Fluctuating hydrodynamics for multiscale simulation of inhomogeneous fluids: mapping all-atom molecular dynamics to capillary waves

We introduce a multiscale framework to simulate inhomogeneous fluids by coarse-graining an all-atom molecular dynamics (MD) trajectory onto sequential snapshots of hydrodynamic fields. We show that the field representation of an atomistic trajectory is quantitatively described by a dynamic field-theoretic model that couples hydrodynamic fluctuations with a Ginzburg-Landau free energy. For liquid-vapor interfaces of argon and water, the parameters of the field model can be adjusted to reproduce the bulk compressibility and surface tension calculated from the positions and forces of atoms in an MD simulation. These optimized parameters also enable the field model to reproduce the static and dynamic capillary wave spectra calculated from atomistic coordinates at the liquid-vapor interface. In addition, we show that a density-dependent gradient coefficient in the Ginzburg-Landau free energy enables bulk and interfacial fluctuations to be controlled separately. For water, this additional degree of freedom is necessary to capture both the bulk compressibility and surface tension emergent from the atomistic trajectory. The proposed multiscale framework illustrates that bottom-up coarse-graining and top-down phenomenology can be integrated with quantitative consistency to simulate the interfacial fluctuations in nanoscale transport processes.     

The multiscale coarse-graining method. VII. Free energy decomposition of coarse-grained effective potentials

The potential of mean force (PMF) with respect to coarse-grained (CG) coordinates is often calculated in order to study the molecular interactions in atomistic molecular dynamics (MD) simulations. The multiscale coarse-graining (MS-CG) approach enables the computation of the many-body PMF of an atomistic system in terms of the CG coordinates, which can be used to parameterize CG models based on all-atom configurations. We demonstrate here that the MS-CG method can also be used to analyze the CG interactions from atomistic MD trajectories via PMF calculations. In addition, MS-CG calculations at different temperatures are performed to decompose the PMF values into energetic and entropic contributions as a function of the CG coordinates, which provides more thermodynamic information regarding the atomistic system. Two numerical examples, liquid methanol and a dimyristoylphosphatidylcholine lipid bilayer, are presented. The results show that MS-CG can be used as an analysis tool, comparable to various free energy computation methods. The differences between the MS-CG approach and other PMF calculation methods, as well as the characteristics and advantages of MS-CG, are also discussed.     

Molecular latent space simulators

Small integration time steps limit molecular dynamics (MD) simulations to millisecond time scales. Markov state models (MSMs) and equation-free approaches learn low-dimensional kinetic models from MD simulation data by performing configurational or dynamical coarse-graining of the state space. The learned kinetic models enable the efficient generation of dynamical trajectories over vastly longer time scales than are accessible by MD, but the discretization of configurational space and/or absence of a means to reconstruct molecular configurations precludes the generation of continuous atomistic molecular trajectories. We propose latent space simulators (LSS) to learn kinetic models for continuous atomistic simulation trajectories by training three deep learning networks to (i) learn the slow collective variables of the molecular system, (ii) propagate the system dynamics within this slow latent space, and (iii) generatively reconstruct molecular configurations. We demonstrate the approach in an application to Trp-cage miniprotein to produce novel ultra-long synthetic folding trajectories that accurately reproduce atomistic molecular structure, thermodynamics, and kinetics at six orders of magnitude lower cost than MD. The dramatically lower cost of trajectory generation enables greatly improved sampling and greatly reduced statistical uncertainties in estimated thermodynamic averages and kinetic rates.

Latent space simulators learn kinetic models for atomistic simulations and generate novel trajectories at six orders of magnitude lower cost.     

Assessing atomistic and coarse-grained force fields for protein-lipid interactions: the formidable challenge of an ionizable side chain in a membrane

Ionizable amino acid side chains play important roles in membrane protein structure and function, including the activation of voltage-gated ion channels, where it has been previously suggested that charged side chains may move through the hydrocarbon core of the membrane. However, all-atom molecular dynamics simulations have demonstrated large free energy barriers for such lipid-exposed motions. These simulations have also revealed that the membrane will deform due to the presence of a charged side chain, leading to a complex solvation microenvironment for which empirical force fields were not specifically parametrized. We have tested the ability of the all-atom CHARMM, Drude polarizable CHARMM, and a recent implementation of a coarse-grained force field to measure the thermodynamics of arginine-membrane interactions as a function of protonation state. We have employed model systems to attempt to match experimental bulk partitioning and quantum mechanical interactions within the membrane and found that free energy profiles from nonpolarizable and polarizable CHARMM simulations are accurate to within 1-2 kcal/mol. In contrast, the coarse-grained simulations failed to reproduce the same membrane deformations, exhibit interactions that are an order of magnitude too small, and thus, have incorrect free energy profiles. These results illustrate the need for careful parametrization of coarse-grained force fields and demonstrate the utility of atomistic molecular dynamics for providing quantitative thermodynamic and mechanistic analysis of protein-lipid interactions.     

