DPD Simulation of Protein Conformations: From α-Helices to β-Structures

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.

Construction of Multiscale Dissipative Particle Dynamics (DPD) Models from Other Coarse-Grained Models

We present a general scheme for converting coarse-grained models into Dissipative Particle Dynamics (DPD) models. We build the corresponding DPD models by analogy with the de novo DPD coarse-graining scheme suggested by Groot and Warren (J. Chem. Phys., 1997). Electrostatic interactions between charged DPD particles are represented though the addition of a long-range Slater Coulomb potential as suggested by González-Melchor et al. (J. Chem. Phys., 2006). The construction is illustrated by converting MARTINI models for various proteins into a DPD representation, but it not restricted to the usual potential form in the MARTINI model-viz., Lennard-Jones potentials. We further extended the DPD scheme away from the typical use of homogeneous particle sizes, therefore faithfully representing the variations in the particle sizes seen in the underlying MARTINI model. The accuracy of the resulting construction of our generalized DPD models with respect to several structural observables has been benchmarked favorably against all-atom and MARTINI models for a selected set of peptides and proteins, and variations in the scales of the coarse-graining of the water solvent.

Persistence length of α-helical poly-L-lysine

The α-helix has a significant role in protein function and structure because of its rigidity. In this study, we investigate the persistence length, l_p, of α-helical poly-L-lysine, PLL, for two molecular weights. PLL experiences a random coil-helix transition as the pH is raised from 7 to 12. Using light scattering experiments to determine the radius of gyration (R_g), hydrodynamic radius, (R_h), the shape factor (R_g/R_h), and second virial coefficient (A₂), and circular dichroism to determine the helical content, we find the structure and l_p of PLL as a function of pH (7.4-11.4) and ionic strength (100-166 mM). With increasing pH, we find an increase in l_p from 2 nm to 15-21 nm because of α-helix formation. We performed dissipative particle dynamics (DPD) simulations and found a similar increase in l_p. While this l_p is less than that predicted by molecular dynamics simulations, it is consistent with other experimental results, which quantify the mechanics of α-helices. By determining the mechanics of helical polypeptides like PLL, we can further understand their implications to protein function.

Flaxseed-derived peptides ameliorate hepatic cholesterol metabolism in Sprague-Dawley rats fed a high-cholesterol and high-fat diet

BACKGROUND

Plant peptides have been reported to have cholesterol-lowering activities. Previous research has found that ≤1 kDa flaxseed peptide (FP₅ ) reduces cholesterol absorption and synthesis in vitro. In this research, we investigated the cholesterol-lowering activity of FP₅ in Sprague-Dawley (SD) rats fed a high-cholesterol and high-fat diet. In addition, amino acid sequences of FP₅ were determined by high-performance liquid chromatography-electrospray ionization-Orbitrap mass spectrometry.

RESULTS

FP₅ supplement significantly decreased the serum and hepatic cholesterol levels and modulated the hepatic gene and protein expression of cholesterol metabolism-related enzymes or regulators (3-hydroxy-3-methylglutaryl coenzyme A reductase, Low-Density Lipoprotein Receptor (LDLR), Cholesterol 7 α-hydroxylase, Niemann-Pick C1-like 1, ATP-binding cassette transporters G5 and G8). Eleven peptides were identified from FP₅ . These peptides were characterized as hydrophobic amino acids such as leucine (L), proline (P), glycine (G), isoleucine (I) and continuous sequences, including LP, LL, LG and II, with low molecular weights.

CONCLUSION

FP₅ has a certain cholesterol-lowering activity in SD rats fed a high-cholesterol and high-fat diet. The possible mechanism for ameliorating hepatic cholesterol metabolism of FP₅ includes inhibiting hepatic cholesterol de novo synthesis, promoting the synthesis and excretion of bile acids, and inhibiting the reabsorption of bile acids during enterohepatic circulation. © 2022 Society of Chemical Industry.

