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Sulfamerazine (4-Amino-N-(4-methylpyrimidin-2-yl) benzenesulfonamide) is a polymorphic molecule crystallizing in three forms: Form I: Pn21a polymorph (with three entries in the Cambridge Structural Database CSD), Form II: Pbca polymorph (with two entries in the CSD) and Form III: P21/c polymorph with only one entry in the CSD). We have experimentally prepared a novel monoclinic P21/c polymorph (Form IV) of the sulfadrug and also obtained crystals of Form II (Pbca polymorph) by following a different synthesis procedure. Both crystals were structurally characterized by single-crystal X-ray diffraction XRD and geometrically optimized by density functional theory DFT. The five crystal structures (1), (3)–(6) of the four mentioned polymorphs were analyzed and discussed in terms of crystal packing, Hirshfeld surface analysis HSA of the intermolecular interactions, voids' distribution in the crystal packing, their related energies and the resulting underlying topologies. The energy and activity relations of the compounds were also investigated by DFT. [ABSTRACT FROM AUTHOR]

Graphene-based nanomaterials have demonstrated significant potential in environmental applications and more particularly in water treatment, especially with the extensive use of emerging pollutants (EP). These pollutants originate either from wastewater treatment plants or agricultural activities. This study focused on the antibiotic amoxycillin which is most commonly administered to humans, livestock, and aquaculture to fight a multitude of infectious diseases. In order to understand the use of graphene oxide as an adsorbent in the removal of amoxycillin and to clarify the interfacial interaction at the molecular level, a Density Function Theory study at the B3PW91/cc-pVDZ level of theory, molecular dynamics simulation, and independent gradient model were performed to determine the structural and energetic properties, and to analyse the different interactions involved in the approach. The obtained results shows that AMX exhibits a nucleophilic behaviour whereas GO acts as an electrophile, and that the adsorption process occurs spontaneously via a parallel mode indicating strong interactions. It was established that the stability of the formed complexes is mainly due to the existence of both hydrogen bonds and Van der Waals type interactions. [ABSTRACT FROM AUTHOR]

This study presents a theoretical investigation of the [3 + 2] cycloaddition (32CA) reaction between cyclic nitrone a1 and substituted alkene b1. The mechanism, regioselectivity, and stereoselectivity of this 32CA reaction were analyzed using transition state theory and reactivity indices obtained from conceptual density functional theory (DFT) at the B3LYP/6-311G(d) level of theory. The results indicate that this cycloaddition reaction proceeds via an asynchronous one-step mechanism, exhibiting a non-polar nature and significant activation energies. These theoretical results are in agreement with the experimental observations. The study also employs topological analyses such as ESP, RDG-NCI, and ELF to determine active sites; distinguish hydrogen bonds, van der Waals interactions, and steric repulsive interactions; and predict electron localization, respectively. [ABSTRACT FROM AUTHOR]

Context: In this study, we detail the synthesis and crystallographic characterization of an unprecedented structure, specifically hypoxanthinium chloride monohydrate ((I) hereafter), which crystallizes in the monoclinic P21/c space group. A comparative analysis was conducted with four related hypoxanthinium salts: hypoxanthinium bromide monohydrate (II), 9-methylhypoxanthinium chloride monohydrate (III), hypoxanthinium nitrate monohydrate (IV), and hypoxanthinium perchlorate monohydrate (V). This analysis has focused mainly on their crystal packing, hydrogen-bonding networks, and non-classical intermolecular interactions, as elucidated by comprehensive Hirshfeld surface and topological analyses. Theoretical investigation of the nonlinear optical (NLO) properties of the hypoxanthinium derivatives (I–V) was performed using the Density Functional Theory (DFT). Methods: The crystalline environment was simulated using the iterative Supermolecule method (SM), and the static and dynamics linear refractive index, linear polarizability, second-order hyperpolarizability, and the third-order nonlinear susceptibility at the DFT/CAM-B3LYP/6–311++G(d,p) level were computed. The results for the macroscopic third-order nonlinear susceptibility of (II) was found to equal χ 3 = 0.81 × 10 - 20 m 2 / V 2 . By replacing the bromine atom in (II) with a chlorine atom as in (III), the χ 3 value will be multiplied by 2.16, and therefore these results are large enough to suggest the potential application of these crystals as NLO materials. [ABSTRACT FROM AUTHOR]

The B3LYP/cc-pVDZ basis set was used to optimize the best results of Pacritinib whose systematic name is (E)- 44-(2-(pyrrolidin-1-yl) ethoxy) −6,11- dioxa-3- aza-2(4,2)- pyrimidine −1,4 (1,3)-dibenzenacyclododecaphan-8-ene (MJ). The NBO analysis confirm the highest stabilization energy 55.36 kcal/mol, from bonding LP (1)–N13 to anti-bonding π*(N10 - C11). The ELF, LOL, ALIE, and RDG, analysis was done by using Multiwfn software, and confirms the localization and delocalization electrons. The thermodynamical properties and electron density were calculated with help of Gaussian-16w software. Analyses of NLO parameters, MEP, UV-vis, and HOMO-LUMO were performed using five different solvents (chloroform, water, acetonitrile, ethanol and DMSO). Docking study was done, against 5C5S protein and we identify the protein-ligand interaction, the best binding score is −6.64 kcal/mol. [ABSTRACT FROM AUTHOR]

