Molecular Dynamics Simulation Data Research Articles

Passiflora edulia Sims leaves Extract as renewable and degradable inhibitor for copper in sulfuric acid solution

In this research, we obtained Passiflora edulia Sims leaves Extract (PESLE) using a simple and green pure water extraction method. Experiment and theoretical calculations data show that PESLE can effectually restrain Cu corrosion in H2SO4 medium. Electrochemical results demonstrate that the PESLE is 800 mg/L, its anti-corrosion nature can reach about 96%. And with the augment of temperature, the anti-corrosion capacity of PESLE can still reach about 95% at a temperature of 318 K. SEM and AFM morphology test data show that PESLE is adsorbed onto the copper interface, the copper sample is effectively protected and the surface becomes relatively flat. The morphology test results directly prove that PESLE efficaciously restrain the corrosion of Cu in H2SO4 environment. XPS test results show that PESLE adsorption onto the Cu interface can detect Cu-N bond, which proves that chemical adsorption occurs. Quantum chemistry calculation data manifest that the three components of PESLE can reveal high anti-corrosion property. Molecular dynamics simulation data manifest the three components of PESLE can be adsorbed at the Cu (111) surface with paralleled way, and can have a large binding energy.

Toughening mechanism based on the physical entanglement of branched epoxy resin in the non-phase-separated inhomogeneous crosslinking network: An experimental and molecular dynamics simulation study

A type of branched epoxy resin (BEP) with side alkyl chains was prepared by the thiol-ene reaction and used as the copolymerization toughening agent of diglycidyl ether of bisphenol A (ER). The content of BEP on the final properties of the BEP/ER copolymerization toughening system (CPTS) was systematically studied by experimental and molecular dynamics simulation (MDS) data. The results suggest that the BEP/ER CPTS exhibited non-phase-separated inhomogeneous crosslinking network and SEM morphologies can be observed nanoscale aggregate structures, which are formed by the physical entanglement of side alkyl chains in BEP due to the polarity difference between side alkyl chains of BEP and the crosslinking backbone chains. Based on the existence of the additional physical crosslinking points that provided by the physical entanglement of side alkyl chains in BEP, the BEP/ER CPTS can exhibit striking comprehensive mechanical properties. The tensile strength, tensile modulus, elongation at break, and impact strength can be simultaneously improved in the BEP-5 system and reach 101.2 MPa, 2.8 GPa, 4.3%, and 22.5 kJ/m2, respectively. This study not only presents a new toughening strategy through the formation of non-phase-separated inhomogeneous crosslinking network by using facile prepared BEP as the toughening agent, but also provides a theoretical explanation for the generation of physical entanglement in the non-phase-separated inhomogeneous crosslinking network through the MDS data.

In-silico Studies Calculated a New Chitin Oligomer Binding Site Inside Vicilin: A Potent Antifungal and Insecticidal Agent.

Vicilins are major seed storage proteins and show differential binding affinities toward sugar moieties of fungal cell wall and insect gut epithelium. Hence, purpose of study is the thorough in-silico characterization of interactions between vicilin and chitin oligomer followed by fungal and insecticidal bioassays. This work covers the molecular simulation studies explaining the interactions between Pisum sativum vicilin (PsV) and chitin oligomer followed by protein bioassay against different pathogens. LC-MS/MS of purified PsV (∼50 kDa) generated residual data along high pea vicilin homology (UniProtKB ID; P13918). Predicted model (PsV) indicated the characteristic homotrimer joined through head-to-tail association and each monomer is containing a bicupin domain. PsV site map analysis showed a new site (Site 4) into which molecular docking confirmed the strong binding of chitin oligomer (GlcNAc)4. Molecular dynamics simulation data (50 ns) indicated that chitin-binding site was comprised of 8 residues (DKEDRNEN). However, aspartate and glutamate significantly contributed in the stability of ligand binding. Computational findings were further verified via significant growth inhibition of Aspergillus flavus, A. niger, and Fusarium oxysporum against PsV. Additionally, the substantial adult population of Brevicoryne brassicae was reduced and different life stages of Tribolium castaneum also showed significant mortality.

