Model reduction for agent-based social simulation: coarse-graining a civil violence model.
Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G
2012-06-01
Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).
Model reduction for agent-based social simulation: Coarse-graining a civil violence model
NASA Astrophysics Data System (ADS)
Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.
2012-06-01
Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).
Role of translational entropy in spatially inhomogeneous, coarse-grained models
NASA Astrophysics Data System (ADS)
Langenberg, Marcel; Jackson, Nicholas E.; de Pablo, Juan J.; Müller, Marcus
2018-03-01
Coarse-grained models of polymer and biomolecular systems have enabled the computational study of cooperative phenomena, e.g., self-assembly, by lumping multiple atomistic degrees of freedom along the backbone of a polymer, lipid, or DNA molecule into one effective coarse-grained interaction center. Such a coarse-graining strategy leaves the number of molecules unaltered. In order to treat the surrounding solvent or counterions on the same coarse-grained level of description, one can also stochastically group several of those small molecules into an effective, coarse-grained solvent bead or "fluid element." Such a procedure reduces the number of molecules, and we discuss how to compensate the concomitant loss of translational entropy by density-dependent interactions in spatially inhomogeneous systems.
Shen, Lin; Yang, Weitao
2016-04-12
We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grest, Gary S.
2017-09-01
Coupled length and time scales determine the dynamic behavior of polymers and polymer nanocomposites and underlie their unique properties. To resolve the properties over large time and length scales it is imperative to develop coarse grained models which retain the atomistic specificity. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details a nd access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using polyethylene as a model system, we probe how the coarse - graining scale affects themore » measured dynamics with different number methylene group s per coarse - grained beads. Using these models we simulate polyethylene melts for times over 500 ms to study the viscoelastic properties of well - entangled polymer melts and large nanoparticle assembly as the nanoparticles are driven close enough to form nanostructures.« less
Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.
Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E
2017-07-01
We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.
Coarse-Grained Models for Automated Fragmentation and Parametrization of Molecular Databases.
Fraaije, Johannes G E M; van Male, Jan; Becherer, Paul; Serral Gracià, Rubèn
2016-12-27
We calibrate coarse-grained interaction potentials suitable for screening large data sets in top-down fashion. Three new algorithms are introduced: (i) automated decomposition of molecules into coarse-grained units (fragmentation); (ii) Coarse-Grained Reference Interaction Site Model-Hypernetted Chain (CG RISM-HNC) as an intermediate proxy for dissipative particle dynamics (DPD); and (iii) a simple top-down coarse-grained interaction potential/model based on activity coefficient theories from engineering (using COSMO-RS). We find that the fragment distribution follows Zipf and Heaps scaling laws. The accuracy in Gibbs energy of mixing calculations is a few tenths of a kilocalorie per mole. As a final proof of principle, we use full coarse-grained sampling through DPD thermodynamics integration to calculate log P OW for 4627 compounds with an average error of 0.84 log unit. The computational speeds per calculation are a few seconds for CG RISM-HNC and a few minutes for DPD thermodynamic integration.
Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora
2016-02-05
Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion ismore » used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.« less
NASA Astrophysics Data System (ADS)
Farrell, Kathryn; Oden, J. Tinsley; Faghihi, Danial
2015-08-01
A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.
Simulation study of entropy production in the one-dimensional Vlasov system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dai, Zongliang, E-mail: liangliang1223@gmail.com; Wang, Shaojie
2016-07-15
The coarse-grain averaged distribution function of the one-dimensional Vlasov system is obtained by numerical simulation. The entropy productions in cases of the random field, the linear Landau damping, and the bump-on-tail instability are computed with the coarse-grain averaged distribution function. The computed entropy production is converged with increasing length of coarse-grain average. When the distribution function differs slightly from a Maxwellian distribution, the converged value agrees with the result computed by using the definition of thermodynamic entropy. The length of the coarse-grain average to compute the coarse-grain averaged distribution function is discussed.
On the applicability of density dependent effective interactions in cluster-forming systems
NASA Astrophysics Data System (ADS)
Montes-Saralegui, Marta; Kahl, Gerhard; Nikoubashman, Arash
2017-02-01
We systematically studied the validity and transferability of the force-matching algorithm for computing effective pair potentials in a system of dendritic polymers, i.e., a particular class of ultrasoft colloids. We focused on amphiphilic dendrimers, macromolecules which can aggregate into clusters of overlapping particles to minimize the contact area with the surrounding implicit solvent. Simulations were performed for both the monomeric and coarse-grained models in the liquid phase at densities ranging from infinite dilution up to values close to the freezing point. The effective pair potentials for the coarse-grained simulations were computed from the monomeric simulations both in the zero-density limit (Φeff0) and at each investigated finite density (Φeff). Conducting the coarse-grained simulations with Φeff0 at higher densities is not appropriate as they failed at reproducing the structural properties of the monomeric simulations. In contrast, we found excellent agreement between the spatial dendrimer distributions obtained from the coarse-grained simulations with Φeff and the microscopically detailed simulations at low densities, where the macromolecules were distributed homogeneously in the system. However, the reliability of the coarse-grained simulations deteriorated significantly as the density was increased further and the cluster occupation became more polydisperse. Under these conditions, the effective pair potential of the coarse-grained model can no longer be computed by averaging over the whole system, but the local density needs to be taken into account instead.
NASA Astrophysics Data System (ADS)
Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em
2017-01-01
Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.
A Coarse-Grained Protein Model in a Water-like Solvent
NASA Astrophysics Data System (ADS)
Sharma, Sumit; Kumar, Sanat K.; Buldyrev, Sergey V.; Debenedetti, Pablo G.; Rossky, Peter J.; Stanley, H. Eugene
2013-05-01
Simulations employing an explicit atom description of proteins in solvent can be computationally expensive. On the other hand, coarse-grained protein models in implicit solvent miss essential features of the hydrophobic effect, especially its temperature dependence, and have limited ability to capture the kinetics of protein folding. We propose a free space two-letter protein (``H-P'') model in a simple, but qualitatively accurate description for water, the Jagla model, which coarse-grains water into an isotropically interacting sphere. Using Monte Carlo simulations, we design protein-like sequences that can undergo a collapse, exposing the ``Jagla-philic'' monomers to the solvent, while maintaining a ``hydrophobic'' core. This protein-like model manifests heat and cold denaturation in a manner that is reminiscent of proteins. While this protein-like model lacks the details that would introduce secondary structure formation, we believe that these ideas represent a first step in developing a useful, but computationally expedient, means of modeling proteins.
Constructing Optimal Coarse-Grained Sites of Huge Biomolecules by Fluctuation Maximization.
Li, Min; Zhang, John Zenghui; Xia, Fei
2016-04-12
Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10,000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems.
NASA Astrophysics Data System (ADS)
Sanyal, Tanmoy; Shell, M. Scott
2016-07-01
Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one at which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.
Gene regulatory networks: a coarse-grained, equation-free approach to multiscale computation.