Context: This research aims to offer a deeper understanding of the bonding interactions between M-Se and M-CO and how these interactions change across the group 6 transition metal series: [Se2M3(CO)10]2- (M = Cr, Mo, W). It also seeks to explore the impact of carbonyl groups on M-M interactions within the clusters. Seven criteria, which are based on QTAIM properties, have been considered and compared with the corresponding criteria in other transition metal clusters. The results confirm that no such bond critical points or bond baths occur between transition metals, which instead have 5c–7e bonding interactions delocalized over their five-membered M3(μ-Se)2 ring, as evidenced by the non-negligible nonbonding delocalization indices. The topological properties of three bond clusters, Cr-Se, Mo-Se, and W-Se, resemble those of "intermediate closed shell characters," which combine covalent and electrostatic properties. Source function calculations indicated that the bonded Se atom contributed the most to each Cr-Se and Mo-Se bcp. The OCO atoms and nonbonded Se atoms also contributed to some extent. However, metal atoms act as sinks rather than as sources of electron density. In contrast, the majority of the metal atoms, both bonded and nonbonded, contribute to Cr-W bcps. Analysis of the delocalization indices δ(M...O) in the three clusters indicates that CO significantly contributes to Cr π-back donation in cluster 1. In contrast, no π-back donation occurs from CO to Mo or W in clusters 2 or 3, respectively. Methods: The B3P86 hybrid functional was used for computations in the Gaussian 09 software. The LanL2DZ basis set was employed for Cr, Mo, and W, while the 6-31G (d, p) basis set was used for C, O, and Se atoms. We performed QTAIM analysis using the AIM2000 and Multiwfn packages, incorporating B3P86/WTBS for Cr, Mo, and W atoms. The 6-311++G(3df,3pd) basis set was used for C, O, and Se atoms. Additionally, we utilized the ELF and SF. [ABSTRACT FROM AUTHOR]

Chromatin conformation capture technologies permit the study of chromatin spatial organization on a genome-wide scale at a variety of resolutions. Despite the increasing precision and resolution of high-throughput chromatin conformation capture (Hi-C) methods, it remains challenging to conclusively link transcriptional activity to spatial organizational phenomena. We have developed a clique-based approach for analyzing Hi-C data that helps identify chromosomal hotspots that feature considerable enrichment of chromatin annotations for transcriptional start sites and, building on previously published work, show that these chromosomal hotspots are not only significantly enriched in RNA polymerase II binding sites as identified by the ENCODE project, but also identify a noticeable increase in FANTOM5 and GTEx transcription within our identified cliques across a variety of tissue types. From the obtained data, we surmise that our cliques are a suitable method for identifying transcription factories in Hi-C data, and outline further extensions to the method that may make it useful for locating regions of increased transcriptional activity in datasets where in-depth expression or polymerase data may not be available. [ABSTRACT FROM AUTHOR]

Gastric adenocarcinoma is one of the most death cause cancers worldwide. Metabolomics is an effective approach for investigating the occurrence and progression of cancer and detecting prognostic biomarkers by studying the profiles of small bioactive molecules. To fully decipher the functional roles of the disrupted metabolites that modulate the cellular mechanism of gastric cancer, integrated gene-metabolite association network methods are critical to map the associations between metabolites and genes. In this study, we constructed a knowledge-based gene-metabolite association network of gastric cancer using the dysregulated metabolites and genes between gastric cancer patients and control group. The topological pathway analysis and gene-protein-metabolite-disease association analysis revealed four key gene-metabolite pathways which include eleven metabolites associated with modulated genes. The integrated gene-metabolite association network enables mechanistic investigation and provides a comprehensive overview regarding the investigation of molecular mechanisms of gastric cancer, which facilitates the in-depth understanding of metabolic biomarker roles in gastric cancer.

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein–protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose. [ABSTRACT FROM AUTHOR]

The tri-nuclear heterometallic tetrahedral cluster [Mo–Ru–Co(µ3–S)(CO)8(Cp)COOCH3] (Cp = η5-C5H4) was studied employing quantum theory of atoms in molecules (QTAIM) to examine bonding interactions, including metal–metal (M–M), metal–sulfur (M–S), metal–carbonyl (M–CO), and metal–cyclopentadienyl (M–Cp) interactions. The electron density of bonding interactions within the cluster has its topological properties calculated based on this theory. Interestingly, the computed local topological characteristics for the Mo–Ru bond show notable distinctions in comparison to the parameters for interactions involving Mo–Co and Ru–Co, since for the latter, critical points and paths were not observed. The distribution of electron density was notably affected by the presence of bridging sulfide ligands in Mo...Co, Ru...Co interactions, much more than in the Mo–Ru bond. The characteristics of the latter bond exhibited attributes typical of interactions between open-shell metals. These features included slightly positive values for ρ(b) and ∇2ρ(b), along with small negative values of H(b)/ρ(b) approaching zero. Additionally, using the source function (SF) and electron localization function (ELF) methods, more focus has been given to the Mo–Ru bond. The core part, [Mo–Ru–Co(µ3–S)], was found to have a multicenter 4c–6e interaction. In this core, the three M–S bonds between the metal atoms and the sulfide ligand showed similar topological parameters that were typical of open-shell (covalent) interactions. Substantial π–back donation from CO to M was identified through the execution of δ(M...OCO) delocalization index calculations. [ABSTRACT FROM AUTHOR]