Coarse-grained force field for simulating polymer-tethered silsesquioxane self-assembly in solution

A coarse-grained model has been developed for simulating the self-assembly of nonyl-tethered polyhedral oligomeric silsesquioxane (POSS) nanoparticles in solution. A mapping scheme for groups of atoms in the atomistic molecule onto beads in the coarse-grained model was established. The coarse-grained force field consists of solvent-mediated effective interaction potentials that were derived via a structural-based coarse-graining numerical iteration scheme. The force field was obtained from initial guesses that were refined through two different iteration algorithms. The coarse-graining scheme was validated by comparing the aggregation of POSS molecules observed in simulations of the coarse-grained model to that observed in all-atom simulations containing explicit solvent. At 300 K the effective coarse-grained potentials obtained from different initial guesses are comparable to each other. At 400 K the differences between the force fields obtained from different initial guesses, although small, are noticeable. The use of a different iteration algorithm employing identical initial guesses resulted in the same overall effective potentials for bare cube corner bead sites. In both the coarse-grained and all-atom simulations, small aggregates of POSS molecules were observed with similar local packings of the silsesquioxane cages and tether conformations. The coarse-grained model afforded a savings in computing time of roughly two orders of magnitude. Further comparisons were made between the coarse-grained monotethered POSS model developed here and a minimal model developed in earlier work. The results suggest that the interactions between POSS cages are long ranged and are captured by the coarse-grained model developed here. The minimal model is suitable for capturing the local intermolecular packing of POSS cubes at short separation distances.     

Mixed atomistic and coarse-grained molecular dynamics: simulation of a membrane-bound ion channel

The recently developed multiscale coarse-graining (MS-CG) method (Izvekov, S.; Voth, G. A. J. Phys. Chem. B 2005, 109, 2469; J. Chem. Phys. 2005, 123, 134105) is used to build a mixed all-atom and coarse-grained (AA-CG) model of the gramicidin A (gA) ion channel embedded in a dimyristoylphosphatidylcholine (DMPC) lipid bilayer and water environment. In this model, the gA peptide was described in full atomistic detail, while the lipid and water molecules were described using coarse-grained representations. The atom-CG and CG-CG interactions in the mixed AA-CG model were determined using the MS-CG method. Molecular dynamics (MD) simulations were performed using the resulting AA-CG model. The results from simulations of the AA-CG model compare very favorably to those from all-atom MD simulations of the entire system. Since the MS-CG method employs a general and systematic approach to obtain effective interactions from the underlying all-atom models, the present approach to rigorously develop mixed AA-CG models has the potential to be extended to many other systems.     

Systematic coarse-graining of nanoparticle interactions in molecular dynamics simulation

A recently developed multiscale coarse-graining procedure [Izvekov, S.; Voth, G. A. J. Phys. Chem. B 2005, 109, 2469] is extended to derive coarse-grained models for nanoparticles. The methodology is applied to C(60) and to carbonaceous nanoparticles produced in combustion environments. The coarse-graining of the interparticle force field is accomplished applying a force-matching procedure to data obtained from trajectories and forces from all-atom MD simulations. The CG models are shown to reproduce accurately the structural properties of the nanoparticle systems studied, while allowing for MD simulations of much larger self-assembled nanoparticle systems.     

Multiscale coarse-graining of ionic liquids

A recently developed multiscale coarse-graining (MS-CG) approach for obtaining coarse-grained force fields from fully atomistic molecular dynamics simulation is applied to the challenging case of the EMIM+NO3- ionic liquid. The force-matching in the MS-CG methodology is accomplished with an explicit separation of bonded and nonbonded forces. While the nonbonded forces are adopted from this force-matching approach, the bonded forces are obtained from fitting the statistical configurational data from the atomistic simulations. The many-body electronic polarizability is also successfully broken into effective pair interactions. With a virial constraint fixing the system pressure, the MS-CG models rebuild satisfactory structural and thermodynamic properties for different temperatures. The MS-CG model developed from a modest atomistic simulation is therefore suitable for simulating much larger systems, because the coarse-grained models show significant time integration efficiency. This approach is expected to be general for coarse-graining other ionic liquids, as well as many other liquid-state systems. The limitations of the present coarse-graining procedure are also discussed.     

