Electron Density Map Research Articles

Ligand Identification in CryoEM and X-ray Maps Using Deep Learning.

Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule ligands bind to active sites of interest. However, the interpretation of density maps is challenging, and cognitive bias can sometimes mislead investigators into modeling fictitious compounds. Ligand identification can be aided by automatic methods, but existing approaches are available only for X-ray diffraction and are based on iterative fitting or feature-engineered machine learning rather than end-to-end deep learning. Here, we propose to identify ligands using a deep learning approach that treats density maps as 3D point clouds. We show that the proposed model is on par with existing machine learning methods for X-ray crystallography while also being applicable to cryoEM density maps. Our study demonstrates that electron density map fragments can aid the training of models that can later be applied to cryoEM structures but also highlights challenges associated with the standardization of electron microscopy maps and the quality assessment of cryoEM ligands.

Water Networks within Metal Organic Nanotubes: Assessment of Techniques to Understand Structure and Properties.

AbstractHybrid materials, such as metal organic nanotubes (MONTs) can possess nanoconfined water molecules within their pore space and the overall behavior of the water within the material may be tuned based upon interactions with the inner channel walls. We have previously developed a range of methods (electron density mapping, kinetic models, and water interaction enthalpies) to evaluate water behavior under nanoconfinement using a uranium‐based metal organic nanotube (UMONT) but have not explored their applicability across a range of materials. In the current study, we test our methodologies on two additional MONT materials (LaMONT and Cu‐LaMONT) to determine if the techniques can be utilized in other systems to predict behavior within complex hybrid materials. In addition, we explored how to use Hirshfeld surface maps generated by the CrystalExplorer software in the visualization and prediction of water behavior within complex hybrid materials.

Outflow from the very massive Wolf-Rayet binary Melnick 34

Melnick 34 (Mk\,34) is one of the most massive binary systems known and is one of the brightest X-ray point sources in the 30 Doradus region. We investigated the impact of this massive system on the surrounding interstellar medium (ISM) using the optical spectroscopic capabilities of the narrow-field mode (NFM) of the Multi-Unit Spectroscopic Explorer (MUSE). MUSE-NFM spatially resolved the ISM in the vicinity of Mk\,34 with a resolution comparable to that of the HST. The analysis of the N ii \,lambda \,6583 and S ii \,lambda \,6717 emission lines reveals a cone-like structure apparently originating from Mk\,34 and extending southeast. Electron density maps and radial velocity measurements of the ISM lines further support an outflow scenario traced by these emissions. While no clear northwestern counterpart to this outflow was observed, we note increased extinction in that direction, towards the R136 cluster. The ISM material along the projected diagonal of the outflow on both sides of Mk\,34 shows similar properties in terms of the emission line ratios seen in the Baldwin-Phillips-Terlevich diagram. These results are consistent across two observational epochs. Additionally, we examined the residual maps within a 0.5" radius of Mk\,34 after modeling and subtracting the point spread function. The observed variations in the residuals could potentially be linked to Mk\,34's known periodic behavior. However, further observations with appropriate cadence are needed to fully monitor the 155\,day periodicity of Mk\,34's X-ray emissions.

Calculate the one – expectation to electronic charge of atomic system contiun two electron

The aim of this work is to calculate the one- electron expectation value of the electronic charge of atomic system Z=2,3….7 and we compare with He atom . the electronic density function D(r1) of He atom and like ions are evaluated . using Hartree –Fock wave.