The tri-nuclear heterometallic tetrahedral cluster [Mo–Ru–Co(µ3–S)(CO)8(Cp)COOCH3] (Cp = η5-C5H4) was studied employing quantum theory of atoms in molecules (QTAIM) to examine bonding interactions, including metal–metal (M–M), metal–sulfur (M–S), metal–carbonyl (M–CO), and metal–cyclopentadienyl (M–Cp) interactions. The electron density of bonding interactions within the cluster has its topological properties calculated based on this theory. Interestingly, the computed local topological characteristics for the Mo–Ru bond show notable distinctions in comparison to the parameters for interactions involving Mo–Co and Ru–Co, since for the latter, critical points and paths were not observed. The distribution of electron density was notably affected by the presence of bridging sulfide ligands in Mo...Co, Ru...Co interactions, much more than in the Mo–Ru bond. The characteristics of the latter bond exhibited attributes typical of interactions between open-shell metals. These features included slightly positive values for ρ(b) and ∇2ρ(b), along with small negative values of H(b)/ρ(b) approaching zero. Additionally, using the source function (SF) and electron localization function (ELF) methods, more focus has been given to the Mo–Ru bond. The core part, [Mo–Ru–Co(µ3–S)], was found to have a multicenter 4c–6e interaction. In this core, the three M–S bonds between the metal atoms and the sulfide ligand showed similar topological parameters that were typical of open-shell (covalent) interactions. Substantial π–back donation from CO to M was identified through the execution of δ(M...OCO) delocalization index calculations. [ABSTRACT FROM AUTHOR]

Sensor Networks (SNs) play an essential role in upcoming technologies like the Internet of Things (IoT), where technical services are highly prone to crucial vulnerability due to attacks. This research motivates to provide a mechanism to identify the link reliability of connected sensor nodes. The privacy-preserving keys are distributed among the corresponding network nodes. When the nodes suffer from an attack, it damages the linking nodes' community. It has the nature of healing itself when the attacks are identified over the network. The self-healing nature is not so complex, and it is termed a lightweight process. A novel link-based intrusion prediction mechanism uses attention-based Deep Neural Networks (𝑎-DNN) for lightweight linkage identification and labelling. This model helps predict basic network patterns using topological analysis with better generalization. The simulation is done with Python where the proposed 𝑘-DNN model outperforms the five different conventional approaches with the adoption of a benchmark dataset (network traffic) for extensive analysis. The AUC is improved in an average manner with the adoption of 𝑘-DNN. This model enhances the linkage connectivity to make different connectivity processes more efficient and reach the target non-convincing. It is sensed that the proposed 𝑎-DNN outperforms the existing approaches by improving the network resilience by maintaining higher energy efficiency. [ABSTRACT FROM AUTHOR]

This research examines the transport networks operating in Milan, Italy, in seven years, from 1856 to 2016. The networks are transformed into graphs and analysed with several techniques from graph theory, including a new centrality index called Icentr. With the help of this index, we identify the nodes, to be considered primary in the transportation network, that are better related both in terms of topology and more interconnected in terms of distance. The findings provide a detailed picture of how the primary nodes have shifted from the city’s inner core to outer areas over the course of the investigated decades, both for the topological case and when the graphs are weighted based on the distance between nodes. Particularly, the effect of distance is more evident in those historical phases when the city expands, creating longer connections between nodes, in contrast to phases when the city becomes denser. The proposed method of analysis appears suitable to be applied to other cities, both for simplicity and effectiveness.

The investigation into a prospective pharmaceutical chalcone derivative employs a comprehensive methodology, integrating theoretical and empirical analyses. Rigorous scrutiny of the compound's distinct attributes is conducted through FT-IR, NMR and UV–Vis spectroscopy. Utilizing Density Functional Theory (DFT), specifically B3LYP/6–311++G(d,p), yields crucial insights into the potential energy surface, molecular structure optimization, vibrational properties, and electronic configuration stability. The study establishes correlations between simulated and actual spectra, and Frontier Orbital Theory (FMOs) explores the compound's chemical properties and electron-hole excitation across various solvents. The lowest energy gaps are observed in UV–visible and HOMO-LUMO analyses for various solvent effects between 3.7 to 3.8 eV Intra-molecular analysis through Natural Bond Orbitals (NBO) is complemented by the calculation and molecular electrostatic potential (MEP) and local descriptors like Fukui functions (f+, f−, f0), alongside topological analyses. Molecular docking is performed for different antifungal protein receptors (6EYY, 3DD4, 7YQP and 3WIX). The lowest binding energies of -8.89, -7.95 and -7.85 Kcal/mol were observed for the receptors 6EYY, 3DD4 and 7YQP. This facet of the research suggests promising pharmaceutical applications for the compound.