Dissipative particle dynamics simulation study on ATRP-brush modification of variably shaped surfaces and biopolymer adsorption

We present a dissipative particle dynamics (DPD) simulation study on the surface modification of initiator embedded microparticles (MPs) of different shapes via atom transfer radical polymerization (ATRP) brush growth. The surface-initiated ATRP-brush growth leads to the formation of a more globular MP shape. We perform the comparative analysis of ATRP-brush growth on three different forms of particle surfaces: cup surface, spherical surface, and flat surface (rectangular/disk-shaped). First, we establish the chemical kinetics of the brush growth: the monomer conversion and the reaction rates. Next, we discuss the structural changes (shape-modification) of brush-modified surfaces by computing the radial distribution function, spatial density distribution, radius of gyration, hydrodynamic radius, and shape factor. The polymer brush-modified particles are well known as the carrier materials for enzyme immobilization. Finally, we study the biopolymer adsorption on ATRP-brush modified particles in a compatible solution. In particular, we explore the effect of ATRP-brush length, biopolymer chain length, and concentration on the adsorption process. Our results illustrate the enhanced biopolymer adsorption with increased brush length, initiator concentration, and biopolymer concentration. Most importantly, when adsorption reaches saturation, the flat surface loads more biopolymers than the other two surfaces. The experimental results verified the same, considering the disk-shaped flat surface particles, cup-shaped particles, and spherical particles.

Coarse-Grained Modeling of Ion-Containing Polymers

Ion-containing polymers have continued to be an important research focus for several decades due to their use as an electrolyte in energy storage and conversion devices. Elucidation of connections between the mesoscopic structure and multiscale dynamics of the ions and solvent remains incompletely understood. Coarse-grained modeling provides an efficient approach for exploring the structural and dynamical properties of these soft materials. The unique physicochemical properties of such polymers are of broad interest. In this review, we summarize the current development and understanding of the structure-property relationship of ion-containing polymers and provide insights into the design of such materials determined from coarse-grained modeling and simulations accompanying significant advances in experimental strategies. We specifically concentrate on three types of ion-containing polymers: proton exchange membranes (PEMs), anion exchange membranes (AEMs), and polymerized ionic liquids (polyILs). We posit that insight into the similarities and differences in these materials will lead to guidance in the rational design of high-performance novel materials with improved properties for various power source technologies.

Dissipative particle dynamics simulations in colloid and Interface science: a review

Dissipative particle dynamics (DPD) is one of the most efficient mesoscale coarse-grained methodologies for modeling soft matter systems. Here, we comprehensively review the progress in theoretical formulations, parametrization strategies, and applications of DPD over the last two decades. DPD bridges the gap between the microscopic atomistic and macroscopic continuum length and time scales. Numerous efforts have been performed to improve the computational efficiency and to develop advanced versions and modifications of the original DPD framework. The progress in the parametrization techniques that can reproduce the engineering properties of experimental systems attracted a lot of interest from the industrial community longing to use DPD to characterize, help design and optimize the practical products. While there are still areas for improvements, DPD has been efficiently applied to numerous colloidal and interfacial phenomena involving phase separations, self-assembly, and transport in polymeric, surfactant, nanoparticle, and biomolecules systems.

A generic force field for simulating native protein structures using dissipative particle dynamics

A coarse-grained force field for molecular dynamics simulations of the native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by mapping the bonds and angles for 20 amino acids onto target distributions obtained from fully atomistic simulations in explicit solvent. A dual-basin potential is introduced for stabilizing backbone angles, to cover a wide spectrum of protein secondary structures. The backbone dihedral potential enables folding of the protein from an unfolded initial state to the folded native structure. The proposed force field is validated by evaluating the structural properties of several model peptides and proteins including the SARS-CoV-2 fusion peptide, consisting of α-helices, β-sheets, loops and turns. Detailed comparisons with fully atomistic simulations are carried out to assess the ability of the proposed force field to stabilize the different secondary structures present in proteins. The compact conformations of the native states were evident from the radius of gyration and the high intensity peaks of the root mean square deviation histograms, which were found to be within 0.4 nm. The Ramachandran-like energy landscape on the phase space of backbone angles (θ) and dihedrals (ϕ) effectively captured the conformational phase space of α-helices at ∼(ϕ = 50°,θ = 90°) and β-strands at ∼(ϕ = ±180°,θ = 90-120°). Furthermore, the residue-residue native contacts were also well reproduced by the proposed DPD model. The applicability of the model to multidomain complexes was assessed using lysozyme and a large α-helical bacterial pore-forming toxin, cytolysin A. Our study illustrates that the proposed force field is generic, and can potentially be extended for efficient in silico investigations of membrane bound polypeptides and proteins using DPD simulations.