Biological activity of MgO nanoparticle synthesis by plasma-assisted reduction method

In the current report, MgO nanoparticles are synthesized by the plasma-assisted reduction method. This method is eco-friendly due to its safety, not use of toxic reducing agents, low cost, and rapid synthesis. Several techniques were employed to determine the crystalline size, particle size, morphology, elemental analysis, and optical properties of the MgO NPs. MgO nanoparticles had a semi-spherical particle structure with diameters ranging from 30.40 to 39.57 nm. The average crystalline size was measured to be 23.7 nm. An analysis using a UV–vis spectrophotometer reveals that the absorbance of MgO nanoparticles results in a significant peak at 354 nm, indicating an energy band gap of 3.2 eV. Subsequent detailed analysis was performed utilizing Rietveld refinement to accurately determine the crystallographic parameters. Additionally, electron density mapping was scrutinized to provide further insights into the atomic arrangement. The antibacterial and antibiofilm activity of MgO NPs was assessed against Klebsiella pneumoniae, Escherichia coli (gram-negative), and Staphylococcus aureus (gram-positive) bacteria at a dose concentration of 10 mg l−1. The antibacterial activity (zone of inhibition) and inhibition biofilm rate of MgO NPs against S aureus were more effective than those of K peneumoniae and E. coli. Consequently, this investigation demonstrates that the MgO NPs exhibited strong antibacterial properties and exhibited significant potential for the inhibition of pathogenic bacteria.

Structural and Functional Characterization of a Novel Class A Flavin Monooxygenase from Bacillus niacini.

A gene cluster responsible for the degradation of nicotinic acid (NA) in Bacillus niacini has recently been identified, and the structures and functions of the resulting enzymes are currently being evaluated to establish pathway intermediates. One of the genes within this cluster encodes a flavin monooxygenase (BnFMO) that is hypothesized to catalyze a hydroxylation reaction. Kinetic analyses of the recombinantly purified BnFMO suggest that this enzyme catalyzes the hydroxylation of 2,6-dihydroxynicotinic acid (2,6-DHNA) or 2,6-dihydroxypyridine (2,6-DHP), which is formed spontaneously by the decarboxylation of 2,6-DHNA. To understand the details of this hydroxylation reaction, we determined the structure of BnFMO using a multimodel approach combining protein X-ray crystallography and cryo-electron microscopy (cryo-EM). A liganded BnFMO cryo-EM structure was obtained in the presence of 2,6-DHP, allowing us to make predictions about potential catalytic residues. The structural data demonstrate that BnFMO is trimeric, which is unusual for Class A flavin monooxygenases. In both the electron density and coulomb potential maps, a region at the trimeric interface was observed that was consistent with and modeled as lipid molecules. High-resolution mass spectral analysis suggests that there is a mixture of phosphatidylethanolamine and phosphatidylglycerol lipids present. Together, these data provide insights into the molecular details of the central hydroxylation reaction unique to the aerobic degradation of NA in Bacillus niacini.

Investigation into the strength of β-Sn/α-CoSn3 and Co/α-CoSn3 interfaces with Ni-doped α-CoSn3 using first-principles calculations

The strength of Pb-free solder/Co-Ni alloy joints was investigated using first-principles calculations. The adhesion work was computed, revealing that the inclusion of Ni in the α-CoSn3 phase reduced the adhesion work for both β-Sn/α-CoSn3 and Co/α-CoSn3 systems. Tensile and shear simulations further demonstrated distinct differences in the mechanical properties between β-Sn/α-(Co,Ni)Sn3 and Co/α-(Co,Ni)Sn3 systems. The results demonstrate that Co/α-(Co,Ni)Sn3 exhibited superior tensile and shear strength. The analysis suggests that failure in β-Sn/α-(Co,Ni)Sn3 structures was more likely to originate either at the interface or near the β-Sn region, as opposed to within the α-(Co,Ni)Sn3 phase for the Co/α-(Co,Ni)Sn3 structures. This observation is consistent with predictions made by Griffith’s fracture theory. Additionally, the valence electron density map illustrates the electron transfer under varying tensile strains.

ResiDEM: Analytical Tool for Isomorphous Difference Electron Density Maps Utilizing Dynamic Residue Identification via Density Clustering.