The present work focused on molecular structure and various spectroscopic studies of 2-[2,3-dichloro-4-(2-methylidenebutanoyl)phenoxy] acetic acid is also called as Ethacrynic acid (EA). The B3LYP/6-311G(d,p) level of theory was adopted to compute the molecular geometry (monomer and dimer) for EA molecule, the computed geometrical parameters are well coincided with related XRD data. The Natural Bond Orbital (NBO) was calculated to find donor-acceptor interaction. The vibrational modes of EA molecule was computed by B3LYP/6-311G(d,p) method and assignments were carried out by finding Potential Energy Distribution (PED) using VEDA software. The deviation in wavenumber of O-H vibrations (in COOH) group evident the intermolecular hydrogen bond interaction is possible between nearby molecules. The Gauge Independent Atomic Orbital (GIAO) method is used to find 1H and 13C NMR chemical shift and correlated with recorded NMR spectrum. The Time-Dependent density functional theory (TD-DFT) is used to determine the various electronic parameters. The intra, inter molecular and non covalent interactions of the EA molecule are examined by Atoms in Molecules (AIM), ELF, LOL and RDG analysis. From AIM analysis the EA molecule form C-H…...Cl hydrogen bond of energies 1.2863 and 1.1922 Kcal/mol in both monomer and dimer were determined. Mulliken atomic charge analysis is used find the electronegativity equalization and charge transfer in the molecular system. Fukui function carried out to identify electrophilic and nucleophilic attack in the EA molecule. Thermal (DTA) and thermogravimetric (TG) analyzes adopted to determine the thermal behavior of compound which denote the compound dissociate around 122.5 °C. The thermodynamic parameters for different temperature were also calculated by B3LYP/6-311G(d,p) method. The EA compound was monitor to the antibacterial activity by agar well diffusion method. Molecular docking analysis carried out using Autodock software with protein inhibit thyroid and breast cancer show binding energies of -4.79 and -3.99 Kcal/mol.

[Display omitted] Based on the processing of supramolecular environments of nitro group from Cambridge Structural Database by means of the 'Atoms in Molecules' analysis of promolecular electron density function, it is demonstrated that the topological stability of intermolecular bonding within one associate reflects trends in prevalence of interactions with particular geometry in real crystals. [ABSTRACT FROM AUTHOR]

The rapid increase in the volume of visual information on the internet stimulates the improvement and search for new approaches to solving the problem of image compression. One of the important characteristics in the field of image processing, in particular in matters of compression, is entropy. The work explores the possibility of using the method of image decomposition based on topological features to reduce entropy in order to further compress the image while maintaining high quality. Topological decomposition involves decomposing an image into components each of which reflects a separate element in the image. Topological decomposition allows us to group global structures and their details into separate matrices of special types. To reduce entropy, it is proposed to remove some detail components and restore the image. A distinctive feature of the proposed approach is that it does not distort the entire image, but only some areas. The proposed method is tested in a practical compression problem using the entropy-dependent RLE algorithm. The results showed that topological decomposition is good at reducing entropy, which will allow us to use the preprocessed image for compression. PSNR, SSIM, MSE, NRM indices are used to assess image quality. When compared with the wavelet transform, the proposed approach is competitive in terms of image quality assessment at a comparable compression ratio, and exceeds it for a certain class of images with slightly noisy long objects. The results open up opportunities for further study of topological decomposition in image compression with potentially greater efficiency and less distortion.

The Network Makeup Artist (NORMA) is a web tool for interactive network annotation visualization and topological analysis, able to handle multiple networks and annotations simultaneously. Precalculated annotations (e.g., Gene Ontology, Pathway enrichment, community detection, or clustering results) can be uploaded and visualized in a network, either as colored pie-chart nodes or as color-filled areas in a 2D/3D Venn-diagram-like style. In the case where no annotation exists, algorithms for automated community detection are offered. Users can adjust the network views using standard layout algorithms or allow NORMA to slightly modify them for visually better group separation. Once a network view is set, users can interactively select and highlight any group of interest in order to generate publication-ready figures. Briefly, with NORMA, users can encode three types of information simultaneously. These are 1) the network, 2) the communities or annotations of interest, and 3) node categories or expression values. Finally, NORMA offers basic topological analysis and direct topological comparison across any of the selected networks. NORMA service is available at http://norma.pavlopouloslab.info, whereas the code is available at https://github.com/PavlopoulosLab/NORMA.