Erban, Radek; Kevrekidis, Ioannis G; Adalsteinsson, David; Elston, Timothy C
2006-02-28
We present computer-assisted methods for analyzing stochastic models of gene regulatory networks. The main idea that underlies this equation-free analysis is the design and execution of appropriately initialized short bursts of stochastic simulations; the results of these are processed to estimate coarse-grained quantities of interest, such as mesoscopic transport coefficients. In particular, using a simple model of a genetic toggle switch, we illustrate the computation of an effective free energy Phi and of a state-dependent effective diffusion coefficient D that characterize an unavailable effective Fokker-Planck equation. Additionally we illustrate the linking of equation-free techniques with continuation methods for performing a form of stochastic "bifurcation analysis"; estimation of mean switching times in the case of a bistable switch is also implemented in this equation-free context. The accuracy of our methods is tested by direct comparison with long-time stochastic simulations. This type of equation-free analysis appears to be a promising approach to computing features of the long-time, coarse-grained behavior of certain classes of complex stochastic models of gene regulatory networks, circumventing the need for long Monte Carlo simulations.
Coarse-grained molecular dynamics simulations for giant protein-DNA complexes
NASA Astrophysics Data System (ADS)
Takada, Shoji
Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.
Temporal acceleration of spatially distributed kinetic Monte Carlo simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chatterjee, Abhijit; Vlachos, Dionisios G.
The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less
Ardham, Vikram Reddy; Leroy, Frédéric
2017-10-21
Coarse-grained models have increasingly been used in large-scale particle-based simulations. However, due to their lack of degrees of freedom, it is a priori unlikely that they straightforwardly represent thermal properties with the same accuracy as their atomistic counterparts. We take a first step in addressing the impact of liquid coarse-graining on interfacial heat conduction by showing that an atomistic and a coarse-grained model of water may yield similar values of the Kapitza conductance on few-layer graphene with interactions ranging from hydrophobic to mildly hydrophilic. By design the water models employed yield similar liquid layer structures on the graphene surfaces. Moreover, they share common vibration properties close to the surfaces and thus couple with the vibrations of graphene in a similar way. These common properties explain why they yield similar Kapitza conductance values despite their bulk thermal conductivity differing by more than a factor of two.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Tong; Gu, YuanTong, E-mail: yuantong.gu@qut.edu.au
As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grainedmore » level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanyal, Tanmoy; Shell, M. Scott, E-mail: shell@engineering.ucsb.edu
Bottom-up multiscale techniques are frequently used to develop coarse-grained (CG) models for simulations at extended length and time scales but are often limited by a compromise between computational efficiency and accuracy. The conventional approach to CG nonbonded interactions uses pair potentials which, while computationally efficient, can neglect the inherently multibody contributions of the local environment of a site to its energy, due to degrees of freedom that were coarse-grained out. This effect often causes the CG potential to depend strongly on the overall system density, composition, or other properties, which limits its transferability to states other than the one atmore » which it was parameterized. Here, we propose to incorporate multibody effects into CG potentials through additional nonbonded terms, beyond pair interactions, that depend in a mean-field manner on local densities of different atomic species. This approach is analogous to embedded atom and bond-order models that seek to capture multibody electronic effects in metallic systems. We show that the relative entropy coarse-graining framework offers a systematic route to parameterizing such local density potentials. We then characterize this approach in the development of implicit solvation strategies for interactions between model hydrophobes in an aqueous environment.« less
Recent Advances in Transferable Coarse-Grained Modeling of Proteins
Kar, Parimal; Feig, Michael
2017-01-01
Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems are employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multi-scale hybrid all-atom/coarse-grained simulations of proteins. PMID:25443957
NASA Astrophysics Data System (ADS)
Zeman, Johannes; Uhlig, Frank; Smiatek, Jens; Holm, Christian
2017-12-01
We present a coarse-grained polarizable molecular dynamics force field for the ionic liquid 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIm][PF6]). For the treatment of electronic polarizability, we employ the Drude model. Our results show that the new explicitly polarizable force field reproduces important static and dynamic properties such as mass density, enthalpy of vaporization, diffusion coefficients, or electrical conductivity in the relevant temperature range. In situations where an explicit treatment of electronic polarizability might be crucial, we expect the force field to be an improvement over non-polarizable models, while still profiting from the reduction of computational cost due to the coarse-grained representation.
NASA Astrophysics Data System (ADS)
Fu, S.-P.; Peng, Z.; Yuan, H.; Kfoury, R.; Young, Y.-N.
2017-01-01
Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiencies have been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 ∼ 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane, such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity Yuan et al. (2010). In this work we implement such an interaction potential in LAMMPS to simulate large-scale lipid systems such as a giant unilamellar vesicle (GUV) and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for RBC dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. To demonstrate that the proposed methods do capture the observed dynamics of vesicles and RBCs, we focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with enclosed volume; 2. RBC shape transitions with different enclosed volume. Finally utilizing the parallel computing capability in LAMMPS, we provide some timing results for parallel coarse-grained simulations to illustrate that it is possible to use LAMMPS to simulate large-scale realistic complex biological membranes for more than 1 ms.
NASA Astrophysics Data System (ADS)
Min, Sa Hoon; Berkowitz, Max L.
2018-04-01
We performed molecular dynamics simulations to study how well some of the water models used in simulations describe shocked states. Water in our simulations was described using three different models. One was an often-used all-atom TIP4P/2005 model, while the other two were coarse-grained models used with the MARTINI force field: non-polarizable and polarizable MARTINI water. The all-atom model provided results in good agreement with Hugoniot curves (for data on pressure versus specific volume or, equivalently, on shock wave velocity versus "piston" velocity) describing shocked states in the whole range of pressures (up to 11 GPa) under study. If simulations of shocked states of water using coarse-grained models were performed for short time periods, we observed that data obtained for shocked states at low pressure were fairly accurate compared to experimental Hugoniot curves. Polarizable MARTINI water still provided a good description of Hugoniot curves for pressures up to 11 GPa, while the results for the non-polarizable MARTINI water substantially deviated from the Hugoniot curves. We also calculated the temperature of the Hugoniot states and observed that for TIP4P/2005 water, they were consistent with those from theoretical calculations, while both coarse-grained models predicted much higher temperatures. These high temperatures for MARTINI water can be explained by the loss of degrees of freedom due to coarse-graining procedure.
Modification of Hazen's equation in coarse grained soils by soft computing techniques
NASA Astrophysics Data System (ADS)
Kaynar, Oguz; Yilmaz, Isik; Marschalko, Marian; Bednarik, Martin; Fojtova, Lucie
2013-04-01
Hazen first proposed a Relationship between coefficient of permeability (k) and effective grain size (d10) was first proposed by Hazen, and it was then extended by some other researchers. However many attempts were done for estimation of k, correlation coefficients (R2) of the models were generally lower than ~0.80 and whole grain size distribution curves were not included in the assessments. Soft computing techniques such as; artificial neural networks, fuzzy inference systems, genetic algorithms, etc. and their hybrids are now being successfully used as an alternative tool. In this study, use of some soft computing techniques such as Artificial Neural Networks (ANNs) (MLP, RBF, etc.) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for prediction of permeability of coarse grained soils was described, and Hazen's equation was then modificated. It was found that the soft computing models exhibited high performance in prediction of permeability coefficient. However four different kinds of ANN algorithms showed similar prediction performance, results of MLP was found to be relatively more accurate than RBF models. The most reliable prediction was obtained from ANFIS model.