Bioassay-guided isolation of human carboxylesterase 2 inhibitory and antioxidant constituents from Laportea bulbifera: Inhibition interactions and molecular mechanism

Laportea bulbifera (Sieb. et. Zucc.) Wedd has long been utilized in Traditional Chinese Medicines (TCM) for the treatment of rheumatoid arthritis. However, the study of systematic anti-inflammatory chemical constituents in L. bulbifera has never been reported. Thus, bioassay-guided isolation for its roots part led to 46 compounds, including 38 phenolic derivatives. Their structures were determined on the basis of 1H and 13C NMR and MS spectra. All compounds were isolated from L. bulbifera for the first time except for 13 compounds. Most of the compounds showed good COX-2 inhibitory activity (IC50: 0.13–3.94 μM) and DPPH radical-scavenging activity (IC50: 1.57–9.55 μM). Four compounds (4, 17, 35, and 43) with different skeletons showed preferential COX-2 over COX-1 inhibition with selective indices ranging from 12 to 171. High content active compounds are important for elucidating the basis of the active substance of TCM. Compound 4 (COX-2, IC50 0.24 μM), a high content compound, represented one of the best selective COX-2 inhibitors. Another high content active compound (35) with a different skeleton might have different mechanism. Further study for the inhibition kinetics against COX-2 indicated compounds 4 and 35 were noncompetitive and competitive COX-2 inhibitors, respectively. Moreover, molecular docking and molecular dynamics simulation data further indicated that compound 4 could bind in the cavity of COX-2 and interacted with key residues VAL-538, PHE-142, and GLY-225 of COX-2 through hydrogen bonds. The results indicated that L. bulbifera roots could be applied as antioxidant and anti-inflammatory agents due to their potent selective COX-2 inhibitory and antioxidant activity of phenolic compounds.

In Situ Monitoring of Scale Effects on Phase Selection and Plasmonic Shifts during the Growth of AgCu Alloy Nanostructures for Anticounterfeiting Applications

Tailoring of plasmon resonances is essential for applications in anticounterfeiting. This is readily achieved by tuning the composition of alloyed metal clusters; in the simplest case, binary alloys are used. Yet, one challenge is the correlation of cluster morphology and composition with the changing optoelectronic properties. Hitherto, the early stages of metal alloy nanocluster formation in immiscible binary systems such as silver and copper have been accessible by molecular dynamics (MD) simulations and transmission electron microscopy (TEM). Here, we investigate in real time the formation of supported silver, copper, and silver–copper-alloy nanoclusters during sputter deposition on poly(methyl methacrylate) by combining in situ surface-sensitive X-ray scattering with optical spectroscopy. While following the transient growth morphologies, we quantify the early stages of phase separation at the nanoscale, follow the shifts of surface plasmon resonances, and quantify the growth kinetics of the nanogranular layers at different thresholds. We are able to extract the influence of scaling effects on the nucleation and phase selection. The internal structure of the alloy cluster shows a copper-rich core/silver-rich shell structure because the copper core yields a lower mobility and higher crystallization tendency than the silver fraction. We compare our results to MD simulation and TEM data. This demonstrates a route to tailor accurately the plasmon resonances of nanosized, polymer-supported clusters which is a crucial prerequisite for anticounterfeiting.

