Derivation of Coarse Grained Models for Multiscale Simulation of Liquid Crystalline Phase Transitions

Phase behavior of polymer dispersed liquid crystals, comparison between mean-field theory, and coarse-grained molecular dynamics simulations

We report a simulation methodology to quantitatively predict the thermodynamic behaviour (phase diagrams) of polymer mixtures, that exhibit phases with broken orientational symmetry. Our system consists of a binary mixture of short oligomers (NA = 4) and long rod-like mesogens (NB = 8). Using coarse-grained molecular dynamics (CGMD) simulations we infer the topology of the temperature-dependent free energy landscape, from the probability distributions of the components for a range of compositions. The mixture exhibits nematic (N) and smectic phases (Sm-A) as a function of two temperature scales, Tc, that governs the demixing transition, and TNI the nematic-isotropic temperature. Thus in addition to the isotropic (I), a nematic (N) phases observed in simulations of similar systems earlier we report the formation of a new entropy-stabilized phase separated smectic-A (Sm-A) phase with alternating mesogen-rich and oligomer-rich layers. Using the mean-field free energy for polymer-dispersed liquid crystals (PDLCs), with suitably chosen parameter values, we construct a mean-field phase diagram that matches those obtained from CGMD simulations. Our results are applicable to mixtures of synthetic and biological macromolecules that undergo phase separation and are orientable, thereby giving rise to the liquid crystalline phases. Our proposed methodology has a distinct advantage over other computational techniques in its applicability to systems with complex molecular interactions and in capturing the coarsening dynamics of systems involving multiple order parameters.

Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining

Understanding the relationship between multiscale morphology and electronic structure is a grand challenge for semiconducting soft materials. Computational studies aimed at characterizing these relationships require the complex integration of quantum-chemical (QC) calculations, all-atom and coarse-grained (CG) molecular dynamics simulations, and back-mapping approaches. However, these methods pose substantial computational challenges that limit their application to the requisite length scales of soft material morphologies. Here, we demonstrate the bottom-up electronic coarse-graining (ECG) of morphology-dependent electronic structure in the liquid-crystal-forming semiconductor, 2-(4-methoxyphenyl)-7-octyl-benzothienobenzothiophene (BTBT). ECG is applied to construct density functional theory (DFT)-accurate valence band Hamiltonians of the isotropic and smectic liquid crystal (LC) phases using only the CG representation of BTBT. By bypassing the atomistic resolution and its prohibitive computational costs, ECG enables the first calculations of the morphology dependence of the electronic structure of charge carriers across LC phases at the ∼20 nm length scale, with robust statistical sampling. Kinetic Monte Carlo (kMC) simulations reveal a strong morphology dependence on zero-field charge mobility among different LC phases as well as the presence of two-molecule charge carriers that act as traps and hinder charge transport. We leverage these results to further evaluate the feasibility of developing mesoscopic, field-based ECG models in future works. The fully CG approach to electronic property predictions in LC semiconductors opens a new computational direction for designing electronic processes in soft materials at their characteristic length scales.

Rigorous Progress in Coarse-Graining

Low-resolution coarse-grained (CG) models provide remarkable computational and conceptual advantages for simulating soft materials. In principle, bottom-up CG models can reproduce all structural and thermodynamic properties of atomically detailed models that can be observed at the resolution of the CG model. This review discusses recent progress in developing theory and computational methods for achieving this promise. We first briefly review variational approaches for parameterizing interaction potentials and their relationship to machine learning methods. We then discuss recent approaches for simultaneously improving both the transferability and thermodynamic properties of bottom-up models by rigorously addressing the density and temperature dependence of these potentials. We also briefly discuss exciting progress in modeling high-resolution observables with low-resolution CG models. More generally, we highlight the essential role of the bottom-up framework not only for fundamentally understanding the limitations of prior CG models but also for developing robust computational methods that resolve these limitations in practice.