The chemical bonding of 3C2O and 3N2C is analyzed in this work through the topological quantum approach using the electronic localization function (ELF) at the CASSCF level and by energetic calculations at the CCSD(T) level using four different basis sets. The results show that the dissociation of the molecules occurs via cleavage of the C‐C bond in the case of 3C2O, while in the case of 3N2C, it occurs via cleavage of the N‐C bond. Furthermore, the results obtained with ELF show monosynaptic basins containing excess electrons and disynaptic basins with a low electron population. This leads us to indicate the existence of three‐center‐two‐electron bonds according to previous results. From the valence bond model, a series of resonance structures have been proposed that support our calculations. In addition, the proposed structures have an ionic nature, indicating a charge shift character. [ABSTRACT FROM AUTHOR]

The synthesis of four novel amide compounds (R1C(O)NHR2) is reported, which contain both bulky (R1=phenyl and adamantyl) and hydrophilic (R2=hydroxyl, methoxyl) groups. The incorporation of such substituents provides compounds with unique properties that combine steric hindrance and hydrophilicity. The synthesized amides were fully characterized by 1H and 13C nuclear magnetic resonance (NMR) and analysed using infrared (IR) and Raman spectroscopy to investigate their vibrational properties in the solid phase, specifically focusing on the amide‐type normal modes of vibrations. Furthermore, the crystal structures of three derivatives were determined by single‐crystal X‐ray diffraction, which provided insights into their molecular arrangements. The occurrence of N−H⋅⋅⋅O=C hydrogen bonding intermolecular interaction is clearly observed and characterized by Hirschfeld surface analysis. Topology analysis using the Quantum Theory of Atom in Molecules and Crystals (QTAIM−C) were employed to investigate the electronic properties of the isolated amide molecules and to analyse the intermolecular interactions within the crystalline structure. The periodic calculations for the crystal revealed a higher electronic density in the C−N bond, indicating an increased covalent character in this bond compared with the C=O bond. This observation indicates the presence of resonance‐assisted hydrogen bonds within the amide core, leading to π electronic delocalization. [ABSTRACT FROM AUTHOR]

In this research, a rational design based on density functional theory (DFT) was performed for molecularly imprinted polymer (MIP) biosensors using pyrrole and acrylamide as the functional monomers for selective detection of renal failure biomarkers, i.e. urea, creatinine, uric acid and xanthine. Theoretical optimization and frequency calculations were employed at M06-2X/6–311 + + G(d,p) level of theory. As the main results, the proper molar ratio for each monomer–template complex, and the most appropriate solvent and cross-linking agent for MIP preparation were achieved. In the preparation of the pre-polymerization complexes, non-polar aprotic solvents were found to perform better stabilization. As cross-linking agent, better results were obtained for divinylbenzene. The selectivity tests showed a high affinity of the studied MIPs for each template compared to its structural analogs. The frontier molecular orbital (FMO) distribution, molecular electrostatic potentials (MEPs), and natural bond orbital (NBO) analysis were explored to predict the potential active sites in the templates and monomers. Theoretical infrared (IR) analysis revealed the formation of strong hydrogen bonds between the template and monomer molecules. This result was confirmed by the quantum theory of atoms in molecules. Finally, this study constitutes a useful protocol to predict optimal conditions, which can considerably reduce the time and cost of MIPs preparation. [ABSTRACT FROM AUTHOR]

Context: Quinolone derivatives have gathered major attention largely due to their wonderful biological activities. Quinolones are a class of molecules that are derived from quinolines and also extracted from natural sources. Most of these quinolones have significant medicinal properties ranging from antiallergenic and anticancer to antimicrobial activities. Some bacteria produce several 2-alkyl-4(1H)-quinolones. In past years, a variety of methods have been reported for the synthesis of quinolone derivatives. In this present work, structural, wave functional, and electronic properties of monomeric and dimeric forms of 2-methyl-4(1H)-quinolone are investigated. From the calculated binding energies, it was found that the formation of dimers is thermodynamically favorable. The analysis of reactivity parameters confirms that the keto form is more reactive than the enol form and keto–keto dimer is more reactive than compared to all monomeric and dimeric forms of our studied compound. Methods: Geometry optimizations of monomers and dimers of studied molecules were carried out using the B3LYP-D3(BJ)/ma-def2-TZVPP level of theory. The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies were calculated using the B3LYP/def2-TZVP level of theory. All DFT calculations were done with the ORCA 5.0.3 program. The reactivity parameters such as ionization potential, electron affinity, global hardness, global softness, electronegativity, chemical potential, and electrophilicity index were calculated. The nature of intermolecular interactions within the dimers was studied using topological analysis such as atoms in molecule (AIM) and reduced density gradient (RDG) surface analyses. To visualize the electron delocalization in the dimer electron localization function (ELF) and localized orbital locator (LOL) studies were also performed. The analyses such as AIM, RDG, ELF, and LOL were carried out by the multifunctional wavefunction analysis program Multiwfn 3.8. [ABSTRACT FROM AUTHOR]

Two 3D Zn(II) and Cd(II) coordination polymers, [Zn2(µ4-dppa)(µ-dpe)(µ-H2O)]n·nH2O (1) and [Cd2(µ8-dppa)(µ-dpe)(H2O)]n (2), have been constructed hydrothermally using 4-(3,5-dicarboxyphenoxy)phthalic acid (H4dppa), 1,2-di(4-pyridyl)ethylene (dpe), and zinc or cadmium chlorides. Both compounds feature 3D network structures. Their structure and topology, thermal stability, catalytic, and anti-wear properties were investigated. Particularly, excellent catalytic performance was displayed by zinc(II)-polymer 1 in the Knoevenagel condensation reaction at room temperature. [ABSTRACT FROM AUTHOR]

