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At least 1,045 records · Page 58

Atomic-Scale Structural Mapping of Active Sites in Monolayer PGM-Free Catalysts by Low-Voltage 4D-STEM

Two-dimensional (2D) materials have attracted a large amount of attention in both basic and applied fields, and scanning transmission electron microscopy (STEM) is often uniquely well-suited for characterizing the atomic-scale structure of these materials [1-4]. As a result, STEM is poised to significantly impact progress on platinum group metal (PGM)-free catalysts, which are currently under intense development to enable low-cost, commercially viable hydrogen fuel cells [5]. While recent advancements have resulted in fuel cell performance comparable to Pt catalysts by some measures [6], cell durability remains a significant challenge, limiting practical applications [7]. Catalytically active sites in PGM-free materials are proposed to be FeN4 complexes embedded in a graphene lattice (Fig. 1b) within layered or other larger materials, but this is still under debate largely due to the range of potential actives sites predicted by computational methods and lack of methods for directly validating these models [5]. Fundamental insights into the atomic structure and resulting degradation pathways of proposed active sites are therefore needed to fully understand and control cell performance and durability [6].2D materials typically make ideal samples for STEM, but those within PGM-free catalysts present additional challenges since these materials are often defect-rich, with a high density of edges, dopant atoms, etc., which significantly increase susceptibility to beam damage at standard operating voltages. This makes analysis of potential FeN4 active sites particularly challenging, since a large proportion of Fe exists at edge sites where beam-induced atomic displacements can prohibit high-resolution structural characterization [6]. Conventional dark-field imaging compounds this problem by producing less signal for a given dose and being less sensitive to light elements than dose-efficient phase contrast imaging techniques such as those enabled by four-dimensional (4D)-STEM [8-10] (Fig. 1a). Consequently, active site structural analysis is often left to methods such as low-resolution imaging combined with quantum chemical calculations [6], which hinders accurate determination of reaction and degradation mechanisms.Here, we demonstrate direct atomic-scale structural mapping of FeN4 sites by performing low-voltage 4D-STEM on a model PGM-free catalyst system with many exposed monolayer regions. To accomplish this, we pair a 30 keV aberration-corrected probe with a fast pixelated detector that has optimal performance at low beam voltages [11]. This enables us to simultaneously image light and heavy elements with high signal-to-noise by center-of-mass analysis (Fig. 1c) while minimizing beam-induced atomic displacements at sensitive sites. The monolayer nature of these materials additionally allows for experimental validation by direct comparison with multislice simulations [12] of model structures (Fig. 1d-e). This work demonstrates how low-voltage 4D-STEM will provide new insights into the atomic-scale structure and degradation mechanisms of active sites in PGM-free catalysts, facilitating the development of low-cost hydrogen fuel cells and other energy conversion technologies in the future [13].

Zachman, Michael↗

Molecular basis for lipid recognition by the prostaglandin D 2 receptor CRTH2

Significance Many amphipathic lipids, including cannabinoids, lysophospholipids, prostanoids, and leukotrienes, bind to G protein–coupled receptors (GPCRs) through the lipid bilayer. How these lipid ligands get anchored to their receptors and enter ligand-binding pockets is largely elusive. Our results revealed a distinctive lipid recognition mechanism for the prostaglandin D 2 (PGD 2 ) receptor CRTH2 that is not shared by other prostanoid receptors. Based on the structural analysis, we propose two representative binding modes of lipids in GPCRs. We also identified critical structural motifs and conformational changes of CRTH2 for capturing lipids from the lipidic environment and lipid transition to the binding pocket, thereby offering unprecedented molecular insight into the dynamic lipid-binding processes for GPCRs.