Coarse-Grained Model Incorporating Short- and Long-Range Effective Potentials for the Fast Simulation of Micelle Formation in Solutions of Ionic Surfactants

A coarse-grained model comprising short- and long-range effective potentials, parametrized with the iterative Boltzmann inversion (IBI) method, is presented for capturing micelle formation in aqueous solutions of ionic surfactants using as a model system sodium dodecyl sulfate (SDS). In the coarse-grained (CG) model, each SDS molecule is represented as a sequence of four beads while each water molecule is modeled as a single bead. The proposed CG scheme involves ten potential energy functions: four of them describe bonded interactions and control the distribution functions of intramolecular degrees of freedom (bond lengths, valence angles, and dihedrals) along an SDS molecule while the other six account for intermolecular interactions between pairs of SDS and water beads and control the radial distribution functions. The nonbonded effective potentials between coarse-grained SDS molecules extend up to about 12 nm and capture structural and morphological features of the micellar solution both at short and long distances. The long-range component of these potentials, in particular, captures correlations between surfactant molecules belonging to different micelles and is essential to describe ordering associated with micelle formation. A new strategy is introduced for determining the effective potentials through IBI by using information (target distribution functions) extracted from independent atomistic simulations of a micellar reference system (a salt-free SDS solution at total surfactant concentration c_T equal to 103 mM, temperature T equal to 300 K, and pressure P equal to 1 atm) obtained through a multiscale approach described in an earlier study. It employs several optimization steps for bonded and nonbonded interactions and a gradual parametrization of the short- and long-range components of the latter, followed by reparametrization of the bonded ones. The proposed CG model can reproduce remarkably accurately the microstructure and morphology of the reference system within only a few hours of computational time. It is therefore very promising for future studies of structural and morphological behavior of various liquid surfactant formulations.

Derivation of coarse-grained force fields for buckling-induced topological defects of liquid crystals

Microscopic details of buckling-induced topological defects are required for molecular design of smectic liquid crystals to control buckling instability of the layers. In this study, we present a multiobjective optimization method to derive the coarse-grained (CG) force fields with sufficiently precise buckling characteristics including the molecular details for molecular dynamics (MD) simulations. We perform CGMD simulations of buckling deformation at sample points in the CG force field parameter space, from which the response surfaces of objective functions such as the scalar orientational order parameters, critical angles of layer collapse, and radial distribution functions are estimated. Since not all objective functions can be optimized simultaneously, we use a genetic algorithm to calculate the Pareto set of optimal solutions. We select the models with different molecular head-tail symmetries to study buckling deformation. The extracted CG model successfully reproduces the buckling deformation in terms of the collapse of smectic layers through the generation of dislocations with dipole disclinations. We also find that the molecular symmetry is a dominant factor to control the class of the buckling-induced dislocations.

Topics in the mathematical design of materials

We present a perspective on several current research directions relevant to the mathematical design of new materials. We discuss: (i) design problems for phase-transforming and shape-morphing materials, (ii) epitaxy as an approach of central importance in the design of advanced semiconductor materials, (iii) selected design problems in soft matter, (iv) mathematical problems in magnetic materials, (v) some open problems in liquid crystals and soft materials and (vi) mathematical problems on liquid crystal colloids. The presentation combines topics from soft and hard condensed matter, with specific focus on those design themes where mathematical approaches could possibly lead to exciting progress. This article is part of the theme issue 'Topics in mathematical design of complex materials'.

Coarse grained simulation of the aggregation and structure control of polyethylene nanocrystals

Polyethylene (PE) telechelics with carboxylate functional groups at both ends have been shown to assemble into hexagonal nanocrystal platelets with a height defined by their chain length in basic CsOH-solution. In this coarse grained (CG) simulation study we show how properties of the functional groups alter the aggregation and crystallization behavior of those telechelics. Systematic variation of the parameters of the CG model showed that important factors which control nanoparticle stability and structure are the PE chain length and the hydrophilicity and the steric demand of the head groups. To characterize the aggregation process we analyzed the number and size of the obtained aggregates as well as intramolecular order and intermolecular alignment of the polymer chains. By comparison of CG and atomistic simulation data, it could be shown that atomistic simulations representing different chemical systems can be emulated with specific, different CG parameter sets. Thus, the results from the (generic) CG simulation models can be used to explain the effect of different head groups and different counterions on the aggregation of PE telechelics and the order of the obtained nanocrystals.