Time-resolved serial femtosecond crystallography (TR-SFX) of biological molecules captures the time-evolved dynamics of the residual motions across crystal structures, enabling the visualization of structural changes in response to chemical and physical stimuli to elucidate the relationship between the structure and function of the system under study. However, interpretations of residual motions can be complex to deconvolute because of various factors such as the system's size, temporal and spatial complexity, and allosteric behavior away from active sites. Relying solely on electron density map visualization can also pose a challenge in differentiating between useful and irrelevant data. In order to accurately identify residues and determine their respective contributions to the reaction dynamics, new tools are needed. We developed a new tool, ResiDEM, which employs a clustering-based approach to group difference electron densities and associate them with proximal residues. It can identify and rank residues with significant motions. Network representation can be used to delineate the interrelations between the residues in motion. With these features, ResiDEM helps to interpret residual motions in TR-SFX data, identify key residues, and elucidate their roles in dynamic processes.

Utilizing anomalous signals for element identification in macromolecular crystallography.

AlphaFold2 has revolutionized structural biology by offering unparalleled accuracy in predicting protein structures. Traditional methods for determining protein structures, such as X-ray crystallography and cryo-electron microscopy, are often time-consuming and resource-intensive. AlphaFold2 provides models that are valuable for molecular replacement, aiding in model building and docking into electron density or potential maps. However, despite its capabilities, models from AlphaFold2 do not consistently match the accuracy of experimentally determined structures, need to be validated experimentally and currently miss some crucial information, such as post-translational modifications, ligands and bound ions. In this paper, the advantages are explored of collecting X-ray anomalous data to identify chemical elements, such as metal ions, which are key to understanding certain structures and functions of proteins. This is achieved through methods such as calculating anomalous difference Fourier maps or refining the imaginary component of the anomalous scattering factor f''. Anomalous data can serve as a valuable complement to the information provided by AlphaFold2 models and this is particularly significant in elucidating the roles of metal ions.

Pulmonary embolism detection without intravenous contrast using electron density and Z-effective maps from dual-energy CT

Abstract Purpose This study aims to evaluate the feasibility of using electron density (ED) maps combined with Z-effective (Zeff) images obtained from unenhanced dual-layer dual-energy CT (dl-DECT) scans of the chest for the detection of pulmonary embolism (PE). Materials and methods A retrospective analysis was conducted on consecutive patients who underwent for contrast-enhanced chest CT (CECT) clinically suspected of PE or acute aortic syndrome. These scans were performed on a single dl-DECT scanner between October 2021 and November 2023. To distinguish emboli from circulating blood, color-coded maps were generated from the ED dataset superimposed on Zeff images, which were acquired from the unenhanced phase. Two radiologists with different levels of expertise independently assessed the presence of PE in the generated ED-Zeff maps, blinded to CECT results, which served as the reference standard. Diagnostic accuracy of ED-Zeff maps was assessed for each reader. Results The final study cohort comprised 150 patients, with 92 males (mean age: 68 ± 10 years, range: 47-93 years) and 58 females (mean age: 66 ± 15 years, range 38-89 years). ED-Zeff maps demonstrated high diagnostic performance, yielding accuracy, sensitivity, and specificity, respectively, of 86.67% (113/150, 95% CI, 80.16%-91.66%), 85% (17/20, 95% CI, 79.89%-92.19%), and 86.92% (113/130, 95% CI, 79.89%-92.19%). Ed-Zeff maps were able to identify PE in 85% of positive cases. Cohen’s kappa coefficient indicated excellent intra- and interobserver agreement (κ ≥ 0.9). Conclusion ED maps combined with Zeff images from unenhanced dl-DECT scans represent a feasible tool for detecting PE and may prove useful in evaluating patients with contraindications to iodinated contrast.

Prediction of Ca2+ Binding Site in Proteins With a Fast and Accurate Method Based on Statistical Mechanics and Analysis of Crystal Structures.

