Dissipative Particle Dynamics Forces Research Articles

A Structure Independent Molecular Fragment Interfuse Model for Mesoscale Dissipative Particle Dynamics Simulation of Peptides.

There is a need to develop robust computational models for mesoscale simulation of the structure of peptides over large length scales toward the discovery of novel peptides for medical applications to address the issues of peptide aggregation, enzymatic degradation, and short half-life. The primary objective was to predict the structure and conformation of peptides whose native structures are not known. This work presents a new model for computation of interaction parameters between the beads in coarse-grained dissipative particle dynamics (DPD) simulation that is properly calibrated for amino acids, supports compressibility requirement of water molecules, and accounts for subtle differences in the structure of amino acids and the charge in the side chain of charged amino acids. This new model is referred to as Structure Independent Molecular Fragment Interfuse Model, abbreviated as SIMFIM, because it accounts for specific interactions between different beads, which represent molecular fragments of the amino acids, in calculating nonbonded interaction parameters in the absence of knowing the actual peptide structure. The electrostatic interactions are incorporated in this model by using a normal distribution of charges around the center of the beads to prevent the collapse of oppositely charged soft beads. The uniquely parameterized DPD force field in the SIMFIM model is optimized for a given peptide with respect to the degree of coarse-grained graining for simulating the peptide over long times and length scales. The SIMFIM model was tested in this work using four peptides, namely, TrpZip2, Rubrivinodin, Lihuanodin, and IC3-CB1/Gai peptides, whose structures were sourced from the Protein Data Bank. The SIMFIM model predicted radius of gyration (Rg) values for the peptides closer to the actual structures as compared to the conventional model, and there was less deviation between the predicted and actual structures of the peptides.

Novel multiscale simulations on the membrane formation via hybrid induced phase separation process based on dissipative particle dynamics

A novel simulation methodology, that was based on dissipative particle dynamics (DPD) combined with information from molecular dynamics (MD) and calculations of an extended Maxwell-Stefan (MS) equations, was established to obtain multiscale analysis on the dynamics of hybrid induced phase separation (HIPS), taking polyvinylidene fluoride-diphenyl carbonate/water–ethanol (PVDF-DPC/water–ethanol) system as an example. Firstly, MS equations were derived to describe the heat transfer across the interface between the casting solution and coagulation to get the temperature profiles of the casting solution. Secondly, MD simulations for the PVDF-DPC solution were conducted to acquire bond and angle distributions of the PVDF chains. And compared to the DPD particle distributions, a novel DPD force field to describe the real flexibility of PVDF chains and a coarse-graining mapping between the MD and DPD were developed. Thirdly, based on the quenching time calculated by the MS equations and the DPD time scale, DPD simulations were carried out to demonstrate the dynamics of phase separation and membrane formation for different parts of the polymer solution via HIPS and compared to that via thermally induced phase separation (TIPS). The simulation results indicated that the mass transfer had a decisive effect on the phase separation of polymer solution near the interface and resulted in a highly asymmetric structure with a denser polymer top layer and porous sublayer, and this effect was together decided by the quenching rate and polymer solidification. For the inner parts of the polymer solution, a mainly isotropic structure was formed due to heat transfer. Based on experimental verification and simulation results, it can be known that the multiscale simulation was much closer to reality and can provide deep insights into the membrane formation prepared via the HIPS process.

Model for the Simulation of the CnEm Nonionic Surfactant Family Derived from Recent Experimental Results.

