Generalized coarse-grained model based on point multipole and Gay-Berne potentials

Understanding dynamics in coarse-grained models. V. Extension of coarse-grained dynamics theory to non-hard sphere systems

Coarse-grained (CG) modeling has gained significant attention in recent years due to its wide applicability in enhancing the spatiotemporal scales of molecular simulations. While CG simulations, often performed with Hamiltonian mechanics, faithfully recapitulate structural correlations at equilibrium, they lead to ambiguously accelerated dynamics. In Paper I [J. Jin, K. S. Schweizer, and G. A. Voth, J. Chem. Phys. 158(3), 034103 (2023)], we proposed the excess entropy scaling relationship to understand the CG dynamics. Then, in Paper II [J. Jin, K. S. Schweizer, and G. A. Voth, J. Chem. Phys. 158(3), 034104 (2023)], we developed a theory to map the CG system into a dynamically consistent hard sphere system to analytically derive an expression for fast CG dynamics. However, many chemical and physical systems do not exhibit hard sphere-like behavior, limiting the extensibility of the developed theory. In this paper, we aim to generalize the theory to the non-hard sphere system based on the Weeks-Chandler-Andersen perturbation theory. Since non-hard sphere-like CG interactions affect the excess entropy term as it deviates from the hard sphere description, we explicitly account for the extra entropy to correct the non-hard sphere nature of the system. This approach is demonstrated for two different types of interactions seen in liquids, and we further provide a generalized description for any CG models using the generalized Gaussian CG models using Gaussian basis sets. Altogether, this work allows for extending the range and applicability of the hard sphere CG dynamics theory to a myriad of CG liquids.

Maximum Entropy Theory of Multiscale Coarse-Graining via Matching Thermodynamic Forces: Application to a Molecular Crystal (TATB)

The MSCG/FM (multiscale coarse-graining via force-matching) approach is an efficient supervised machine learning method to develop microscopically informed coarse-grained (CG) models. We present a theory based on the principle of maximum entropy (PME) enveloping the existing MSCG/FM approaches. This theory views the MSCG/FM method as a special case of matching the thermodynamic forces from the extended ensemble described by the set of thermodynamic (relevant) system coordinates. This set may include CG coordinates, the stress tensor, applied external fields, and so forth, and may be characterized by nonequilibrium conditions. Following the presentation of the theory, we discuss the consistent matching of both bonded and nonbonded interactions. The proposed PME formulation is used as a starting point to extend the MSCG/FM method to the constant strain ensemble, which together with the explicit matching of the bonded forces is better suited for coarse-graining anisotropic media at a submolecular resolution. The theory is demonstrated by performing the fine coarse-graining of crystalline 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a well-known insensitive molecular energetic material, which exhibits highly anisotropic mechanical properties.

Perturbative Expansion in Reciprocal Space: Bridging Microscopic and Mesoscopic Descriptions of Molecular Interactions

Determining the Fourier representation of various molecular interactions is important for constructing density-based field theories from a microscopic point of view, enabling a multiscale bridge between microscopic and mesoscopic descriptions. However, due to the strongly repulsive nature of short-ranged interactions, interparticle interactions cannot be formally defined in Fourier space, which renders coarse-grained (CG) approaches in k-space somewhat ambiguous. In this paper, we address this issue by designing a perturbative expansion of pair interactions in reciprocal space. Our perturbation theory, starting from reciprocal space, elucidates the microscopic origins underlying zeroth-order (long-range attractions) and divergent repulsive interactions from higher order contributions. We propose a systematic framework for constructing a faithful Fourier-space representation of molecular interactions, capturing key structural correlations in various systems, including simple model systems and molecular CG models of liquids. Building upon the Ornstein-Zernike equation, our approach can be combined with appropriate closure relations, and to further improve the closure approximations, we develop a bottom-up parameterization strategy for inferring the bridge function from microscopic statistics. By incorporating the bridge function into the Fourier representation, our findings suggest a systematic, bottom-up approach to performing coarse-graining in reciprocal space, leading to the systematic construction of a bottom-up classical field theory of complex aqueous systems.