Predicting the precise locations of metal binding sites within metalloproteins is a crucial challenge in biophysics. A fast, accurate, and interpretable computational prediction method can complement the experimental studies. In the current work, we have developed a method to predict the location of Ca2+ ions in calcium-binding proteins using a physics-based method with an all-atom description of the proteins, which is substantially faster than the molecular dynamics simulation-based methods with accuracy as good as data-driven approaches. Our methodology uses the three-dimensional reference interaction site model (3D-RISM), a statistical mechanical theory, to calculate Ca2+ ion density around protein structures, and the locations of the Ca2+ ions are obtained from the density. We have taken previously used datasets to assess the efficacy of our method as compared to previous works. Our accuracy is 88%, comparable with the FEATURE program, one of the well-known data-driven methods. Moreover, our method is physical, and the reasons for failures can be ascertained in most cases. We have thoroughly examined the failed cases using different structural and crystallographic measures, such as B-factor, R-factor, electron density map, and geometry at the binding site. It has been found that x-ray structures have issues in many of the failed cases, such as geometric irregularities and dubious assignment of ion positions. Our algorithm, along with the checks for structural accuracy, is a major step in predicting calcium ion positions in metalloproteins.

Conformational variability in the D2 loop of Plasmodium Apical Membrane antigen 1

Apical Membrane Antigen 1 (AMA1) plays a vital role in the invasion of the host erythrocyte by the malaria parasite, Plasmodium. It is thus an important target for vaccine and anti-malaria therapeutic strategies that block the invasion process. AMA1, present on the surface of the parasite, interacts with RON2, a component of the parasite’s rhoptry neck (RON) protein complex, which is transferred to the erythrocyte membrane during invasion. The D2 loop of AMA1 plays an essential role in invasion as it partially covers the RON2-binding site and must therefore be displaced for invasion to proceed. Several structural studies have shown that the D2 loop is very mobile, a property that is probably important for the function of AMA1. Here we present three crystal structures of AMA1 from P. falciparum (strains 3D7 and FVO) and P. vivax (strain Sal1), in which the D2 loop could be largely traced in the electron density maps. The D2 loop of PfAMA1-FVO and PvAMA1 (as a complex with a monoclonal antibody Fab) has a conformation previously noted in the P. knowlesi AMA1 structure. The D2 loop of PfAMA1-3D7, however, reveals a novel conformation. We analyse the conformational variability of the D2 loop in these structures, together with those previously reported. Three different conformations can be distinguished, all of which are highly helical and show some similarity in their secondary structure organisation. We discuss the significance of these observations in the light of the flexible nature of the D2 loop and its role in AMA1 function.

Molecular Basis of the Substrate Specificity of Phosphotriesterase from Pseudomonas diminuta: A Combined QM/MM MD and Electron Density Study.

The occurrence of organophosphorus compounds, pesticides, and flame-retardants in wastes is an emerging ecological problem. Bacterial phosphotriesterases are capable of hydrolyzing some of them. We utilize modern molecular modeling tools to study the hydrolysis mechanism of organophosphorus compounds with good and poor leaving groups by phosphotriesterase from Pseudomonas diminuta (Pd-PTE). We compute Gibbs energy profiles for enzymes with different cations in the active site: native Zn2+cations and Co2+cations, which increase the steady-state rate constant. Hydrolysis occurs in two elementary steps via an associative mechanism and formation of the pentacoordinated intermediate. The first step, a nucleophilic attack, occurs with a low energy barrier independently of the substrate. The second step has a low energy barrier and considerable stabilization of products for substrates with good leaving groups. For substrates with poor leaving groups, the reaction products are destabilized relative to the ES complex that suppresses the reaction. The reaction proceeds with low energy barriers for substrates with good leaving groups with both Zn2+and Co2+cations in the active site; thus, the product release is likely to be a limiting step. Electron density and geometry analysis of the QM/MM MD trajectories of the intermediate states with all considered compounds allow us to discriminate substrates by their ability to be hydrolyzed by the Pd-PTE. For hydrolyzable substrates, the cleaving bond between a phosphorus atom and a leaving group is elongated, and electron density depletion is observed on the Laplacian of electron density maps.