Using a comprehensive set of recently published experimental results for training and validation, we have developed computational models appropriate for simulations of aqueous solutions of poly(ethylene oxide) alkyl ethers, an important class of micelle-forming nonionic surfactants, usually denoted CnEm. These models are suitable for use in simulations that employ a moderate amount of coarse graining and especially for dissipative particle dynamics (DPD), which we adopt in this work. The experimental data used for training and validation were reported earlier and produced in our laboratory using dynamic light scattering (DLS) measurements performed on 12 members of the CnEm compound family yielding micelle size distribution functions and mass-weighted mean aggregation numbers at each of several surfactant concentrations. The range of compounds and quality of the experimental results were designed to support the development of computational models. An essential feature of this work is that all simulation results were analyzed in a way that is consistent with the experimental data. Proper account is taken of the fact that a broad distribution of micelle sizes exists, so mass-weighted averages (rather than number-weighted averages) over this distribution are required for the proper comparison of simulation and experimental results. The resulting DPD force field reproduces several important trends seen in the experimental critical micelle concentrations and mass-averaged mean aggregation numbers with respect to surfactant characteristics and concentration. We feel it can be used to investigate a number of open questions regarding micelle sizes and shapes and their dependence on surfactant concentration for this important class of nonionic surfactants.

Dissipative particle dynamics model of homogalacturonan based on molecular dynamics simulations

In this study we present an alternative dissipative particle dynamics (DPD) parametrization strategy based on data extracted from the united-atom molecular simulations. The model of the homogalacturonan was designed to test the ability of the formation of large-scale structures via hydrogen bonding in water. The extraction of coarse-grained parameters from atomistic molecular dynamics was achieved by means of the proposed molecule aggregation algorithm based on an iterative nearest neighbour search. A novel approach to a time-scale calibration scheme based on matching the average velocities of coarse-grained particles enabled the DPD forcefield to reproduce essential structural features of homogalacturonan molecular chains. The successful application of the proposed parametrization method allowed for the reproduction of the shapes of radial distribution functions, particle velocities and diffusivity of the atomistic molecular dynamics model using DPD force field. The structure of polygalacturonic acid molecules was mapped into the DPD force field by means of the distance and angular bond characteristics, which closely matched the MD results. The resulting DPD trajectories showed that randomly dispersed homogalacturonan chains had a tendency to aggregate into highly organized 3D structures. The final structure resembled a three-dimensional network created by tightly associated homogalacturonan chains organized into thick fibres.

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.

We present a machine learning approach to automated force field development in dissipative particle dynamics (DPD). The approach employs Bayesian optimization to parametrize a DPD force field against experimentally determined partition coefficients. The optimization process covers a discrete space of over 40 000 000 points, where each point represents the set of potentials that jointly forms a force field. We find that Bayesian optimization is capable of reaching a force field of comparable performance to the current state-of-the-art within 40 iterations. The best iteration during the optimization achieves an R2 of 0.78 and an RMSE of 0.63 log units on the training set of data, these metrics are maintained when a validation set is included, giving R2 of 0.8 and an RMSE of 0.65 log units. This work hence provides a proof-of-concept, expounding the utility of coupling automated and efficient global optimization with a top down data driven approach to force field parametrization. Compared to commonly employed alternative methods, Bayesian optimization offers global parameter searching and a low time to solution.

Implicit-solvent dissipative particle dynamics force field based on a four-to-one coarse-grained mapping scheme.

A new set of efficient solvent-free dissipative particle dynamics (DPD) force fields was developed for phospholipids and peptides. To enhance transferability, this model maps around four heavy atoms and their connected hydrogen atoms into a coarse-grained elementary bead based on functional group. The effective hybrid potential between any pair of beads is composed of a short-range repulsive soft-core potential that directly adopts the form of an explicit-solvent DPD model and a long-range attractive hydrophobic potential. The parameters of the attractive potentials for lipid molecules were obtained by fitting the explicit-solvent DPD simulation of one bead of any type in a water box, then finely tuning it until the bilayer membrane properties obtained in the explicit-solvent model were matched. These parameters were further extended to amino acids according to bead type. The structural and elastic properties of bilayer membranes, free energy profiles for a lipid flip-flop and amino acid analogues translocating across the membrane, and membrane pore formation induced by antimicrobial peptides obtained from this solvent-free DPD force field considerably agreed with the explicit-solvent DPD results. Importantly, the efficiency of this method is guaranteed to accelerate the assembly of vesicles composed of several thousand lipids by up to 50-fold, rendering the experimental liposome dynamics as well as membrane-peptide interactions feasible at accessible computational expense.

