Structure Determination Research Articles

Structural determination, energy transfer and color-tunable photoluminescence of stable LiYSiO4: Ce/Tb/Sm Phosphors toward nUV pumped wLEDs application

Study on photon emission of Ce3+-doped phosphors is essential for advanced optoelectronic application. However, it remains quite difficult to design near-ultraviolet excitable Ce3+-activated silicate blue/cyan-emitting phosphors because of the combined influence of iconicity of Ce3+, crystal field strength, and nephelauxetic effect. Herein, Ce3+ incorporated into a proper host LiYSiO4 (LYS) phosphor is mechanistically investigated and shown efficient blue/cyan photoluminescence (PL) owing to Ce3+ 5d1 electronic state experiencing appropriate crystal field splitting. The comprehensive analysis based on structural refinement, dynamic/static spectra, and density functional theory calculations indicates that Ce3+ ions are energetically favored in octahedral Y site as compared with Li site in the host, resulting in attractive PL properties. According to the principle of color superposition and via cascading energy transfer (ET) from Ce3+ → Tb3+ → Sm3+, systematic PL tuning in a large color gamut is realized by further codoping with the green- and red-emissions of Tb3+ and Sm3+ in the phosphor LYS: Ce3+/Tb3+/Sm3+. The direct ET from Ce3+ → Sm3+ is difficult to occur due to the metal-metal charge transfer effect. Of note, the PL thermal-quenching of Ce3+ is mainly associated with multiphonon relaxation, while the quenching of Tb3+/ Sm3+ is primarily due to the cross relaxation (CR) process via dipole-dipole (d-d) interaction. The appropriate distance between the two nearest adjacent Y sites in the host together with the ET are conducive to weaken the CR process of Tb3+/Sm3+, leading to high PL efficiency. Finally, a prototype pc-wLED assembled via a remote ‘capping’ packaging strategy and by using only the stably composition-optimized white-emitting LYS: Ce3+/Tb3+/Sm3+ demonstrates that the phosphor is promising for high-quality of light.

Neural net analysis of NMR spectra from strongly-coupled spin systems

Extracting parameters such as chemical shifts and coupling constants from proton NMR spectra is often a first step in using spectra for compound identification and structure determination. This can become challenging when scalar couplings between protons are comparable in size to chemical shift differences (strongly coupled), as is often the case with low-field (bench top) spectrometers. Here we explore the potential utility of AI methods, in particular neural networks, for extracting parameters from low-field spectra. Rather than seeking large experimental sets of spectra for training a network, we chose quantum mechanical simulation of sets, something that is possible with modern software packages and computer resources. We show that application of a network trained on 2-D J-resolved spectra and applied to a spectrum of iduronic acid, shows some promise, but also meets with some obstacles. We suggest that these may be overcome with improved pulse sequences and more extensive simulations.

Self-Consistent Determination of Single-Impurity Anderson Model Using Hybrid Quantum-Classical Approach on a Spin Quantum Simulator.

The accurate determination of the electronic structure of strongly correlated materials using first principle methods is of paramount importance in condensed matter physics, computational chemistry, and material science. However, due to the exponential scaling of computational resources, incorporating such materials into classical computation frameworks becomes prohibitively expensive. In 2016, Bauer etal. proposed a hybrid quantum-classical approach to correlated materials [B. Bauer et al., Hybrid quantum-classical approach to correlated materials, Phys. Rev. X 6, 031045 (2016).PRXHAE2160-330810.1103/PhysRevX.6.031045] that can efficiently tackle the electronic structure of complex correlated materials. Here, we experimentally demonstrate that approach to tackle the computational challenges associated with strongly correlated materials. By seamlessly integrating quantum computation into classical computers, we address the most computationally demanding aspect of the calculation, namely the computation of the Green's function, using a spin quantum processor. Furthermore, we realize a self-consistent determination of the single impurity Anderson model through a feedback loop between quantum and classical computations. A quantum phase transition in the Hubbard model from the metallic phase to the Mott insulator is observed as the strength of electron correlation increases. As the number of qubits with high control fidelity continues to grow, our experimental findings pave the way for solving even more complex models, such as strongly correlated crystalline materials or intricate molecules.

