Mean Square Displacement Research Articles

Revisiting the exposed surface characteristics on the stability and photoelectric properties of MAPbI3.

In this work, the stability and photoelectric properties of the MAI-terminated and PbI2-terminated of MAPbI3 (001) were thoroughly investigated using density functional theory calculation. To study the stability of exposed surface, adsorption energy of water molecules, ab initio molecular dynamics (AIMD), mean square displacement (MSD) and X-ray diffraction (XRD) were calculated. MSD of PbI2-terminated surface is greater by two orders of magnitude compared to MAI-terminated surface. For the photoelectric properties of MAPbI3, the bandgap, absorption coefficients, joint density of states (JDOS) and dielectric constants were investigated. The inhibitory effect of water on the photoelectric performance for PbI2-terminated surface is more significant than that of MAI-terminated surface. Although the photoelectric properties of water molecules adsorption on MAI-terminated surface is basically unchanged, the diffusion of water molecules reduces the photoelectric properties of MAPbI3. Overall, the stability and photoelectric properties of MAI-terminated surface are superior to PbI2-terminated surface. Therefore, we advocate paying attention to the exposed surface of MAPbI3 during the thin film production process and adjusting synthesis parameters to prepare MAI-terminated surface dominated thin film, which should substantially improve the performance of MAPbI3 in the application.

Active fractal networks with stochastic force monopoles and force dipoles: Application to subdiffusion of chromosomal loci.

Motivated by the well-known fractal packing of chromatin, we study the Rouse-type dynamics of elastic fractal networks with embedded, stochastically driven, active force monopoles and force dipoles that are temporally correlated. We compute, analytically-using a general theoretical framework-and via Langevin dynamics simulations, the mean square displacement (MSD) of a network bead. Following a short-time superdiffusive behavior, force monopoles yield anomalous subdiffusion with an exponent identical to that of the thermal system. In contrast, force dipoles do not induce subdiffusion, and the early superdiffusive MSD crosses over to a relatively small, system-size-independent saturation value. In addition, we find that force dipoles may lead to "crawling" rotational motion of the whole network, reminiscent of that found for triangular micro-swimmers and consistent with general theories of the rotation of deformable bodies. Moreover, force dipoles lead to network collapse beyond a critical force strength, which persists with increasing system size, signifying a true first-order dynamical phase transition. We apply our results to the motion of chromosomal loci in bacteria and yeast cells' chromatin, where anomalous sub-diffusion, MSD∼tν with ν≃0.4, was found in both normal and cells depleted of adenosine triphosphate (ATP), albeit with different apparent diffusion coefficients. We show that the combination of thermal, monopolar, and dipolar forces in chromatin is typically dominated by the active monopolar and thermal forces, explaining the observed normal cells vs the ATP-depleted cells behavior.

A simulation study of microstructure and dynamics of dual-functionalised imidazolium based ionic liquids (DFILs)

ABSTRACT We studied the liquid structures and dynamics of a series of dual-functionalised ionic liquids (DFILs) by Md simulations. The studied DFILs consist of functionalised imidazolium cations with a nitrile group and varying lengths of ether side chains, paired with bis(trifluoromethyl sulfonyl) imide anions, denoted as [C2CNIm(EtO)nMe][Tf2N]. We instigated distribution functions, Voronoi tessellation, and cluster analysis, to probe the liquid structures. Furthermore, we explored dynamic properties such as mean-square displacements (MSD), self-diffusivity coefficients, hydrogen bonding, ion pairing, and ion cage effects. Our findings revealed a correlation between the length of the ether side chains and the density of the studied DFILs when the longer side chains lead to a decreased density. Calculated partial radial distribution functions (PRDF) of ether side chains of the cations demonstrated a tendency for self-aggregation as the chain length increased. The combined distribution functions diagrams show that the hydrogen bond between ions is more pronounced for cations with smaller side chains. Anions displayed higher diffusivity than the cations, and among the cations, [C2CNIm(EtO)6Me]+ has the lowest diffusion coefficient. Various methods evaluated the micro-heterogeneity dynamics of DFILs.

