Mesoscopic dynamics of colloids simulated with dissipative particle dynamics and fluid particle model

We report results of numerical simulations of complex fluids, using a combination of discrete-particle methods. Our molecular modeling repertoire comprises three simulation techniques: molecular dynamics (MD), dissipative particle dynamics (DPD), and the fluid particle model (FPM). This type of model can depict multi-resolution molecular structures (see the Figure) found in complex fluids ranging from single micelle, colloidal crystals, large-scale colloidal aggregates up to the mesoscale processes of hydrodynamical instabilities in the bulk of colloidal suspensions. We can simulate different colloidal structures in which the colloidal beds are of comparable size to the solvent particles. This undertaking is accomplished with a two-level discrete particle model consisting of the MD paradigm with a Lennard-Jones (L-J) type potential for defining the colloidal particle system and DPD or FPM for modeling the solvent. We observe the spontaneous emergence of spherical or rod-like micelles and their crystallization in stable hexagonal or worm-like structures, respectively. The ordered arrays obtained by using the particle model are similar to the 2D colloidal crystals observed in laboratory experiments. The micelle shape and its hydrophobic or hydrophilic character depend on the ratio between the scaling factors of the interactions between colloid–colloid to colloid–solvent. Unlike the miscellar arrays, the colloidal aggregates involve the colloid–solvent interactions prescribed by the DPD forces. Different from the assumption of equilibrium growth, the two-level particle model can display much more realistic molecular physics, which allows for the simulation of aggregation for various types of colloids and solvent liquids over a very broad range of conditions. We discuss the potential prospects of combining MD, DPD, and FPM techniques in a single three-level model. Finally, we present results from large-scale simulation of the Rayleigh–Taylor instability and dispersion of colloidal slab in 2D and 3D. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00894-001-0068-3.Electronic Supplementary Material available.     

Structural Transformations of Ice at High Pressures Via Molecular Dynamics Simulations

Abstract

A simple classical model is used for the study of the structural transformations of ice under high pressures, such as ice VIII to VII and X, via classical molecular dynamics (MD) simulation. In the present MD simulation, pair potentials of a simple form between pair of atoms and a thee-body potential representing the H-O-H angle dependence, originally developed by Kawamura et al., were used. Starting with a stable ice VIII at low pressure and low temperature, we have carried out two different MD runs, one with increasing pressure keeping the temperature constant (simulation I) and the other with increasing temperature under constant pressure (simulation II). From these MD simulations we have obtained the structural transformations from ice VIII to VII for both simulations; the former was finally transformed into ice X for the simulation I. The present results are compatible with recent experiments on high pressure ices.     

Some Recent Developments in Computational Chemistry

Abstract

Some recent developments in the use of computational methods to predict the properties of condensed phases are discussed; the use of Gibbs ensemble Monte Carlo to predict the phase equilibria of bulk phases, the use of molecular dynamics to elucidate Atomic Force Microscopy experiments on organic films, and the use of combined Monte Carlo/molecular dynamics techniques to enable the direct prediction of particle fluxes along pressure gradients in model microporous materials.     

An assessment of optimal time scale of conformational resampling for parallel cascade selection molecular dynamics

Parallel cascade selection molecular dynamics (PaCS-MD) has been proposed as a conformational sampling method for enhancing structural transitions from a given reactant to a product by repeating cycles of short-time MD simulations. In the present paper, we assessed how the time scale of a short-time MD simulation affected the computational efficiency by changing the simulation length. In conclusion, ps-order (t_ps) PaCS-MD simulations showed a higher computational efficiency as a total simulation time over the cycles than ns-order (t_ns) PaCS-MD simulations, indicating that t_ps might be suitable for generating structural transitions efficiently.     

On the similarity of properties in solution or in the crystalline state: A molecular dynamics study of hen lysozyme

As protein crystals generally possess a high water content, it is assumed that the behaviour of a protein in solution and in crystal environment is very similar. This assumption can be investigated by molecular dynamics (MD) simulation of proteins in the different environments. Two 2ns simulations of hen egg white lysozyme (HEWL) in crystal and solution environment are compared to one another and to experimental data derived from both X-ray and NMR experiments, such as crystallographic B-factors, NOE atom–atom distance bounds, ³J_{H N}-coupling constants, and ¹H-¹⁵N bond vector order parameters. Both MD simulations give very similar results. The crystal simulation reproduces X-ray and NMR data slightly better than the solution simulation.     