Ruff, Kiersten M.; Harmon, Tyler S.; Pappu, Rohit V.
2015-01-01
We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences. PMID:26723608
Coarse-Graining of Polymer Dynamics via Energy Renormalization
NASA Astrophysics Data System (ADS)
Xia, Wenjie; Song, Jake; Phelan, Frederick; Douglas, Jack; Keten, Sinan
The computational prediction of the properties of polymeric materials to serve the needs of materials design and prediction of their performance is a grand challenge due to the prohibitive computational times of all-atomistic (AA) simulations. Coarse-grained (CG) modeling is an essential strategy for making progress on this problem. While there has been intense activity in this area, effective methods of coarse-graining have been slow to develop. Our approach to this fundamental problem starts from the observation that integrating out degrees of freedom of the AA model leads to a strong modification of the configurational entropy and cohesive interaction. Based on this observation, we propose a temperature-dependent systematic renormalization of the cohesive interaction in the CG modeling to recover the thermodynamic modifications in the system and the dynamics of the AA model. Here, we show that this energy renormalization approach to CG can faithfully estimate the diffusive, segmental and glassy dynamics of the AA model over a large temperature range spanning from the Arrhenius melt to the non-equilibrium glassy states. Our proposed CG strategy offers a promising strategy for developing thermodynamically consistent CG models with temperature transferability.
Coarse-graining of proteins based on elastic network models
NASA Astrophysics Data System (ADS)
Sinitskiy, Anton V.; Voth, Gregory A.
2013-08-01
To simulate molecular processes on biologically relevant length- and timescales, coarse-grained (CG) models of biomolecular systems with tens to even hundreds of residues per CG site are required. One possible way to build such models is explored in this article: an elastic network model (ENM) is employed to define the CG variables. Free energy surfaces are approximated by Taylor series, with the coefficients found by force-matching. CG potentials are shown to undergo renormalization due to roughness of the energy landscape and smoothing of it under coarse-graining. In the case study of hen egg-white lysozyme, the entropy factor is shown to be of critical importance for maintaining the native structure, and a relationship between the proposed ENM-mode-based CG models and traditional CG-bead-based models is discussed. The proposed approach uncovers the renormalizable character of CG models and offers new opportunities for automated and computationally efficient studies of complex free energy surfaces.
Landau-Lifshitz-Bloch equation for exchange-coupled grains
NASA Astrophysics Data System (ADS)
Vogler, Christoph; Abert, Claas; Bruckner, Florian; Suess, Dieter
2014-12-01
Heat-assisted recording is a promising technique to further increase the storage density in hard disks. Multilayer recording grains with graded Curie temperature is discussed to further assist the write process. Describing the correct magnetization dynamics of these grains, from room temperature to far above the Curie point, during a write process is required for the calculation of bit error rates. We present a coarse-grained approach based on the Landau-Lifshitz-Bloch (LLB) equation to model exchange-coupled grains with low computational effort. The required temperature-dependent material properties such as the zero-field equilibrium magnetization as well as the parallel and normal susceptibilities are obtained by atomistic Landau-Lifshitz-Gilbert simulations. Each grain is described with one magnetization vector. In order to mimic the atomistic exchange interaction between the grains a special treatment of the exchange field in the coarse-grained approach is presented. With the coarse-grained LLB model the switching probability of a recording grain consisting of two layers with graded Curie temperature is investigated in detail by calculating phase diagrams for different applied heat pulses and external magnetic fields.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir A.; Skripnyak, Natalia V.; Skripnyak, Evgeniya G.; Skripnyak, Vladimir V.
2017-01-01
Inelastic deformation and damage at the mesoscale level of ultrafine grained (UFG) light alloys with distribution of grain size were investigated in wide loading conditions by experimental and computer simulation methods. The computational multiscale models of representative volume element (RVE) with the unimodal and bimodal grain size distributions were developed using the data of structure researches aluminum and magnesium UFG alloys. The critical fracture stress of UFG alloys on mesoscale level depends on relative volumes of coarse grains. Microcracks nucleation at quasi-static and dynamic loading is associated with strain localization in UFG partial volumes with bimodal grain size distribution. Microcracks arise in the vicinity of coarse and ultrafine grains boundaries. It is revealed that the occurrence of bimodal grain size distributions causes the increasing of UFG alloys ductility, but decreasing of the tensile strength.
Optimization of droplets for UV-NIL using coarse-grain simulation of resist flow
NASA Astrophysics Data System (ADS)
Sirotkin, Vadim; Svintsov, Alexander; Zaitsev, Sergey
2009-03-01
A mathematical model and numerical method are described, which make it possible to simulate ultraviolet ("step and flash") nanoimprint lithography (UV-NIL) process adequately even using standard Personal Computers. The model is derived from 3D Navier-Stokes equations with the understanding that the resist motion is largely directed along the substrate surface and characterized by ultra-low values of the Reynolds number. By the numerical approximation of the model, a special finite difference method is applied (a coarse-grain method). A coarse-grain modeling tool for detailed analysis of resist spreading in UV-NIL at the structure-scale level is tested. The obtained results demonstrate the high ability of the tool to calculate optimal dispensing for given stamp design and process parameters. This dispensing provides uniform filled areas and a homogeneous residual layer thickness in UV-NIL.
Grain-scale modeling and splash parametrization for aeolian sand transport.
Lämmel, Marc; Dzikowski, Kamil; Kroy, Klaus; Oger, Luc; Valance, Alexandre
2017-02-01
The collision of a spherical grain with a granular bed is commonly parametrized by the splash function, which provides the velocity of the rebounding grain and the velocity distribution and number of ejected grains. Starting from elementary geometric considerations and physical principles, like momentum conservation and energy dissipation in inelastic pair collisions, we derive a rebound parametrization for the collision of a spherical grain with a granular bed. Combined with a recently proposed energy-splitting model [Ho et al., Phys. Rev. E 85, 052301 (2012)PLEEE81539-375510.1103/PhysRevE.85.052301] that predicts how the impact energy is distributed among the bed grains, this yields a coarse-grained but complete characterization of the splash as a function of the impact velocity and the impactor-bed grain-size ratio. The predicted mean values of the rebound angle, total and vertical restitution, ejection speed, and number of ejected grains are in excellent agreement with experimental literature data and with our own discrete-element computer simulations. We extract a set of analytical asymptotic relations for shallow impact geometries, which can readily be used in coarse-grained analytical modeling or computer simulations of geophysical particle-laden flows.
Relative entropy and optimization-driven coarse-graining methods in VOTCA
Mashayak, S. Y.; Jochum, Mara N.; Koschke, Konstantin; ...