59 BASIC BIOLOGICAL SCIENCES↗

Multiphysics Lattice Discrete Particle Modeling (M-LDPM) for the Simulation of Shale Fracture Permeability

A three-dimensional multiphysics lattice discrete particle model (M-LDPM) framework is formulated to investigate the fracture permeability behavior of shale. The framework features a dual lattice system mimicking the mesostructure of the material and simulates coupled mechanical and flow behavior. The mechanical lattice model simulates the granular internal structure of shale, and describes heterogeneous deformation by means of discrete compatibility and equilibrium equations. The network of flow lattice elements constitutes a dual graph of the mechanical lattice system. A discrete formulation of mass balance for the flow elements is presented to model fluid flow along cracks and intact materials. The overall computational framework is implemented with a mixed explicit–implicit integration scheme and a staggered coupling method that makes use of the dual lattice topology enabling the seamless two-way coupling of the mechanical and flow behaviors. The proposed model is used for the computational analysis of shale fracture permeability behavior by simulating triaxial direct shear tests on Marcellus shale specimens under various confining pressures. The simulated mechanical response is calibrated against the experimental data, and the predicted permeability values are also compared with the experimental measurements. Moreover, the paper presents the scaling analysis of both the mechanical response and permeability measurements based on simulations performed on geometrically similar specimens with increasing size. The simulated stress strain curves reflect a significant size effect in the post-peak due to the presence of localized fractures. The scaling analysis of permeability measurements enables prediction of permeability for large specimens by extrapolating the numerical results of small ones.

58 GEOSCIENCES↗

Understanding Processes Controlling the Temporal and Spatial Variations of PBL Structures Over the ARM SGP Site

The surface heat, moisture, and momentum fluxes are transferred to the atmosphere above through the planetary boundary layer (PBL), where vertical mixing due to turbulent eddies of different sizes plays critical roles. Therefore, reliably representing PBL processes in numerical models is critical for weather, climate, and air quality prediction. Currently, there are over ten PBL schemes that are selectable within the advanced research version of the Weather Research and Forecasting (WRF) model, indicative of the challenges in capturing the impacts of turbulence within the PBL in models. Further improvements in PBL parameterizations are needed for both weather and climate models, as emphasized in many recent national reports, but require an advanced understanding of the underlying boundary layer processes from observations. This project takes advantage of Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) investments in the atmospheric boundary layer observations and Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) simulations to characterize PBL structures, understand key physical processes controlling the mixed layer development, and to evaluate PBL parameterization.

54 ENVIRONMENTAL SCIENCES↗

Design of InGaN-ZnSnGa 2 N 4 quantum wells for high-efficiency amber light emitting diodes

A novel type-II InGaN-ZnSnGa 2 N 4 quantum well (QW) structure is proposed based on recent experimental achievements for the successful epitaxy of ZnSnN 2 -GaN alloys and the determination of their band offsets with GaN. The simulation results indicate that this structure is promising as the active region for high-efficiency InGaN-based amber (λ ~ 590 nm) light-emitting diodes (LEDs). The hole wavefunction in the valence band is better confined with the insertion of a monolayer scale of ZnSnGa 2 N 4 into the InGaN QW while the electron wavefunction in the conduction band is better confined with the incorporation of an AlGaN layer in the GaN quantum barrier. The band structure of the InGaN-ZnSnGa 2 N 4 QW is numerically simulated based on the experimentally measured band offsets between ZnSnGa 2 N 4 and GaN. With the InGaN-ZnSnGa 2 N 4 QW design, a low In content (20%) is required in the InGaN layer to reach a peak emission wavelength of ~590 nm, yet an In composition of 25% is needed to reach the same emission wavelength for a conventional InGaN QW with the same layer thicknesses. Moreover, the electron-hole wavefunction overlap (Гe1-hh1) for the InGaN-ZnSnGa 2 N 4 QW design reaches 18% for an emission wavelength at ~590 nm. This result is much improved over the conventional InGaN QW overlap of 5% emitting at the same wavelength. The increase in electron-hole wavefunction overlap results in an approximately 14 times enhancement in the predicted spontaneous emission radiative recombination rate of the InGaN-ZnSnGa 2 N 4 QW as compared to that of the conventional InGaN QW. This InGaN-ZnSnGa 2 N 4 QW structure design can be promising to pave a new way to achieve high efficiency amber LEDs.