Molecular dynamics and dissipative particle dynamics simulations for prediction of miscibility in polyethylene terephthalate/polylactide blends

The miscibility of polyethylene terephthalate (PET)/polylactide (PLA) blends is studied through atomistic molecular dynamics (MD) and mesoscale dissipative particle dynamics (DPD) simulation. Five PET/PLA blends (with the weight ratio at 90/10, 70/30, 50/50, 30/70 and 10/90) as well as pure PET and PLA are examined. The solubility parameter values obtained by using the MD simulation are in good agreement with the reference data. The Flory–Huggins parameters, χ, which are computed for different blends and determined from the cohesive energy densities, with the radial distribution functions g(r) of the inter-molecular atoms, suggest that PET is completely miscible with PLA over the entire composition range. This is further proved by the mesoscopic morphologies of PET/PLA blends. All the simulation results are qualitatively consistent with the experimental results, and demonstrate that the modelling strategies in this study may serve as a powerful tool for predicting miscibility and mesoscopic morphology of polymer blends.     

Comparison of computational model and X-ray crystal structure of human serotonin transporter: potential application for the pharmacology of human monoamine transporters

Abstract

The human serotonin transporter (hSERT) played a significant role in neurological process whose structural basis had been analysed for many years. Recently, the first homology model was constructed for hSERT based on the crystal structure of drosophila melanogaster dopamine transporter was published, and the inhibitory mechanism underlying the binding mode between hSERT and approved antidepressants was substantially investigated by molecular dynamics (MD) simulation. Right after this publication, the X-ray crystallographic structures of hSERT were reported, which provided a good opportunity to reassess the performance of previous simulation. In this study, the analyses of side-chain contact map, stereochemical quality and ligand-binding pocket were firstly conducted, which revealed that the constructed homology model of hSERT could successfully reproduce the reported crystal structure. Secondly, the approved antidepressant escitalopram was docked into the X-ray structure, and its binding pose was consistent with the reported docking pose in the homology model. Finally, MD simulation were performed based on the crystal structure of hSERT, and structural features revealed as critical for escitalopram-hSERT interaction by previous simulation were successfully recaptured. Thus, the newly reported X-ray crystal structure of hSERT was precisely predicted by computational model, which demonstrated its reliability in understanding the pharmacology of other human monoamine transporters whose 3-D structure remained unknown.     

Dissipative particle dynamics simulation on the meso-scale structure of diblock copolymer under cylindrical confinement

The meso-scale structure of symmetric diblock copolymer under cylindrical confinement is studied by dissipative particle dynamics (DPD). The simulation results show that coiled cylindrical geometry is favored in the presence of larger cylinder radius (R/L ₀>～1.5), and the number of rings depends on the cylinder radius. Because of the cylinder wall's selectivity, each block can form the central core, but only the preferential block forms the outmost layer. An approximately linear relationship exists between structure transition point, which is approximately in proportion to the 3/5 exponential of chain length of copolymer and number of layers. As the cylinder radius is decreased, a helical morphology is found. Lamellae parallel to the underside of the cylinder appear when the cylinder radius is made smaller (R/L ₀ < ～1.1).     

Predicting rheology of suspensions of spherical and non-spherical particles using dissipative particle dynamics (DPD): methodology and experimental validation

The rheology of non-dilute colloidal suspensions is a complex phenomenon and predictive numerical methodologies for it are still in the emerging phases. Dissipative particle dynamics (DPD), a particle-based numerical scheme for phenomena in the mesoscopic regime, has emerged as an attractive technique to tackle this problem. In this article, a practical methodology for using DPD for quantitative prediction of the rheology of non-dilute suspensions is presented and validated with focused, specific experiments. Some pertinent issues are highlighted to make DPD more amenable to being a computational tool for practical applications. The presence of solid particles of disparate sizes and non-spherical geometries poses special challenges. Methodologies to address them are presented with validations and efficient techniques are suggested to make them computationally amenable.     

Applications of DL_POLY to modelling of mesoscopic particulate systems

The molecular dynamics package DL_POLY has at its heart a number of versatile and efficient dynamics algorithms that can readily be adapted to extend the application of this code well beyond the time and length scales typically associated with atomistic simulations. In order to achieve this, it is necessary to substitute the appropriate interparticle potentials and forces in place of the default functional forms in DL_POLY, which are mainly suitable for molecular systems. To facilitate this, it may be required to incorporate additional factors, into the simulation, such as velocity-dependent dissipation effects (friction), rotational degrees of freedom and non-spherosymmetric forces. In this paper, we will discuss some of the practical details of implementing these changes to DL_POLY (version 2) together with applications of discrete particle dynamics methods, such as dissipative particle dynamics (DPD) and granular dynamics (GD) (also known as the discrete or distinct element method, DEM) to particle packing in composite systems and pharmaceutical powders. We also consider how well the approach of simulating particles of arbitrary shape using rigid assemblies of fused soft spheres (each individually interacting via pairwise continuous potentials) compares to true hard-body simulations of polygonal particles.     

