotton (GhCESA7). However, 26–30% of these cryo-EM structures remain unresolved, including the N-terminal domain, half of the class-specific region, the gating loop region, and the C-terminal domain. Here, we describe the generation and evaluation of a full-length hybrid GhCESA1 model based on this cryo-EM PttCESA8 structure, with unresolved regions completed using this in silico refined GhCESA1 model. All-atom molecular dynamics simulations and subsequent energy minimizations were performed for the in silico and hybrid GhCESA1 models in a lipid bilayer-water-ion environment, and structural stability, dynamics, energetics, contacts, and quality were evaluated. The unresolved regions were found to be the most dynamic, in agreement with their poor electron density with cryo-EM. The hybrid model exhibited a higher total secondary structure content, more favorable intra-protein and protein-lipid interaction energies, and improved quality metrics. Moreover, hydrogen bonding was revealed to be a primary mechanism for intra-protein and protein-lipid contacts. These results demonstrate that in silico structure prediction and refinement may be useful to augment experimental structure determination, especially for disordered and unstructured regions. Furthermore, this hybrid model can serve as a steppingstone to derive full-length homology models of other CESAs found in more experimentally tractable organisms.

59 BASIC BIOLOGICAL SCIENCES↗