A multiscale coarse-graining method for biomolecular systems

A new approach is presented for obtaining coarse-grained (CG) force fields from fully atomistic molecular dynamics (MD) trajectories. The method is demonstrated by applying it to derive a CG model for the dimyristoylphosphatidylcholine (DMPC) lipid bilayer. The coarse-graining of the interparticle force field is accomplished by an application of a force-matching procedure to the force data obtained from an explicit atomistic MD simulation of the biomolecular system of interest. Hence, the method is termed a "multiscale" CG (MS-CG) approach in which explicit atomistic-level forces are propagated upward in scale to the coarse-grained level. The CG sites in the lipid bilayer application were associated with the centers-of-mass of atomic groups because of the simplicity in the evaluation of the forces acting on them from the atomistic data. The resulting CG lipid bilayer model is shown to accurately reproduce the structural properties of the phospholipid bilayer.     

Molecular dynamics with the united-residue model of polypeptide chains. II. Langevin and Berendsen-bath dynamics and tests on model alpha-helical systems

The implementation of molecular dynamics (MD) with our physics-based protein united-residue (UNRES) force field, described in the accompanying paper, was extended to Langevin dynamics. The equations of motion are integrated by using a simplified stochastic velocity Verlet algorithm. To compare the results to those with all-atom simulations with implicit solvent in which no explicit stochastic and friction forces are present, we alternatively introduced the Berendsen thermostat. Test simulations on the Ala(10) polypeptide demonstrated that the average kinetic energy is stable with about a 5 fs time step. To determine the correspondence between the UNRES time step and the time step of all-atom molecular dynamics, all-atom simulations with the AMBER 99 force field and explicit solvent and also with implicit solvent taken into account within the framework of the generalized Born/surface area (GBSA) model were carried out on the unblocked Ala(10) polypeptide. We found that the UNRES time scale is 4 times longer than that of all-atom MD simulations because the degrees of freedom corresponding to the fastest motions in UNRES are averaged out. When the reduction of the computational cost for evaluation of the UNRES energy function is also taken into account, UNRES (with hydration included implicitly in the side chain-side chain interaction potential) offers about at least a 4000-fold speed up of computations relative to all-atom simulations with explicit solvent and at least a 65-fold speed up relative to all-atom simulations with implicit solvent. To carry out an initial full-blown test of the UNRES/MD approach, we ran Berendsen-bath and Langevin dynamics simulations of the 46-residue B-domain of staphylococcal protein A. We were able to determine the folding temperature at which all trajectories converged to nativelike structures with both approaches. For comparison, we carried out ab initio folding simulations of this protein at the AMBER 99/GBSA level. The average CPU time for folding protein A by UNRES molecular dynamics was 30 min with a single Alpha processor, compared to about 152 h for all-atom simulations with implicit solvent. It can be concluded that the UNRES/MD approach will enable us to carry out microsecond and, possibly, millisecond simulations of protein folding and, consequently, of the folding process of proteins in real time.     

Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent

A general, transferable coarse-grain (CG) framework based on the Gay-Berne potential and electrostatic point multipole expansion is presented for polypeptide simulations. The solvent effect is described by the Generalized Kirkwood theory. The CG model is calibrated using the results of all-atom simulations of model compounds in solution. Instead of matching the overall effective forces produced by atomic models, the fundamental intermolecular forces such as electrostatic, repulsion-dispersion, and solvation are represented explicitly at a CG level. We demonstrate that the CG alanine dipeptide model is able to reproduce quantitatively the conformational energy of all-atom force fields in both gas and solution phases, including the electrostatic and solvation components. Replica exchange molecular dynamics and microsecond dynamic simulations of polyalanine of 5 and 12 residues reveal that the CG polyalanines fold into "alpha helix" and "beta sheet" structures. The 5-residue polyalanine displays a substantial increase in the "beta strand" fraction relative to the 12-residue polyalanine. The detailed conformational distribution is compared with those reported from recent all-atom simulations and experiments. The results suggest that the new coarse-graining approach presented in this study has the potential to offer both accuracy and efficiency for biomolecular modeling.     