A density-dependent model of Cirsium vulgare population dynamics using field-estimated parameter values

Two versions of a stage-structured model of Cirsium vulgare population dynamics were developed. Both incorporated density dependence at one stage in the life cycle of the plant. In version 1 density dependence was assumed to operate during germination whilst in version 2 it was included at the seedling stage. Density-dependent parameter values for the model were estimated from annual census data in a factorial grazing experiment. Version 1 of the model produced significant estimates of density dependence under field conditions. The estimated values, when included in a simulation of the dynamics, produced two-point limit cycles under conditions of hard grazing. The limit cycles were most pronounced at the early rosette stage. Comparison of the effects of density dependence at the two different stages in the life cycle revealed a strong difference in predicted dynamics. This emphasizes the importance of determining where density dependence operates under field conditions and the potential problems of arbitrarily assigning it to particular life-history stages. Version 1 of the model produced a good prediction of observed mean plant density across the different grazing treatments (r ²=0.81, P<0.001).     

Dissipative particle dynamics simulation of a gold nanoparticle system

Dissipative particle dynamics (DPD) was carried out to study systems containing gold atoms, organic ether (oligohydroquinonyl ether terminated with a thiol group) and organic solvents. The components in the simulated system are very different in size and chemical nature. Our simulation showed that the reproduction of the macroscopic experimental phase separation, properly dividing the polymeric molecule into beads, selecting the size of gold bead, and choosing the appropriate interaction parameters between beads are crucial. In addition, the solvent effect was the dominant factor for the formation of spherical aggregates of Au atoms and organic ether molecules. We report the interaction strengths between the solvent and gold clusters. Our work has demonstrated that DPD methods can be applied to the study of complex meso-scale systems.     

The new program OPAL for molecular dynamics simulations and energy refinements of biological macromolecules

Summary A new program for molecular dynamics (MD) simulation and energy refinement of biological macromolecules, OPAL, is introduced. Combined with the supporting program TRAJEC for the analysis of MD trajectories, OPAL affords high efficiency and flexibility for work with diferent force fields, and offers a user-friendly interface and extensive trajectory analysis capabilities. Salient features are computational speeds of up to 1.5 GFlops on vector supercomputers such as the NEC SX-3, ellipsoidal boundaries to reduce the system size for studies in explicit solvents, and natural treatment of the hydrostatic pressure. Practical applications of OPAL are illustrated with MD simulations of pure water, energy minimization of the NMR structure of the mixed disulfide of a mutant E. coli glutaredoxin with glutathione in different solvent models, and MD simulations of a small protein, pheromone Er-2, using either instantaneous or time-averaged NMR restraints, or no restraints.Abbreviations D diffusion constant in cm²/s - Er-2 pheromone 2 from Euplotes raikovi - GFlop one billion floating point operations per second - Grx(C14S)-SG mixed disulfide between a mutant E. coli glutaredoxin, with Cys¹⁴ replaced by Ser, and glutathione - MD molecular dynamics - NOE nuclear Overhauser enhancement - rmsd root-mean-square deviation - density in g/cm³     

Molecular modeling and dynamics studies of purine nucleoside phosphorylase from Bacteroides fragilis

Purine nucleoside phosphorylase (PNP) catalyzes the reversible phosphorolysis of N-ribosidic bonds of purine nucleosides and deoxynucleosides, except adenosine, to generate ribose 1-phosphate and the purine base. This work describes for the first time a structural model of PNP from Bacteroides fragilis (Bf). We modeled the complexes of BfPNP with six different ligands in order to determine the structural basis for specificity of these ligands against BfPNP. Comparative analysis of the model of BfPNP and the structure of HsPNP allowed identification of structural features responsible for differences in the computationally determined ligand affinities. The molecular dynamics (MD) simulation was assessed to evaluate the overall stability of the BfPNP model. The superposition of the final onto the initial minimized structure shows that there are no major conformational changes from the initial model, which is consistent with the relatively low root mean square deviation (RMSD). The results indicate that the structure of the model was stable during MD, and does not exhibit loosely structured loop regions or domain terminals.     