High Adsorption of α-Glucosidase on Polymer Brush-Modified Anisotropic Particles Acquired by Electrospraying-A Combined Experimental and Simulation Study

In this particular contribution, we aim to immobilize a model enzyme such as α-glucosidase onto poly(DMAEMA) [poly(2-dimethyl amino ethyl methacrylate)] brush-modified anisotropic (cup- and disc-shaped) biocompatible polymeric particles. The anisotropic particles comprising a blend of PLA [poly(lactide)] and poly(MMA-co-BEMA) [poly((methyl methacrylate)-co-(2-(2-bromopropionyloxy) ethyl methacrylate)] were acquired by electrospraying, a scalable and convenient technique. We have also demonstrated the role of a swollen polymer brush grafted on the surface of cup-/disc-shaped particles via surface-initiated atom transfer radical polymerization in immobilizing an unprecedentedly high loading of enzyme [441 mg/g (cup)-589 mg/g (disc) of particles, 15-20 times higher than that of the literature-reported system] as compared to non-brush-modified particles. Circular dichroism spectroscopy was used to predict the structural changes of the enzyme upon immobilization onto the carrier particles. An enormously high amount of enzymes with preserved activity (∼85 ± 13% for cups and ∼78 ± 15% for discs) was found to adhere onto brush-modified particles at pH 7 via electrostatic adsorption. These findings were further explored at the atomistic level using a coarse-grained dissipative particle dynamics simulation approach, which exhibited excellent correlation with experimental results. In addition, accelerated particle separation was also achieved via magnetic force-induced aggregation within 20 min (without a centrifuge) by incorporating magnetic nanoparticles into disc-shaped particles while electrojetting. This further strengthens the technical feasibility of the process, which holds immense potential to be applied for various enzymes intended for several applications.

Closed-Form Coexistence Equation for Phase Separation of Polymeric Mixtures in Dissipative Particle Dynamics

To date, no extensive study of the phase diagram for binary fluid mixtures in dissipative particle dynamics (DPD) has been published. This is especially pertinent for newer parameterization schemes where the self-self interaction, or the effective volume, of different particle types is varied. This work presents an exhaustive study of the parameter space concerning DPD particles with soft interaction potentials. Moreover, we propose a closed-form coexistence equation or binodal curve that is inspired by the Flory-Huggins model. This equation describes the phase diagram of all binary mixtures made up out of monomers, homopolymers, and the mixtures thereof when self-self interactions are varied. The mean absolute percentage error (MAPE) of the equation on simulated data, including validation simulations, is 1.02%. The equation can a priori predict the phase separation of mixtures using only DPD interaction parameters. The proposed coexistence equation can therefore be used to directly validate interaction parameters resulting from novel parameterization schemes, including coarse graining and equations of state, without the need for additional simulations. Finally, it is shown that the choice of bond potential markedly influences phase behavior.