Genetic programming-assisted micromechanical models of graphene origami-enabled metal metamaterials

Graphene origami (GOri) enabled metallic metamaterials are novel nanomaterials simultaneously possessing negative Poisson's ratio (NPR) and enhanced mechanical properties that are independent of the topology/architecture of the structure. Predicting their material properties via existing micromechanical models, however, is a great challenge. In this paper, a highly efficient micromechanical modeling approach based on molecular dynamics (MD) simulation and genetic programming (GP) algorithm is developed to address this key issue. The GP-based Halpin-Tsai model is extensively trained from MD simulation data to accurately predict the Young's modulus of GOri/Cu metamaterials with various GOri folding degrees, graphene contents and temperatures with a high coefficient of determination (R2) of ∼0.95. Meanwhile, the well-trained GP-based rule of mixture can accurately predict the coefficient of thermal expansion (CTE), Poisson's ratio and density of metamaterials with R2 of ∼0.95, ∼0.93 and ∼0.99, respectively. The excellent agreement between our estimated results and experimental data shows that the models developed herein are highly efficient and accurate in predicting mechanical properties that are essential for the analysis and design of functionally graded metal metamaterial composite structures. The theoretical results demonstrate that the proposed functionally graded metamaterial beam achieves significantly improved bending performance.

Fracture of model end-linked networks.

Advances in polymer chemistry over the last decade have enabled the synthesis of molecularly precise polymer networks that exhibit homogeneous structure. These precise polymer gels create the opportunity to establish true multiscale, molecular to macroscopic, relationships that define their elastic and failure properties. In this work, a theory of network fracture that accounts for loop defects is developed by drawing on recent advances in network elasticity. This loop-modified Lake-Thomas theory is tested against both molecular dynamics (MD) simulations and experimental fracture measurements on model gels, and good agreement between theory, which does not use an enhancement factor, and measurement is observed. Insight into the local and global contributions to energy dissipated during network failure and their relation to the bond dissociation energy is also provided. These findings enable a priori estimates of fracture energy in swollen gels where chain scission becomes an important failure mechanism.

On the equivalence of Eulerian Smoothed Particle Hydrodynamics, Total Lagrangian Smoothed Particle Hydrodynamics and molecular dynamics simulations for solids

Significant advances in nanoscale research have enabled the continuous miniaturization of devices. With the reduction in the size of the devices, it is important to identify if the continuum scale methods remain applicable to such small-scale systems. Motivated by this, the present work tries to understand the equivalence, or its lack thereof, of the continuum scale Eulerian Smoothed Particle Hydrodynamics (ESPH) and Total Lagrangian Smoothed Particle Hydrodynamics (TLSPH) with the atomistic scale molecular dynamics (MD) simulations. The equivalence is studied using four simple problems — (i) uniaxial tensile testing of a beam, (ii) stress profile in a pre-notched plate under small extension, (iii) head-on collision of two elastic rubber-like rings, and (iv) large deformation of a cantilever beam subjected to an impact at the free end. Using MD simulation data as the pseudo-experimental data, we show that both ESPH and TLSPH provide results that are qualitatively and quantitatively in agreement with the MD simulations if the properties at the continuum scale are obtained directly from the MD simulations, and the same initial conditions are chosen. The comparisons are based on the stress–strain behavior, the distribution of normal and shear stresses, the temporal evolution of the variables such as kinetic energy, etc.

Coarse-grain mechanical modelling of cg islands

CpG islands are the regions of the genome that contain a large number of sites with a non-methylated cytosine nucleotide followed by a guanine. CpG islands are associated with most gene promoters in mammals. Methylation in CpG islands often results in gene silencing. Despite the significance of these regions, their mechanical properties have not been widely investigated. We employ the cgDNA+ coarse-grain model of DNA to understand the structure and flexibility of CpG islands. It has been demonstrated that the cgDNA+ model, trained on large scale atomistic Molecular Dynamics simulation data, can accurately and efficiently predict the equilibrium distribution of sequence-dependent DNA configurations.