Longer simulations sample larger subspaces of conformations while maintaining robust mechanisms of motion

Recent studies suggest that protein motions observed in molecular simulations are related to biochemical activities, although the computed time scales do not necessarily match those of the experimentally observed processes. The molecular origin of this conflicting observation is explored here for a test protein, cyanovirin‐N (CV‐N), through a series of molecular dynamics simulations that span a time range of three orders of magnitude up to 0.4 μs. Strikingly, increasing the simulation time leads to an approximately uniform amplification of the motional sizes, while maintaining the same conformational mechanics. Residue fluctuations exhibit amplitudes of 1–2 Å in the nanosecond simulations, whereas their average sizes increase by a factor of 4–5 in the microsecond regime. The mean‐square displacements averaged over all residues (y) exhibit a power law dependence of the form y ∝ x^0.26 on the simulation time (x). Essential dynamics analysis of the trajectories, on the other hand, demonstrates that CV‐N has robust preferences to undergo specific types of motions that already can be detected at short simulation times, provided that multiple runs are performed and carefully analyzed. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Intestinal transport of TRH analogs through PepT1: the role of in silico and in vitro modeling

The present study involves molecular docking, molecular dynamics (MD) simulation studies, and Caco‐2 cell monolayer permeability assay to investigate the effect of structural modifications on PepT1‐mediated transport of thyrotropin releasing hormone (TRH) analogs. Molecular docking of four TRH analogs was performed using a homology model of human PepT1 followed by subsequent MD simulation studies. Caco‐2 cell monolayer permeability studies of four TRH analogs were performed at apical to basolateral and basolateral to apical directions. Inhibition experiments were carried out using Gly‐Sar, a typical PepT1 substrate, to confirm the PepT1‐mediated transport mechanism of TRH analogs. P_app of the four analogs follows the order: NP‐1894 < NP‐2378 < NP‐1896 < NP‐1895. Higher absorptive transport was observed in the case of TRH analogs, indicating the possibility of a carrier‐mediated transport mechanism. Further, the significant inhibition of the uptake of Gly‐Sar by TRH analogs confirmed the PepT1‐mediated transport mechanism. Glide docking scores of all the four analogues were in good agreement with their transport rates, suggesting the role of substrate binding affinity in the PepT1‐mediated transport of TRH analogs. MD simulation studies revealed that the polar interactions with amino acid residues present in the active site are primarily responsible for substrate binding, and a downward trend was observed with the increase in bulkiness at the N‐histidyl moiety of TRH analogs. Copyright © 2014 John Wiley & Sons, Ltd.     

Calculation of the Generalized Susceptibility for a Highly Supercooled Fluid Through Molecular-Dynamics Simulation

Abstract

A new method of computation of generalized susceptibility and dynamical structure factor through molecular dynamics (MD) simulation is proposed. This gives rise to a reliable and accurate result more than that calculated from a conventional method with a direct Fourier transformation. Computational results are presented for the imaginary part of the generalized susceptibility, X″ (ω), for a binary soft-sphere fluid with a super-long-time molecular dynamics (MD) simulation. Both α- and β-peaks in X″ (ω) in a supercooled fluid is shown for the first time through the present MD computation. The MD result obtained is in a good agreement with that obtained by the trapping diffusion model, which we have previously proposed for the glass transition.     

DPD simulation of non-Newtonian electroosmotic fluid flow in nanochannel

We use the dissipative particle dynamics (DPD) method to simulate the non-Newtonian electroosmotic flow (EOF) through nanochannels. Contrary to a large amount of past computational efforts dedicated to the study of EOF profile, this work pays attention to the EOF of non-Newtonian fluids, which has been rarely touched in past publications. Practically, there are many MEMS/NEMS devices, in which the EOF behaviour should be treated assuming both non-continuum and non-Newtonian conditions. Therefore, our concern in this work is to simulate the EOF through nanochannels considering both non-Newtonian fluid properties and non-continuum flow conditions. We have chosen DPD as our working tool because it provides several important advantages comparing with the classical time consuming molecular dynamics method. Using the DPD method, we explore the effect of a few important fluid properties and nanochannel parameters on the EOF behaviour and the resulting flow rate magnitudes. Our investigation will result in a number of findings, which have not been reported in past research works.     

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct “enhanced network models”, describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. “Ab-initio network models” combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.     

Molecular-Dynamics Simulations for the Density Autocorrelation Function in a Supercooled Fluid Phase

Abstract

We have re-calculated the self part of the density autocorrelation function F_s(k, t) (incoherent scattering function) for the binary soft-sphere fluid with a much longer molecular-dynamics (MD) simulation than our previous MD calculations, and with a larger system size (N = 4000) to a longer time window as well as to study a system-size dependence, if it exists. The full density autocorrelation function F(k, t) was also computed. It is found that all F(k, t)'s that we have computed in this work can be fitted over a wide range of time steps (at least over three figures of the decay) by a Williams-Watts stretched exponential function F_s(k, t) = A exp [— (t/t ₀)^β], where A, β and t ₀ are adjustable parameters. Other significant dynamical behaviours were also presented in mean square displacements and non-Gaussian parameters for highly supercooled fluids with N = 4000. The present results are compatible to our previous computations with N = 500, but a significant size dependence is suggested.