Gaussian representation of coarse-grained interactions of liquids: Theory, parametrization, and transferability

Coarse-grained (CG) interactions determined via bottom-up methodologies can faithfully reproduce the structural correlations observed in fine-grained (atomistic resolution) systems, yet they can suffer from limited extensibility due to complex many-body correlations. As part of an ongoing effort to understand and improve the applicability of bottom-up CG models, we propose an alternative approach to address both accuracy and transferability. Our main idea draws from classical perturbation theory to partition the hard sphere repulsive term from effective CG interactions. We then introduce Gaussian basis functions corresponding to the system's characteristic length by linking these Gaussian sub-interactions to the local particle densities at each coordination shell. The remaining perturbative long-range interaction can be treated as a collective solvation interaction, which we show exhibits a Gaussian form derived from integral equation theories. By applying this numerical parametrization protocol to CG liquid systems, our microscopic theory elucidates the emergence of Gaussian interactions in common phenomenological CG models. To facilitate transferability for these reduced descriptions, we further infer equations of state to determine the sub-interaction parameter as a function of the system variables. The reduced models exhibit excellent transferability across the thermodynamic state points. Furthermore, we propose a new strategy to design the cross-interactions between distinct CG sites in liquid mixtures. This involves combining each Gaussian in the proper radial domain, yielding accurate CG potentials of mean force and structural correlations for multi-component systems. Overall, our findings establish a solid foundation for constructing transferable bottom-up CG models of liquids with enhanced extensibility.

A Mori-Zwanzig Dissipative Particle Dynamics Approach for Anisotropic Coarse Grained Molecular Dynamics

Coarse grained (CG) molecular dynamics simulations are widely used to accelerate atomistic simulations but generally lack a formalism to preserve the dynamics of the system. For spherical particles, the Mori-Zwanzig approach, while computationally complex, has ameliorated this problem. Here we present an anisotropic dissipative particle dynamics (ADPD) model as an extension of this approach, which accounts for the anisotropy for both conservative and nonconservative interactions. For a simple anisotropic system we parametrize the coarse grained force field representing ellipsoidal CG particles from the full-atomistic simulation. To represent the anisotropy of the system, both the conservative and dissipative terms are approximated using the Gay-Berne (GB) functional forms via a force-matching approach. We compare our model with other CG models and demonstrate that it yields better results in both static and dynamical properties. The inclusion of the anisotropic nonconservative force preserves the microscopic dynamical details, and hence the dynamical properties, such as diffusivity, can be better reproduced by the aspherical model. By generalizing the isotropic DPD model, this framework is effective and promising for the development of the CG model for polymers, macromolecules, and biological systems.

Enhancing pressure consistency and transferability of structure-based coarse-graining

Coarse-graining, which models molecules with coarse-grained (CG) beads, allows molecular dynamics simulations to be applied to systems with large length and time scales while preserving the essential molecular structure. However, CG models generally have insufficient representability and transferability. A commonly used method to resolve this problem is multi-state iterative Boltzmann inversion (MS-IBI) with pressure correction, which matches both the structural properties and pressures at different thermodynamic states between CG and all-atom (AA) simulations. Nevertheless, this method is usually effective only in a narrow pressure range. In this paper, we propose a modified CG scheme to overcome this limitation. We find that the fundamental reason for this limitation is that CG beads at close distances are ellipsoids rather than isotropically compressed spheres, as described in conventional CG models. Hence, we propose a method to compensate for such differences by slightly modifying the radial distribution functions (RDFs) derived from AA simulations and using the modified RDFs as references for pressure-corrected MS-IBI. We also propose a method to determine the initial non-bonded potential using both the target RDF and pressure. Using n-dodecane as a case study, we demonstrate that the CG model developed using our scheme reproduces the RDFs and pressures over a wide range of pressure states, including three reference low-pressure states and two test high-pressure states. The proposed scheme allows for accurate CG simulations of systems in which pressure or density varies with time and/or position.