The electronic characterization of monomer and dimer molecule's C6H6O4 was also calculated using the DFT (B3LYP/6311G++(d,p)) method. The calculated TDOS, HOMO, and LUMO were performed through intramolecular charge transfer to investigate the molecule's stability. In dimethylsulfoxide (DMSO), the UV spectrum has been determined. According to Swiss-ADME, Aspergillus oryzae is not mutagenic or carcinogenic. Additionally calculated were the Mulliken charges, Fukui indices and MEP. Swiss-ADME was used to forecast predictions and significant descriptors of the compounds' physicochemical characteristics. The intermolecular interactions were examined using topological analysis techniques like RDG and IRI. For the 1JNK Protein, Aspergillus oryzae has a binding affinity of –6.21. [ABSTRACT FROM AUTHOR]

Abstract Ensuring healthy lives and promoting well-being for all at all ages is the third goal of the sustainable development plan, so it was necessary to identify the most important problems that threaten health in our world. The World Health Organization declared that antibiotic resistance is one of the uppermost global public health threats facing humanity and searching for new antibiotics is slow. This problem can be approached by improving available drugs to combat various bacterial threats. To circumvent bacterial resistance, three copper(II) complexes based on the pefloxacin drug were prepared and characterized using analytical, spectroscopic, and thermal techniques. The resulting data suggested the formation of one octahedral binary and two distorted square pyramidal ternary complexes. Fluorescence spectra results revealed the formation of a turn-on fluorophore for amino acid detection. Computational calculations investigated quantum and reactivity parameters. Molecular electrostatic potential profiles and noncovalent bond interaction-reduced density gradient analysis indicated the active sites on the complex surface. The complexes were subjected to six microbial species, where the octahedral binary complex provoked its antimicrobial potency in comparison with ternary complexes. The enhanced antimicrobial activity against gram-negative bacterium E-coli compared to gentamicin was exhibited by the three complexes. Docking simulation was performed based on the crystal structure of E. coli and S. pneumoniae receptors using 5I2D and 6O15 codes. The binary complex exhibited a potent fitness score with 5I2D (TBE = − 107 kcal/mol) while ternary complexes displayed the highest docked score of fitness with 6O15.

Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p

A novel heterocyclic organic compound, 4-Acetamido benzoic acid (4AMBA) had a wide range of applications in the field of drug discovery arena. The molecular structural stability conformation had been carried out using the Molecular Potential Energy Surface (MPES) scan with chosen suitable dihedral angle. For both the calculated and experimental procedures, the identifications of the chemical bonds of pertinent functional groups were investigated using spectral measurements (FT-IR and FT-Raman). The DFT/B3LYP/6–311++G(d,p) basis set, which is a highly compatible technique, was implemented to execute the quantum computational studies. Further, to enhance the molecular (inter and intra) interactions, reactivity regions between the atoms were performed using reactivity sites such as MEP, NBO, NLMO, NHO, and Hirshfeld surface analysis. In addition, the topological analysis for the various solvents and the electronic properties of the appropriate wavelength, the energy gap of the UV–Visible spectrum (both theoretical (various solvents) and experimental), FMO theories (HOMO and LUMO) energies and topological analyses were attained. The significant features that explain the biological behavior of the header composite were computed with the least possible binding energy using protein-ligand interactions with appropriate protein receptors, such as 1J1R, 1G1K, and 1J1Q.

The titled compound TA structure was optimized in B3LYP/cc-pVDZ basis set using Gaussian software. In natural bond orbital analysis the highest stabilization energy is 82.3 kcal/mol, which is confirmed by LP(1)-C19 to antibonding π*(C13-C14). Electron localization and delocalization areas are confirmed by wavefunction studies. The Gaussian-16w software establishes thermodynamic properties for a titled compound which is confirmed by various solvents. The HOMO and LUMO analysis ethanol have the highest energy gap value, which is 5.88 eV. In molecular electrostatic potential study nitrogen is the nucleophilic attack (blue color) and oxygen is the electrophilic attack (red color). In non-linear optical (NLO) study water solvent shows the highest dipole moment activity. The docking study showed the greatest binding affinity score of −4.08 kcal/mol.

Initially, we have done the conformational analysis, total of 564 confirmations were available, we noted highest energy value is 56.499 and the ring energy is 67.982. After getting conformational analysis results, we choose the highest energy value structure, that structure is only used for further DFT calculations. The B3LYP/cc-pVDZ basis set was used to optimize the best results for the 3-(1-(3-(5-((1-methyl piperidin-4-yl) methoxy)pyrimidin-2-yl) benzyl)-6-oxo-1,6 -dihydropyridazin -3-yl)benzonitrile (CD). The NBO analysis confirms the highest stabilization energy 39.53 kcal/mol, from bonding LP (1) - N22 to anti-bonding π*(N21 - C24). The ELF, LOL, ALIE, and RDG, analysis was done by using Multiwfn software and confirmed the localization and delocalization of electrons. The thermodynamic properties and electron density were calculated with the help of Gaussian-16w software. Analyses of NLO parameters, MEP, UV-vis, and HOMO-LUMO were performed using five different solvents (chloroform, water, acetonitrile, ethanol, and DMSO). The docking study was done using Autodock software, and we identify the protein-ligand interaction, the best binding score is -5.69 kcal/mol.