Investigating the energetic and entropic components of effective potentials across a glass transition

By eliminating unnecessary details, coarse-grained (CG) models provide the necessary efficiency for simulating scales that are inaccessible to higher resolution models. However, because they average over atomic details, the effective potentials governing CG degrees of freedom necessarily incorporate significant entropic contributions, which limit their transferability and complicate the treatment of thermodynamic properties. This work employs a dual-potential approach to consider the energetic and entropic contributions to effective interaction potentials for CG models. Specifically, we consider one- and three-site CG models for ortho-terphenyl (OTP) both above and below its glass transition. We employ the multiscale coarse-graining (MS-CG) variational principle to determine interaction potentials that accurately reproduce the structural properties of an all-atom (AA) model for OTP at each state point. We employ an energy-matching variational principle to determine an energy operator that accurately reproduces the intra- and inter-molecular energy of the AA model. While the MS-CG pair potentials are almost purely repulsive, the corresponding pair energy functions feature a pronounced minima that corresponds to contacting benzene rings. These energetic functions then determine an estimate for the entropic component of the MS-CG interaction potentials. These entropic functions accurately predict the MS-CG pair potentials across a wide range of liquid state points at constant density. Moreover, the entropic functions also predict pair potentials that quite accurately model the AA pair structure below the glass transition. Thus, the dual-potential approach appears a promising approach for modeling AA energetics, as well as for predicting the temperature-dependence of CG effective potentials.

Modeling of the photo-induced stress in azobenzene polymers by combining theory and computer simulations

It has been shown recently that the photo-induced deformations in azobenzene-containing polymers of a side-chain architecture can be explained by means of the so-called orientational approach. The explanation is based on the following sequence of steps: (i) reorientation of azobenzenes under illumination, (ii) reorientation of the polymer backbones coupled mechanically to azobenzenes, and (iii) development of large stress in a material. Step (i) is based on the angle selective absorption of the azobenzene chromophore, which is a well established fact. Step (iii) has been validated in a series of recent theoretic studies in an infinite coupling limit. Concerning step (ii), in a real material, the backbone-azobenzene coupling will be always finite, resulting in a decrease of the effective torque sensed by the backbones and in a time delay in their reorientation. To study the relevance of these effects in detail, we perform coarse-grained molecular dynamics simulations of side-chain azobenzene-containing oligomers in bulk at conditions close to the glassy state. The focus is on the dynamical properties of such a system and on its response to the illumination, with the latter modeled either as an orientation potential applied to the azobenzenes or via their stochastic photo-isomerization. By matching the amount of light-induced stress evaluated in both cases, we obtained the equivalent orientation potential as a function of the illumination intensity and the system density.

Dual-potential approach for coarse-grained implicit solvent models with accurate, internally consistent energetics and predictive transferability

The dual-potential approach promises coarse-grained (CG) models that accurately reproduce both structural and energetic properties, while simultaneously providing predictive estimates for the temperature-dependence of the effective CG potentials. In this work, we examine the dual-potential approach for implicit solvent CG models that reflect large entropic effects from the eliminated solvent. Specifically, we construct implicit solvent models at various resolutions, R, by retaining a fraction 0.10 ≤ R ≤ 0.95 of the molecules from a simple fluid of Lennard-Jones spheres. We consider the dual-potential approach in both the constant volume and constant pressure ensembles across a relatively wide range of temperatures. We approximate the many-body potential of mean force for the remaining solutes with pair and volume potentials, which we determine via multiscale coarse-graining and self-consistent pressure-matching, respectively. Interestingly, with increasing temperature, the pair potentials appear increasingly attractive, while the volume potentials become increasingly repulsive. The dual-potential approach not only reproduces the atomic energetics but also quite accurately predicts this temperature-dependence. We also derive an exact relationship between the thermodynamic specific heat of an atomic model and the energetic fluctuations that are observable at the CG resolution. With this generalized fluctuation relationship, the approximate CG models quite accurately reproduce the thermodynamic specific heat of the underlying atomic model.