Bottom-up Coarse-Graining: Principles and Perspectives

Large-scale computational molecular models provide scientists a means to investigate the effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship between variations on the molecular scale and macroscopic observable properties facilitates an understanding of the molecular interactions driving the properties of real world materials and complex systems (e.g., those found in biology, chemistry, and materials science). As a result, discovering an explicit, systematic connection between microscopic nature and emergent mesoscopic behavior is a fundamental goal for this type of investigation. The molecular forces critical to driving the behavior of complex heterogeneous systems are often unclear. More problematically, simulations of representative model systems are often prohibitively expensive from both spatial and temporal perspectives, impeding straightforward investigations over possible hypotheses characterizing molecular behavior. While the reduction in resolution of a study, such as moving from an atomistic simulation to that of the resolution of large coarse-grained (CG) groups of atoms, can partially ameliorate the cost of individual simulations, the relationship between the proposed microscopic details and this intermediate resolution is nontrivial and presents new obstacles to study. Small portions of these complex systems can be realistically simulated. Alone, these smaller simulations likely do not provide insight into collectively emergent behavior. However, by proposing that the driving forces in both smaller and larger systems (containing many related copies of the smaller system) have an explicit connection, systematic bottom-up CG techniques can be used to transfer CG hypotheses discovered using a smaller scale system to a larger system of primary interest. The proposed connection between different CG systems is prescribed by (i) the CG representation (mapping) and (ii) the functional form and parameters used to represent the CG energetics, which approximate potentials of mean force (PMFs). As a result, the design of CG methods that facilitate a variety of physically relevant representations, approximations, and force fields is critical to moving the frontier of systematic CG forward. Crucially, the proposed connection between the system used for parametrization and the system of interest is orthogonal to the optimization used to approximate the potential of mean force present in all systematic CG methods. The empirical efficacy of machine learning techniques on a variety of tasks provides strong motivation to consider these approaches for approximating the PMF and analyzing these approximations.

Interplay of orientational order and roughness in simulated thin film growth of anisotropically interacting particles

Roughness and orientational order in thin films of anisotropic particles are investigated using kinetic Monte Carlo simulations on a cubic lattice. Anisotropic next-neighbor interactions between the lattice particles were chosen to mimic the effects of shape anisotropy in the interactions of disk- or rodlike molecules with van der Waals attractions. Increasing anisotropy leads first to a preferred orientation in the film (which is close to the corresponding equilibrium transition) while the qualitative mode of roughness evolution (known from isotropic systems) does not change. At strong anisotropies, an effective step-edge (Ehrlich-Schwoebel) barrier appears and a nonequilibrium roughening effect is found, accompanied by reordering in the film which can be interpreted as the nucleation and growth of domains of lying-down disks or rods. The information on order and roughness is combined into a diagram of dynamic growth modes.

Anisotropic numerical potentials for coarse-grained modeling from high-speed multidimensional lookup table and interpolation algorithms

A high-speed numerical potential delivering computational performance comparable with complex coarse-grained analytic potentials makes available models that have greater degrees of physical and chemical accuracy. This opens the possibility of increased accuracy in classical molecular dynamics simulations of anisotropic systems. In this work, we report the development of a high-speed lookup table (LUT) of four-dimensional gridded data, that uses cubic B-spline interpolations to derive off grid values and their associated partial derivatives that are located between the known grid data points. The accuracy of the coarse-grained numerical potential using a LUT from uniaxial Gay-Berne (GB) potential produced array of values is within a 3% and a 5% margin of error respectively for the interpolation of the uniaxial GB potential and its partial derivatives. The numerical potential model and partial derivatives speedup is made competitive with the analytical potential by exploiting graphics processing units on board functionality. The capability of the numerical potential is demonstrated by comparing minimizations of a box of 500 naphthalene molecules. The minimizations using a full atomistic (NAMD/CHARMM force field), a biaxial GB and a numerical potential from a LUT using data from the CHARMM pair potential was done. The numerical potential model is significantly more accurate in its approximation of the atomistic local minimum configuration than is the biaxial GB analytical potential function. This demonstrates that using a numerical potential founded on a direct lookup of the atomistic potential landscape significantly improves coarse grain (CG) modeling of complex molecules, possibly paving the way for accurate anisotropic system CG modeling.