Ion-exchange of copper into mordenite and clinoptilolite zeolites by molecular dynamics simulations and experimental investigations

Copper-exchanged zeolites have been subjected to several investigations because of their application as selective redox-active catalysts, and sensors. However, the ability of different types of zeolites to exchange Cu ions remains a matter of debate. All-atom molecular dynamics (MD) simulations, energy dispersive X-ray spectroscopy (EDS), and X-ray Fluorescence (XRF) methods have been used to evaluate the exchange of Cu(II) in mordenite and clinoptilolite zeolites using an aqueous method in the current study. Several parameters of copper ions have been measured for both types of zeolites, such as ion exchange ratio, mean square displacement (MSD), diffusion coefficient, and radial distribution function (RDF). These parameters were calculated for each zeolite system at different Cu ion concentrations in the feed solution. Copper exchange ratio and RDF analyses revealed a higher exchange ratio of copper ions in the mordenite framework. Analysis of the potential energy indicates the major adsorption sites for mordenite and clinoptilolite, which are located in the largest cavities of the zeolites. The adsorption energy of the mordenite sites (1.52 eV) was larger than that of clinoptilolite (1.28 eV). The stronger attraction between the copper ions and mordenite sites is consistent with the lower diffusion coefficients of the ions in this zeolite. The ion-exchange abilities of the zeolites were examined using EDS analysis. According to the EDS results, the mordenite zeolite exchanged more copper ions than the clinoptilolite, which is in agreement with the computational results.

Numerical simulation of the two-dimensional fractional Schrödinger equation for describing the quantum dynamics on a comb with the absorbing boundary conditions

This paper mainly contributes to investigating a distinctive fractional Schrödinger equation (FSE) for describing the quantum dynamics on a comb. The special characteristic of the comb is that the diffusion versus the x-direction only occurs on the x-axis. We replace the infinite boundary with the absorbing boundary conditions (ABCs), which can be obtained using the Laplace transform. We utilize the integration property to deal with the singularity function in the FSE and propose the finite difference method. The stability and convergence of this scheme are investigated. The L1 scheme to discretize the Caputo fractional derivative needs a particularly expensive computational and storage cost. To increase the calculation speed, a fast algorithm is used to improve the operation efficiency. By introducing a source term, the exact solution and the numerical solution are compared. The comparison of the CPU time for the L1 scheme and fast scheme is given. The comparison between the FSE on a comb and the classical one is also analyzed and discussed. The transport process versus the x-axis and the y-axis with various parameters are shown. Finally, the mean square displacement (MSD) is investigated. We find that the solution with the ABCs has a better agreement with the exact expression compared to the solution with truncated zero boundary conditions.

Investigating zero-point vibrations of solid hydrogen via statistical moment method

Zero-point vibrations of solid hydrogen are investigated by analyzing the molecular mean-squared displacement (MSD) and mean-squared relative displacement functions within the statistical moment method approach in statistical mechanics. Numerical computations of these thermodynamic properties were conducted for solid hydrogen from 0 K to its phase transition temperature using the Wigner-Kirkwood mean-field potential derived from the Buckingham exp-6 potential. We have shown that the quantum-mechanical zero-point vibrations play an important role at low temperature. And these thermodynamic quantities increase with temperature, suggesting that both thermal and quantum effects play a significant role near the liquid-solid phase transition. The favorable consistency between our findings and the recent experimental inelastic neutron scattering measurements of MSD attests to the potential of SMM as a novel approach for determining the atomic vibrations of solid hydrogen. This approach allows us to study these effects including the anharmonicity of lattice vibrations.