DPD of diffusion-weighted MRI

Diffusion weighted magnetic resonance imaging (DW-MRI) experiments can be simulated by coupling dissipative particle dynamics (DPD) with Bloch equations. DPD gives hydrodynamics with thermal fluctuations at a well-defined temperature by introducing momentum conserving particle interaction forces and a fluctuation dissipation theorem. The Bloch equations are a set of differential equations that describe the evolution of nuclear magnetization as a function of time. Here we successfully simulate DW-MRI by using the solution of Bloch equations for each DPD particle while computing its trajectories through DPD forces. To this end, a spin echo sequence combined with different diffusion-weighting gradients was implemented and tested for the diffusion of a fluid bound by different diffusion regimes. Fluid confinement was easily incorporated, which enabled investigating different diffusion regimes and the performance of different pulse sequences. The three different sequences applied were: spin echo single-sided bipolar gradient, spin echo two-sided bipolar gradient and spin echo uni-polar gradient; and the three imaged diffusion regimes of interest were: free diffusion, localization and motional narrowing.

Micelle Formation in Alkyl Sulfate Surfactants Using Dissipative Particle Dynamics.

We use dissipative particle dynamics (DPD) to study micelle formation in alkyl sulfate surfactants, with alkyl chain lengths ranging from 6 to 12 carbon atoms. We extend our recent DPD force field [ J. Chem. Phys. 2017 , 147 , 094503 ] to include a charged sulfate chemical group and aqueous sodium ions. With this model, we achieve good agreement with the experimentally reported critical micelle concentrations (CMCs) and can match the trend in mean aggregation numbers versus alkyl chain length. We determine the CMC by fitting a charged pseudophase model to the dependence of the free surfactant on the total surfactant concentration above the CMC and compare it with a direct operational definition of the CMC as the point at which half of the surfactant is classed as micellar and half as monomers and submicellar aggregates. We find that the latter provides the best agreement with experimental results. Finally, with the same model, we are able to observe the sphere-to-rod morphological transition for sodium dodecyl sulfate (SDS) micelles and determine that it corresponds to SDS concentrations in the region of 300-500 mM.

Reducing the effects of compressibility in DPD-based blood flow simulations through severe stenotic microchannels

Viscous fluid flow simulations based on dissipative particle dynamics (DPD) may bear compressible flow effects when flowing through severe stenotic geometries. This is caused by the soft repulsive potential employed in the DPD force field, which limits the particle-based fluid system ability to sustain a large degree of compression. To mitigate this problem, a Morse potential was added to the DPD force field. We studied the fluid properties of the modified fluid model (DPD–Morse) and compared it with a previously published conventional DPD based fluid model. Our DPD–Morse model demonstrated reduced compressibility while preserving other fluid properties such as the fluid density and viscosity. We further investigated the fluid flow properties for a severe 3D stenotic microchannel with a 67% stenosis, using the two models. The DPD fluid model presented a significant density gradient along the flow direction, where the fluid density increased upstream towards the stenosis and decreased downstream from the stenosis before regaining its initial value. In contrast, the DPD–Morse model demonstrated a far better uniform fluid density distribution along the flow direction. We compared both solutions with CFD simulations. The DPD–Morse fluid resembled the behavior of the continuum fluid model whereas DPD fluid deviated from it. To estimate the effect that the difference between the two DPD formulations may have on the platelet activation potential, we have further embedded a platelet model within the flow field and investigated the shear stress accumulation along the platelet transport trajectory. In the stenotic section, the DPD fluid demonstrated a larger stress gradient than the DPD–Morse fluid. The platelet transport period was shorter for the DPD fluid as it generated a larger fluid density gradient that overestimated the acceleration of the platelet through the stenosis. With reduced fluid compressibility, our modified DPD–Morse fluid model was more accurate than the DPD fluid model when computing the platelet activation potential in a severe stenosis.

Dissipative Particle Dynamics Simulations for Phospholipid Membranes Based on a Four-To-One Coarse-Grained Mapping Scheme.