A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). I. General theory and model

Water is undoubtedly one of the most important molecules for a variety of chemical and physical systems, and constructing precise yet effective coarse-grained (CG) water models has been a high priority for computer simulations. To recapitulate important local correlations in the CG water model, explicit higher-order interactions are often included. However, the advantages of coarse-graining may then be offset by the larger computational cost in the model parameterization and simulation execution. To leverage both the computational efficiency of the CG simulation and the inclusion of higher-order interactions, we propose a new statistical mechanical theory that effectively projects many-body interactions onto pairwise basis sets. The many-body projection theory presented in this work shares similar physics from liquid state theory, providing an efficient approach to account for higher-order interactions within the reduced model. We apply this theory to project the widely used Stillinger-Weber three-body interaction onto a pairwise (two-body) interaction for water. Based on the projected interaction with the correct long-range behavior, we denote the new CG water model as the Bottom-Up Many-Body Projected Water (BUMPer) model, where the resultant CG interaction corresponds to a prior model, the iteratively force-matched model. Unlike other pairwise CG models, BUMPer provides high-fidelity recapitulation of pair correlation functions and three-body distributions, as well as N-body correlation functions. BUMPer extensively improves upon the existing bottom-up CG water models by extending the accuracy and applicability of such models while maintaining a reduced computational cost.

Assessment of an anisotropic coarse-grained model for cis-1,4-polybutadiene: a bottom-up approach

The spherical representation usually utilized for the coarse-grained particles of soft matter systems is an assumption and pertinent studies have shown that both structural and dynamical properties can depend on anisotropic effects. On these grounds, we develop coarse-grained equations of motion which take into account explicitly the anisotropy of the beads. As a first step, this model incorporates only conservative terms. Inclusion of the dissipative and random terms is in principle possible but is beyond the scope of this study. The translational dynamics of the beads is tracked using the position and momentum of their center of mass, while their rotational dynamics is modeled by representing their orientation through the use of quaternions, similarly to the case of rigid bodies. The associated force and torque controlling the motion are derived from atomistic molecular dynamics (MD) simulations via a bottom-up approach and define a coarse-grained potential. The assumptions of the model are clearly stated and checked for a reference system of a cis-1,4-polybutadiene melt. In particular, the choice of the angular velocity as a slow variable is justified by comparing its dynamics to atomic vibrations. The accuracy of this approach to reproduce static structural features of the polymer melt is assessed.

A systematic strategy for the investigation of vaccines and drugs targeting bacteria

Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.

MOLC. A reversible coarse grained approach using anisotropic beads for the modelling of organic functional materials

We describe the development and implementation of a coarse grained (CG) modelling approach where complex organic molecules, and particularly the π-conjugated ones often employed in organic electronics, are modelled in terms of connected sets of attractive-repulsive biaxial Gay-Berne ellipsoidal beads. The CG model is aimed at reproducing realistically large scale morphologies (e.g. up to 100 nm thick films) for the materials involved, while being able to generate, with a back-mapping procedure, atomistic coordinates suitable, with limited effort, to be applied for charge transport calculations. Detailed methodology and an application to the common hole transporter material α-NPD are provided.