Advances and Challenges in Scoring Functions for RNA–Protein Complex Structure Prediction

RNA–protein complexes play a crucial role in cellular functions, providing insights into cellular mechanisms and potential therapeutic targets. However, experimental determination of these complex structures is often time-consuming and resource-intensive, and it rarely yields high-resolution data. Many computational approaches have been developed to predict RNA–protein complex structures in recent years. Despite these advances, achieving accurate and high-resolution predictions remains a formidable challenge, primarily due to the limitations inherent in current RNA–protein scoring functions. These scoring functions are critical tools for evaluating and interpreting RNA–protein interactions. This review comprehensively explores the latest advancements in scoring functions for RNA–protein docking, delving into the fundamental principles underlying various approaches, including coarse-grained knowledge-based, all-atom knowledge-based, and machine-learning-based methods. We critically evaluate the strengths and limitations of existing scoring functions, providing a detailed performance assessment. Considering the significant progress demonstrated by machine learning techniques, we discuss emerging trends and propose future research directions to enhance the accuracy and efficiency of scoring functions in RNA–protein complex prediction. We aim to inspire the development of more sophisticated and reliable computational tools in this rapidly evolving field.

Rapid design method for composite emergency steel piers with thin-walled steel tube framework and discussion on "temporary-permanent" transition

To address the conflict between the reserve of repair materials for existing bridge piers and the demands for emergency repairs, as well as the challenge of converting temporary emergency structures into permanent ones without significant disassembly, a novel composite emergency steel pier has been developed. This pier utilizes commonly available thin-walled steel tube sections as the framework, I-beams as the connecting elements, and incorporates a "temporary-permanent" transition function. Taking the emergency steel pier for medium-height bridge piers in high-speed rail systems as an example, this study introduces three evaluation metrics—security coefficient (n), stability coefficient k), and variation coefficient (V)—analyzing the factors influencing the design and application thresholds of the emergency steel piers from perspectives of strength, stability, and load distribution uniformity. Based on this, a rapid design method for composite emergency steel piers with thin-walled steel tube frameworks that does not require numerical simulation has been developed and experimentally validated. Research findings indicate that when used for the emergency repair of medium-height or lower bridge piers in high-speed railways, the column line stiffness of the thin-walled steel tube framework composite emergency steel piers should range between 0.34 × 10 exp7 kN/mm to 4.15 × 10 exp7 kN/mm. The transverse and longitudinal spacing of the columns should be 1 m to 3 m and 1.5 m to 3 m respectively. The line stiffness of the plinth beams I and II should be greater than 0.69 kN/mm and 1.01 kN/mm respectively. Within these parameter ranges, the emergency steel pier will not experience strength failure or instability, and the load distribution among the columns remains uniformly favorable. In applications to other scenarios, the rapid generation of composite emergency steel piers with thin-walled steel tube frameworks can be achieved by following three steps: parameter selection and structural configuration determination, calculation of the pier-beam linear stiffness ratio, and criterion-based result verification. The rapid design and implementation of composite emergency steel piers help alleviate the contradiction between material stockpiling and repair demands. Furthermore, the pre-designed "temporary-permanent" transition functionality facilitates integrated operations for emergency repairs and permanent restorations.

Native mass spectrometry prescreening of G protein-coupled receptor complexes for cryo-EM structure determination.

G protein-coupled receptors (GPCRs) are essential transmembrane proteins playing key roles in human health and disease. Understanding their atomic-level molecular structure and conformational states is imperative for advancing drug development. Recent breakthroughs in single-particle cryogenic electron microscopy (cryo-EM) have propelled the structural biology of GPCRs into a new era. Nevertheless, the preparation of suitable GPCR samples and their complexes for cryo-EM analysis remains challenging due to their poor stability and highly dynamic nature. Here, we present our online buffer exchange-native MS method combined with Direct Mass Technology (OBE-nMS+DMT) which facilitates high-throughput analysis and guides sample preparation. We applied this method to optimize the GPR119-Gs complex sample prior to cryo-EM analysis, leading to a 3.51Å resolution structure from only 396 movies collected on a 200kV Glacios. This study suggests that the OBE-nMS+DMT method emerges as a powerful tool for prescreening sample conditions in cryo-EM studies of GPCRs and other membrane protein complexes.