In this article, a new set of parameters compatible with the dissipative particle dynamics (DPD) force field is developed for phospholipids. The coarse-grained (CG) models of these molecules are constructed by mapping four heavy atoms and their attached hydrogen atoms to one bead. The beads are divided into types distinguished by charge type, polarizability, and hydrogen-bonding capacity. First, we derive the relationship between the DPD repulsive force and Flory-Huggins χ-parameters based on this four-to-one CG mapping scheme. Then, we optimize the DPD force parameters for phospholipids. The feasibility of this model is demonstrated by simulating the structural and thermodynamic properties of lipid bilayer membranes, including the membrane thickness, the area per lipid, the lipid tail orientation, the bending rigidity, the rupture behavior, and the potential of mean force for lipid flip-flop.

A particle-based multiscale simulation procedure within the material point method framework

Recent studies of nano energetic composites have underscored the need for an effective multiscale procedure for simulating the responses of discrete nano and sub-micron structures and assemblies to impact loading. A particle-based simulation procedure is proposed with a concurrent link between the dissipative particle dynamics (DPD) method and the material point method (MPM), and a hierarchical bridge from molecular dynamics to DPD, in order to effectively discretize the multiphase interactions associated with multiscale failure evolution. The proposed procedure is illustrated using simulations of the dynamic and impact responses of discrete metallic nano structures. It is shown that the DPD forces can be effectively coarse-grained using the MPM background grid, and that the concurrent link between the MPM and DPD enables near-seamless integration of constitutive modeling at the continuum level with force-based modeling at the mesoparticle level. Additional improvements and applications that build on the current results are discussed.

Dissipative particle dynamics model for colloid transport in porous media

We use a dissipative particle dynamics (DPD) model to study colloid transport in porous media. Unlike many existing numerical models, the DPD model directly couples dynamics of the fluid and colloidal particles. In the model, fluid, colloids, and soil grains are all represented by DPD particles. The interaction between particles is modeled by central and non-central DPD forces, which conserve both linear and angular momentums exactly. Additional van der Waals forces are applied between colloids and collectors. Other transport processes, including gravitational sedimentation, interception of colloids by soil grains (acting as colloid collectors) due to a finite size of colloids, and the Brownian diffusion of colloids are also included in the DPD model.We use the DPD model to study the contact efficiency in colloid filtration in saturated porous media and compare our results with empirical models based on filtration theory. Results of the DPD model agree well with the empirical models for low-concentration suspensions and colloids being small relative to the collector size. For colloid suspensions with larger colloids (relative to the collector size) and/or higher concentration, the agreement between the DPD model and the empirical models deteriorates. In the transport of a concentrated suspension of large colloids, the fluid flow is strongly affected by the linear and angular motions of the colloids, which are mainly disregarded in filtration theory. On the other hand, the DPD model fully couples the fluid flow and colloid transport and, thus, is expected to be accurate for a wide range of colloid sizes and concentrations.

A new algorithm for simulating flows of conducting fluids in the presence of electric fields

We propose an algorithm based on dissipative particle dynamics (DPD) for simulations of conducting fluids in the presence of an electric field. In this model, the electrostatic equations are solved in each DPD time step to determine the charge density at the fluid surfaces. These surface charges are distributed on a thin layer of fluid particles near the interface, and the corresponding interfacial electric forces are added to other DPD forces. The algorithm is applied to the electrospinning process at the Taylor cone formation stage. It is shown that, when the applied voltage is sufficiently high, the algorithm captures the formation of a Taylor cone with analytical apex angle 98.6°. Our results demonstrate the potential of the presented DPD algorithm for simulating two-phase problems in the presence of an electric field with non-periodic boundary conditions.