Understanding Missing Entropy in Coarse-Grained Systems: Addressing Issues of Representability and Transferability

Coarse-grained (CG) models facilitate efficient simulation of complex systems by integrating out the atomic, or fine-grained (FG), degrees of freedom. Systematically derived CG models from FG simulations often attempt to approximate the CG potential of mean force (PMF), an inherently multidimensional and many-body quantity, using additive pairwise contributions. However, they currently lack fundamental principles that enable their extensible use across different thermodynamic state points, i.e., transferability. In this work, we investigate the explicit energy-entropy decomposition of the CG PMF as a means to construct transferable CG models. In particular, despite its high-dimensional nature, we find for liquid systems that the entropic component to the CG PMF can similarly be represented using additive pairwise contributions, which we show is highly coupled to the CG configurational entropy. This approach formally connects the missing entropy that is lost due to the CG representation, i.e., translational, rotational, and vibrational modes associated with the missing degrees of freedom, to the CG entropy. By design, the present framework imparts transferable CG interactions across different temperatures due to the explicit definition of an additive entropic contribution. Furthermore, we demonstrate that transferability across composition state points, such as between bulk liquids and their mixtures, is also achieved by designing combining rules to approximate cross-interactions from bulk CG PMFs. Using the predicted CG model for liquid mixtures, structural correlations of the fitted CG model were found to corroborate a high-fidelity combining rule. Our findings elucidate the physical nature and compact representation of CG entropy and suggest a new approach for overcoming the transferability problem. We expect that this approach will further extend the current view of CG modeling into predictive multiscale modeling.

Transferability of Local Density-Assisted Implicit Solvation Models for Homogeneous Fluid Mixtures

The application of bottom-up coarse grained (CG) models to study the equilibrium mixing behavior of liquids is rather challenging, since these models can be significantly influenced by the density or the concentration of the state chosen during parametrization. This dependency leads to low transferability in density/concentration space and has been one of the major limitations in bottom-up coarse graining. Recent approaches proposed to tackle this shortcoming range from the addition of thermodynamic constraints, to an extended ensemble parametrization, to the addition of supplementary terms to the system's Hamiltonian. To study fluid phase equilibria with bottom-up CG models, the application of local density (LD) potentials appears to be a promising approach, as shown in previous work by Sanyal and Shell [T. Sanyal, M. S. Shell, J. Phys. Chem. B, 2018, 122, 5678]. Here, we want to further explore this method and test its ability to model a system which contains structural inhomogeneities only on the molecular scale, namely, solutions of methanol and water. We find that a water-water LD potential improves the transferability of an implicit-methanol CG model toward high water concentration. Conversely, a methanol-methanol LD potential does not significantly improve the transferability of an implicit-water CG model toward high methanol concentration. These differences appear due to the presence of cooperative interactions in water at high concentrations that the LD potentials can capture. In addition, we compare two different approaches to derive our CG models, namely, relative entropy optimization and the Inverse Monte Carlo method, and formally demonstrate under which analytical and numerical assumptions these two methods yield equivalent results.

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.

Ultra-Coarse-Grained Liquid State Models with Implicit Hydrogen Bonding

Coarse-graining (CG) methodologies have been widely used to extend the time and length scales of computer simulations by averaging over the atomistic details beneath the resolution of the CG models. Despite the efficiency of CG models, important configurational information during a given process may be lost at the CG resolution. One example of this is the topology of the hydrogen bonding network in the liquid state. When the functional group that participates in hydrogen bonding (e.g., -OH in methanol) is coarse-grained into one CG site, the effective interactions of the resultant CG model are usually derived from an averaged overall trajectory and, thus, do not take into account the hydrogen bonding interactions and topologies that are present at the all-atom resolution. In order to overcome this challenge, the present study develops new ultra-coarse-grained (UCG) models that include internal states within the CG sites that participate in hydrogen bonding, where each state represents a specific configuration such as the hydrogen bonding donor or acceptor. Internal states of the UCG beads are modeled to remain in quasi-equilibrium, and the degree of mixing is controlled by utilizing the effective local density of the UCG sites. In particular, we consider two groups of UCG models with different types of hydrogen bonding motifs: chain-like and ring-like. Using five different liquid systems that contain the same fundamental functional groups as biomolecules, we demonstrate the ability of the UCG models to reproduce the structural properties that originate from the configurations beneath the resolution of the UCG model. This proposed approach can also be applied to other liquids with such specific and directional interactions, or even to complex biomolecular systems in which hydrogen bonding is critical.