Coarse-grained simulation of the translational and rotational diffusion of globular proteins by dissipative particle dynamics

With simplified interactions and degrees of freedom, coarse-grained (CG) simulations have been successfully applied to study the translational and rotational diffusion of proteins in solution. However, in order to reach larger lengths and longer timescales, many CG simulations employ an oversimplified model for proteins or an implicit-solvent model in which the hydrodynamic interactions are ignored, and thus, the real kinetics are more or less unfaithful. In this work, we develop a CG model based on the dissipative particle dynamics (DPD) that can be universally applied to different types of proteins. The proteins are modeled as a group of rigid DPD beads without conformational changes. The fluids (including solvent and ions) are also modeled as DPD beads. The electrostatic interactions between charged species are explicitly considered by including charge distributions on DPD particles. Moreover, a surface friction between the protein and fluid beads is applied to control the slip boundary condition. With this model, we investigate the self-diffusion of a single globular protein in bulk solution. The translational and rotational diffusion coefficients of the protein can be tuned by the surface frictional constant to fit the predictions of the Stokes-Einstein (SE) relation. We find that both translational and rotational diffusion coefficients that meet with the prediction of the SE relation based on experimental results of the hydrodynamic radius are reached at almost the same frictional constant for different types of proteins. Such scaling behavior indicates that the model can be applied to simulate the translational and rotational diffusion together for various types of proteins.

Native-Based Dissipative Particle Dynamics Approach for α-Helical Folding

We developed a dissipative particle dynamics (DPD) approach that captures polyalanine folding into a stable helical conformation. Within the proposed native-based approach, the DPD parameters are derived based on the contact map constructed from the molecular dynamics (MD) simulations. We show that the proposed approach reproduces the folding of polypeptides of various lengths, including bundle formation for sufficiently long polypeptides. The proposed approach also allows one to capture the folding of the helical segments of the lysozyme. With further development of computationally efficient native-based DPD approaches for folding, modeling of a range of biomaterials incorporating α-helical segments could be extended to time and length scales far beyond those accessible in molecular dynamics simulations.

Stabilization Mechanism for a Nonfibrillar Amyloid β Oligomer Based on Formation of a Hydrophobic Core Determined by Dissipative Particle Dynamics

Neurotoxicity caused by nonfibrillar amyloid β (Aβ) oligomers in the brain is suggested to be associated with the onset of Alzheimer's disease (AD). Elucidating the structural features of Aβ oligomers is critical for promoting drug discovery research for AD. One of the Aβ oligomers, known as Aβ*56, is a dodecamer that impairs memory when injected into healthy rats, suggesting that Aβ*56 may contribute to cognitive deficits in AD patients. Another dodecamer structure, formed by 20-residue peptide segments derived from the Aβ peptide (Aβ_17-36), has been revealed by X-ray crystallography. The structure of the Aβ_17-36 dodecamer is composed of trimer units and shows the oligomer antibody A11 reactivity, which are characteristic of Aβ*56, indicating that Aβ*56 and the Aβ_17-36 dodecamer share a similar structure. However, the structure of the C-terminal regions (Aβ_37-42) remains unclear. The C-terminal region, which is abundant in hydrophobic residues, is thought to play a key role in stabilizing the oligomer structure by forming a hydrophobic core. In this study, we employed dissipative particle dynamics, a coarse-grained simulation method with soft core potentials, utilizing the crystal structure information to unravel Aβ dodecamer structures with C-terminal regions. The simulation results were validated by the reported experimental data. Hence, an analysis of the simulation results can provide structural insights into Aβ oligomers. Our simulations revealed the stabilization mechanism of the dodecamer structure at the molecular level. We showed that C-terminal regions spontaneously form a hydrophobic core in the central cavity, contributing to stabilizing the dodecamer structure. Furthermore, four consecutive hydrophobic residues in the C-terminal region (i.e., Val39-Ala42) are important for core formation.