Interaction Studies between Carbonic Anhydrase and a Sulfonamide Inhibitor by Experimental and Theoretical Approaches

The most used approaches in structure-based drug design possess peculiar characteristics with advantages and limitations, and thus the management of complementary data from various techniques is of particular interest to synergistically achieve the development of effective enzyme inhibitors. In this Letter, we describe the application of experimental and computational techniques to study the interactions between human carbonic anhydrases and sulfonamide inhibitors. In particular, a series of affinity-labeled carbonic anhydrase inhibitors containing sulfonamido photoprobes was designed and synthesized, and one of these compounds, a benzophenone derivative, was chosen as a model photoprobe/inhibitor. A photoaffinity labeling method followed by mass spectrometry analysis was then applied to elucidate the inhibitor binding site, and a comparison with X-ray crystallography and molecular dynamics simulation data was carried out, highlighting that to have a comprehensive view of the protein/inhibitor complex stabilization all three kinds of experiments are necessary.

Multiscale Constitutive Modeling of the Mechanical Properties of Polypropylene Fibers from Molecular Simulation Data

We present a multiscale approach to create a constitutive model that predicts the mechanical properties of polypropylene fibers based on chemical and physical characteristics. The development of this method relies on validation with experimental stress–strain curves from nine different isotactic polypropylene (iPP) fibers with their varying molecular weight characteristics, Hermans orientation factors, and crystallinity. Complementary molecular models were built by using molecular dynamics (MD) simulations with united atom models. Tensile deformation simulations adapting a quasi-static procedure resulted in stress–strain curves that aligned well with the experimentally measured ones. A neural network model was trained on the MD simulation data to create correlations that predict parameters for a chosen constitutive model that describes the mechanical properties of the polypropylene fibers. This computational approach is amenable to be applied to polymer fiber systems and aims to aid in the design of polymeric materials to achieve targeted mechanical properties.

A method to construct the dynamic landscape of a bio-membrane with experiment and simulation

Biomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.

Evaluation of immune evasion in SARS-CoV-2 Delta and Omicron variants

Emerging SARS-CoV-2 variants with higher transmissibility and immune escape remain a persistent threat across the globe. This is evident from the recent outbreaks of the Delta (B.1.617.2) and Omicron variants. These variants have originated from different continents and spread across the globe. In this study, we explored the genomic and structural basis of these variants for their lineage defining mutations of the spike protein through computational analysis, protein modeling, and molecular dynamic (MD) simulations. We further experimentally validated the importance of these deletion mutants for their immune escape using a pseudovirus-based neutralization assay, and an antibody (4A8) that binds directly to the spike protein's NTD. Delta variant with the deletion and mutations in the NTD revealed a better rigidity and reduced flexibility as compared to the wild-type spike protein (Wuhan isolate). Furthermore, computational studies of 4A8 monoclonal antibody (mAb) revealed a reduced binding of Delta variant compared to the wild-type strain. Similarly, the MD simulation data and virus neutralization assays revealed that the Omicron also exhibitsimmune escape, as antigenic beta-sheets appear to be disrupted. The results of the present study demonstrate the higher possibility of immune escape and thereby achieved better fitness advantages by the Delta and Omicron variants, which warrants further demonstrations through experimental evidences. Our study, based on in-silico computational modelling, simulations, and pseudovirus-based neutralization assay, highlighted and identified the probable mechanism through which the Delta and Omicron variants are more pathogenically evolved with higher transmissibility as compared to the wild-type strain.

A molecular mechanics and molecular dynamics study of the structural organization of Cu(II), Ni(II), Co(II), and Fe(II) stearates as potential catalysts for in situ upgrading of heavy oil

Metal stearates may show a substantial catalytic effect in the thermal methods of in situ upgrading of heavy oil. Their good solubility in oil makes it possible to efficiently distribute them over oil reservoirs. Furthermore, in situ synthesis of metal oxide and metal sulfide nanoparticles is possible under conditions of steam injection or other thermal treatments. The initial molecular structure and arrangement of molecules of copper, nickel, cobalt, and iron transition metal stearates are elucidated using the molecular mechanics and molecular dynamics methods. All the simulated complexes are arranged into lamellar layers with additional arrangement of aliphatic chains and metal atoms in two-dimensional periodic arrays. According to the molecular dynamics simulation data, the disordering of hydrocarbon chains and the overall molecular organization takes place at high temperatures. The simulated structures can be further used for studying the solubility of the studied metal stearates in hydrocarbons and the mechanisms of nanoparticle formation from them under conditions used for in situ upgrading of heavy oil.