Au⋅⋅⋅H−X (X=N or C) hydrogen bonding is gaining increasing interest, both in the study of its intrinsic nature and in their operability in different fields. While the role of these interactions has been studied in the stabilization of gold(I) complexes, their role during the minimum free energy reaction pathway of a given catalytic process remains unexplored. We report herein that complex [Au(C≡CPh)(pip)] (pip=piperidine) catalyses the A3‐coupling reaction for the synthesis of propargylamines, thanks to the ability of Au(I) to promote weak hydrogen bonding interactions with the reactants along the free energy profile. Density Functional Theory (DFT) calculations show that these Au⋅⋅⋅H−X interactions play a directing role in the catalysed A3‐coupling. Topological non‐covalent interactions (NCI), interaction region indicator (IRI) and quantum theory of atoms in molecules (QTAIM) analysis in real space of the electron density provide a description of these interactions accurately. [ABSTRACT FROM AUTHOR]

Aims: Oral squamous cell carcinoma (OSCC), a most frequent type of head-and-neck cancer, is becoming more common and posing a substantial health risk. Using a network biology strategy, this study intended to find and investigate critical genes associated with OSCC. Materials and Methods: The extended protein–protein interaction networks for differentially expressed genes related to smoking and nonsmoking conditions of OSCC were constructed and visualized using Cytoscape software. The hub genes/proteins were determined based on degree and betweenness centrality measures and then evaluated and validated for expression using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and their relationship to the sensitivity of small molecules was discovered utilizing the Gene Set Cancer Analysis (GSCA) web server. Results: A total of 596 differentially expressed genes were screened, and four genes, interleukin (IL)-6, JUN, tumor necrosis factor (TNF), and vascular endothelial growth factor A (VEGFA), were identified as hub proteins, and their expression and overall survival in head-and-neck cancers were further investigated using GEPIA2. TNF and VEGFA gene expressions were considerably greater in cancers when compared to normal samples, while JUN and IL-6 gene expressions were not statistically significant. Further, these hub proteins are found to have a substantial favorable correlation with overall survival of head-and-neck cancer patients. Finally, GSCA was used to predict gene-specific potential drugs that act on these molecules by combining mRNA expression and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer and the Cancer Therapeutics Response Portal. Conclusions: The hub genes/proteins identified in this study could help researchers better understand the molecular processes involved in the progression and metastasis of oral cancer in smokers. [ABSTRACT FROM AUTHOR]

Morphological hierarchies constitute a rich and powerful family of graph-based structures that can be used for image modeling, processing and analysis. In this article, we focus on an important subfamily of morphological hierarchies, namely the trees that model partial partitions of the image support. This subfamily includes in particular the component-tree and the tree of shapes. In this context, we provide some new graph-based structures (one directed acyclic graph and three trees): the graph of valued shapes, the tree of valued shapes, the complete tree of shapes and the topological tree of shapes. These new objects create a continuum between the two notions of component-tree and tree of shapes. In particular, they allow to establish that these two trees (together with a third notion of adjacency tree generally considered in topological image analysis) can be defined and handled in a unified framework. In addition, this framework enables to enrich the component-tree with additional information, leading on the one hand to a topological description of grey-level images that relies on the same paradigm as persistent homology, and on the other hand to the proposal of a topological version of tree of shapes. This article provides a theoretical analysis of these new morphological hierarchies and their links with the usual ones. It also proposes an algorithmic description of two ways of building these new morphological hierarchies, and a discussion on the links that exist between these morphological hierarchies and certain topological invariants and descriptors. [ABSTRACT FROM AUTHOR]

Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids. [ABSTRACT FROM AUTHOR]

As data sets grow to exascale, automated data analysis and visualization are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. We report the first shared SMP algorithm for fully parallel contour tree computation, with formal guarantees of O(lg V lg t) parallel steps and O(V lg V) work for data with V samples and t contour tree supernodes, and implementations with more than 30× parallel speed up on both CPU using TBB and GPU using Thrust and up 70× speed up compared to the serial sweep and merge algorithm.

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein–protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose.

The potential of 2,6-bis(4-fluorophenyl)-3,3-dimethylpiperidin-4-one (BFDP) as an anti-Parkinson's, anti-lung cancer, and anti-human infectious agent was extensively assessed in the current study. To accomplish this, the compound BFDP was synthesised and analysed using several spectroscopic approaches, such as NMR, mass and FT-IR spectral studies. The computational calculations for the molecule were carried out using density functional theory (DFT) at the B3LYP/6-311G++ (d,p) level of theory. A X-ray diffraction (XRD) study allows us to analyse the crystalline structure of our BFDP molecule. Intermolecular interactions were assessed using 3D Hirshfeld surfaces (3D-HS) and 2D fingerprint plots. AIM and NCI-RDG were done using quantum calculations and the DFT technique, and topological ELF and LOL, as well as vibrational parameters, have been obtained. The thermodynamic and thermal properties of the BFDP compound were determined. To investigate the pharmacokinetic characteristics of BFDP, a molecular docking study and an in silico ADMET study were done.