Structural Correlations and Percolation in Twisted Perylene Diimides Using a Simple Anisotropic Coarse-Grained Model

Large, twisted, and fused conjugated molecular architectures have begun to appear more prominently in the organic semiconductor literature. From a modeling perspective, such structures present a challenge to conventional simulation techniques; atomistic resolutions are computationally inefficient, while traditional isotropic coarse-grained models do not capture the inherent anisotropies of the molecules. In this work, we develop a simple coarse-grained model that explicitly incorporates the anisotropy of these molecular architectures, thereby providing a route toward analyzing π-stacking, and thus qualitative electronic structure, at a computationally efficient coarse-grained resolution. Our simple coarse-grained model maintains relative orientations of conjugated rings, as well as inter-ring dihedrals, that are critical for understanding electronic and excitonic transport in bulk systems. We apply this model to understand structural correlations in several recently synthesized perylene diimide (PDI)-based organic semiconductors. Twisted and nonplanar molecular architectures are found to promote amorphous morphologies while maintaining local π-stacking. A graph theoretical network analysis demonstrates that these twisted molecules are more likely to form percolating three-dimensional pathways for charge motion than strictly planar molecules, which show connectivity in only one dimension.

Investigation of nematic to smectic phase transition and dynamical properties of strongly confined semiflexible polymers using Langevin dynamics

We investigated the nematic to smectic phase transition for strongly confined semiflexible polymer solutions in slit-like confinements using GPU-accelerated Langevin dynamics. We characterized the phase transitions from the nematic to smectic phases for semi-flexible polymer solutions as the polymer density increased. The dependence for the lyotropic nematic to smectic transition can be collapsed by scaling exponents between 0.2 and 0.3. The smectic C phase is found for all the cases with the polymer orientation director tilted with respect to smectic layer lateral alignment. As the chain rigidity increases, the transition density decreases for systems in which the polymer persistence length (P) to slit height (H) ratios are 1.25, 2.5, 3.75, 5 and 25. We also characterized the polymer dynamics for the isotropic-nematic-smectic transitions. The overall polymer diffusivity decreased steadily as the polymer density increased. We observed anomalous polymer diffusion along the nematic director near the isotropic-nematic transition, similar to previously reported behavior for nematic-forming ellipsoids. Polymer diffusivity decreased sharply by two orders of magnitude upon the nematic-smectic transition.

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales

Understanding the connections between the characteristic dynamical time scales associated with a coarse-grained (CG) and a detailed representation is central to the applicability of the coarse-graining methods to understand molecular processes. The process of coarse graining leads to an accelerated dynamics, owing to the smoothening of the underlying free-energy landscapes. Often a single time-mapping factor is used to relate the time scales associated with the two representations. We critically examine this idea using a model system ideally suited for this purpose. Single molecular transport properties are studied via molecular dynamics simulations of the CG and atomistic representations of a liquid crystalline, azobenzene containing mesogen, simulated in the smectic and the isotropic phases. The out-of-plane dynamics in the smectic phase occurs via molecular hops from one smectic layer to the next. Hopping can occur via two mechanisms, with and without significant reorientation. The out-of-plane transport can be understood as a superposition of two (one associated with each mode of transport) independent continuous time random walks for which a single time-mapping factor would be rather inadequate. A comparison of the free-energy surfaces, relevant to the out-of-plane transport, qualitatively supports the above observations. Thus, this work underlines the need for building CG models that exhibit both structural and dynamical consistency to the underlying atomistic model.