Phase behavior and extraction mechanism of methanol-n-hexane separation using choline-based deep eutectic solvent

Deep eutectic solvents (DESs) have attracted increasing attention as green solvents in recent years owing to their potential for use in azeotropic separation and their advantages, such as low vapor pressure, non-toxicity, and low cost. To separate methanol (MeOH)-n-hexane (NHA) azeotrope, three choline-based DESs were prepared using glycerol, ethylene glycol (EG), and urea as the hydrogen bond receptors. The liquid–liquid equilibrium (LLE) data of DES-MeOH-NHA were measured at 298.15 K and 1 atm. The distribution coefficient and selectivity were obtained to compare the extraction efficiencies of different DESs. To further explore the extraction mechanism of LLE, the molecular dynamics (MD) method was used to study the internal mechanism of MeOH extraction by DESs. In addition, the experimental and MD simulation data were compared. Based on the MD simulation, the interaction energies between DES and MeOH/NHA, radial distribution function, and spatial distribution function between DES and MeOH were obtained. In addition, the experimental results were in good agreement with the simulation results, and both the results established that choline chloride (ChCl)/EG(1:2) had the highest extraction efficiency for methanol among the three DESs. Additionally, MD simulation results showed that Cl- plays a vital role in the LLE, and the interaction force between Cl- and MeOH was primarily provided by the electrostatic force.

Molecular dynamics simulation of metallic Al-Ce liquids using a neural network machine learning interatomic potential.

Al-rich Al-Ce alloys have the possibility of replacing heavier steel and cast irons for use in high-temperature applications. Knowledge about the structures and properties of Al-Ce alloys at the liquid state is vital for optimizing the manufacture process to produce desired alloys. However, reliable molecular dynamics simulation of Al-Ce alloy systems remains a great challenge due to the lack of accurate Al-Ce interatomic potential. Here, an artificial neural network (ANN) deep machine learning (ML) method is used to develop a reliable interatomic potential for Al-Ce alloys. Ab initio molecular dynamics simulation data on the Al-Ce liquid with a small unit cell (∼200 atoms) and on the known Al-Ce crystalline compounds are collected to train the interatomic potential using ANN-ML. The obtained ANN-ML model reproduces well the energies, forces, and atomic structure of the Al90Ce10 liquid and crystalline phases of Al-Ce compounds in comparison with the ab initio results. The developed ANN-ML potential is applied in molecular dynamics simulations to study the structures and properties of the metallic Al90Ce10 liquid, which would provide useful insight into the guiding experimental process to produce desired Al-Ce alloys.

FSATOOL 2.0: An integrated molecular dynamics simulation and trajectory data analysis program.

Molecular dynamics simulation is important in the computational study of the biomolecules. In this paper, we upgrade our previous FSATOOL to version 2.0. It is no longer a plugin as before. Besides the existed enhanced sampling and Markov state model analysis module, FSATOOL 2.0 has three new features now. First, it contains a molecular dynamics simulation engine on both CPU and GPU device. The engine works with an embedded enhanced sampling module. Second, it can do the free energy calculation by various practical methods, including the weighted histogram analysis method and Gaussian mixture model. Third, it has many subroutines to process the trajectory data, such as principal component analysis, time-structure based independent component analysis, contact analysis, and Φ-value analysis. Most importantly, all these calculations are integrated into one package. The trajectory data format is compatible with all the modules. With a proper input parameter file, users can do the molecular dynamics simulation and data analysis work by only a few simplified commands. The capabilities and theoretical backgrounds of FSATOOL 2.0 are introduced in the paper.

Time-dependent principal component analysis: A unified approach to high-dimensional data reduction using adiabatic dynamics.