2015-07-20
We discuss recent advances of the VOTCA package for systematic coarse-graining. Two methods have been implemented, namely the downhill simplex optimization and the relative entropy minimization. We illustrate the new methods by coarse-graining SPC/E bulk water and more complex water-methanol mixture systems. The CG potentials obtained from both methods are then evaluated by comparing the pair distributions from the coarse-grained to the reference atomistic simulations.We have also added a parallel analysis framework to improve the computational efficiency of the coarse-graining process.
2013-11-01
duration, or shock-pulse shape. Used in this computational study is a coarse-grained model of the lipid vesicle as a simplified model of a cell...Figures iv List of Tables iv 1. Introduction 1 2. Model and Methods 3 3. Results and Discussion 6 3.1 Simulation of the Blast Waves with Low Peak...realistic detail but to focus on a simple model of the major constituent of a cell membrane, the phospholipid bilayer. In this work, we studied the
A coarse-grained DNA model for the prediction of current signals in DNA translocation experiments
NASA Astrophysics Data System (ADS)
Weik, Florian; Kesselheim, Stefan; Holm, Christian
2016-11-01
We present an implicit solvent coarse-grained double-stranded DNA (dsDNA) model confined to an infinite cylindrical pore that reproduces the experimentally observed current modulations of a KaCl solution at various concentrations. Our model extends previous coarse-grained and mean-field approaches by incorporating a position dependent friction term on the ions, which Kesselheim et al. [Phys. Rev. Lett. 112, 018101 (2014)] identified as an essential ingredient to correctly reproduce the experimental data of Smeets et al. [Nano Lett. 6, 89 (2006)]. Our approach reduces the computational effort by orders of magnitude compared with all-atom simulations and serves as a promising starting point for modeling the entire translocation process of dsDNA. We achieve a consistent description of the system's electrokinetics by using explicitly parameterized ions, a friction term between the DNA beads and the ions, and a lattice-Boltzmann model for the solvent.
Computationally Guided Design of Polymer Electrolytes for Battery Applications
NASA Astrophysics Data System (ADS)
Wang, Zhen-Gang; Webb, Michael; Savoie, Brett; Miller, Thomas
We develop an efficient computational framework for guiding the design of polymer electrolytes for Li battery applications. Short-times molecular dynamics (MD) simulations are employed to identify key structural and dynamic features in the solvation and motion of Li ions, such as the structure of the solvation shells, the spatial distribution of solvation sites, and the polymer segmental mobility. Comparative studies on six polyester-based polymers and polyethylene oxide (PEO) yield good agreement with experimental data on the ion conductivities, and reveal significant differences in the ion diffusion mechanism between PEO and the polyesters. The molecular insights from the MD simulations are used to build a chemically specific coarse-grained model in the spirit of the dynamic bond percolation model of Druger, Ratner and Nitzan. We apply this coarse-grained model to characterize Li ion diffusion in several existing and yet-to-be synthesized polyethers that differ by oxygen content and backbone stiffness. Good agreement is obtained between the predictions of the coarse-grained model and long-timescale atomistic MD simulations, thus providing validation of the model. Our study predicts higher Li ion diffusivity in poly(trimethylene oxide-alt-ethylene oxide) than in PEO. These results demonstrate the potential of this computational framework for rapid screening of new polymer electrolytes based on ion diffusivity.
NASA Astrophysics Data System (ADS)
Sellers, Michael; Lisal, Martin; Schweigert, Igor; Larentzos, James; Brennan, John
2015-06-01
In discrete particle simulations, when an atomistic model is coarse-grained, a trade-off is made: a boost in computational speed for a reduction in accuracy. Dissipative Particle Dynamics (DPD) methods help to recover accuracy in viscous and thermal properties, while giving back a small amount of computational speed. One of the most notable extensions of DPD has been the introduction of chemical reactivity, called DPD-RX. Today, pairing the current evolution of DPD-RX with a coarse-grained potential and its chemical decomposition reactions allows for the simulation of the shock behavior of energetic materials at a timescale faster than an atomistic counterpart. In 2007, Maillet et al. introduced implicit chemical reactivity in DPD through the concept of particle reactors and simulated the decomposition of liquid nitromethane. We have recently extended the DPD-RX method and have applied it to solid hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) under shock conditions using a recently developed single-site coarse-grain model and a reduced RDX decomposition mechanism. A description of the methods used to simulate RDX and its tranition to hot product gases within DPD-RX will be presented. Additionally, examples of the effect of microstructure on shock behavior will be shown. Approved for public release. Distribution is unlimited.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir
2012-03-01
Features of mechanical behavior of nanostructured and ultrafine-grained metals under quasistatic and shock wave loadings are discussed. Features of mechanical behavior of nanostructured and ultrafine grained metals over a wide range of strain rates are discussed. A constitutive model for mechanical behavior of metal alloys under shock wave loading including a grain size distribution, a precipitate hardening, and physical mechanisms of shear stress relaxation is presented. Strain rate sensitivity of the yield stress of face-centered-cubic, hexagonal close-packed metal alloys depends on grain size, whereas the Hugoniot elastic limits of ultrafine-grained copper, aluminum, and titanium alloys are close to values of coarse-grained counterparts. At quasi-static loading the yield strength and the tensile strength of titanium alloys with grain size from 300 to 500 nm are twice higher than at coarse-grained counterparts. But the spall strength of the UFG titanium alloys exceeds the value of coarse-grained counterparts only for 10 percents.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir; Skripnyak, Evgeniya; Meyer, Lothar W.; Herzig, Norman; Skripnyak, Nataliya
2012-02-01
Researches of the last years have allowed to establish that the laws of deformation and fracture of bulk ultrafine-grained and coarse-grained materials are various both in static and in dynamic loading conditions. Development of adequate constitutive equations for the description of mechanical behavior of bulk ultrafine-grained materials at intensive dynamic influences is complicated in consequence of insufficient knowledge about general rules of inelastic deformation and nucleation and growth of cracks. Multi-scale computational model was used for the investigation of deformation and fracture of bulk structured aluminum and magnesium alloys under stress pulse loadings on mesoscale level. The increment of plastic deformation is defined by the sum of the increments caused by a nucleation and gliding of dislocations, the twinning, meso-blocks movement, and grain boundary sliding. The model takes into account the influence on mechanical properties of alloys an average grains size, grain sizes distribution of and concentration of precipitates. It was obtained the nucleation and gliding of dislocations caused the high attenuation rate of the elastic precursor of ultrafine-grained alloys than in coarse grained counterparts.