Potent and broad HIV-1 neutralization in fusion peptide-primed SHIV-infected macaques.

An antibody-based HIV-1 vaccine will require the induction of potent cross-reactive HIV-1-neutralizing responses. To demonstrate feasibility toward this goal, we combined vaccination targeting the fusion-peptide site of vulnerability with infection by simian-human immunodeficiency virus (SHIV). In four macaques with vaccine-induced neutralizing responses, SHIV infection boosted plasma neutralization to 45%-77% breadth (geometric mean 50% inhibitory dilution [ID50] ∼100) on a 208-strain panel. Molecular dissection of these responses by antibody isolation and cryo-electron microscopy (cryo-EM) structure determination revealed 15 of 16 antibody lineages with cross-clade neutralization to be directed toward the fusion-peptide site of vulnerability. In each macaque, isolated antibodies from memory B cells recapitulated the plasma-neutralizing response, with fusion-peptide-binding antibodies reaching breadths of 40%-60% (50% inhibitory concentration [IC50]<50μg/mL) and total lineage-concentrations estimates of 50-200μg/mL. Longitudinal mapping indicated that these responses arose prior to SHIV infection. Collectively, these results provide invivo molecular examples for one to a few B cell lineages affording potent, broadly neutralizing plasma responses.

Synthesis, Characterization, Crystal structure determination and DFT study of a six coordinated Cu (II) complex of a phosphorous based tris-(2-pyridinylamino) phosphene sulphide ligand and its acid catalysed hydrolysis

One mono nuclear copper(II) complex (Cu-TPPS-OOCCH3 with structural formula C17H19CuN6O3PS) is synthesized using a novel tripodal tetradentate ligand, tris-(2-pyridinylamino)phosphene sulphide (TPPS), which has three pyridinylamino groups attached to a phosphorus atom connected to a sulphur atom (PS). The equatorial positions of the complex are occupied by three amino N-atoms of three aminopyridyl groups and one O-atom of the acetate group. The apical position is occupied by other O-atom of acetate group and one secondary N-atom of the tripodal ligand. The complex has been synthesized and purified as green solid and characterized by various spectroscopic techniques and the structure has been determined by X-ray single crystal diffraction study. The geometry optimizations and calculations of energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of the compounds are performed by using the hybrid B3LYP density functional theory (DFT) along with the def2TZVP basis set.

Structure determination of as-made zeolite ITQ-52 by three-dimensional electron diffraction

The complete crystal structures of two as-made zeolites with the ITQ-52 structure (IFW framework type), where an alkylphosphonium and an aminophosphonium dications have been used as their respective organic structure-directing agents, have been solved by three-dimensional electron diffraction. Both organic cations have also been located within the 10-ring that connects the cavities of the IFW framework using the diffraction data

Structural determination of a carbocation-derived rearrangement product observed during Thiele cage opening: insight into the mechanism of an alkyl-extended pinacol reaction

A substituted bishomocubane structure colloquially known as a Thiele cage was previously observed to undergo an alkyl-extended pinacol-type rearrangement, wherein 1,2-aryl migration and ketone formation occurred together with (or at least in close succession to) opening of a strained cyclobutane bond. While there was some indication that the rearrangement reaction might proceed via a stepwise process involving a sequence of carbocation intermediates, previous studies did not uncover any direct evidence for the formation of carbocations, and did not fully explain the regio- and stereospecificity of the reaction. Here we describe the isolation and detailed characterization of a second rearrangement product formed under the pinacol reaction conditions, the existence of which implicates the formation of discrete carbocation intermediates along the reaction pathway. Observation of this new product also finally explains the fate of any Thiele cage material that is converted to a carbocation, but which is not geometrically predisposed to react through a facile 1,2-aryl migration. As such, our findings resolve previous questions surrounding the origin of regio- and stereospecificity in the alkyl-extended pinacol rearrangement.

DREAMweb: An online tool for graph-based modeling of NMR protein structure.