Digging deeper into NGC 6868 II: ionized gas and excitation mechanism

ABSTRACT We studied the ionized gas in the inner region ($\sim$$680\times 470$ pc2) of the galaxy NGC 6868 using Gemini/GMOS (Gemini Multi-Object Spectrograph) integral field unit observations. Channel maps reveal complex kinematics and morphology, indicating multiple processes at work in NGC 6868. Through emission-line fitting, we identified two ubiquitous components in our data: a narrow ($\sigma \sim 110$ km s$^{-1}$) tracing an ionized gas disc and a broad component ($\sigma \sim 300$ km s$^{-1}$) mainly associated with inflowing/outflowing gas. The derived V-band reddening shows a spatial distribution consistent with that obtained from stellar population synthesis, although with generally higher values. For the first time, we measured the electron temperature in NGC 6868, finding values ranging from $\sim$14 000 K in the central region to $\gtrsim 20000$ K with an outward increasing temperature gradient. The electron density map exhibits an inverse relationship, with central values reaching $N_e\sim 4000$ cm–3 for the broad component decreasing to $N_e\sim 100$ cm–3 towards the edges of the field of view. Using BPT diagrams, we found that all spaxels are consistent with both active galactic nucleus (AGN) and shock ionization. However, when this information is combined with our kinematic and temperature findings, and further supported by the WHAN diagram, we argue that an AGN is the dominant ionization mechanism in the central region of NGC 6868, while the extended outer component is ionized by a combination of hot low-mass evolved stars and shocks. According to our findings, shocks play a significant role in the ionization balance of this galaxy.

Electron density mapping using maximum entropy method and room temperature magnetism in Cr3+ substituted SnS2

Electron density mapping using maximum entropy method and room temperature magnetism in Cr3+ substituted SnS2

Preliminary Exploration of Low Frequency Low-Pressure Capacitively Coupled Ar-O2 Plasma

Non-thermal plasma as an emergent technology has received considerable attention for its wide range of applications in agriculture, material synthesis, and the biomedical field due to its low cost and portability. It has promising antimicrobial properties, making it a powerful tool for bacterial decontamination. However, traditional techniques for producing non-thermal plasma frequently rely on radiofrequency (RF) devices, despite their effectiveness, are intricate and expensive. This study focuses on generating Ar-O2 capacitively coupled plasma under vacuum conditions, utilizing a low-frequency alternating current (AC) power supply, to evaluate the system’s antimicrobial efficacy. A single Langmuir probe diagnostic was used to assess the key plasma parameters such as electron density (ne), electron temperature (Te), and electron energy distribution function (EEDF). Experimental results showed that ne increases (7 × 1015 m−3 to 1.5 × 1016 m−3) with a rise in pressure and AC power. Similarly, the EEDF modified into a bi-Maxwellian distribution with an increase in AC power, showing a higher population of low-energy electrons at higher power. Finally, the generated plasma was tested for antimicrobial treatment of Xanthomonas campestris pv. Vesicatoria. It is noted that the plasma generated by the AC power supply, at a pressure of 0.5 mbar and power of 400 W for 180 s, has 75% killing efficiency. This promising result highlights the capability of the suggested approach, which may be a budget-friendly and effective technique for eliminating microbes with promising applications in agriculture, biomedicine, and food processing.

NucleoFind: a deep-learning network for interpreting nucleic acid electron density.

Nucleic acid electron density interpretation after phasing by molecular replacement or other methods remains a difficult problem for computer programs to deal with. Programs tend to rely on time-consuming and computationally exhaustive searches to recognise characteristic features. We present NucleoFind, a deep-learning-based approach to interpreting and segmenting electron density. Using an electron density map from X-ray crystallography obtained after molecular replacement, the positions of the phosphate group, sugar ring and nitrogenous base group can be predicted with high accuracy. On average, 78% of phosphate atoms, 85% of sugar atoms and 83% of base atoms are positioned in predicted density after giving NucleoFind maps produced following successful molecular replacement. NucleoFind can use the wealth of context these predicted maps provide to build more accurate and complete nucleic acid models automatically.

