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A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context.
Assuntos
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/genética , Reprodutibilidade dos Testes , Proteínas/química , Simulação de Dinâmica Molecular , Concentração de Íons de HidrogênioRESUMO
Experimental studies of TiO2 nanotubes have been conducted for nearly three decades and have revealed the remarkable advantages of this material. Research based on computer simulations is much rarer, with research using density functional theory (DFT) being the most significant in this field. It should be noted, however, that this approach has significant limitations when studying the macroscopic properties of nanostructures such as nanosheets and nanotubes. An alternative with great potential has emerged: classical molecular dynamics simulations (MD). MD Simulations offer the possibility to study macroscopic properties such as the density of phonon states (PDOS), power spectra, infrared spectrum, water absorption and others. From this point of view, the present study focuses on the distinction between the phases of anatase and rutile TiO2. The LAMMPS package is used to study both the structural properties by applying the radial distribution function (RDF) and the electromagnetic properties of these phases. Our efforts are focused on exploring the effect of temperature on the vibrational properties of TiO2 anatase nanotubes and an in-depth analysis of how the phononic softening phenomenon affects TiO2 nanostructures to improve the fundamental understanding in different dimensions and morphological configurations. A careful evaluation of the stability of TiO2 nanolamines and nanotubes at different temperatures is performed, as well as the adsorption of water on the nanosurface of TiO2, using three different water models.
Assuntos
Nanoestruturas , Água , Temperatura , Água/química , Titânio/químicaRESUMO
The present work describes the development of a conceptual representation model of the domain of the theory of formal grammars and abstract machines through ontological modeling. The main goal is to develop an ontology capable of deriving new knowledge about the mood of an Alzheimer's patient in the categories of wandering, nervous, depressed, disoriented or bored. The patients are from elderly care centers in Ambato Canton-Ecuador. The population consists of 147 individuals of both sexes, diagnosed with Alzheimer's disease, with ages ranging from 75 to 89 years. The methods used are the taxonomic levels, the semantic categories and the ontological primitives. All these aspects allow the computational generation of an ontological structure, in addition to the use of the proprietary tool Pellet Reasoner as well as Apache NetBeans from Java for process completion. As a result, an ontological model is generated using its instances and Pellet Reasoner to identify the expected effect. It is noted that the ontologies come from the artificial intelligence domain. In this case, they are represented by aspects of real-world context that relate to common vocabularies for humans and applications working in a domain or area of interest.
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In the last decade, TiO2 nanotubes have attracted the attention of the scientific community and industry due to their exceptional photocatalytic properties, opening a wide range of additional applications in the fields of renewable energy, sensors, supercapacitors, and the pharmaceutical industry. However, their use is limited because their band gap is tied to the visible light spectrum. Therefore, it is essential to dope them with metals to extend their physicochemical advantages. In this review, we provide a brief overview of the preparation of metal-doped TiO2 nanotubes. We address hydrothermal and alteration methods that have been used to study the effects of different metal dopants on the structural, morphological, and optoelectrical properties of anatase and rutile nanotubes. The progress of DFT studies on the metal doping of TiO2 nanoparticles is discussed. In addition, the traditional models and their confirmation of the results of the experiment with TiO2 nanotubes are reviewed, as well as the use of TNT in various applications and the future prospects for its development in other fields. We focus on the comprehensive analysis and practical significance of the development of TiO2 hybrid materials and the need for a better understanding of the structural-chemical properties of anatase TiO2 nanotubes with metal doping for ion storage devices such as batteries.
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In recent years, both chitosan and ZnO nanostructures have been identified as potential antibacterial substances; however, the potential applications of chitosan adsorbed on ZnO nanowires have not been explored and could offer exciting new perspectives for both materials, for example, in biocompatible electronic circuits. In this work, we investigate the effect of chitosan on the electronic properties of triangular ZnO nanowires (ZnO NWs) from a theoretical perspective. All calculations were performed using density functional theory within the generalized gradient approximation. We considered six different positions of the chitosan molecule (CS) on the nanowire surface. We varied the amine position of CS, viewing it parallel, perpendicular, and at a 45° angle with respect to the NW axis. Our results show that all configurations are chemically stable; moreover, the interaction of the NW surface with the OH radical of CS creates flat states within the band gap energy of the ZnO NWs that might resemble p-doping. In addition, these states induce changes in the band gap energy of the ZnO NWs. All NWs show high chemical stability regardless of the CS position; hence, the adsorption results of all NW assemblies appear to be chemically favorable.
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LDPE (low-density polyethylene) foams were prepared using the improved compression moulding technique (ICM) with relative densities ranging from 0.3 to 0.7 and with different levels of chemical blowing agents (from 1% to 20%). The density gradients, cellular structure and thermal conductivity of the foams were characterized. The density and amount of CBA used were found to have a significant effect on the cellular structure both at the mesoscale (density gradients) and at the microscale (different cell sizes and cell densities). In addition, the thermal conductivity of the samples is very sensitive to the local structure where the heat flux is located. The technique used to measure this property, the Transient Plane Source method (TPS), makes it possible to detect the presence of density gradients. A simple method for determining these gradients based on thermal conductivity data was developed.
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Infrared (IR) and Terahertz (THz) spectroscopy simulations were carried out using CHARMM35b2 to determine protein stability. The stabilities of three bacterial cold shock proteins (Csps) originating from mesophiles, thermophiles and hyper- thermophiles respectively were investigated in this study. The three different Csps were investigated by Normal-Mode analysis and Molecular Dynamics simulation of THz spectra using the Hessian matrix for solvated systems, interpreted in the harmonic approximation at optimum near-melting temperatures of each homologue, by incorporating differences in the hydrous and anhydrous states of the Csps. The results show slight variations in the large scale protein motion. However, the IR spectra of Csps observed at the low frequency saddle surface region, clearly distinguishes the thermophilic and mesophilic proteins based on their stability. Further studies on protein stability employing low-frequency collective modes have the potential to reveal functionally important conformational changes that are biologically significant.