Dissipative Particle Dynamics Simulations of a Protein-Directed Self-Assembly of Nanoparticles

Design and fabrication of multifunctional porous structures play key roles in the development of high-performance energy storage devices. Our experiments demonstrated that nanostructured porous components, such as electrodes and interlayers, generated from the protein-directed self-assembly of nanoparticles can significantly improve the battery performances. The protein-directed assembly of nanoparticles in solution is a complex process involving the complicated interactions among proteins, particles, and solvent molecules. In this paper, we investigate the effects of coating proteins and specific solvent environments on the assembled porous structures. Comprehensive dissipative particle dynamics (DPD) simulations have been implemented to explore the molecular interactions and uncover the fundamental mechanisms in a gelatin-directed self-assembly of carbon black particles under different solvent conditions. Our simulations show that compact triple-strand "rod-like" structures are formed in water while loose curved "sheet-like" structures are formed in an acetic acid/water mixture. The structural difference is mainly due to the redistribution of the charges on the gelatin side chains under specific acid-solvent conditions. The strong and flexible "sheet-like" structures lead to a homogenous porous structure with high porosity and with large functionalized surfaces. Our simulations results can reasonably explain the experimental observations; this work demonstrates the great potential of DPD as a powerful tool in guiding future experimental design and optimization.

Encoding and selecting coarse-grain mapping operators with hierarchical graphs

Coarse-grained (CG) molecular dynamics (MD) can simulate systems inaccessible to fine-grained (FG) MD simulations. A CG simulation decreases the degrees of freedom by mapping atoms from an FG representation into agglomerate CG particles. The FG to CG mapping is not unique. Research into systematic selection of these mappings is challenging due to their combinatorial growth with respect to the number of atoms in a molecule. Here we present a method of reducing the total count of mappings by imposing molecular topology and symmetry constraints. The count reduction is illustrated by considering all mappings for nearly 50 000 molecules. The resulting number of mapping operators is still large, so we introduce a novel hierarchical graphical approach which encodes multiple CG mapping operators. The encoding method is demonstrated for methanol and a 14-mer peptide. With the test cases, we show how the encoding can be used for automated selection of reasonable CG mapping operators.

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.

Adhesion and Separation of Nanoparticles on Polymer-Grafted Porous Substrates

This work explores interactions of functionalized nanoparticles (NP) with polymer brushes (PB) in a binary mixture of good and poor solvents. NP-PB systems are used in multiple applications, and we are particularly interested in the problem of chromatographic separation of NPs on polymer-grafted porous columns. This process involves NP flow through the pore channels with walls covered by PBs. NP-PB adhesion is governed by adsorption of polymer chains to NP surface and entropic repulsion caused by the polymer chain confinement between NP and the channel wall. Both factors depend on the solvent composition, variation of which causes contraction or expansion of PB. Using dissipative particle dynamics simulations in conjunction with the ghost tweezers free energy calculation technique, we examine the free energy landscapes of functionalized NPs within PB-grafted channels depending on the solvent composition at different PB grafting densities and polymer-solvent affinities. The free energy landscape determines the probability of NP location at a given distance to the surface, positions of equilibrium adhesion states, and the Henry constant that characterizes adsorption equilibrium and NP partitioning between the stationary phase of PB and mobile phase of flowing solvent. We analyze NP transport through a polymer-grafted channel and calculate the mean velocity and retention time of NP depending on the NP size and solvent composition. We find that, with the increase of the bad (poor) solvent fraction and respective PB contraction, NP separation exhibits a transition from the hydrodynamic size exclusion regime with larger NPs having shorter retention time to the adsorption regime with smaller NPs having shorter retention time. The observed reversal of the sequence of elution is reminiscent of the critical condition in polymer chromatography at which the retention time is molecular weight independent. This finding suggests the possibility of the existence of an analogous special regime in nanoparticle chromatography at which NPs with like surface properties elute together regardless of their size. The latter has important practical implications: NPs can be separated by surface chemistry rather than by their size employing the gradient mode of elution with controlled variation of solvent composition.

Characterizing the structure and properties of dry and wet polyethylene glycol using multi-scale simulations

Multi-scale simulations to study the structure and material properties of PEG in dry and wet conditions.