Sequence transferable coarse-grained model of amphiphilic copolymers

Polymer properties are inherently multi-scale in nature, where delicate local interaction details play a key role in describing their global conformational behavior. In this context, deriving coarse-grained (CG) multi-scale models for polymeric liquids is a non-trivial task. Further complexities arise when dealing with copolymer systems with varying microscopic sequences, especially when they are of amphiphilic nature. In this work, we derive a segment-based generic CG model for amphiphilic copolymers consisting of repeat units of hydrophobic (methylene) and hydrophilic (ethylene oxide) monomers. The system is a simulation analogue of polyacetal copolymers [S. Samanta et al., Macromolecules 49, 1858 (2016)]. The CG model is found to be transferable over a wide range of copolymer sequences and also to be consistent with existing experimental data.

Cholesteric ordering predicted using a coarse-grained polymeric model with helical interactions

The understanding of cholesteric liquid crystals at a molecular level is challenging. Limited insights are available to bridge between molecular structures and macroscopic chiral organization. In the present study, we introduce a novel coarse-grained (CG) molecular model, which is represented by flexible chain particles with helical interactions (FCh), to study the liquid crystalline phase behavior of cholesteric molecules such as double strand DNA and α-helix polypeptides using molecular dynamics (MD) simulations. The isotropic-cholesteric phase transitions of FCh molecules were simulated for varying chain flexibilities. A wall confinement was used to break the periodicity along the cholesteric helix director in order to predict the equilibrium cholesteric pitch. The left-handed cholesteric phase was shown for FCh molecules with right-handed chiral interactions, and a spatially inhomogeneous distribution of the nematic order parameter profile was observed in cholesteric phases. It was found that the chain flexibility plays an important role in determining the macroscopic cholesteric pitch and the structure of the cholesteric liquid crystal phase. The simulations provide insight into the relationship between microscopic molecular characteristics and the macroscopic phase behavior.

A framework for multi-scale simulation of crystal growth in the presence of polymers

We present a multi-scale simulation method for modeling crystal growth in the presence of polymer excipients. The method includes a coarse-grained (CG) model for small molecules of known crystal structure whose force field is obtained using structural properties from atomistic simulations. This CG model is capable of stabilizing the molecular crystal structure and capturing the crystal growth from the melt for a wide range of small organic molecules, as demonstrated by application of our method to the molecules isoniazid, urea, sulfamethoxazole, prilocaine, oxcarbazepine, and phenytoin. This CG model can also be used to study the effect of additives, such as polymers, on the inhibition of crystal growth by polymers, as exemplified by our simulation of suppression of the rate of crystal growth of phenytoin, an active pharmaceutical ingredient (API), by a cellulose excipient, functionalized with acetate (Ac), hydroxy-propyl (Hp) and succinate (Su) groups. We show that the efficacy of the cellulosic polymers in slowing crystal growth of small molecules strongly depends on the functional group substitution on the cellulose backbone, with the acetate substituent group slowing crystal growth more than does the deprotonated succinate group, which we confirm by experimental drug supersaturation studies.

Thermodynamics of a Compressible Maier-Saupe Model Based on the Self-Consistent Field Theory of Wormlike Polymer

This paper presents a theoretical formalism for describing systems of semiflexible polymers, which can have density variations due to finite compressibility and exhibit an isotropic-nematic transition. The molecular architecture of the semiflexible polymers is described by a continuum wormlike-chain model. The non-bonded interactions are described through a functional of two collective variables, the local density and local segmental orientation tensor. In particular, the functional depends quadratically on local density-variations and includes a Maier–Saupe-type term to deal with the orientational ordering. The specified density-dependence stems from a free energy expansion, where the free energy of an isotropic and homogeneous homopolymer melt at some fixed density serves as a reference state. Using this framework, a self-consistent field theory is developed, which produces a Helmholtz free energy that can be used for the calculation of the thermodynamics of the system. The thermodynamic properties are analysed as functions of the compressibility of the model, for values of the compressibility realizable in mesoscopic simulations with soft interactions and in actual polymeric materials.