Interlaced coarse-graining for the dynamical cluster approximation
NASA Astrophysics Data System (ADS)
Haehner, Urs; Staar, Peter; Jiang, Mi; Maier, Thomas; Schulthess, Thomas
The negative sign problem remains a challenging limiting factor in quantum Monte Carlo simulations of strongly correlated fermionic many-body systems. The dynamical cluster approximation (DCA) makes this problem less severe by coarse-graining the momentum space to map the bulk lattice to a cluster embedded in a dynamical mean-field host. Here, we introduce a new form of an interlaced coarse-graining and compare it with the traditional coarse-graining. We show that it leads to more controlled results with weaker cluster shape and smoother cluster size dependence, which with increasing cluster size converge to the results obtained using the standard coarse-graining. In addition, the new coarse-graining reduces the severity of the fermionic sign problem. Therefore, it enables calculations on much larger clusters and can allow the evaluation of the exact infinite cluster size result via finite size scaling. To demonstrate this, we study the hole-doped two-dimensional Hubbard model and show that the interlaced coarse-graining in combination with the DCA+ algorithm permits the determination of the superconducting Tc on cluster sizes, for which the results can be fitted with the Kosterlitz-Thouless scaling law. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) awarded by the INCITE program, and of the Swiss National Supercomputing Center. OLCF is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.
Coarse-grained Simulations of Conformational Changes in Multidrug Resistance Transporters
NASA Astrophysics Data System (ADS)
Jewel, S. M. Yead; Dutta, Prashanta; Liu, Jin
2016-11-01
The overexpression of multidrug resistance (MDR) systems on the gram negative bacteria causes serious problems for treatment of bacterial infectious diseases. The system effectively pumps the antibiotic drugs out of the bacterial cells. During the pumping process one of the MDR components, AcrB undergoes a series of large-scale conformational changes which are responsible for drug recognition, binding and expelling. All-atom simulations are unable to capture those conformational changes because of computational cost. Here, we implement a hybrid coarse-grained force field that couples the united-atom protein models with the coarse-grained MARTINI water/lipid, to investigate the proton-dependent conformational changes of AcrB. The simulation results in early stage ( 100 ns) of proton-dependent conformational changes agree with all-atom simulations, validating the coarse-grained model. The coarse-grained force field allows us to explore the process in microsecond simulations. Starting from the crystal structures of Access(A)/Binding(B)/Extrusion(E) monomers in AcrB, we find that deprotonation of Asp407 and Asp408 in monomer E causes a series of large-scale conformational changes from ABE to AAA in absence of drug molecules, which is consistent with experimental findings. This work is supported by NIH Grant: 1R01GM122081-01.
A coarse grain model for protein-surface interactions
NASA Astrophysics Data System (ADS)
Wei, Shuai; Knotts, Thomas A.
2013-09-01
The interaction of proteins with surfaces is important in numerous applications in many fields—such as biotechnology, proteomics, sensors, and medicine—but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.
A simple, efficient polarizable coarse-grained water model for molecular dynamics simulations.
Riniker, Sereina; van Gunsteren, Wilfred F
2011-02-28
The development of coarse-grained (CG) models that correctly represent the important features of compounds is essential to overcome the limitations in time scale and system size currently encountered in atomistic molecular dynamics simulations. Most approaches reported in the literature model one or several molecules into a single uncharged CG bead. For water, this implicit treatment of the electrostatic interactions, however, fails to mimic important properties, e.g., the dielectric screening. Therefore, a coarse-grained model for water is proposed which treats the electrostatic interactions between clusters of water molecules explicitly. Five water molecules are embedded in a spherical CG bead consisting of two oppositely charged particles which represent a dipole. The bond connecting the two particles in a bead is unconstrained, which makes the model polarizable. Experimental and all-atom simulated data of liquid water at room temperature are used for parametrization of the model. The experimental density and the relative static dielectric permittivity were chosen as primary target properties. The model properties are compared with those obtained from experiment, from clusters of simple-point-charge water molecules of appropriate size in the liquid phase, and for other CG water models if available. The comparison shows that not all atomistic properties can be reproduced by a CG model, so properties of key importance have to be selected when coarse graining is applied. Yet, the CG model reproduces the key characteristics of liquid water while being computationally 1-2 orders of magnitude more efficient than standard fine-grained atomistic water models.
NASA Astrophysics Data System (ADS)
He, Xibing; Shinoda, Wataru; DeVane, Russell; Anderson, Kelly L.; Klein, Michael L.
2010-02-01
A coarse-grained (CG) forcefield for linear alkylbenzene sulfonates (LAS) was systematically parameterized. Thermodynamic data from experiments and structural data obtained from all-atom molecular dynamics were used as targets to parameterize CG potentials for the bonded and non-bonded interactions. The added computational efficiency permits one to employ computer simulation to probe the self-assembly of LAS aqueous solutions into different morphologies starting from a random configuration. The present CG model is shown to accurately reproduce the phase behavior of solutions of pure isomers of sodium dodecylbenzene sulfonate, despite the fact that phase behavior was not directly taken into account in the forcefield parameterization.
NASA Astrophysics Data System (ADS)
Vu, Tuan V.; Papavassiliou, Dimitrios V.
2018-05-01
In order to investigate the interfacial region between oil and water with the presence of surfactants using coarse-grained computations, both the interaction between different components of the system and the number of surfactant molecules present at the interface play an important role. However, in many prior studies, the amount of surfactants used was chosen rather arbitrarily. In this work, a systematic approach to develop coarse-grained models for anionic surfactants (such as sodium dodecyl sulfate) and nonionic surfactants (such as octaethylene glycol monododecyl ether) in oil-water interfaces is presented. The key is to place the theoretically calculated number of surfactant molecules on the interface at the critical micelle concentration. Based on this approach, the molecular description of surfactants and the effects of various interaction parameters on the interfacial tension are investigated. The results indicate that the interfacial tension is affected mostly by the head-water and tail-oil interaction. Even though the procedure presented herein is used with dissipative particle dynamics models, it can be applied for other coarse-grained methods to obtain the appropriate set of parameters (or force fields) to describe the surfactant behavior on the oil-water interface.
Coarse-grained modeling of RNA 3D structure.