Probing eukaryotic cell mechanics via mesoscopic simulations

Cell mechanics has proven to be important in many biological processes. Although there is a number of experimental techniques which allow us to study mechanical properties of cell, there is still a lack of understanding of the role each sub-cellular component plays during cell deformations. We present a new mesoscopic particle-based eukaryotic cell model which explicitly describes cell membrane, nucleus and cytoskeleton. We employ Dissipative Particle Dynamics (DPD) method that provides us with the unified framework for modeling of a cell and its interactions in the flow. Data from micropipette aspiration experiments were used to define model parameters. The model was validated using data from microfluidic experiments. The validated model was then applied to study the impact of the sub-cellular components on the cell viscoelastic response in micropipette aspiration and microfluidic experiments.

Multiscale simulations for understanding the evolution and mechanism of hierarchical peptide self-assembly

Multiscale molecular simulations that combine and systematically link several hierarchies can provide insights into the evolution and dynamics of hierarchical peptide self-assembly from the molecular level to the mesoscale.

Harnessing Cooperative Interactions between Thermoresponsive Aptamers and Gels To Trap and Release Nanoparticles

We use computational modeling to design a device that can controllably trap and release particles in solution in response to variations in temperature. The system exploits the thermoresponsive properties of end-grafted fibers and the underlying gel substrate. The fibers mimic the temperature-dependent behavior of biological aptamers, which form a hairpin structure at low temperatures (T) and unfold at higher T, consequently losing their binding affinity. The gel substrate exhibits a lower critical solution temperature and thus, expands at low temperatures and contracts at higher T. By developing a new dissipative particle dynamics simulation, we examine the behavior of this hybrid system in a flowing fluid that contains buoyant nanoparticles. At low T, the expansion of the gel causes the hairpin-shaped fibers to extend into the path of the fluid-driven particle. Exhibiting a high binding affinity for these particles at low temperature, the fibers effectively trap and extract the particles from the surrounding solution. When the temperature is increased, the unfolding of the fiber and collapse of the supporting gel layer cause the particles to be released and transported away from the layer by the applied shear flow. Since the temperature-induced conformational changes of the fiber and polymer gel are reversible, the system can be used repeatedly to "catch and release" particles in solution. Our findings provide guidelines for creating fluidic devices that are effective at purifying contaminated solutions or trapping cells for biological assays.

The effects of shear and particle shape on the physical adsorption of polyvinyl pyrrolidone on carbon nanoparticles

The effects of shear and particle shape on the physical adsorption of a polymer (polyvinyl pyrrolidone, PVP) on carbon nanoparticles (CNPs) were studied with dissipative particle dynamics (DPD) methods. It was found that the conformation of the polymer during adsorption and desorption from the nanoparticle can be classified into three possible types, i.e. adsorbed, shear-affected and separated, depending on the magnitude of the shear rate in the flow. Spherical and graphene sheet-shaped particles with adsorbed PVP were manipulated in a Couette flow to determine the threshold shear rates leading to changes in the polymer adsorption state. It was found that the polymer was stably adsorbed under higher shear conditions for graphene sheets. In addition, the end-to-end distance and the radius of gyration of the polymer adsorbate was clearly related to the adsorption state, as the polymer underwent a transition from adsorbed to the separated state when the shear rate increased. The critical shear rate at which the polymer desorbed from the surface could be useful in applications where nanoparticles can be used as a molecular delivery system. The physical adsorption and desorption of the same polymer molecules on a flat surface were also investigated. The desorption of the polymer from the flat surface occurred when the shearing force was stronger than the attraction between the PVP and the surface.

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.

Mechanism of Inhibition of Human Islet Amyloid Polypeptide-Induced Membrane Damage by a Small Organic Fluorogen