Systematic reduction of the dimensionality is highly demanded in making a comprehensive interpretation of experimental and simulation data. Principal component analysis (PCA) is a widely used technique for reducing the dimensionality of molecular dynamics (MD) trajectories, which assists our understanding of MD simulation data. Here, we propose an approach that incorporates time dependence in the PCA algorithm. In the standard PCA, the eigenvectors obtained by diagonalizing the covariance matrix are time independent. In contrast, they are functions of time in our new approach, and their time evolution is implemented in the framework of Car-Parrinello or Born-Oppenheimer type adiabatic dynamics. Thanks to the time dependence, each of the step-by-step structural changes or intermittent collective fluctuations is clearly identified, which are often keys to provoking a drastic structural transformation but are easily masked in the standard PCA. The time dependence also allows for reoptimization of the principal components (PCs) according to the structural development, which can be exploited for enhanced sampling in MD simulations. The present approach is applied to phase transitions of a water model and conformational changes of a coarse-grained protein model. In the former, collective dynamics associated with the dihedral-motion in the tetrahedral network structure is found to play a key role in crystallization. In the latter, various conformations of the protein model were successfully sampled by enhancing structural fluctuation along the periodically optimized PC. Both applications clearly demonstrate the virtue of the new approach, which we refer to as time-dependent PCA.

Insights into the Structure and Dynamics of Imidazolium Ionic Liquid and Tetraethylene Glycol Dimethyl Ether Cosolvent Mixtures: A Molecular Dynamics Approach.

In this work, the effect of molecular cosolvents tetraethylene glycol dimethyl ether (TEGDME) on the structure and versatile nature of mixtures of these compounds with imidazolium-based ionic liquid 1-butyl-3-methylimidazolium hexafluorophosphate ([bmim][PF6]) is analyzed and discussed at a molecular level by means of all-atom molecular dynamics (MD) simulations. In the whole concentration range of the binary mixtures, the structures and properties evolution was studied by means of systematic molecular dynamics simulations of the fraction of hydrogen bonds, the radial and spatial distribution functions for the various molecular ions and molecular species in the system, together with the snapshots visualization of equilibrated simulation boxes with a color-coding scheme and the rotational dynamics of coumarin 153 (C153) in the binary mixtures. The goal of the work is to provide a molecular-level understanding of significant improvement of ionic conductivity and self-diffusion with the presence of TEGDME as a cosolvent, which causes an enhancement to the ion translational motion and fluidity in the [bmim][PF6] ionic liquids (ILs). Under a mixture concentration change, the microstructure changes of [bmim][PF6] with the TEGDME molar fraction (XTEG) above 0.50 show a slight difference from that of neat [bmim][PF6] IL and concentrated [bmim][PF6]/TEGDME mixture in terms of the radial and spatial distribution functions. The relative diffusivities of solvent molecules to cations as a function of concentration were found to depend on the solvent but not on the anion. A TEGDME increase is found to be advantageous to the dissipation of the polar regions as well as the nonpolar regions in the [bmim][PF6] ionic liquids. These conclusions are consistent with the experimental results, which verified that the unique, complex, and versatile nature of [bmim][PF6]/TEGDME mixture can be correctly modeled and discussed at a molecular level using MD simulation data.

Where is the hydrodynamic limit?

ABSTRACT In this paper, the classical hydrodynamic theory is compared to molecular dynamics simulation data using two different dynamical modes, namely, the transverse and longitudinal modes. The comparison is based on the dynamics of the equilibrium fluctuations for four different systems, the Lennard-Jones system, model liquids for butane, toluene, and water. Using an error estimator limit of 1%, it is found that for the transverse dynamics the classical hydrodynamic theory holds down to 5–14 nm depending on the fluidic system. For the longitudinal dynamics, this characteristic length scale is approximately doubled. From the dispersion relations, it is furthermore concluded that classical hydrodynamics qualitatively accounts for the dominating processes at even lower length scales.