An exactly solvable model for non-Fickian transport in dynamically heterogeneous media

Abstract Diffusion, observed in various condensed phases, finds its theoretical background in Einstein’s theory of Brownian motion, characterized by the linear time-dependence of mean square displacement (MSD) denoting Fickian behavior and the Gaussian distribution of particle displacement. Nevertheless, diverse systems exhibit either non-linear, non-Fickian time-dependence of the MSD or non-Gaussian displacement distribution. Montroll and Weiss’s continuous-time random walk (CTRW) model and the stochastic diffusivity (SD) model have provided insights into anomalous diffusion phenomena and Fickian-yet-non-Gaussian transport in dynamically heterogeneous environments, respectively. Building upon these approaches, Song et al developed a generalized transport equation with an environment-dependent diffusion kernel, providing a quantitative explanation for non-Fickian MSD and non-Gaussian displacement distribution. Based on the generalized transport equation, this study introduces an exactly solvable model for a non-Gaussian displacement distribution, accommodating arbitrary time profiles in its MSD, including both Fickian and non-Fickian behaviors. Our findings confirm the model’s capability in describing such transport processes. Furthermore, the proposed model unifies the CTRW model under fast environmental fluctuations and the SD model under Fickian time dependencies, making it suitable for understanding tracer particle motion within explicit solvent or complex media.

Molecular Dynamics Simulations Reveal How Competing Protein-Surface Interactions for Glycine, Citrate, and Water Modulate Stability in Antibody Fragment Formulations.

The design of stable formulations remains a major challenge for protein therapeutics, particularly the need to minimize aggregation. Experimental formulation screens are typically based on thermal transition midpoints (Tm), and forced degradation studies at elevated temperatures. Both approaches give limited predictions of long-term storage stability, particularly at low temperatures. Better understanding of the mechanisms of action for formulation of excipients and buffers could lead to improved strategies for formulation design. Here, we identified a complex impact of glycine concentration on the experimentally determined stability of an antibody Fab fragment and then used molecular dynamics simulations to reveal mechanisms that underpin these complex behaviors. Tm values increased monotonically with glycine concentration, but associated ΔSvh measurements revealed more complex changes in the native ensemble dynamics, which reached a maximum at 30 mg/mL. The aggregation kinetics at 65 °C were similar at 0 and 20 mg/mL glycine, but then significantly slower at 50 mg/mL. These complex behaviors indicated changes in the dominant stabilizing mechanisms as the glycine concentration was increased. MD revealed a complex balance of glycine self-interaction, and differentially preferred interactions of glycine with the Fab as it displaced hydration-shell water, and surface-bound water and citrate buffer molecules. As a result, glycine binding to the Fab surface had different effects at different concentrations, and led from preferential interactions at low concentrations to preferential exclusion at higher concentrations. During preferential interaction, glycine displaced water from the Fab hydration shell, and a small number of water and citrate molecules from the Fab surface, which reduced the protein dynamics as measured by root-mean-square fluctuation (RMSF) on the short time scales of MD. By contrast, the native ensemble dynamics increased according to ΔSvh, suggesting increased conformational changes on longer time scales. The aggregation kinetics did not change at low glycine concentrations, and so the opposing dynamics effects either canceled out or were not directly relevant to aggregation. During preferential exclusion at higher glycine concentrations, glycine could only bind to the Fab surface through the displacement of citrate buffer molecules already favorably bound on the Fab surface. Displacement of citrate increased the flexibility (RMSF) of the Fab, as glycine formed fewer bridging hydrogen bonds to the Fab surface. Overall, the slowing of aggregation kinetics coincided with reduced flexibility in the Fab ensemble at the very highest glycine concentrations, as determined by both RMSF and ΔSvh, and occurred at a point where glycine binding displaced neither water nor citrate. These final interactions with the Fab surface were driven by mass action and were the least favorable, leading to a macromolecular crowding effect under the regime of preferential exclusion that stabilized the dynamics of Fab.

Investigation on Melting Curves and Phase Diagrams for CaO3 Using Deep Learning Potentials.