Human islet amyloid polypeptide (hIAPP) is believed to be responsible for the death of insulin-producing β-cells. However, the mechanism of membrane damage at the molecular level has not been fully elucidated. In this article, we employ coarse- grained dissipative particle dynamics simulations to study the interactions between a lipid bilayer membrane composed of 70% zwitterionic lipids and 30% anionic lipids and hIAPPs with α-helical structures. We demonstrated that the key factor controlling pore formation is the combination of peptide charge-induced electroporation and peptide hydrophobicity-induced lipid disordering and membrane thinning. According to these mechanisms, we suggest that a water-miscible tetraphenylethene BSPOTPE is a potent inhibitor to rescue hIAPP-induced cytotoxicity. Our simulations predict that BSPOTPE molecules can bind directly to the helical regions of hIAPP and form oligomers with separated hydrophobic cores and hydrophilic shells. The micelle-like hIAPP-BSPOTPE clusters tend to be retained in the water/membrane interface and aggregate therein rather than penetrate into the membrane. Electrostatic attraction between BSPOTPE and hIAPP also reduces the extent of hIAPP binding to the anionic lipid bilayer. These two modes work together and efficiently prevent membrane poration.

Probing the role of electrostatics of polypeptide main-chain in protein folding by perturbing N-terminal residue stereochemistry: DFT study with oligoalanine models

Energetics of folding (ΔH_E→F, in kcal mol⁻¹) from the extended (E) structure to the folded (F) structure for Ia and Ib critically depend on the geometrical relationship between the backbone peptide units of the polypeptide structure.

Hydrogen bonding in DPD: application to low molecular weight alcohol–water mixtures

In this work, our proposed procedure to mimic hydrogen bonding in DPD and its application to study the physical properties of low molecular weight alcohols is reported.

Nanodomain Formation of Ganglioside GM1 in Lipid Membrane: Effects of Cholera Toxin-Mediated Cross-Linking

Cross-linking of specific lipid components by proteins mediates transmembrane signaling and material transport. In this work, we conducted coarse-grained simulation to investigate the interactions of binding units of chorela toxin (CTB) with mixed ganglioside GM1 and dipalmitoylphosphatidylcholine (DPPC) lipid bilayer membrane. We determine that the binding of CTB pentamers cross-links GM1 molecules into protein-sized nanodomains that have distinct lipid order compared with the bulk. The toxin in the nanodomain partially penetrates into the membrane. The local disordering can also transmit across the membrane via lipid coupling. Comparison simulations on CTB binding to a membrane that is composed of various lipid components demonstrate that several factors are responsible for the nanodomain formation: (a) the negatively charged headgroup of a GM1 receptor is responsible for the multivalent binding; (b) the head groups being full of hydrogen-bonding donors and receptors stabilize the GM1 cluster itself and ensure the toxin binding with high affinity; and

Modeling Aggregation of Ionic Surfactants Using a Smeared Charge Approximation in Dissipative Particle Dynamics Simulations

Using dissipative particle dynamics (DPD) simulations, we explore the specifics of micellization in the solutions of anionic and cationic surfactants and their mixtures. Anionic surfactant sodium dodecyl sulfate (SDS) and cationic surfactant cetyltrimethylammonium bromide (CTAB) are chosen as characteristic examples. Coarse-grained models of the surfactants are constructed and parameterized using a combination of atomistic molecular simulation and infinite dilution activity coefficient calibration. Electrostatic interactions of charged beads are treated using a smeared charge approximation: the surfactant heads and dissociated counterions are modeled as beads with charges distributed around the bead center in an implicit dielectric medium. The proposed models semiquantitatively describe self-assembly in solutions of SDS and CTAB at various surfactant concentrations and molarities of added electrolyte. In particular, the model predicts a decline in the free surfactant concentration with the increase of the total surfactant loading, as well as characteristic aggregation transitions in single-component surfactant solutions caused by the addition of salt. The calculated values of the critical micelle concentration reasonably agree with experimental observations. Modeling of catanionic SDS-CTAB mixtures show consecutive transitions to worm-like micelles and then to vesicles caused by the addition of CTAB to micellar solution of SDS.

On the importance of shear dissipative forces in coarse-grained dynamics of molecular liquids

In this work we demonstrate from first principles that the shear frictions describing dissipative forces in the direction normal to the vector connecting the coarse-grained (CG) particles in dissipative particle dynamics (DPD) could be dominant for certain real molecular liquids at high-resolution coarse-graining.