42 ENGINEERING↗

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

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

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Molecular insights into the structure-property relationships of 3D printed polyamide reverse-osmosis membrane for desalination

3D-printing is an emerging method for manufacturing polyamide (PA) reserve osmosis (RO) membranes for water treatment and desalination, which can precisely control membrane structural properties, such as thickness, roughness, and resolution. However, the synthesis-structure (i.e., degree of cross-linking (DC), m-phenylenediamine/trimesoyl chloride (MPD/TMC) ratio, and membrane thickness) to property (permeability and water-salt selectivity) relationships for these membranes has not been well understood. At the same time, a microscopic understanding of the physical mechanism of water and salt transport is needed to guide the design of high-performance 3D-printed membranes and improve the printing efficiency. Furthermore, the atomic-scale transport features and energetics of water and salt ions are studied at high pressure for the 3D-printed PA RO membranes with the different DCs and MPD/TMC ratios through non-equilibrium molecular dynamics (NEMD) simulations. Factoring in membrane structure properties, rejection ratio of salt ions and pressure-dependent water flux, 3D-printed PA membranes having an MPD/TMC ratio of 3.0:2.0 and a DC between 80%~90% attains ideal performance: high water flux, high rejection of salt ions, and excellent structural integrity. Mechanistically, water permeability for highly cross-linked PA RO membranes depends on the temporary on-and-off channels that allow water molecules to jump from one cavity to another at high pressure. In addition, higher pressures cause rapid compaction of PA membranes’ free volume and membrane thickness. Membrane failure at high pressure is determined by the DC and MPD/TMC ratios-dependent compressive yield strength. In short, these findings provide physical insights for optimizing existing PA membranes and designing next-generation desalination membranes at the molecular level.

3D-printed PA RO membrane↗

Effects of Dissolution Regimes on Flow Channelization and Solute Transport in 3D Fracture Networks: Insights From Graph‐Based Reactive Transport Modeling

We investigate how mineral dissolution reshapes flow pathways and solute transport in three‐dimensional discrete fracture networks using a computationally efficient graph‐based reactive transport model. The DFNs are inspired by field‐site observations of fractured carbonate and represent realistic connectivity and structural heterogeneity. Flow is simulated with the Reynolds equation, and dissolution follows first‐order kinetics with diffusive limitations captured through an effective mass‐transfer coefficient. By systematically varying two key dimensionless parameters, the effective Damköhler number (Da), governing reaction versus advection rates, and a transport parameter (Da), analogous to the Thiele modulus, distinct flow channelization regimes emerge: mildly channelized at low G, highly channelized at intermediate Da, and extreme wormhole formation at high Da and low G. Eulerian and Lagrangian analyses, including breakthrough curves, particle tortuosity, dispersivity, and flow channeling indicators quantitatively characterize the progression of dissolution‐driven network restructuring. Across all regimes, initial fracture heterogeneity persists. The results underscore how the interplay between this initial structure, advection, reaction, and diffusion critically shapes subsurface flow pathways, with implications for applications ranging from groundwater remediation to enhanced geothermal systems.

54 ENVIRONMENTAL SCIENCES↗

Asymmetric Composition of Ionic Aggregates and the Origin of High Correlated Transference Number in Water-in-Salt Electrolytes

"Water-in-salt" electrolytes open up exciting new avenues for expanding the electrochemical window of aqueous electrolytes. We investigated the solvation structure and dynamics of highly concentrated lithium bis(trifluoromethane)sulfonimide aqueous electrolyte using experimentally corroborated molecular dynamics simulations. The simulations revealed that the heterogeneous structure of the electrolyte comprises percolating networks of ion and water domains/aggregates. Interestingly, the ionic regions are composed of more TFSI - ions than Li + ions. The Li + -ion transport mechanism was further explored. Li + ions can hop along the coordinated TFSI- ions in the ionic aggregates. The calculated correlated transference number of the 20 m electrolyte is similar to 0.32, which is reasonably high for the high concentration due to a weak negative correlation between the motion of cations and anions within the heterogeneous microscopic domains. These molecular dynamics results connect the heterogeneous structure of the electrolyte to the correlated dynamics of the Li + ion and provide a new understanding of the Li + -ion transport mechanism in this novel electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect‐Mediated Ordering of Condensed Water Structures in Microporous Zeolites