Melting in the deep rocky parts of planets plays an important role in geological processes such as planet formation, seismicity, magnetic field generation, thermal convection, and crustal evolution. Such processes are the key way to understanding the dynamics of planetary interiors and the history as well as mechanisms of planetary evolution. We herein investigate the melting curves and pressure-temperature (P-T)-phase diagrams for CaO3, a candidate mineral for the lower mantle, by means of the deep learning potential model. Using first-principles, molecular dynamics, and quasi-harmonic approximation, the reliability of the deep learning potential model is verified by calculating the high-temperature and high-pressure equations of state and phase transition pressures for the orthorhombic and tetragonal structures of CaO3 described by space groups Aea2 and P4̅21m, respectively. The melting temperatures of 975, 850, and 755 K at zero pressure are obtained by the single-phase, void, and two-phase methods, respectively, and their melting temperatures are analyzed by the radial distribution function and mean-square displacement to analyze the melting process. Finally, the melting phase diagrams of CaO3 at 0-135 GPa were obtained by the two-phase method.

Investigation of self-diffusion and specific heat capacity of eutectic al-si systems using molecular dynamics simulations with ADP

Aluminum-silicon (Al-Si) alloys are of significant interest in various engineering applications due to their favorable mechanical properties and low density. Understanding the thermodynamic and transport properties of these alloys is essential for optimizing their performance in practical applications. In this study, an angular dependent potential (ADP) for Al-Si systems is employed to describe the atomic interactions and dynamics of an Al-Si alloy system. A set of molecular dynamics (MD) simulations are performed to explore the diffusion behavior of the Al-Si alloy at different temperatures, with a specific focus on the eutectic composition of the Al-Si system. The mean squared displacement (MSD) method is applied to calculate its diffusion coefficients, enabling a detailed analysis of the system’s atomic mobility and transport characteristics. Furthermore, the specific heat capacity of the Al-Si system is determined through energy fluctuation analysis, providing insights into the system’s thermodynamic behavior. The obtained diffusion coefficients play a vital role in predicting the kinetics of the eutectic solidification of Al-Si alloys, while the specific heat capacity will facilitate the understanding of the thermal behavior and the energy changes associated with the eutectic reaction in such alloys.

Differentiation between high-grade gliomas and solitary brain metastases based on multidiffusion MRI model quantitative analysis.

Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional magnetic resonance imaging (MRI) remains challenging due to their similar imaging features. This study aimed to evaluate the diagnostic performance of advanced diffusion models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator magnetic resonance imaging (MAP-MRI), incomparison to traditional techniques like diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) for distinguishing HGGs from SBMs. In total, 17 patients with HGGs and 26 patients with SBMs were prospectively recruited based on the established inclusion and exclusion criteria. Structural MRI sequences and diffusion spectrum imaging (DSI) were utilized to assess quantitative parameter models, including NODDI, MAP-MRI, DWI, DTI, and DKI. Quantitative parameters were measured for both the tumor parenchymal area and the peritumoral edema area. The quantitative parameters of the two patient groups were compared using either the independent Student's t-test or the Mann-Whitney U test. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Finally, the DeLong test was employed to compare the diagnostic performance of each model through pairwise comparisons of ROC curves. Isotropic volume fraction (Viso) based on NODDI; mean squared displacement (MSD) and the return to plane probabilities (RTPP) based on MAP-MRI; radial diffusivity (RDk) and mean diffusivity (MDk) based on DKI; and axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) based on DTI of the peritumoral edema tumor were significantly different between HGGs and SBMs (p < 0.05). The optimal single discriminant parameters for each model are NODDI_Viso, MAP-MRI_MSD, DKI_MDk, and DTI_AD. Among these, the AUC of Viso (0.809) exceeds that of MSD (0.733), MDk (0.718), and AD (0.779). The combined model, which incorporates DTI_AD, DKI_RD, and NODDI_Viso, demonstrated superior diagnostic performance (0.897). Advanced diffusion MRI quantitative parameters derived from NODDI, such as Viso, have the potential to enhance the differentiation between HGGs and SBMs. The integrated utilization of these models is anticipated to enhance diagnostic accuracy and refine MRI protocols for brain tumor assessment.