The value of accurate protein structural models closely conforming to the experimental data is indisputable. DREAMweb deploys an improved DREAM algorithm, DREAMv2, that incorporates a tighter bound in the constraint set of the underlying optimization approach. This reduces the artifacts while modeling the protein structure by solving the distance-geometry problem. DREAMv2 follows a bottom-up strategy of building smaller substructures for regions with a larger concentration of experimental bounds and consolidating them before modeling the rest of the protein structure. This improves secondary structure conformance in the final models consistent with experimental data. The proposed method efficiently models regions with sparse coverage of experimental data by reducing the possibility of artifacts compared to DREAM. To balance performance and accuracy, smaller substructures ( atoms) are solved in this regime, allowing faster builds for the other parts under relaxed conditions. DREAMweb is accessible as an internet resource. The improvements in results are showcased through benchmarks on 10 structures. DREAMv2 can be used in tandem with any NMR-based protein structure determination workflow, including an iterative framework where the NMR assignment for the NOESY spectra is incomplete or ambiguous. DREAMweb is freely available for public use at http://pallab.cds.iisc.ac.in/DREAM/ and downloadable at https://github.com/niladriranjandas/DREAMv2.git.

Understanding Barriers to STEM: Teachers' Insights on African American Underrepresentation

This study focuses on the development of a measurement instrument to identify Middle and High School mathematics and science teachers’ beliefs about the main factors of underrepresentation of African American students in STEM (Science, Technology, Engineering, and Mathematics) fields. The research method using the stages of instrument development were (1) test design which involved construction of initial item pool by conducting extensive review of literature and coding of participating teachers personal statements (2) determination of validity which involved expert review process to confirm construct and face validity of items, (3) pilot testing which involved collecting data from a second set of participants, (4) determination of reliability which involves conducting a reliability analysis based on data collected from pilot testing and (5) determination of factorial structure which involved Exploratory Factor Analysis (EFA) to identify underlying factors in participating teachers’ belief structures. First, to obtain trustworthy information, voluntary middle and high school mathematics and science teachers were asked to write personal statements where they explain their main reasons for choosing teaching as a career. Secondly, qualitative data obtained from participating teachers’ personal statements were coded. Coding was applied to identify and to group the phrases or sentences that convey the same or similar reasons. Then results from an extensive literature review on this topic were blended in teachers’ common expressions which were determined because of coding procedure. Then 8 content experts assessed content validity and face validity. Finally, the survey was piloted to African American middle and high school mathematics and science teachers. Fifty-three (53) surveys were completed and received back from teachers. Then, exploratory factor analysis was conducted to identify any underlying factors in the scale. Reliability analyses were also conducted for both the entire survey and for each of the factors. Results of the study suggested four underlying components: (1) Access and Resources, (2) Role Models and Representation, (3) Bias and Discrimination, (4) Curriculum and Pedagogy.

Homonuclear Super-Resolution NMR Spectroscopy.

Homonuclear 1H NMR (nuclear magnetic resonance) spectra such as the [1H,1H]-NOESY (Nuclear Overhauser Enhancement spectroscopy) are essential for biomolecular structural biology. However, the spectrum contains hundreds to thousands of cross peaks meaning that within approximately 100 ppm2 there is significant signal overlap. Spectral resolution is thus a limiting factor for data interpretation for dynamics and structure elucidation. Acquiring the spectra at higher magnetic fields such as at a 1.2 GHz 1H frequency helps to reduce spectral crowding, since resolution scales proportionally to the magnetic field strength. Here, we show that the linewidths' of cross peaks in [1H,1H]-NOESY and [1H,1H]-TOCSY spectra can be further reduced by a factor of 2-3 in each dimension by super-resolution spectroscopy. In the indirect dimension a composite exponential-cosine weighted number of scans along the time increments are recorded and digitally smoothened by a window function. Furthermore, measurement time saving by reduced-acquisition super-resolution (RASR) is introduced. Application to the 20 kDa protein KRAS shows that highly resolved NMR spectra suitable for automated analysis can be acquired within less than 3 hours. The method opens an avenue towards automated chemical shift assignment, dynamics and structure determination of unlabeled small and medium size proteins within 24 hours.