Dawson, Wayne K; Maciejczyk, Maciej; Jankowska, Elzbieta J; Bujnicki, Janusz M
2016-07-01
Functional RNA molecules depend on three-dimensional (3D) structures to carry out their tasks within the cell. Understanding how these molecules interact to carry out their biological roles requires a detailed knowledge of RNA 3D structure and dynamics as well as thermodynamics, which strongly governs the folding of RNA and RNA-RNA interactions as well as a host of other interactions within the cellular environment. Experimental determination of these properties is difficult, and various computational methods have been developed to model the folding of RNA 3D structures and their interactions with other molecules. However, computational methods also have their limitations, especially when the biological effects demand computation of the dynamics beyond a few hundred nanoseconds. For the researcher confronted with such challenges, a more amenable approach is to resort to coarse-grained modeling to reduce the number of data points and computational demand to a more tractable size, while sacrificing as little critical information as possible. This review presents an introduction to the topic of coarse-grained modeling of RNA 3D structures and dynamics, covering both high- and low-resolution strategies. We discuss how physics-based approaches compare with knowledge based methods that rely on databases of information. In the course of this review, we discuss important aspects in the reasoning process behind building different models and the goals and pitfalls that can result. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Coarse-Grained Models for Protein-Cell Membrane Interactions
Bradley, Ryan; Radhakrishnan, Ravi
2015-01-01
The physiological properties of biological soft matter are the product of collective interactions, which span many time and length scales. Recent computational modeling efforts have helped illuminate experiments that characterize the ways in which proteins modulate membrane physics. Linking these models across time and length scales in a multiscale model explains how atomistic information propagates to larger scales. This paper reviews continuum modeling and coarse-grained molecular dynamics methods, which connect atomistic simulations and single-molecule experiments with the observed microscopic or mesoscale properties of soft-matter systems essential to our understanding of cells, particularly those involved in sculpting and remodeling cell membranes. PMID:26613047
2015-01-01
Many commonly used coarse-grained models for proteins are based on simplified interaction sites and consequently may suffer from significant limitations, such as the inability to properly model protein secondary structure without the addition of restraints. Recent work on a benzene fluid (LettieriS.; ZuckermanD. M.J. Comput. Chem.2012, 33, 268−27522120971) suggested an alternative strategy of tabulating and smoothing fully atomistic orientation-dependent interactions among rigid molecules or fragments. Here we report our initial efforts to apply this approach to the polar and covalent interactions intrinsic to polypeptides. We divide proteins into nearly rigid fragments, construct distance and orientation-dependent tables of the atomistic interaction energies between those fragments, and apply potential energy smoothing techniques to those tables. The amount of smoothing can be adjusted to give coarse-grained models that range from the underlying atomistic force field all the way to a bead-like coarse-grained model. For a moderate amount of smoothing, the method is able to preserve about 70–90% of the α-helical structure while providing a factor of 3–10 improvement in sampling per unit computation time (depending on how sampling is measured). For a greater amount of smoothing, multiple folding–unfolding transitions of the peptide were observed, along with a factor of 10–100 improvement in sampling per unit computation time, although the time spent in the unfolded state was increased compared with less smoothed simulations. For a β hairpin, secondary structure is also preserved, albeit for a narrower range of the smoothing parameter and, consequently, for a more modest improvement in sampling. We have also applied the new method in a “resolution exchange” setting, in which each replica runs a Monte Carlo simulation with a different degree of smoothing. We obtain exchange rates that compare favorably to our previous efforts at resolution exchange (LymanE.; ZuckermanD. M.J. Chem. Theory Comput.2006, 2, 656−666). PMID:25400525
Emperador, Agustí; Sfriso, Pedro; Villarreal, Marcos Ariel; Gelpí, Josep Lluis; Orozco, Modesto
2015-12-08
Molecular dynamics simulations of proteins are usually performed on a single molecule, and coarse-grained protein models are calibrated using single-molecule simulations, therefore ignoring intermolecular interactions. We present here a new coarse-grained force field for the study of many protein systems. The force field, which is implemented in the context of the discrete molecular dynamics algorithm, is able to reproduce the properties of folded and unfolded proteins, in both isolation, complexed forming well-defined quaternary structures, or aggregated, thanks to its proper evaluation of protein-protein interactions. The accuracy and computational efficiency of the method makes it a universal tool for the study of the structure, dynamics, and association/dissociation of proteins.
Extension of a coarse grained particle method to simulate heat transfer in fluidized beds
Lu, Liqiang; Morris, Aaron; Li, Tingwen; ...
2017-04-18
The heat transfer in a gas-solids fluidized bed is simulated with computational fluid dynamic-discrete element method (CFD-DEM) and coarse grained particle method (CGPM). In CGPM fewer numerical particles and their collisions are tracked by lumping several real particles into a computational parcel. Here, the assumption is that the real particles inside a coarse grained particle (CGP) are made from same species and share identical physical properties including density, diameter and temperature. The parcel-fluid convection term in CGPM is calculated using the same method as in DEM. For all other heat transfer mechanisms, we derive in this study mathematical expressions thatmore » relate the new heat transfer terms for CGPM to those traditionally derived in DEM. This newly derived CGPM model is verified and validated by comparing the results with CFD-DEM simulation results and experiment data. The numerical results compare well with experimental data for both hydrodynamics and temperature profiles. Finally, the proposed CGPM model can be used for fast and accurate simulations of heat transfer in large scale gas-solids fluidized beds.« less
Extension of a coarse grained particle method to simulate heat transfer in fluidized beds
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Liqiang; Morris, Aaron; Li, Tingwen
The heat transfer in a gas-solids fluidized bed is simulated with computational fluid dynamic-discrete element method (CFD-DEM) and coarse grained particle method (CGPM). In CGPM fewer numerical particles and their collisions are tracked by lumping several real particles into a computational parcel. Here, the assumption is that the real particles inside a coarse grained particle (CGP) are made from same species and share identical physical properties including density, diameter and temperature. The parcel-fluid convection term in CGPM is calculated using the same method as in DEM. For all other heat transfer mechanisms, we derive in this study mathematical expressions thatmore » relate the new heat transfer terms for CGPM to those traditionally derived in DEM. This newly derived CGPM model is verified and validated by comparing the results with CFD-DEM simulation results and experiment data. The numerical results compare well with experimental data for both hydrodynamics and temperature profiles. Finally, the proposed CGPM model can be used for fast and accurate simulations of heat transfer in large scale gas-solids fluidized beds.« less
Hybrid continuum-coarse-grained modeling of erythrocytes
NASA Astrophysics Data System (ADS)
Lyu, Jinming; Chen, Paul G.; Boedec, Gwenn; Leonetti, Marc; Jaeger, Marc
2018-06-01
The red blood cell (RBC) membrane is a composite structure, consisting of a phospholipid bilayer and an underlying membrane-associated cytoskeleton. Both continuum and particle-based coarse-grained RBC models make use of a set of vertices connected by edges to represent the RBC membrane, which can be seen as a triangular surface mesh for the former and a spring network for the latter. Here, we present a modeling approach combining an existing continuum vesicle model with a coarse-grained model for the cytoskeleton. Compared to other two-component approaches, our method relies on only one mesh, representing the cytoskeleton, whose velocity in the tangential direction of the membrane may be different from that of the lipid bilayer. The finitely extensible nonlinear elastic (FENE) spring force law in combination with a repulsive force defined as a power function (POW), called FENE-POW, is used to describe the elastic properties of the RBC membrane. The mechanical interaction between the lipid bilayer and the cytoskeleton is explicitly computed and incorporated into the vesicle model. Our model includes the fundamental mechanical properties of the RBC membrane, namely fluidity and bending rigidity of the lipid bilayer, and shear elasticity of the cytoskeleton while maintaining surface-area and volume conservation constraint. We present three simulation examples to demonstrate the effectiveness of this hybrid continuum-coarse-grained model for the study of RBCs in fluid flows.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir
2011-06-01
Features of mechanical behavior of nanostructured (NS) and ultrafine grained (UFG) metal and ceramic materials under quasistatic and shock wave loadings are discussed in this report. Multilevel models developed within the approach of computational mechanics of materials were used for simulation mechanical behavior of UFG and NS metals and ceramics. Comparisons of simulation results with experimental data are presented. Models of mechanical behavior of nanostructured metal alloys takes into account a several structural factors influencing on the mechanical behavior of materials (type of a crystal lattice, density of dislocations, a size of dislocation substructures, concentration and size of phase precipitation, and distribution of grains sizes). Results show the strain rate sensitivity of the yield stress of UFG and polycrystalline alloys is various in a range from 103 up to 106 1/s. But the difference of the Hugoniot elastic limits of a UFG and coarse-grained alloys may be not considerable. The spall strength, the yield stress of UFG and NS alloys are depend not only on grains size, but a number of factors such as a distribution of grains sizes, a concentration and sizes of voids and cracks, a concentration and sizes of phase precipitation. Some titanium alloys with grain sizes from 300 to 500 nm have the quasi-static yield strength and the tensile strength twice higher than that of coarse grained counterparts. But the spall strength of the UFG titanium alloys is only 10 percents above than that of coarse grained alloys. At the same time it was found the spall strength of the bulk UFG aluminium and magnesium alloys with precipitation strengthening is essentially higher in comparison of coarse-grained counterparts. The considerable decreasing of the strain before failure of UFG alloys was predicted at high strain rates. The Hugoniot elastic limits of oxide nanoceramics depend not only on the porosity, but also on sizes and volume distribution of voids.