A Review of Multiscale Computational Methods in Polymeric Materials

Polymeric materials display distinguished characteristics which stem from the interplay of phenomena at various length and time scales. Further development of polymer systems critically relies on a comprehensive understanding of the fundamentals of their hierarchical structure and behaviors. As such, the inherent multiscale nature of polymer systems is only reflected by a multiscale analysis which accounts for all important mechanisms. Since multiscale modelling is a rapidly growing multidisciplinary field, the emerging possibilities and challenges can be of a truly diverse nature. The present review attempts to provide a rather comprehensive overview of the recent developments in the field of multiscale modelling and simulation of polymeric materials. In order to understand the characteristics of the building blocks of multiscale methods, first a brief review of some significant computational methods at individual length and time scales is provided. These methods cover quantum mechanical scale, atomistic domain (Monte Carlo and molecular dynamics), mesoscopic scale (Brownian dynamics, dissipative particle dynamics, and lattice Boltzmann method), and finally macroscopic realm (finite element and volume methods). Afterwards, different prescriptions to envelope these methods in a multiscale strategy are discussed in details. Sequential, concurrent, and adaptive resolution schemes are presented along with the latest updates and ongoing challenges in research. In sequential methods, various systematic coarse-graining and backmapping approaches are addressed. For the concurrent strategy, we aimed to introduce the fundamentals and significant methods including the handshaking concept, energy-based, and force-based coupling approaches. Although such methods are very popular in metals and carbon nanomaterials, their use in polymeric materials is still limited. We have illustrated their applications in polymer science by several examples hoping for raising attention towards the existing possibilities. The relatively new adaptive resolution schemes are then covered including their advantages and shortcomings. Finally, some novel ideas in order to extend the reaches of atomistic techniques are reviewed. We conclude the review by outlining the existing challenges and possibilities for future research.

Coarse-grained modeling of crystal growth and polymorphism of a model pharmaceutical molecule

We describe a systematic coarse-graining method to study crystallization and predict possible polymorphs of small organic molecules. In this method, a coarse-grained (CG) force field is obtained by inverse-Boltzmann iteration from the radial distribution function of atomistic simulations of the known crystal. With the force field obtained by this method, we show that CG simulations of the drug phenytoin predict growth of a crystalline slab from a melt of phenytoin, allowing determination of the fastest-growing surface, as well as giving the correct lattice parameters and crystal morphology. By applying meta-dynamics to the coarse-grained model, a new crystalline form of phenytoin (monoclinic, space group P2₁) was predicted which is different from the experimentally known crystal structure (orthorhombic, space group Pna2₁). Atomistic simulations and quantum calculations then showed the polymorph to be meta-stable at ambient temperature and pressure, and thermodynamically more stable than the conventional orthorhombic crystal at high pressure. The results suggest an efficient route to study crystal growth of small organic molecules that could also be useful for identification of possible polymorphs as well.

Development of a coarse-grained water forcefield via multistate iterative Boltzmann inversion

A coarse-grained water model is developed using multistate iterative Boltzmann inversion. Following previous work, the k-means algorithm is used to dynamically map multiple water molecules to a single coarse-grained bead, allowing the use of structure-based coarse-graining methods. The model is derived to match the bulk and interfacial properties of liquid water and improves upon previous work that used single state iterative Boltzmann inversion. The model accurately reproduces the density and structural correlations of water at 305 K and 1.0 atm, stability of a liquid droplet at 305 K, and shows little tendency to crystallize at physiological conditions. This work also illustrates several advantages of using multistate iterative Boltzmann inversion for deriving generally applicable coarse-grained forcefields.