Influence of the extraction method on functional properties of commercial snail secretion filtrates

Snail secretion is a complex mixture of several components, including proteins, glycoproteins, mucopolysaccharides and smaller molecules. Its growing use in nutraceutical, cosmetic and biomedical applications, as well as a component of edible and green packaging to replace chemical plasticizer, implies more affordable and sustainable extraction methods. We chose four extracts obtained from Cornu aspersum snails, different by origin, extraction medium (namely, citric acid, lactic acid or none) and additives and we performed a series of characterizations including the SDS-page, the measure of pH and density, the evaluation of dry matter and of protein content, supported by structural determinations by means of UV-visible and infrared spectroscopy, X-Rays diffraction and thermogravimetric measurements. Biological assays comprising evaluation of cytotoxicity and antibacterial activity were also carried out. All the tests were performed both on the as received snail filtrates and on the samples after proper dialysis to remove preservatives added by manufacturers. The obtained results put into evidence that the properties and composition of the final extract are strongly influenced by the collection method, that can be relevant for the proper use of snail filtrate in specific applications.

Colorimetric Detection of Aqueous N-Nitrosodimethylamine via Photonitrosation of a Naphtholsulfonate Indicator.

N-Nitrosamines are contaminants found throughout the environment, including in drinking water, and many nitrosamines are likely potent carcinogens. Correspondingly, there is a need for rapid and cost-effective in-field detection methods that can provide timely information about their contamination levels in water. This study details a colorimetric assay for detecting aqueous N-nitrosodimethylamine (NDMA) by photochemical nitrosation of a commercial naphtholsulfonate, to offer an attractive alternative to traditional laboratory-based analysis. The resulting naphthoquinone-oxime coordinates to aqueous iron(II) ions to form a green complex, allowing for direct visual detection. Characterization via Mössbauer and electron paramagnetic resonance (EPR) spectroscopy, alongside single-crystal structure determination, provides comprehensive structure information on the iron indicator complex. Optimization of detection conditions, including UV irradiation and response times, led to an improved colorimetric detection method with a limit of detection of 0.66 ppm for NDMA. The practical applicability and selectivity of this colorimetric detection scheme make it a promising candidate for the development of field-deployable sensors for NDMA in environmental water samples.

Bioinformatic study of keratinases from the S01 family from Streptomyces microflavus strain Dsm 40593

Aim. Determination and study of the primary structures and domain organization of keratinase precursors (serine proteases from the S01 family) of S. microflavus DSM 40593 using bioinformatic methods. Methods. In the research information presented in databases on the NCBI server was analyzed. Computerized sequence analysis was performed using the BLAST program on the NCBI server. Results. BLAST analysis of the genome sequence of the strain S. microflavus DSM 40593 was carried out using the sequence of the precursor AGK81825 as a query. Thanks to bioinformative analysis, seven genes encoding precursors of serine proteases from the S01 family were found in the genome of the strain S. microflavus DSM 40593. Conclusions. In the genomes of streptomycetes, there may be more than one gene encoding precursors of keratinases from the S01 family. It was established that the amino acid sequences of the enzymatic domains of keratinase precursors from the S01 family are characterized by higher similarity indices than the sequences of foldase domains.

Improved GAN-based deep learning approach for strain field prediction and failure analysis of precast bridge slab joints

Nonlinear finite element analysis (FEA) is crucial for understanding complex stress-strain behaviors and assessing potential structural failure risks. Building on the recent success of deep learning (DL) methods in physical field predictions, there has been growing interest in forecasting internal force fields of structures beyond the existing data scope. In this study, a data-driven strain field analysis model based on an improved Generative Adversarial Network (GAN) is proposed. To enrich the input data, this novel approach incorporates the Signed Distance Field (SDF) derived from the characteristics of the original Finite Element (FE) models. The generator, based on U-Net, is enhanced with channel attention mechanisms and loss penalty terms, forming the core of the improved GAN. The effectiveness of the proposed method is demonstrated using two parallel datasets comprising 3-Headed bar tension models across two planes. Subsequently, the generated strain field is subjected to feature extraction using the 2D-Principal Component Analysis (2D-PCA) method, followed by structural failure determination through the K-Nearest Neighbor (KNN) algorithm. The results indicate that the proposed improved approach achieves a significant reduction in Root Mean Square Error (RMSE) of 20.71 % and 13.21 % across the two datasets, with the structural failure determination method reaching an F1-score of 0.971. Thus, the intelligent strain field analysis method introduced here effectively predicts strain distributions and promptly identifies failure states, offering valuable insights for further numerical analysis and structural design.