General van der Waals potential for common organic molecules

This work presents a systematic development of a new van der Waals potential (vdW2016) for common organic molecules based on symmetry-adapted perturbation theory (SAPT) energy decomposition. The Buf-14-7 function, as well as Cubic-mean and Waldman-Hagler mixing rules were chosen given their best performance among other popular potentials. A database containing 39 organic molecules and 108 dimers was utilized to derive a general set of vdW parameters, which were further validated on nucleobase stacking systems and testing organic dimers. The vdW2016 potential is anticipated to significantly improve the accuracy and transferability of new generations of force fields for organic molecules.

Equilibrium structures of anisometric, quadrupolar particles confined to a monolayer

We investigate the structural properties of a two-dimensional system of ellipsoidal particles carrying a linear quadrupole moment in their center. These particles represent a simple model for a variety of uncharged, non-polar conjugated organic molecules. Using optimization tools based on ideas of evolutionary algorithms, we first examine the ground state structures as we vary the aspect ratio of the particles and the pressure. Interestingly, we find, besides the intuitively expected T-like configurations, a variety of complex structures, characterized with up to three different particle orientations. In an effort to explore the impact of thermal fluctuations, we perform constant-pressure molecular dynamics simulations within a range of rather low temperatures. We observe that ground state structures formed by particles with a large aspect ratio are in particular suited to withstand fluctuations up to rather high temperatures. Our comprehensive investigations allow for a deeper understanding of molecular or colloidal monolayer arrangements under the influence of a typical electrostatic interaction on a coarse-grained level.

Coarse-Grained Modeling of Nucleic Acids Using Anisotropic Gay-Berne and Electric Multipole Potentials

In this work, we attempt to apply a coarse-grained (CG) model, which is based on anisotropic Gay-Berne and electric multipole (EMP) potentials, to the modeling of nucleic acids. First, a comparison has been made between the CG and atomistic models (AMBER point-charge model) in the modeling of DNA and RNA hairpin structures. The CG results have demonstrated a good quality in maintaining the nucleic acid hairpin structures, in reproducing the dynamics of backbone atoms of nucleic acids, and in describing the hydrogen-bonding interactions between nucleic acid base pairs. Second, the CG and atomistic AMBER models yield comparable results in modeling double-stranded DNA and RNA molecules. It is encouraging that our CG model is capable of reproducing many elastic features of nucleic acid base pairs in terms of the distributions of the interbase pair step parameters (such as shift, slide, tilt, and twist) and the intrabase pair parameters (such as buckle, propeller, shear, and stretch). Finally, The GBEMP model has shown a promising ability to predict the melting temperatures of DNA duplexes with different lengths.

Coarse-graining the structure of polycyclic aromatic hydrocarbons clusters

Clusters of polycyclic aromatic hydrocarbons are essential components of soot and may concentrate a significant fraction of carbon matter in the interstellar medium.

Tabulation as a high-resolution alternative to coarse-graining protein interactions: Initial application to virus capsid subunits

Traditional coarse-graining based on a reduced number of interaction sites often entails a significant sacrifice of chemical accuracy. As an alternative, we present a method for simulating large systems composed of interacting macromolecules using an energy tabulation strategy previously devised for small rigid molecules or molecular fragments [S. Lettieri and D. M. Zuckerman, J. Comput. Chem. 33, 268-275 (2012); J. Spiriti and D. M. Zuckerman, J. Chem. Theory Comput. 10, 5161-5177 (2014)]. We treat proteins as rigid and construct distance and orientation-dependent tables of the interaction energy between them. Arbitrarily detailed interactions may be incorporated into the tables, but as a proof-of-principle, we tabulate a simple α-carbon Gō-like model for interactions between dimeric subunits of the hepatitis B viral capsid. This model is significantly more structurally realistic than previous models used in capsid assembly studies. We are able to increase the speed of Monte Carlo simulations by a factor of up to 6700 compared to simulations without tables, with only minimal further loss in accuracy. To obtain further enhancement of sampling, we combine tabulation with the weighted ensemble (WE) method, in which multiple parallel simulations are occasionally replicated or pruned in order to sample targeted regions of a reaction coordinate space. In the initial study reported here, WE is able to yield pathways of the final ∼25% of the assembly process.

