Symmetry breaking and structural polymorphism in a bacterial microcompartment shell protein for chol
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Ochoa, Jessica M.↗
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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↗
RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D
Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.
59 BASIC BIOLOGICAL SCIENCES↗
PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions
Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.
59 BASIC BIOLOGICAL SCIENCES↗
Graph Identification of Proteins in Tomograms (GRIP-Tomo) 2.0: Topologically aware classification for proteins
Cryo-electron tomography (cryo-ET) enables structural characterization of biomolecules under near-native conditions. Existing approaches for interpreting the resulting three-dimensional volumes are computationally expensive and have difficulty interpreting density associated with small proteins/complexes. To explore alternate approaches for identifying proteins in cryo-ET data we pursued a Graph Network and topologically invariant approach. Here, we report on a fast algorithm that classifies particles by searching for nuances of evolutionarily conversed motifs and the geometrical characteristics of protein structure. GRIP-Tomo 2.0 is a machine-learning pipeline that extracts interpretable topological features of protein structures within noisy experimental backgrounds. Compared to version 1.0, the new pipeline includes three upgrades that significantly improve performance including synthetic tomogram generation simulating realistic noise, graph-based persistent feature extraction as protein fingerprints, and high-performance computing acceleration. GRIP-Tomo 2.0 achieves over 90% accuracy in classifying between proteins and noise using both real and synthetic datasets which represents a foundational step toward advancing cryo-ET workflows and empowering automated visual proteomics.
Li, Chengxuan↗
Synthesis, Crystal Structure, and Physical Properties of BaSnS 2
Phase-pure BaSnS 2 , with space group P2 1 /c, is synthesized, and the structural and physical properties are investigated. We report thermal properties and optical measurements are reported for the first time. The Debye temperature and Sommerfeld coefficient are obtained from temperature-dependent heat capacity measurements, the latter indicating that BaSnS 2 is an electrical insulator. A direct bandgap of 2.4 eV is obtained from diffuse reflectance and photoluminescence spectroscopy. The findings herein lay the foundation for understanding the physical properties of this material and are part of a continuing effort to investigate previously unexplored ternary chalcogenides.
semiconductors↗
What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create
A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics.
97 MATHEMATICS AND COMPUTING↗
Interplay of Bright Triplet and Dark Excitons Revealed by Magneto‐Photoluminescence of Individual PbS/CdS Quantum Dots
Abstract A low‐temperature polarization‐resolved magneto‐photoluminescence experiment is performed on individual PbS/CdS core/shell quantum dots (QDs). The experiment enables a direct measurement of the exciton Landé g factor and the anisotropic zero‐field splitting of the lowest emissive bright exciton triplet in PbS/CdS QDs. While anisotropic splittings of individual QDs distribute randomly in 104—325 μeV range, the exciton Landé g factors increase from 0.95 to 2.70 as the emission energy of the QD increases from 1.0 to 1.2 eV. The tight‐binding calculations allow to rationalize these trends as a direct consequence of reducing a cubic symmetry of QD via addition/removal of a few (<70) atoms from the surfaces of the PbS core. Furthermore, it is observed that while right ( σ + ) and left ( σ − ) circularly polarized photoluminescence (PL) peaks split linearly with magnetic field as expected for Zeeman effect, the energy splitting between X and Y linearly polarized PL peaks remains nearly unchanged. The theoretical study reveals rich and complex magnetic field‐induced interplay of bright triplet and dark exciton states explaining this puzzling behavior. These findings fill the missing gaps in the understanding of lead salt QDs and provide foundation for development of classical and quantum light sources operating at telecommunication wavelengths.
Kim, Younghee↗
Dispersed Nickel Phthalocyanine Molecules on Carbon Nanotubes as Cathode Catalysts for Li-CO 2 Batteries
The Li-CO 2 battery has great potential for both CO 2 utilization and energy storage, but its practical application is limited by low energy efficiency and short cycle life. Efficient cathode catalysts are needed to address this issue. Herein, this work reports on molecularly dispersed electrocatalysts (MDEs) of nickel phthalocyanine (NiPc) anchored on carbon nanotubes (CNTs) as the cathode catalyst for Li-CO 2 batteries. The dispersed NiPc molecules efficiently catalyze CO 2 reduction, while the conductive and porous CNTs networks facilitate CO 2 evolution reaction, leading to enhanced discharging and charging performance compared to the NiPc and CNTs mixture. Octa-cyano substitution on NiPc (NiPc-CN) further enhances the interaction between the molecule and CNTs, resulting in better cycling stability. The Li-CO 2 battery with the NiPc-CN MDE cathode shows a high discharge voltage of 2.72 V and a small discharging–charging potential gap of 1.4 V, and can work stably for over 120 cycles. The reversibility of the cathode is confirmed by experimental characterizations. Finally, this work lays a foundation for the development of molecular catalysts for Li-CO 2 battery cathodes.