Computational exploration of novel ketoprofen derivatives: Molecular dynamics simulations and MM-PBSA calculations for COX-2 inhibition as promising anti-inflammatory drugs

Computer-aided drug design is widely employed to identify novel compounds for therapeutic applications. Ketoprofen (KTP), a commonly used and marketed nonsteroidal anti-inflammatory drug (NSAID), is effective in treating pain, fever, inflammation, and some cancers. In this research, we explored the behavior of six analogues designed by structurally modifying the KTP molecule. Specifically, KTP-A and KTP-B contain a –CN group at the ortho position, KTP-C and KTP-D have a –CN group at the meta position, and KTP-E and KTP-F feature a –CF3 group at the meta position. To assess these analogues, we conducted molecular dynamics simulations (MD) to study their inhibitory effects on human cyclooxygenase 2 (COX-2), providing detailed insights into the structure and dynamics of the protein both with and without ligands. MD simulation, enhanced by technological advances, has proven to be a powerful tool for new drug discovery. We further quantified the binding affinity of these drug molecules toward COX-2 using molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations. The dynamic properties were evaluated through analyses of root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), covariance matrix, principal component analysis (PCA), and Gibbs free energy landscapes (FEL). Ultimately, this study confirms that the six KTP derivatives are promising candidates for the treatment of inflammation, with KTP-B standing out as particularly effective.

Evaluation of tamoxifen analogues as potential estrogen receptor alpha inhibitors for breast cancer treatment: A computational approach

Estrogen receptors, particularly ERα, play a key role in breast cancer progression, making them prime targets for therapeutic intervention. Tamoxifen (TAM), a selective estrogen receptor modulator (SERM), has been widely used for the treatment of ER+ breast cancer; however, its clinical application is limited by side effects and the emergence of resistance. This study aims to identify and evaluate TAM analogues with improved efficacy and reduced side effects by employing molecular docking and molecular dynamics (MD) simulations. Droloxifene, endoxifen, and afimoxifene emerged as promising candidates, exhibiting strong binding affinities with ERα, as indicated by highly negative binding energy (BE) values in docking simulations. MD simulations further validated the stability of the complexes formed between these analogues and ERα, with low root mean square deviation (RMSD) values and stable radius of gyration (Rg) profiles. Root mean square fluctuation (RMSF) analysis revealed balanced flexibility, with droloxifene and afimoxifene showing optimized flexibility for stable binding. Hydrogen bond analysis indicated more stable interactions between these analogues and ERα compared to TAM, suggesting enhanced binding affinity. MM/GBSA binding free energy analysis confirmed the high affinity of these analogues, with droloxifene displaying the most effective binding free energy (ΔGtotal) value. ADMET profiling suggests that droloxifene and endoxifen have superior pharmacokinetic properties relative to TAM. Overall, droloxifene, endoxifen, and afimoxifene represent promising alternatives to TAM, with the potential for further clinical development in breast cancer treatment. Experimental validation in cell-based and in vivo models will be crucial in future studies to confirm their efficacy and safety profiles.

Capture behavior of self-propelled particles into a hexatic ordering obstacle

Abstract Computer simulations are utilized to investigate the dynamic behavior of self-propelled particles (SPPs) within a complex obstacle environment. The findings reveal that SPPs exhibit three distinct aggregation states within the obstacle, each contingent on specific conditions. A phase diagram outlining the aggregation states concerning self-propulsion conditions is presented. The results illustrate a transition of SPPs from a dispersion state to a transition state as persistence time increases within the obstacle. Conversely, as the driving strength increases, self-propelled particles shift towards a cluster state. A systematic exploration of the interplay between driving strength, persistence time, and matching degree on the dynamic behavior of self-propelled particles is conducted. Furthermore, an analysis is performed on the spatial distribution of SPPs along the y-axis, capture rate, maximum capture probability, and mean-square displacement. The insights gained from this research serve as valuable contributions to understanding the capture and collection of active particles.