A polarizable coarse-grained protein model for dissipative particle dynamics

We present a new coarse-grained polarizable protein model for the dissipative particle dynamics (DPD) method.

Morphological transformations in polymer brushes in binary mixtures: DPD study

Morphological transformations in polymer brushes in a binary mixture of good and bad solvents are studied using dissipative particle dynamics simulations drawing on a characteristic example of polyisoprene natural rubber in an acetone-benzene mixture. A coarse-grained DPD model of this system is built based on the experimental data in the literature. We focus on the transformation of dense, collapsed brush in bad solvent (acetone) to expanded brush solvated in good solvent (benzene) as the concentration of benzene increases. Compared to a sharp globule-to-coil transition observed in individual tethered chains, the collapsed-to-expanded transformation in brushes is found to be gradual without a prominent transition point. The transformation becomes more leveled as the brush density increases. At low densities, the collapsed brush is highly inhomogeneous and patterned into bunches composed of neighboring chains due to favorable polymer-polymer interaction. At high densities, the brush is expanded even in bad solvent due to steric restrictions. In addition, we considered a model system similar to the PINR-acetone-benzene system, but with the interactions between the solvent components worsened to the limit of miscibility. Enhanced contrast between good and bad solvents facilitates absorption of the good solvent by the brush, shifting the collapsed-to-expanded transformation to lower concentrations of good solvent. This effect is especially pronounced for higher brush densities.

Self-assembly in Nafion membranes upon hydration: water mobility and adsorption isotherms

By means of dissipative particle dynamics (DPD) and Monte Carlo (MC) simulations, we explored geometrical, transport, and sorption properties of hydrated Nafion-type polyelectrolyte membranes. Composed of a perfluorinated backbone with sulfonate side chains, Nafion self-assembles upon hydration and segregates into interpenetrating hydrophilic and hydrophobic subphases. This segregated morphology determines the transport properties of Nafion membranes that are widely used as compartment separators in fuel cells and other electrochemical devices, as well as permselective diffusion barriers in protective fabrics. We introduced a coarse-grained model of Nafion, which accounts explicitly for polymer rigidity and electrostatic interactions between anionic side chains and hydrated metal cations. In a series of DPD simulations with increasing content of water, a classical percolation transition from a system of isolated water clusters to a 3D network of hydrophilic channels was observed. The hydrophilic subphase connectivity and water diffusion were studied by constructing digitized replicas of self-assembled morphologies and performing random walk simulations. A non-monotonic dependence of the tracer diffusivity on the water content was found. This unexpected behavior was explained by the formation of large and mostly isolated water domains detected at high water content and high equivalent polymer weight. Using MC simulations, we calculated the chemical potential of water in the hydrated polymer and constructed the water sorption isotherms, which extended to the oversaturated conditions. We determined that the maximum diffusivity and the onset of formation of large water domains corresponded to the saturation conditions at 100% humidity. The oversaturated membrane morphologies generated in the canonical ensemble DPD simulations correspond to the metastable and unstable states of Nafion membrane that are not realized in the experiments.

Theoretical insight into the relationship between the structures of antimicrobial peptides and their actions on bacterial membranes

Antimicrobial peptides with diverse cationic charges, amphiphathicities, and secondary structures possess a variety of antimicrobial activities against bacteria, fungi, and other generalized targets. To illustrate the relationship between the structures of these peptide and their actions at microscopic level, we present systematic coarse-grained dissipative particle dynamics simulations of eight types of antimicrobial peptides with different secondary structures interacting with a lipid bilayer membrane. We find that the peptides use multiple mechanisms to exert their membrane-disruptive activities: A cationic charge is essential for the peptides to selectively target negatively charged bacterial membranes. This cationic charge is also responsible for promoting electroporation. A significant hydrophobic portion is necessary to disrupt the membrane through formation of a permeable pore or translocation. Alternatively, the secondary structure and the corresponding rigidity of the peptides determine the pore structure and the translocation pathway.