NASA Astrophysics Data System (ADS)
Morelli, Marco J.; Allen, Rosalind J.; Tǎnase-Nicola, Sorin; ten Wolde, Pieter Rein
2008-01-01
In many stochastic simulations of biochemical reaction networks, it is desirable to "coarse grain" the reaction set, removing fast reactions while retaining the correct system dynamics. Various coarse-graining methods have been proposed, but it remains unclear which methods are reliable and which reactions can safely be eliminated. We address these issues for a model gene regulatory network that is particularly sensitive to dynamical fluctuations: a bistable genetic switch. We remove protein-DNA and/or protein-protein association-dissociation reactions from the reaction set using various coarse-graining strategies. We determine the effects on the steady-state probability distribution function and on the rate of fluctuation-driven switch flipping transitions. We find that protein-protein interactions may be safely eliminated from the reaction set, but protein-DNA interactions may not. We also find that it is important to use the chemical master equation rather than macroscopic rate equations to compute effective propensity functions for the coarse-grained reactions.
NASA Astrophysics Data System (ADS)
Sellers, Michael S.; Lísal, Martin; Schweigert, Igor; Larentzos, James P.; Brennan, John K.
2017-01-01
In discrete particle simulations, when an atomistic model is coarse-grained, a tradeoff is made: a boost in computational speed for a reduction in accuracy. The Dissipative Particle Dynamics (DPD) methods help to recover lost accuracy of the viscous and thermal properties, while giving back a relatively small amount of computational speed. Since its initial development for polymers, one of the most notable extensions of DPD has been the introduction of chemical reactivity, called DPD-RX. In 2007, Maillet, Soulard, and Stoltz introduced implicit chemical reactivity in DPD through the concept of particle reactors and simulated the decomposition of liquid nitromethane. We present an extended and generalized version of the DPD-RX method, and have applied it to solid hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Demonstration simulations of reacting RDX are performed under shock conditions using a recently developed single-site coarse-grain model and a reduced RDX decomposition mechanism. A description of the methods used to simulate RDX and its transition to hot product gases within DPD-RX is presented. Additionally, we discuss several examples of the effect of shock speed and microstructure on the corresponding material chemistry.
Direct construction of mesoscopic models from microscopic simulations
NASA Astrophysics Data System (ADS)
Lei, Huan; Caswell, Bruce; Karniadakis, George Em
2010-02-01
Starting from microscopic molecular-dynamics (MD) simulations of constrained Lennard-Jones (LJ) clusters (with constant radius of gyration Rg ), we construct two mesoscopic models [Langevin dynamics and dissipative particle dynamics (DPD)] by coarse graining the LJ clusters into single particles. Both static and dynamic properties of the coarse-grained models are investigated and compared with the MD results. The effective mean force field is computed as a function of the intercluster distance, and the corresponding potential scales linearly with the number of particles per cluster and the temperature. We verify that the mean force field can reproduce the equation of state of the atomistic systems within a wide density range but the radial distribution function only within the dilute and the semidilute regime. The friction force coefficients for both models are computed directly from the time-correlation function of the random force field of the microscopic system. For high density or a large cluster size the friction force is overestimated and the diffusivity underestimated due to the omission of many-body effects as a result of the assumed pairwise form of the coarse-grained force field. When the many-body effect is not as pronounced (e.g., smaller Rg or semidilute system), the DPD model can reproduce the dynamic properties of the MD system.
eSPEM - A SPEM Extension for Enactable Behavior Modeling
NASA Astrophysics Data System (ADS)
Ellner, Ralf; Al-Hilank, Samir; Drexler, Johannes; Jung, Martin; Kips, Detlef; Philippsen, Michael
OMG's SPEM - by means of its (semi-)formal notation - allows for a detailed description of development processes and methodologies, but can only be used for a rather coarse description of their behavior. Concepts for a more fine-grained behavior model are considered out of scope of the SPEM standard and have to be provided by other standards like BPDM/BPMN or UML. However, a coarse granularity of the behavior model often impedes a computer-aided enactment of a process model. Therefore, in this paper we present eSPEM, an extension of SPEM, that is based on the UML meta-model and focused on fine-grained behavior and life-cycle modeling and thereby supports automated enactment of development processes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Trément, Sébastien; Rousseau, Bernard, E-mail: bernard.rousseau@u-psud.fr; Schnell, Benoît
2014-04-07
We apply operational procedures available in the literature to the construction of coarse-grained conservative and friction forces for use in dissipative particle dynamics (DPD) simulations. The full procedure rely on a bottom-up approach: large molecular dynamics trajectories of n-pentane and n-decane modeled with an anisotropic united atom model serve as input for the force field generation. As a consequence, the coarse-grained model is expected to reproduce at least semi-quantitatively structural and dynamical properties of the underlying atomistic model. Two different coarse-graining levels are studied, corresponding to five and ten carbon atoms per DPD bead. The influence of the coarse-graining levelmore » on the generated force fields contributions, namely, the conservative and the friction part, is discussed. It is shown that the coarse-grained model of n-pentane correctly reproduces self-diffusion and viscosity coefficients of real n-pentane, while the fully coarse-grained model for n-decane at ambient temperature over-predicts diffusion by a factor of 2. However, when the n-pentane coarse-grained model is used as a building block for larger molecule (e.g., n-decane as a two blobs model), a much better agreement with experimental data is obtained, suggesting that the force field constructed is transferable to large macro-molecular systems.« less
NASA Astrophysics Data System (ADS)
Farrell, Kathryn; Oden, J. Tinsley
2014-07-01
Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and methods through applications to representative atomic structures and we discuss extensions to the validation process for molecular models of polymer structures encountered in certain semiconductor nanomanufacturing processes. The powerful method of model plausibility as a means for selecting interaction potentials for coarse-grained models is discussed in connection with a coarse-grained hexane molecule. Discussions of how all-atom information is used to construct priors are contained in an appendix.