Highly Scalable and Memory Efficient Ultra-Coarse-Grained Molecular Dynamics Simulations

The use of coarse-grained (CG) models can significantly increase the time and length scales accessible to computational molecular dynamics (MD) simulations. To address very large-scale phenomena, however, requires a careful consideration of memory requirements and parallel MD load balancing in order to make efficient use of current supercomputers. In this work, a CG-MD code is introduced which is specifically designed for very large, highly parallel simulations of systems with markedly non-uniform particle distributions, such as those found in highly CG models having an implicit solvent. The CG-MD code uses an unorthodox combination of sparse data representations with a Hilbert space-filling curve (SFC) to provide dynamic topological descriptions, reduced memory overhead, and advanced load-balancing characteristics. The results of representative large-scale simulations indicate that our approach can offer significant advantages over conventional MD techniques, and should enable new classes of CG-MD systems to be investigated.

Liposomal nanohybrid cerasomes for mitochondria-targeted drug delivery

Mitochondrial dysfunctions cause numerous human disorders and the development of mitochondria-targeted nanocarriers for drug delivery has aroused great attention. Herein, we report the synthesis of a liposomal nanohybrid cerasome modified with triphosphonium (TPP) for drug delivery to the mitochondrial matrix. The cerasomes were observed to possess an average size of about 38 nm in diameter, and the theoretical simulation of GBEMP mapping demonstrated that the amphiphilic organotrialkoxysilanes were stable as a bilayer equilibrium conformation after self-assembly. The cerasomes showed good stability, excellent biocompatibility and sustainable drug release behavior. Moreover, the TPP-targeted cerasomes resulted in greater drug accumulation in mitochondria, thus leading to a greater antitumor effect as compared to non-targeted cerasomes by using doxorubicin as a modal drug. The specific accumulation of TPP-targeted cerasomes within mitochondria was also confirmed by using JC-1 as the fluorescent probe to analyze the mitochondrial transmembrane potential change.

United polarizable multipole water model for molecular mechanics simulation

We report the development of a united AMOEBA (uAMOEBA) polarizable water model, which is computationally 3-5 times more efficient than the three-site AMOEBA03 model in molecular dynamics simulations while providing comparable accuracy for gas-phase and liquid properties. In this coarse-grained polarizable water model, both electrostatic (permanent and induced) and van der Waals representations have been reduced to a single site located at the oxygen atom. The permanent charge distribution is described via the molecular dipole and quadrupole moments and the many-body polarization via an isotropic molecular polarizability, all located at the oxygen center. Similarly, a single van der Waals interaction site is used for each water molecule. Hydrogen atoms are retained only for the purpose of defining local frames for the molecular multipole moments and intramolecular vibrational modes. The parameters have been derived based on a combination of ab initio quantum mechanical and experimental data set containing gas-phase cluster structures and energies, and liquid thermodynamic properties. For validation, additional properties including dimer interaction energy, liquid structures, self-diffusion coefficient, and shear viscosity have been evaluated. The results demonstrate good transferability from the gas to the liquid phase over a wide range of temperatures, and from nonpolar to polar environments, due to the presence of molecular polarizability. The water coordination, hydrogen-bonding structure, and dynamic properties given by uAMOEBA are similar to those derived from the all-atom AMOEBA03 model and experiments. Thus, the current model is an accurate and efficient alternative for modeling water.