Molecular dynamics and thermodynamic simulations of segregation phenomena in binary metal nanoparticles

Journal of Thermal Analysis and Calorimetry - An approach combining atomistic molecular dynamics (MD) and thermodynamic simulations has been applied to predict the distribution of components in...     

Relating kinetic rates and local energetic roughness by accelerated molecular-dynamics simulations

We show that our accelerated molecular-dynamics (MD) approach can extend the time scale in all-atom MD simulations of biopolymers. We also show that this technique allows for the kinetic rate information to be recaptured. In deducing the kinetic rates, the relationship between the local energetic roughness of the potential-energy landscape and the effective diffusion coefficient is established. These are demonstrated on a very slow but important biomolecular process: the dynamics of cis-trans-isomerization of Ser-Pro motifs. We do not only recapture the slow kinetic rates, which is difficult in traditional MD, but also obtain the underlying roughness of the energy landscape of proteins at atomistic resolution.     

Multiscale coarse-graining of monosaccharides

A systematic multiscale coarse-graining (MS-CG) algorithm is applied to build coarse-grained models for monosaccharides in aqueous solution. The methodology is demonstrated for the example of alpha-D-glucopyranose. The nonbonded interactions are directly derived from the force-matching approach, whereas the bonded interactions are obtained through Boltzmann statistical analyses of the underlying atomistic trajectory. The MS-CG model is shown to reproduce many structural and thermodynamic properties in the constant NPT ensemble. Although the model is derived at a single temperature, pressure, and concentration, it is shown to be reasonably transferable to other thermodynamic states. In this model, long-range interactions are effectively mapped into short-range forces with a moderate cutoff and are evaluated by table look-up. As a result, molecular dynamics employing the MS-CG model is approximately 3 orders of magnitude more efficient than its atomistic counterpart. Consequently, the model is particularly suitable for simulating carbohydrate systems at large length and long time scales. Results for an alpha-(1-->4)-d-glucan with 14 glucose units are also presented, demonstrating that the MS-CG algorithm is also applicable to the coarse-graining of other saccharide systems.     

On Coarse-Graining by the Inverse Monte Carlo Method: Dissipative Particle Dynamics Simulations Made to a Precise Tool in Soft Matter Modeling

We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD) simulations, which are then used in coarse-grained dissipative particle dynamics (DPD) simulations. Here, the effective potentials were obtained by applying the inverse Monte Carlo method [Lyubartsev and Laaksonen, Phys. Rev. E. 52, 3730 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. In our first application of the method, the effective potentials were used in DPD simulations of aqueous NaCl solutions. With the same computational effort we were able to simulate systems of one order of magnitude larger than the MD simulations. The results from the MD and DPD simulations are in excellent agreement.     

Efficient estimation of binding free energies between peptides and an MHC class II molecule using coarse‐grained molecular dynamics simulations with a weighted histogram analysis method

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with the weighted histogram analysis method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse‐grained (CG) force field (MARTINI) is less prone to significant error induced by inadequate‐sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3–4 residue peptide segments while leaving the remaining peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and reliably estimate the binding free energy between an arbitrary peptide and an MHC class II molecule. © 2017 Wiley Periodicals, Inc.     

Structure-based coarse-graining in liquid slabs

Structure-based coarse-graining relies on matching the pair correlation functions of a reference (atomistic) and a coarse-grained system. As such, it is designed for systems with uniform density distributions. Here, we demonstrate how it can be generalized for inhomogeneous systems by coarse-graining slabs of liquid water and methanol in vacuum, as well as a single benzene molecule at the water-vacuum interface. Our conclusion is that coarse-graining performed in inhomogeneous systems improves thermodynamic properties and the structure of interfaces without significant alterations to the local structure of the bulk liquid.     

Coarse-graining: a procedure to generate equilibrated and relaxed models of amorphous polymers

We present a coarse-graining procedure to construct models of amorphous polymers. The method, which was applied to polyethylene, is based on a generation-relaxation strategy previously developed to provide independent atomistic microstructures. The coarse-graining was performed by assigning positions to mesoscopic particles denoted blobs, which represent groups of atoms, through distance, angle and dihedral distribution functions. The interaction energy between pairs of blobs was evaluated through a soft potential, whose parameters were derived from atomistic models. Three levels of coarse-graining that differ in the number of atoms included in the blob have been considered. The structural and energy-related properties calculated using the coarse-grained models developed in this study are in good agreement with those obtained using atomistic simulations.