25 ENERGY STORAGE↗
Dynamic Structural Change of Plant Epidermal Cell Walls under Strain
Abstract The molecular foundations of epidermal cell wall mechanics are critical for understanding structure–function relationships of primary cell walls in plants and facilitating the design of bioinspired materials. To uncover the molecular mechanisms regulating the high extensibility and strength of the cell wall, the onion epidermal wall is stretched uniaxially to various strains and cell wall structures from mesoscale to atomic scale are characterized. Upon longitudinal stretching to high strain, epidermal walls contract in the transverse direction, resulting in a reduced area. Atomic force microscopy shows that cellulose microfibrils exhibit orientation‐dependent rearrangements at high strains: longitudinal microfibrils are straightened out and become highly ordered, while transverse microfibrils curve and kink. Small‐angle X‐ray scattering detects a 7.4 nm spacing aligned along the stretch direction at high strain, which is attributed to distances between individual cellulose microfibrils. Furthermore, wide‐angle X‐ray scattering reveals a widening of (004) lattice spacing and contraction of (200) lattice spacing in longitudinally aligned cellulose microfibrils at high strain, which implies longitudinal stretching of the cellulose crystal. These findings provide molecular insights into the ability of the wall to bear additional load after yielding: the aggregation of longitudinal microfibrils impedes sliding and enables further stretching of the cellulose to bear increased loads.
59 BASIC BIOLOGICAL SCIENCES↗
Designing Advanced Electrolytes for High-Voltage High-Capacity Disordered Rocksalt Cathodes
Lithium (Li)-excess transition metal oxide materials which crystallize in the cation-disordered rock salt (DRX) structure are promising cathodes for realizing low-cost, high-energy-density Li batteries. However, the state-of-the-art electrolytes for Li-ion batteries cannot meet the high-voltage stability requirement for high-voltage DRX cathodes, thus new electrolytes are urgently demanded. It has been reported that the solvation structures and properties of the electrolytes critically influence the performance and stability of the batteries. In this study, the structure–property relationships of various electrolytes with different solvent-to-diluent ratios are systematically investigated through a combination of theoretical calculations and experimental tests and analyses. This approach guides the development of electrolytes with unique solvation structures and characteristics, exhibiting high voltage stability, and enhancing the formation of stable electrode/electrolyte interphases. These electrolytes enable the realization of Li||Li 1.094 Mn 0.676 Ti 0.228 O 2 (LMTO) DRX cells with improved performance compared to the conventional electrolyte. Specifically, Li||LMTO cells with the optimized advanced controlled-solvation electrolyte deliver higher specific capacity and longer cycle life compared to cells with the conventional electrolyte. Additionally, the investigation into the structure–property relationship provides a foundational basis for designing advanced electrolytes, which are crucial for the stable cycling of emerging high-voltage cathodes.
25 ENERGY STORAGE↗
Toward Standardized Microscale Tensile Testing for Two‐Photon Polymerization‐Fabricated Materials in Liquid
Two-photon polymerization (TPP) enables the fabrication of intricate 3D microstructures with submicron precision, offering significant potential in biomedical applications like tissue engineering. In such applications, to print materials and structures with defined mechanics, it is crucial to understand how TPP printing parameters impact the material properties in a physiologically relevant liquid environment. Herein, an experimental approach utilizing microscale tensile testing (μTT) for the systematic measurement of TPP-fabricated microfibers submerged in liquid as a function of printing parameters is introduced. Using a diurethane dimethacrylate-based resin, the influence of printing parameters on microfiber geometry is first explored, demonstrating cross-sectional areas ranging from 1 to 36 μm 2 . Tensile testing reveals Young's moduli between 0.5 and 1.5 GPa and yield strengths from 10 to 60 MPa. The experimental data show an excellent fit with the Ogden hyperelastic polymer model, which enables a detailed analysis of how variations in writing speed, laser power, and printing path influence the mechanical properties of TPP microfibers. The μTT method is also showcased for evaluating multiple commercial resins and for performing cyclic loading experiments. Collectively, this study builds a foundation toward a standardized microscale tensile testing framework to characterize the mechanical properties of TPP printed structures.