New parametrization method for dissipative particle dynamics

We introduce an improved method of parametrizing the Groot-Warren version of dissipative particle dynamics (DPD) by exploiting a correspondence between DPD and Scatchard-Hildebrand regular solution theory. The new parametrization scheme widens the realm of applicability of DPD by first removing the restriction of equal repulsive interactions between like beads, and second, by relating all conservative interactions between beads directly to cohesive energy densities. We establish the correspondence by deriving an expression for the Helmoltz free energy of mixing, obtaining a heat of mixing which is exactly the same form as that for a regular mixture (quadratic in the volume fraction) and an entropy of mixing which reduces to the ideal entropy of mixing for equal molar volumes. We equate the conservative interaction parameters in the DPD force law to the cohesive energy densities of the pure fluids, providing an alternative method of calculating the self-interaction parameters as well as a route to the cross interaction parameter. We validate the new parametrization by modeling the binary system SnI(4)SiCl(4), which displays liquid-liquid coexistence below an upper critical solution temperature around 140 degrees C. A series of DPD simulations were conducted at a set of temperatures ranging from 0 degrees C to above the experimental upper critical solution temperature using conservative parameters based on extrapolated experimental data. These simulations can be regarded as being equivalent to a quench from a high temperature to a lower one at constant volume. Our simulations recover the expected phase behavior ranging from solid-liquid coexistence to liquid-liquid coexistence and eventually leading to a homogeneous single phase system. The results yield a binodal curve in close agreement with the one predicted using regular solution theory, but, significantly, in closer agreement with actual solubility measurements.

Simulation of Suspensions in Constricted Geometries by Dissipative Particle Dynamics

We investigate the flow of a suspension through a constriction by means of the mesoscopic technique known as dissipative particle dynamics (DPD). The dispersed phase was modeled as a set of soft spheres interacting through a conservative force while suspended and continuum phases interact via DPD forces. It is shown that a Poiseuille steady state is achieved in the presence of bounding walls and under a pressure gradient in a cylindrical pipe. Flow geometry in the laminar regime is explored and discussed for periodic conditions in the presence of a cylindrical narrowing or constriction.

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 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.

Large scale and mesoscopic hydrodynamics for dissipative particle dynamics

Decay rates and related transport coefficients of hydrodynamic disturbances in the isothermal dissipative particle dynamics (DPD) fluid depend strongly on how the probing wave length (in simulations: sizes of colloidal particles, polymers, pores, etc.) compares to the dynamic correlation length and to the range of the DPD forces. In this article the wave number dependent transport properties (dispersion relations) of the DPD fluid are calculated analytically using methods of kinetic theory, as a natural generalization of the work by Marsh et al. [Phys. Rev. E 56, 1976 (1997)]. The Navier–Stokes transport coefficients are recovered in the hydrodynamic limit of long wavelength disturbances.

A TWO-LEVEL, DISCRETE PARTICLE APPROACH FOR LARGE-SCALE SIMULATION OF COLLOIDAL AGGREGATES

Most numerical techniques employed for aggregation simulation are based on equilibrium growth assumption and Smoluchowski theory. We present a new two-level discrete particle model, which can be employed in simulating large colloidal clusters in highly nonequilibrium physical conditions. We consider the system of colloidal particles (CP) interacting via conservative CP–CP repulsive-attractive two-body forces, which is initially mixed in a dissipative solvent. In order to obtain a high-resolution picture of colloidal dynamics, we employ around 20 million particles consisting of two kinds of particles. For bridging the spatio-temporal scales between nanoscale colloidal and the solvent particles (SP), the solvent is modeled by dissipative particle dynamics (DPD) fluid. We focus on the systems size for which the CP–SP interactions can also be described by the DPD forces. Unlike previous numerical techniques, the two-level particle model can display much more realistic physics, thus allowing for the simulation of aggregation for various types of colloids and solvent liquids in a broad range of conditions. We show that not only large and static clusters but also the initial stages of aggregation evolution can be better scrutinized. The large-scale simulation results obtained in two-dimensions show that the mean cluster size grows with time t according to the power law tκ. Because of the time-dependence of growth mechanism, the value of κ necessarily must change. We have first κ = 1 with a value of 1 achieved asymptotically with time. We can also discern intermediate-scale structures. We emphasize that the method developed here can be easily extended to algorithms dealing with multi-level hierarchy and multiphase fluid dynamics.