Abstract Ab‐initio molecular dynamics simulations and transmission infrared spectroscopy are employed to characterize the structure of water networks in defect‐functionalized microporous zeolites. Thermodynamically stable phases of clustered water molecules are localized at some of the defects in zeolite Beta, which include catalytic sites such as framework Lewis acidic Sn atoms in closed and hydrolyzed‐open forms, as well as silanol nests. These water clusters compete with ideal gas‐like structures at low water densities and pore‐filling phases at higher water densities, with the equilibrium phase determined by the water chemical potential. The physical characteristics of these phases are determined by the defect identity, with the local binding and orientation of hydroxyl moieties around the defects playing a central role. The results suggest general principles for how the structure of polar solvents in microporous solid acids is influenced by local defect functionalization, and the thermodynamic stability of the condensed phases surrounding such sites, in turn, implies that the catalysis of Lewis acids will be influenced by local water ordering.

Bukowski, Brandon C.↗

Defect‐Mediated Ordering of Condensed Water Structures in Microporous Zeolites

Abstract Ab‐initio molecular dynamics simulations and transmission infrared spectroscopy are employed to characterize the structure of water networks in defect‐functionalized microporous zeolites. Thermodynamically stable phases of clustered water molecules are localized at some of the defects in zeolite Beta, which include catalytic sites such as framework Lewis acidic Sn atoms in closed and hydrolyzed‐open forms, as well as silanol nests. These water clusters compete with ideal gas‐like structures at low water densities and pore‐filling phases at higher water densities, with the equilibrium phase determined by the water chemical potential. The physical characteristics of these phases are determined by the defect identity, with the local binding and orientation of hydroxyl moieties around the defects playing a central role. The results suggest general principles for how the structure of polar solvents in microporous solid acids is influenced by local defect functionalization, and the thermodynamic stability of the condensed phases surrounding such sites, in turn, implies that the catalysis of Lewis acids will be influenced by local water ordering.

Bukowski, Brandon C.↗

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. Here, we also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

36 MATERIALS SCIENCE↗

Advanced Structured Adsorbent Architectures for Transformative Carbon Dioxide Capture Performance (Final Report)

Svante is a world leader at using solid sorbents for low-cost Carbon Dioxide (CO 2 ) capture, a technology which is recognized as critical in meeting the dual mandates of energy security/reliability and the mitigation of man-made CO 2 emissions. Svante has been developing proprietary adsorbent material compositions, forming them into structured laminates, developing and optimizing process cycles, and system design for efficient capture of CO 2 from post-combustion flue gases of thermal power plants and industrial facilities. The deployment of first-generation CO 2 capture technology has been significantly hampered by high costs and energy penalties, among other barriers. Second generation CO 2 capture technologies (including the Mark I variant of Svante’s Veloxotherm™ adsorption-based technology), utilizing single adsorbent architecture, show promise for reducing the barriers to deploying CO 2 capture plants in commercially meaningful numbers. The objective of this project was to evaluate the Recipient’s transformational (Mark-II) VeloxoTherm™ Technology via the development and bench-scale testing of an advanced structured adsorbent, including novel Bi-layer, laminated adsorbent structures and segmented beds. Svante selected, synthesized, and characterized tailored solid adsorbents for computational modeling, advanced structured adsorbent development, process simulations, and dynamic bench scale (~1-10 kg/day CO 2 captured) testing using an existing single-bed VeloxoTherm™ Station (VTS) coupled with a natural gas-fired boiler. Segmented beds used the in-house, multi-bed Process Demonstration Unit (PDU) to demonstrate key performance indicators (KPIs), such as recovery, product purity, regeneration energy, and the integrated system's productivity in lifetime analysis. Segmented beds were used at a 1 tonne per day (TPD) unit at an industrial site to provide bench-scale validation of performance in an industrial setting. Svante was developing and optimizing the post-combustion CO 2 adsorption technology architectures, including the Bi-layer and segmented laminated adsorbent structure design, integrated rapid cycle temperature swing adsorption (RC-TSA) cycle, flow path architecture, and adsorbent bed construction and packaging (including gas porting) to progress towards achievement of DOE’s Transformational CO 2 Capture goals of 95% CO 2 purity and a cost of electricity at least 30% lower than a supercritical Pulverized Coal (PC) power plant with CO 2 capture, or approximately $30 per tonne of CO 2 captured ready for demonstration by 2030. The main requirements to reach the DOE target cost of carbon capture below $30/MT using Rapid-Cycling Temperature Swing Adsorption (RC-TSA) are as follows: (1) Increased capacity at different CO 2 concentrations, (2) Increased sorbents cycle life, (3) Increased O 2 resistance, and (4) Decreased steam requirement to extract 1 kg of CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms-a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Half-Metallic and Half-Semiconductor Gaps in Cr-Based Chalcogenides: DFT + U Calculations