Experimental and theoretical investigations of a novel imidazoline quaternary ammonium salt as an effective inhibitor of Q235 steel in 1 M HCl

In this paper, the inhibition efficiency and mechanism of a newly synthesized imidazoline-pyridine quaternary amine salt (IPS) as a corrosion inhibitor for carbon steel in 1.00 mol/L HCl at different temperatures were investigated experimentally and theoretically. The inhibitor is confirmed by nuclear magnetic resonance spectroscopy (NMR) and fourier transform infrared spectroscopy (FT-IR). Electrochemical and weight loss indicate that the IPS displays a stable protection performance at different temperatures. Moreover, scanning electron microscopy (SEM), energy dispersive spectrometer (EDS) and X-ray photoelectron spectroscopy (XPS) indicates that the IPS can be stably adsorbed on Q235 steel surface. Molecular dynamics (MD) show that mainly imidazole and pyridine rings of IPS are adsorbed on the surface of Fe. Moreover, radial distribution function (RDF) and the mean-square displacement (MSD) were used to study inhibitor/metal interactions and migration rate of corrosive species, respectively. The results can provide useful guidance for further study on the corrosion inhibition of imidazole-pyridine quaternary amine salts.

Relaxation dynamics of a liquid in the vicinity of an attractive surface: The process of escaping from the surface.

We analyze the displacements of the particles of a glass-forming molecular liquid perpendicular to a confining solid surface using extensive molecular dynamics simulations with atomistic models. In the vicinity of an attractive surface, the liquid molecules are trapped. Transient localization of liquid molecules near the surface introduces a relaxation process related to the escape of molecules from the surface into the dynamics of the interfacial liquid layer. To describe this process, we analyze several dynamical observables of the confined liquid. The self-intermediate scattering function and the mean-squared displacement of the particles located in the interfacial layer are dominated by the process of escaping from the surface. This relaxation process is also associated with a strong heterogeneity in the mobility of the interfacial particles. The studied model liquid is hydrogenated methyl methacrylate. For the confining wall, we consider different models, namely a periodic single layer of graphene and a frozen amorphous configuration of the bulk liquid (frozen wall). Near graphene, where the liquid molecules form a layered structure and adopt parallel-to-surface orientation, a clear separation between small-scale movements of the molecules near the surface and the process of escaping from the surface is observed. This is reflected in the three-step relaxation of the interfacial layer. However, near the frozen wall, where the liquid molecules do not have a preferential alignment, a clear three-step relaxation is not seen, even though the dynamical quantities are controlled by the process of escaping from the surface.

DFT based investigations on inherent CO2 adsorption and direct dissociation capability of Ti2C and Nb2C mxenes

Transition metal carbide MXenes, specifically Ti2C and Nb2C, have been investigated for their ability to efficiently adsorb and dissociate CO2 using First Principles Calculations based on Density Functional Theory (FPS-DFT). Pure Ti2C and Nb2C sheets were studied with the adsorption of 1 to 4 CO2 molecules, and the results were analyzed for each case. For 4 CO2 molecules adsorbed on Ti2C and Nb2C sheets, the weight percentage (wt%) ratio was found to be 21.39% and 14.33%, respectively. The Density of States (DOS) analysis revealed that, upon CO2 adsorption, the CO2 molecule dissociates into CO and O atoms on the MXene surface. The CO molecule showed no significant hybridization with the host sheet atoms, whereas the O atom exhibited strong hybridization with the MXene surface. Transition State (TS) profiles illustrated the dissociation steps on both Ti2C and Nb2C surfaces. Phonon calculations confirmed the dynamic stability of both pure and CO2 adsorbed MXenes. Molecular Dynamics (MD) simulations conducted at 900 K indicated uniform temperature and Mean Square displacement (MSD) profiles, suggesting the stability of both pure and CO2 adsorbed MXenes at elevated temperatures, as well as uniform CO2 adsorption behavior. The adsorption energies for Ti2C and Nb2C sheets were calculated to be in the range of -1.89 to -2.77eV, suggesting that the adsorption process is favorable, spontaneous, and predominantly involves chemisorption. These findings indicate that Ti2C and Nb2C MXenes, in their intrinsic forms, are promising candidates for CO2 adsorption and dissociation technologies.