Analysis of pulsed direct current reactive magnetron sputtering on a silicon target

Reactive sputtering is a very useful technique, particularly, for producing inhomogeneous interference filters, where the refractive index changes smoothly during deposition. In such a context, precise control of deposition parameters is crucial for replicating the desired optical properties. This study employed a pulsed DC power source to investigate the influence of a duty cycle on target poisoning, sputtering plasma characteristics, electric signals, and optical and morphological properties of synthesized films. Reactive pulsed DC magnetron sputtering was characterized by analyzing the behavior of plasma emission via optical emission spectroscopy and voltage-current signals, while modulating parameters such as the oxygen content within the vacuum chamber. A set of thin films was coated on glass substrates under different system conditions. These films underwent characterization employing spectroscopic ellipsometry to ascertain their optical constants, atomic force microscopy for surface morphology analysis, and x-ray diffraction for the determination of crystalline structures. The results indicate that longer duty cycles required higher oxygen levels to poison the target. Additionally, a detailed analysis of electrical signals revealed nonsquare waveforms, whose characteristics were influenced by both the duty cycle and the oxygen content within the sputtering chamber, resulting in higher effective voltages during the on-time of the voltage pulse. Grown films via reactive pulsed DC magnetron sputtering were also compared to films grown via conventional DC magnetron sputtering at equivalent conditions of target poisoning.

Extracting the partonic structure of colorless exchanges at the Electron Ion Collider

We investigate the determination of the partonic structure of colorless exchanges in deep inelastic diffractive ep scattering at the Electron Ion Collider (EIC), using the standard decomposition into Pomeron and Reggeon contributions. We perform fits to simulated diffractive cross section pseudodata in four variables, including the momentum transfer t, to estimate the achievable precision on the Pomeron and Reggeon quark and gluon distributions. We analyze the influence of different cuts in the kinematic variables, beam energy configurations, and luminosities, including a “first year” scenario. We conclude that the EIC will be able to constrain the partonic structure of the subleading Reggeon exchange with a precision comparable to that of the leading Pomeron exchange. Published by the American Physical Society 2024

Kinetic and catalytic mechanism of the methionine-derived glucosinolate biosynthesis enzyme methylthioalkylmalate synthase

In Brassica plants, methionine-derived aliphatic glucosinolates are chemically diverse natural products that serve as plant defense compounds, as well as molecules with dietary health-promoting effects. During their biosynthesis, methylthioalkylmalate synthase (MAMS) catalyzes the elongation reaction of the aliphatic chain. The MAMS catalyzed condensation of 4-methylthio-2-oxobutanoic acid (4-MTOB) and acetyl-CoA generates a 2-malate derivative that either enters the pathway for synthesis of C3-glucosinolates or undergoes additional extension reactions, which lead to C4- to C9-glucosinolates. Recent determination of the x-ray crystal structure of MAMS from Brassica juncea (Indian mustard) provided insight on the molecular evolution of MAMS, especially substrate specificity changes, from the leucine biosynthesis enzyme α-isopropylmalate synthase (IPMS) but left details of the reaction mechanism unanswered. Here we use the B. juncea MAMS2A (BjMAMS2A) isoform to analyze the kinetic and catalytic mechanism of this enzyme. Initial velocity studies indicate that MAMS follows an ordered bi bi kinetic mechanism, which based on the x-ray crystal structure, involves binding of 4-MTOB followed by acetyl-CoA. Examination of the pH-dependence of kcat and kcat/Km are consistent with acid/base catalysis. Site-directed mutagenesis of three residues originally proposed to function in the reaction mechanism - Arg89 (R89A, R89K, R89Q), Glu227 (E227A, E227D, E227Q), and His388 (H388A, H388N, H388Q, H388D, and H388E) - showed that only two mutants (E227Q and H388N) retained activity. Based on available structural and biochemical data, a revised reaction mechanism for MAMS-catalyzed elongation of methionine-derived aliphatic glucosinolates is proposed, which is likely also conserved in IPMS from leucine biosynthesis in plants and microbes.