Using full-potential linear-augmented plane waves plus local orbitals (FP-LAPW) method, within the generalized gradient approximation (GGA) and GGA + U (Hubbard Coulomb onsite correction) as well as the modified Becke-Johnson approach (mBJ-GGA and mBJ-GGA + U), we have carried out a systematic investigation of the structural, electronic, and magnetic properties of CrS, CrSe, and CrTe compounds in two competing phases: the zinc-blende (ZB) and wurtzite (WZ) structures. We obtained half-metallic (HM) gaps of 1.35 (2.32), 1.65 (2.49), and 1.52 (1.80) for the CrS, CrSe, and CrTe compounds, respectively, in the ZB phase within the GGA + U (mBJ-GGA + U) approach. The HM gaps are 1.78, 2.11, and 1.53 for CrS, CrSe, and CrTe compounds, respectively, in the WZ phase using the GGA + U. Notably, the CrSe and CrTe using the mBJ-GGA + U approach are a half-semiconductor (HSC) in the WZ phase. The HSC gaps are 0.94 and 0.25 eV for CrSe and CrTe compounds, respectively, while CrS has a HM gap of 2.30 eV. We observed a HSC-to-HM transition for the CrSe and CrTe crystal structures on application of strain. The CrS, CrSe, and CrTe compounds have a total magnetic moment of 4.0 µ{sub B} per formula unit with the magnetization predominantly from the Cr ion. The main features observed from the density of states and strain evolution should motivate further experimental exploration on the possible application of the CrS, CrSe, and CrTe compounds for spintronic applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Propagation of Degradation-Induced Defects in Zeolitic Imidazolate Frameworks

Isolated defects induced by water and acid gases have been extensively characterized in ZIF-8, a prototypical metal–organic framework material, yet there is little understanding regarding how these single bond-breaking events lead to the structural amorphization observed after prolonged experimental exposure in acidic environments. We use density functional theory calculations to provide the first analysis of defect propagation in a zeolitic imidazolate framework (ZIF) material. Given a single bond-breaking event (the first step in the formation of any defect state), we exhaustively explore the energetics of subsequent defect states and find strong preference for additional bond-breaking located adjacent to the previous defect in both two-defect and three-defect systems. This series of favorable reaction energies is more exothermic when we replace water with sulfuric acid as a protonating agent, in agreement with experimental observations that ZIF-8 degradation is accelerated in humid acid gas environments. To offer initial insights into experimental signatures of defect propagation, we compare the simulated powder pattern in structures at varying levels of defect concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulating a Mesoscale Convective System Using WRF with a New Spectral Bin Microphysics: Part 1: Hail vs Graupel

A modified Fast Spectral Bin Microphysics scheme (FSBM-2) embedded into the Weather Research and Forecasting Model (WRF) is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM-2 uses modified source codes as compared to the current FSBM (FSBM-1). In contrast to FSBM-1, FSBM-2 can simulate hail of several cm in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall-line structures both in the convective and stratiform regions. In contrast, if graupel particles are used to represent high-density hydrometeors in convective areas, the ratio of convective-to-stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM-2 show a good agreement with observations. The regeneration of CCN by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8-9 km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification. Key words: Mesoscale convective systems (MCS), squall lines, spectral bin microphysics, large hail, in-cloud nucleation, size distributions of hydrometeors in MCS.

Shpund, Kobby↗

Molecular mechanism of biased signaling at the kappa opioid receptor

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

59 BASIC BIOLOGICAL SCIENCES↗