The impact of resolution upon entropy and information in coarse-grained models

By eliminating unnecessary degrees of freedom, coarse-grained (CG) models tremendously facilitate numerical calculations and theoretical analyses of complex phenomena. However, their success critically depends upon the representation of the system and the effective potential that governs the CG degrees of freedom. This work investigates the relationship between the CG representation and the many-body potential of mean force (PMF), W, which is the appropriate effective potential for a CG model that exactly preserves the structural and thermodynamic properties of a given high resolution model. In particular, we investigate the entropic component of the PMF and its dependence upon the CG resolution. This entropic component, SW, is a configuration-dependent relative entropy that determines the temperature dependence of W. As a direct consequence of eliminating high resolution details from the CG model, the coarsening process transfers configurational entropy and information from the configuration space into SW. In order to further investigate these general results, we consider the popular Gaussian Network Model (GNM) for protein conformational fluctuations. We analytically derive the exact PMF for the GNM as a function of the CG representation. In the case of the GNM, -TSW is a positive, configuration-independent term that depends upon the temperature, the complexity of the protein interaction network, and the details of the CG representation. This entropic term demonstrates similar behavior for seven model proteins and also suggests, in each case, that certain resolutions provide a more efficient description of protein fluctuations. These results may provide general insight into the role of resolution for determining the information content, thermodynamic properties, and transferability of CG models. Ultimately, they may lead to a rigorous and systematic framework for optimizing the representation of CG models.

Ionic Liquid Crystals: Versatile Materials

This Review covers the recent developments (2005-2015) in the design, synthesis, characterization, and application of thermotropic ionic liquid crystals. It was designed to give a comprehensive overview of the "state-of-the-art" in the field. The discussion is focused on low molar mass and dendrimeric thermotropic ionic mesogens, as well as selected metal-containing compounds (metallomesogens), but some references to polymeric and/or lyotropic ionic liquid crystals and particularly to ionic liquids will also be provided. Although zwitterionic and mesoionic mesogens are also treated to some extent, emphasis will be directed toward liquid-crystalline materials consisting of organic cations and organic/inorganic anions that are not covalently bound but interact via electrostatic and other noncovalent interactions.

Derivation of coarse-grained simulation models of chlorophyll molecules in lipid bilayers for applications in light harvesting systems

The correct interplay of interactions between protein, pigment and lipid molecules is highly relevant for our understanding of the association behavior of the light harvesting complex (LHCII) of green plants. To cover the relevant time and length scales in this multicomponent system, a multi-scale simulation ansatz is employed that subsequently uses a classical all atomistic (AA) model to derive a suitable coarse grained (CG) model which can be backmapped into the AA resolution, aiming for a seamless conversion between two scales. Such an approach requires a faithful description of not only the protein and lipid components, but also the interaction functions for the indispensable pigment molecules, chlorophyll b and chlorophyll a (referred to as chl b/chl a). In this paper we develop a CG model for chl b and chl a in a dipalmitoylphosphatidyl choline (DPPC) bilayer system. The structural properties and the distribution behavior of chl within the lipid bilayer in the CG simulations are consistent with those of AA reference simulations. The non-bonded potentials are parameterized such that they fit to the thermodynamics based MARTINI force-field for the lipid bilayer and the protein. The CG simulation shows chl aggregation in the lipid bilayer which is supported by fluorescence quenching experiments. It is shown that the derived chl model is well suited for CG simulations of stable, structurally consistent, trimeric LHCII and can in the future be used to study their large scale aggregation behavior.

Unusual, photo-induced self-assembly of azobenzene-containing amphiphiles

Stimuli-responsive self-assembly is playing an increasingly important role in emerging applications, ranging from smart materials to biosensors. However, obtaining essential information for further development, such as molecular arrangement and interaction, is still experimentally challenging. A molecular-level understanding of the stimuli-responsive self-assembly is needed. Azobenzene-containing (azo-containing) amphiphiles organize into photo-responsive assemblies because of the cis-trans isomerization triggered by the irradiation of ultraviolet (UV) and visible light. In this study, we applied a coarse grained (CG) molecular dynamics (MD) simulation, with the necessary potential parameters fitted from theoretical calculation data, to study the photo-induced self-assembly of 4,4'-bis(hydroxymethyl)-azobenzene (AzoCO), a simple azo-containing amphiphile. An unusual "chaotic micelle" and "monolayer phase" were obtained with cis- and trans-AzoCO molecules, respectively. The structural information and formation mechanism were studied. The "chaotic micelle" possesses a chaotic but not a pure hydrophobic interior as commonly understood. Through comparative simulations, we found that the azo (-N[double bond, length as m-dash]N-) group of azobenzene plays a crucial role in the formation of the "chaotic micelle". The "monolayer phase" is arranged by abreast rod-like trans-AzoCO molecules; the axial symmetry of the trans-AzoCO molecule drives the formation of this structure. The novel "chaotic micelle" and "monolayer phase" have potential applications in nanotechnology and bioengineering. This work is expected to trigger further studies on stimuli-responsive phenomena and materials.