H2 diffusion in cement nanopores and its implication for underground hydrogen storage

Understanding the transport and adsorption characteristics of hydrogen (H2) in calcium silicate hydrate (C-S-H) nanopores is critical to minimize the leakage risks from cement in the wellbore region during underground H2 storage (UHS). However, the critical physiochemical properties of H2 in C-S-H nanopores remain inadequately understood. In this work, we perform molecular dynamics simulations to comprehensively investigate the H2 distribution and diffusion properties in the C-S-H nanopores, considering the crucial parameters of temperature, pressure, and pore size. We evaluate how the density distribution, mean squared displacement (MSD) and diffusion coefficient of H2 evolve with variations in these crucial parameters by comparing H2 properties in C-S-H nanopores with those of bulk H2. We show that H2 molecules are prone to adsorb on C-S-H walls and form a high-density adsorption layer due to strong interactions between C-S-H walls and H2. We find that the confinement of C-S-H nanopores significantly limits the diffusion of H2, leading to smaller diffusion coefficients. Moreover, the diffusion of H2 demonstrates pronounced anisotropic characteristics, with H2 diffusing significantly faster in the direction parallel to C-S-H walls than in the direction perpendicular to the C-S-H walls. We demonstrate that there is a critical pressure, beyond which the diffusion coefficient of H2 parallel to C-S-H walls is close to that in the bulk phase and remains stable. We also show that the impact of nano-confinement gradually diminishes with increasing pore size. Under a given temperature/pressure condition, once the pore size exceeds a threshold, the H2 diffusion coefficient in the C-S-H nanopore is close to that of bulk H2. Our results provide valuable insights into H2 diffusion and adsorption in the C-S-H nanopores at the molecular level, which is critical to assessing and minimizing H2 leakage risks from cement in the wellbore.

Phytobioinformatics screening of ayurvedic plants for potential α-glucosidase inhibitors in diabetes management

The enzyme α-glucosidase in the small intestine regulates blood glucose levels and stimulates the hydrolysis of oligosaccharides and polysaccharides, increasing glucose levels in the body. Inhibiting this enzyme slows glucose digestion and absorption and as a result post-prandial blood glucose levels remain low, causing decreased insulin demand. Here, we investigated the ayurvedic antidiabetic plants and virtually screened an in-house library of 478 phytochemicals of these plants against the human α-glucosidase. We identified 11 secondary metabolites, including palmitic acid α-monoglyceride, (+)-(2 R)-6-propionyloxyethyl-4′,5,7-trihydroxyisoflavanone, Abruquinone E, and Aurantiamide Acetate, among others, showed stronger interactions with the receptor than the native ligand N-acetyl cysteine. Surprisingly, except one, all of these metabolites were from Abrus precatorius L. [Fabaceae] affirming its ethnopharmacological use against diabetes. The stability of the interactions between the ligands and receptor protein was evaluated through Molecular Dynamic (MD) simulation trajectories including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), H bonds, β-factor analysis, and binding energy calculation through MM/GBSA method. The efficacy of top metabolites in inhibiting α-glucosidase is depicted in pharmacophore analysis. A comprehensive pharmacokinetics analysis confirmed the druggability, safety, and efficiency of top drug candidates. Additionally, we predicted the interactions of these top metabolites within the biological system. The medicinal properties described in this study will help develop active drug candidates for therapeutic purposes. Further experiments are recommended to prove the effectiveness of these metabolites in inhibiting the α-glucosidase enzyme for exploring their potential in the treatment of diabetes.

Molecular Dynamics Simulation Insights into Hydrogen Bonding‐Mediated Conformational Changes Topoisomerase‐IB

AbstractTopoisomerase‐IB changes the topological state of DNA during central dogma by the formation of intermediate bond in between active amino acid and DNA strand. How the hydrogen bonding provides hooks restriction during the topological change and gives the conformational change. This study employs a 200 ns Molecular Dynamics (MD) simulation to analyze the conformational changes of Topo‐IB resulting from artificially created intermediate bonds. Specifically, the study focuses on hydrogen bonding interactions between Tyrosine at position Y509 in the protein and Thymine at DT561 in the DNA. The investigation reveals that these artificial intermediate bonds act as temporary hooks, stabilizing the complex's structure, and driving significant conformational changes. The analysis of Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) values underscores the dynamic nature of the complex, with artificial intermediate bonds playing a pivotal role.