A comparative study of trypsin specificity based on QM/MM molecular dynamics simulation and QM/MM GBSA calculation

Hydrogen bonding and polar interactions play a key role in identification of protein-inhibitor binding specificity. Quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) simulations combined with DFT and semi-empirical Hamiltonian (AM1d, RM1, PM3, and PM6) methods were performed to study the hydrogen bonding and polar interactions of two inhibitors BEN and BEN1 with trypsin. The results show that the accuracy of treating the hydrogen bonding and polar interactions using QM/MM MD simulation of PM6 can reach the one obtained by the DFT QM/MM MD simulation. Quantum mechanics/molecular mechanics generalized Born surface area (QM/MM-GBSA) method was applied to calculate binding affinities of inhibitors to trypsin and the results suggest that the accuracy of binding affinity prediction can be significantly affected by the accurate treatment of the hydrogen bonding and polar interactions. In addition, the calculated results also reveal the binding specificity of trypsin: (1) the amidinium groups of two inhibitors generate favorable salt bridge interaction with Asp189 and form hydrogen bonding interactions with Ser190 and Gly214, (2) the phenyl of inhibitors can produce favorable van der Waals interactions with the residues His58, Cys191, Gln192, Trp211, Gly212, and Cys215. This systematic and comparative study can provide guidance for the choice of QM/MM MD methods and the designs of new potent inhibitors targeting trypsin.

Heat conduction in nanoscale materials: a statistical-mechanics derivation of the local heat flux

We derive a coarse-grained model for heat conduction in nanoscale mechanical systems. Starting with an all-atom description, this approach yields a reduced model, in the form of conservation laws of momentum and energy. The model closure is accomplished by introducing a quasilocal thermodynamic equilibrium, followed by a linear response approximation. Of particular interest is the constitutive relation for the heat flux, which is expressed nonlocally in terms of the spatial and temporal variation of the temperature. Nanowires made of copper and silicon are presented as examples.

Rupture mechanism of liquid crystal thin films realized by large-scale molecular simulations

The ability of liquid crystal (LC) molecules to respond to changes in their environment makes them an interesting candidate for thin film applications, particularly in bio-sensing, bio-mimicking devices, and optics. Yet the understanding of the (in)stability of this family of thin films has been limited by the inherent challenges encountered by experiment and continuum models. Using unprecedented large-scale molecular dynamics (MD) simulations, we address the rupture origin of LC thin films wetting a solid substrate at length scales similar to those in experiment. Our simulations show the key signatures of spinodal instability in isotropic and nematic films on top of thermal nucleation, and importantly, for the first time, evidence of a common rupture mechanism independent of initial thickness and LC orientational ordering. We further demonstrate that the primary driving force for rupture is closely related to the tendency of the LC mesogens to recover their local environment in the bulk state. Our study not only provides new insights into the rupture mechanism of liquid crystal films, but also sets the stage for future investigations of thin film systems using peta-scale molecular dynamics simulations.

An Anisotropic Coarse-Grained Model for Proteins Based On Gay-Berne and Electric Multipole Potentials

Gay–Berne anisotropic potential has been widely used to evaluate the nonbonded interactions between coarse-grained particles being described as elliptical rigid bodies. In this paper, we are presenting a coarse-grained model for twenty kinds of amino acids and proteins, based on the anisotropic Gay–Berne and point electric multipole (EMP) potentials. We demonstrate that the anisotropic coarse-grained model, namely GBEMP model, is able to reproduce many key features observed from experimental protein structures (Dunbrack Library), as well as from atomistic force field simulations (using AMOEBA, AMBER, and CHARMM force fields), while saving the computational cost by a factor of about 10–200 depending on specific cases and atomistic models. More importantly, unlike other coarse-grained approaches, our framework is based on the fundamental intermolecular forces with explicit treatment of electrostatic and repulsion-dispersion forces. As a result, the coarse-grained protein model presented an accurate description of nonbonded interactions (particularly electrostatic component) between hetero/homodimers (such as peptide–peptide, peptide–water). In addition, the encouraging performance of the model was reflected by the excellent correlation between GBEMP and AMOEBA models in the calculations of the dipole moment of peptides. In brief, the GBEMP model given here is general and transferable, suitable for simulating complex biomolecular systems.