mechanical characterization↗
An Adsorptive Membrane Platform for Precision Ion Separation: Membrane Design and First‐Principles Studies
One of the key challenges in separation science is the lack of precise ion separation methods and mechanistic understanding crucial for efficiently recovering critical materials from complex aqueous matrices. Herein, first-principles electronic structure calculations and in situ Raman spectroscopy are studied to elucidate the factors governing ion discrimination in an adsorptive membrane specifically designed for transition metal ion separation. Density functional theory calculations and in situ Raman data jointly reveal the thermodynamically favorable binding preferences and detailed adsorption mechanisms for competing ions. How membrane binding preferences correlate with the electronic properties of ligands is explored, such as orbital hybridization and electron localization. The findings underscore the importance of the phenolate group in oxime ligands for achieving high selectivity among competing transition metal ions. In-depth understanding on which specific atomistic site within the microenvironment of metal-ligand binding pockets governs the ion discrimination behaviors of the host will build a solid foundation to guide the rational design of next-generation materials for precision separation essential for energy technologies and environment remediation. In tandem, synthetic controllability is demonstrated to transform 3D micrometer-scale crystals to a 2D crystalline selective layer in membranes, paving the way for more precise and sustainable advances in separation science.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Quantifying sensitivity in numerical weather prediction-modeled offshore wind speeds through an ensemble modeling approach
A decade of research has shown that numerical weather prediction (NWP)-modeled wind speeds can be highly sensitive to the inputs and setups within the NWP model. For wind resource characterization applications, this sensitivity is often addressed by constructing a range of setups and selecting the one that best validates against observations. However, this approach is not possible in areas that lack high-quality hub height observations, especially offshore wind areas. In such cases, techniques to quantify and disseminate confidence in NWP-modeled wind speeds in the absence of observations are needed. We address this need in the present study and propose best practices for quantifying the spread in NWP-modeled wind speeds. We implement an ensemble approach in which we consider 24 different setups to the Weather Research and Forecasting (WRF) model. We construct the ensemble by considering variations in WRF version, WRF namelist, atmospheric forcing, and sea surface temperature (SST) forcing. Our analysis finds that the standard deviation produces more consistent estimates compared to the interquartile range and tends to be the more conservative estimator for ensemble variability. We further find that model spread increases closer to the surface and on shorter time scales. In conclusion, we explore methods to attribute total ensemble variability to the different ensemble components (e.g., atmospheric forcing and SST product) and find that contributions by components also vary depending on time scale. We anticipate that the methods and results presented in this paper will provide a reasonable foundation for further research into ensemble-based wind resource data sets.
17 WIND ENERGY↗
OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design
Abstract This paper provides a summary of the work done within the OC6 Phase II project, which was focused on the implementation and verification of an advanced soil–structure interaction model for offshore wind system design and analysis. The soil–structure interaction model comes from the REDWIN project and uses an elastoplastic, macroelement model with kinematic hardening, which captures the stiffness and damping characteristics of offshore wind foundations more accurately than more traditional and simplified soil–structure interaction modeling approaches. Participants in the OC6 project integrated this macroelement capability to coupled aero‐hydro‐servo‐elastic offshore wind turbine modeling tools and verified the implementation by comparing simulation results across the modeling tools for an example monopile design. The simulation results were also compared to more traditional soil–structure interaction modeling approaches like apparent fixity, coupled springs, and distributed springs models. The macroelement approach resulted in smaller overall loading in the system due to both shifts in the system frequencies and increased energy dissipation. No validation work was performed, but the macroelement approach has shown increased accuracy within the REDWIN project, resulting in decreased uncertainty in the design. For the monopile design investigated here, that implies a less conservative and thus more cost‐effective offshore wind design.
17 WIND ENERGY↗
Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices
Abstract This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21 % . Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5 % . Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3 % without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.
17 WIND ENERGY↗
AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations
We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.
17 WIND ENERGY↗
Chapter 12: Gene Editing Technologies for Biofuel Production in Thermophilic Microbes
Thermophilic microbes are an attractive bioproduction platform due to their inherently lower contamination risk and their ability to perform thermostable enzymatic processes which may be required for biomass processing and other industrial applications. The engineering of microbes for industrial scale processes requires a suite of genetic engineering tools to optimize existing biological systems as well as to design and incorporate new metabolic pathways within strains. Yet, such tools are often lacking and/or inadequate for novel microbes, especially thermophiles. This chapter focuses on genetic tool development and engineering strategies, in addition to challenges, for thermophilic microbes. We provide detailed instructions and techniques for tool development for an anaerobic thermophile, Caldanaerobacter subterraneus subsp. tengcongensis, including culturing, plasmid construction, transformation, and selection. This establishes a foundation for advanced genetic tool development necessary for the metabolic engineering of this microbe and potentially other thermophilic organisms.
BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