In this work, the electron density distribution of (Z)-3-N-(ethyl)-2-N '-(3-methoxyphenyl imino) thiazolidine-4-one is determined by single-crystal X-ray refinements using a spherical structure factors and multipolar model of Hansen and Coppens. The following crystal properties are determined: laplacian of electron density and critical points. These parameters are basic for understanding the nature of intra- and intermolecular charge transfer and to highlight the chemical reactivity of the molecule. From the deformation density maps, density accumulations are visible in bonding as well as in the lone-pair regions of oxygen atoms (O1 and O2). The results of reduced density gradient, of natural bond orbital and of Hirshfeld surface analysis allow obtaining respectively; information's of the intra non-bonded interactions, charge transfer and to understand what kind of interatomic contacts give the largest contributions in crystal structure. The relative high value of local reactivity descriptors indicate that S atom is the most preferred site for nucleophilic attacks whereas C4 and C8 sites are the most nucleophilic centers. In addition, the compound under investigation presents a biological activity when it is docked into the protein (PDB ID: 2AZ5) with the binding energy system of –6.3 kcal/mol. This compound showed excellent interaction with amino acids constitutes this protein and showed significant inhibition of tumor necrosis factor. [ABSTRACT FROM AUTHOR]

Urban planning is considered one of the most critical topics in the design and development strategies of cities. There are a vast number of urban planning rule sets that focus on dominating the geometrical perspective over other approaches when it comes to planning decisions. In this paper, a different point of view towards urban planning is suggested, concentrating on the topological analysis and relations between city elements. The streets of cities are chosen to reflect this topological relation and to investigate the topological relations to the limits; six different-sized cities were selected for analysis: three large cities and three relatively small ones. The results of the study uncovered the hierarchical pattern underlying the street structure of cities; analyses showed that street networks in large cities have a higher degree of hierarchical level than in relatively small cities. Urban planners can benefit from the results of the analyses in this study to make better planning decisions in large or small cities. The paper provides analysis results towards achieving the optimum goals of urban planning to make cities more living and more efficient. [ABSTRACT FROM AUTHOR]

Ensuring healthy lives and promoting well-being for all at all ages is the third goal of the sustainable development plan, so it was necessary to identify the most important problems that threaten health in our world. The World Health Organization declared that antibiotic resistance is one of the uppermost global public health threats facing humanity and searching for new antibiotics is slow. This problem can be approached by improving available drugs to combat various bacterial threats. To circumvent bacterial resistance, three copper(II) complexes based on the pefloxacin drug were prepared and characterized using analytical, spectroscopic, and thermal techniques. The resulting data suggested the formation of one octahedral binary and two distorted square pyramidal ternary complexes. Fluorescence spectra results revealed the formation of a turn-on fluorophore for amino acid detection. Computational calculations investigated quantum and reactivity parameters. Molecular electrostatic potential profiles and noncovalent bond interaction-reduced density gradient analysis indicated the active sites on the complex surface. The complexes were subjected to six microbial species, where the octahedral binary complex provoked its antimicrobial potency in comparison with ternary complexes. The enhanced antimicrobial activity against gram-negative bacterium E-coli compared to gentamicin was exhibited by the three complexes. Docking simulation was performed based on the crystal structure of E. coli and S. pneumoniae receptors using 5I2D and 6O15 codes. The binary complex exhibited a potent fitness score with 5I2D (TBE = − 107 kcal/mol) while ternary complexes displayed the highest docked score of fitness with 6O15. [ABSTRACT FROM AUTHOR]

Reaction of 3-aminobenzenesulfonic acid (HL1) with Cu(NO3)2·2.5H2O in H2O/DMF leads to the formation of the new bis(3-aminobenzenesulfonato-κN)-diaqua-bis(dimethylformamide-κO)-copper(II) complex [Cu(L1)2(DMF)2(H2O)2] (1) (HL1 = 3-aminobenzenesulfonic acid and DMF = N,N-dimethylformamide). Single crystal X-ray analysis reveals that the hexacoordinated copper(II) center adopts a distorted octahedral geometry with trans-oriented two 3-aminobenzenesulfonate ligands (L1−), two water and two dimethylformamide (DMF) molecules. Comparison of its crystal structure with that of the known bis(4-aminobenzenesulfonato-κN)diaquabis(dimethylformamide-κO)-copper(II) complex [Cu(L2)2(DMF)2(H2O)2] (2) (HL2 = 4-aminobenzenesulfonic acid) discloses that 1 and 2 are the isomers with an identical empirical formula (C18H30CuN4O10S2) and equal numbers of same coordinated solvents (DMF and water). H-bonded supramolecular structures and their corresponding topological analyses revealed a 2D with 6-connected hxl/Shubnikov plane net (3,6) for 1 and a 3D with 8-connected bcu; 8/4/c1; sqc3 net for 2, which are completely different. [ABSTRACT FROM AUTHOR]