Polymorph selection of pharmaceutical cocrystals via bench-top and continuous production techniques

Polymorphism can be a valuable tool as well as an impediment in the development and approval of pharmaceuticals, providing an opportunity to tune active pharmaceutical ingredient (API) physicochemical properties. The control of polymorphism in cocrystalline systems and other multicomponent forms remains underexplored. The study herein aims to investigate the potential of several techniques, liquid-assisted grinding (LAG), solvent evaporation (SE), supercritical enhanced atomization (SEA) and electrospraying, to control the cocrystal polymorphic outcome of three cocrystals: isonicotinamide-citric acid (IsoCa), ethenzamide-saccharin (EthSac) and ethenzamide-gentisic acid (EthGa). Solvent selection employing LAG and SE showed little effect on polymorphic outcome. Electrospraying and SEA primarily produced the α form of IsoCa, with process parameter variations leading to the β form during SEA, and a mixture of α and γ from electrospraying. Electrospraying led to the stable form I of EthSac, while SEA could produce pure form II, and a mixture. Electrospraying produced the form I of EthGa while SEA could produce form II, with an unknown polymorphic impurity. Density functional theory (DFT) computed electron density (ED) maps of cocrystal polymorph binary systems further rationalised the polymorphic predominance observed through the electrospraying. Ultimately this study provides a general road map for polymorph selection via atomization-based methodologies.

Supramolecular assembly governed by tetrel, CN⋅⋅⋅π and other weak noncovalent interactions in two acrylonitrile derivatives with D-π-A topology: Crystallography, optical properties and theoretical studies

Two D-π-A acrylonitriles, (Z)-3-(4-methoxyphenyl)-2-(pyridin-4-yl)acrylonitrile (1) and (Z)-3-(4-piperidin-1-yl)-2-(pyridin-4-yl)acrylonitrile (2), were synthesized to investigate how the varying donor moieties affect their structural and optical properties. Compound 1 crystallized with two crystallographically independent molecules, each showing different orientations of the methoxy group, and exhibited herringbone molecular arrangement in the solid-state. This structure is stabilized by CH···N/π interactions, π-stacking, cyano···π stacking (CN···π) and a σ-hole tetrel bond involving the C and O atoms of the methoxy group. Compound 2 crystallized with a single molecule in the asymmetric unit and displayed columnar packing mode. This structure is stabilized intermolecular CH···N interactions, where all nitrogen atoms serve as acceptors, as well as by intermolecular CH···π interactions and π-stacking between adjacent pyridyl rings. Hirshfeld surfaces and 2D-fingerprint plots revealed the effect of donor moieties on the intermolecular interactions. The energetics of the molecular dimers observed in these structures were characterized by both CLP-PIXEL energy and DFT calculations. The nature of the tetrel bond was characterized using molecular electrostatic surface potential and deformation electron density maps. Theoretical charge density analysis was performed to characterize the noncovalent interactions in various molecular dimers of 1 and 2. The absorption spectra of compounds 1 and 2 exhibit a 40 nm red-shift in solution, attributed to the presence of the piperidyl moiety in compound 2.

PhAI: A deep-learning approach to solve the crystallographic phase problem.

X-ray crystallography provides a distinctive view on the three-dimensional structure of crystals. To reconstruct the electron density map, the complex structure factors [Formula: see text] of a sufficiently large number of diffracted reflections must be known. In a conventional experiment, only the amplitudes [Formula: see text] are obtained, and the phases ϕ are lost. This is the crystallographic phase problem. In this work, we show that a neural network, trained on millions of artificial structure data, can solve the phase problem at a resolution of only 2 angstroms, using only 10 to 20% of the data needed for direct methods. The network works in common space groups and for modest unit-cell dimensions and suggests that neural networks could be used to solve the phase problem in the general case for weakly scattering crystals.