Investigation of coarse-grained mappings via an iterative generalized Yvon-Born-Green method

Low resolution coarse-grained (CG) models enable highly efficient simulations of complex systems. The interactions in CG models are often iteratively refined over multiple simulations until they reproduce the one-dimensional (1-D) distribution functions, e.g., radial distribution functions (rdfs), of an all-atom (AA) model. In contrast, the multiscale coarse-graining (MS-CG) method employs a generalized Yvon-Born-Green (g-YBG) relation to determine CG potentials directly (i.e., without iteration) from the correlations observed for the AA model. However, MS-CG models do not necessarily reproduce the 1-D distribution functions of the AA model. Consequently, recent studies have incorporated the g-YBG equation into iterative methods for more accurately reproducing AA rdfs. In this work, we consider a theoretical framework for an iterative g-YBG method. We numerically demonstrate that the method robustly determines accurate models for both hexane and also a more complex molecule, 3-hexylthiophene. By examining the MS-CG and iterative g-YBG models for several distinct CG representations of both molecules, we investigate the approximations of the MS-CG method and their sensitivity to the CG mapping. More generally, we explicitly demonstrate that CG models often reproduce 1-D distribution functions of AA models at the expense of distorting the cross-correlations between the corresponding degrees of freedom. In particular, CG models that accurately reproduce intramolecular 1-D distribution functions may still provide a poor description of the molecular conformations sampled by the AA model. We demonstrate a simple and predictive analysis for determining CG mappings that promote an accurate description of these molecular conformations.

Perspective: Coarse-grained models for biomolecular systems

By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.

Representability and Transferability of Kirkwood-Buff Iterative Boltzmann Inversion Models for Multicomponent Aqueous Systems

We discuss the application of the Kirkwood-Buff iterative Boltzmann inversion (KB-IBI) method for molecular coarse-graining (Ganguly et al. J. Chem. Theory Comput. 2012, 8, 1802) to multicomponent aqueous mixtures. Using a fixed set of effective single-site solvent-solvent potentials previously derived for binary urea-water systems, solute-solvent and solute-solute KB-IBI coarse-grained (CG) potentials have been derived for benzene in urea-water mixtures. Preferential solvation and salting-in coefficients of benzene are reproduced in quantitative agreement with the atomistic force field model. The transferability of the CG models is discussed, and it is shown that free energies of formation of hydrophobic benzene clusters obtained from simulations with the CG model are in good agreement with results obtained from all-atom simulations. The state-point representability of the CG models is discussed with respect to reproducing thermodynamic quantities such as pressure, isothermal compressibility, and preferential solvation. Combined use of KB-IBI and pressure corrections in deriving single-site CG models for pure-water, binary mixtures of urea and water, and ternary mixtures of benzene in urea-water at infinite benzene dilution provides an improved scheme to representing the atomistic pressure and the preferential solvation between the solution components. It is also found that the application of KB-IBI leads to a faster and improved convergence of the pressure and potential energy compared to the IBI method.

Dual translocation pathways in smectic liquid crystals facilitated by molecular flexibility

We investigate translocation mechanisms in smectic A liquid crystals (LCs) by a realistic, coarse-grained model of a LC compound comprising a stiff azobenzene core with flexible tails. We observe that the molecules can permeate from one smectic layer to the next via two different mechanisms, with and without significant reorientation, the former being facilitated through transverse interlayer intermediates. This is possible due to the intrinsic flexibility of the molecules. The two processes lead to characteristic signatures in the Van Hove self-correlation function, which can also be observed experimentally.