A coarse-grained model of microtubule self-assembly
NASA Astrophysics Data System (ADS)
Regmi, Chola; Cheng, Shengfeng
Microtubules play critical roles in cell structures and functions. They also serve as a model system to stimulate the next-generation smart, dynamic materials. A deep understanding of their self-assembly process and biomechanical properties will not only help elucidate how microtubules perform biological functions, but also lead to exciting insight on how microtubule dynamics can be altered or even controlled for specific purposes such as suppressing the division of cancer cells. Combining all-atom molecular dynamics (MD) simulations and the essential dynamics coarse-graining method, we construct a coarse-grained (CG) model of the tubulin protein, which is the building block of microtubules. In the CG model a tubulin dimer is represented as an elastic network of CG sites, the locations of which are determined by examining the protein dynamics of the tubulin and identifying the essential dynamic domains. Atomistic MD modeling is employed to directly compute the tubulin bond energies in the surface lattice of a microtubule, which are used to parameterize the interactions between CG building blocks. The CG model is then used to study the self-assembly pathways, kinetics, dynamics, and nanomechanics of microtubules.
Structure and Relaxation in Solutions of Monoclonal Antibodies.
Wang, Gang; Varga, Zsigmond; Hofmann, Jennifer; Zarraga, Isidro E; Swan, James W
2018-03-22
Reversible self-association of therapeutic antibodies is a key factor in high protein solution viscosities. In the present work, a coarse-grained computational model accounting for electrostatic, dispersion, and long-ranged hydrodynamic interactions of two model monoclonal antibodies is applied to understand the nature of self-association, predicting the solution microstructure and resulting transport properties of the solution. For the proteins investigated, the structure factor across a range of solution conditions shows quantitative agreement with neutron-scattering experiments. We observe a homogeneous, dynamical association of the antibodies with no evidence of phase separation. Calculations of self-diffusivity and viscosity from coarse-grained dynamic simulations show the appropriate trends with concentration but, respectively, over- and under-predict the experimentally measured values. By adding constraints to the self-associated clusters that rigidify them under flow, prediction of the transport properties is significantly improved with respect to experimental measurements. We hypothesize that these rigidity constraints are associated with missing degrees of freedom in the coarse-grained model resulting from patchy and heterogeneous interactions among coarse-grained domains. These results demonstrate how structural anisotropy and anisotropy of interactions generated by features at the 2-5 nm length scale in antibodies are sufficient to recover the dynamics and rheological properties of these important macromolecular solutions.
Coarse graining of atactic polystyrene and its derivatives
NASA Astrophysics Data System (ADS)
Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.
2014-03-01
Capturing large length scales in polymers and soft matter while retaining atomistic properties is imperative to computational studies of dynamic systems. Here we present a new methodology developing coarse-grain model based on atomistic simulation of atactic polystyrene (PS). Similar to previous work by Fritz et al., each monomer is described by two coarse grained beads. In contrast to this earlier work where intramolecular potentials were based on Monte Carlo simulation of both isotactic and syndiotactic single PS molecule to capture stereochemistry, we obtained intramolecular interactions from a single molecular dynamics simulation of an all-atom atactic PS melts. The non-bonded interactions are obtained using the iterative Boltzmann inversion (IBI) scheme. This methodology has been extended to coarse graining of poly-(t-butyl-styrene) (PtBS). An additional coarse-grained bead is used to describe the t-butyl group. Similar to the process for PS, the intramolecular interactions are obtained from a single all atom atactic melt simulation. Starting from the non-bonded interactions for PS, we show that the IBI method for the non-bonded interactions of PtBS converges relatively fast. A generalized scheme for substituted PS is currently in development. We would like to acknowledge Prof. Kurt Kremer for helpful discussions during this work.
Coarse graining for synchronization in directed networks
NASA Astrophysics Data System (ADS)
Zeng, An; Lü, Linyuan
2011-05-01
Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kevrekidis, Ioannis G.
The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.
NASA Astrophysics Data System (ADS)
Pazzona, Federico G.; Pireddu, Giovanni; Gabrieli, Andrea; Pintus, Alberto M.; Demontis, Pierfranco
2018-05-01
We investigate the coarse-graining of host-guest systems under the perspective of the local distribution of pore occupancies, along with the physical meaning and actual computability of the coarse-interaction terms. We show that the widely accepted approach, in which the contributions to the free energy given by the molecules located in two neighboring pores are estimated through Monte Carlo simulations where the two pores are kept separated from the rest of the system, leads to inaccurate results at high sorbate densities. In the coarse-graining strategy that we propose, which is based on the Bethe-Peierls approximation, density-independent interaction terms are instead computed according to local effective potentials that take into account the correlations between the pore pair and its surroundings by means of mean-field correction terms without the need for simulating the pore pair separately. Use of the interaction parameters obtained this way allows the coarse-grained system to reproduce more closely the equilibrium properties of the original one. Results are shown for lattice-gases where the local free energy can be computed exactly and for a system of Lennard-Jones particles under the effect of a static confining field.
Bayesian calibration of coarse-grained forces: Efficiently addressing transferability
NASA Astrophysics Data System (ADS)
Patrone, Paul N.; Rosch, Thomas W.; Phelan, Frederick R.
2016-04-01
Generating and calibrating forces that are transferable across a range of state-points remains a challenging task in coarse-grained (CG) molecular dynamics. In this work, we present a coarse-graining workflow, inspired by ideas from uncertainty quantification and numerical analysis, to address this problem. The key idea behind our approach is to introduce a Bayesian correction algorithm that uses functional derivatives of CG simulations to rapidly and inexpensively recalibrate initial estimates f0 of forces anchored by standard methods such as force-matching. Taking density-temperature relationships as a running example, we demonstrate that this algorithm, in concert with various interpolation schemes, can be used to efficiently compute physically reasonable force curves on a fine grid of state-points. Importantly, we show that our workflow is robust to several choices available to the modeler, including the interpolation schemes and tools used to construct f0. In a related vein, we also demonstrate that our approach can speed up coarse-graining by reducing the number of atomistic simulations needed as inputs to standard methods for generating CG forces.
NASA Astrophysics Data System (ADS)
Skripnyak, Vladimir A.; Skripnyak, Natalia V.; Skripnyak, Evgeniya G.; Skripnyak, Vladimir V.
2015-06-01
Inelastic deformation and damage at the mesoscale level of ultrafine grained (UFG) Al 1560 aluminum and Ma2-1 magnesium alloys with distribution of grain size were investigated in wide loading conditions by experimental and computer simulation methods. The computational multiscale models of representative volume element (RVE) with the unimodal and bimodal grain size distributions were developed using the data of structure researches aluminum and magnesium UFG alloys. The critical fracture stress of UFG alloys on mesoscale level depends on relative volumes of coarse grains. Microcracks nucleation at quasi-static and dynamic loading is associated with strain localization in UFG partial volumes with bimodal grain size distribution. Microcracks arise in the vicinity of coarse and ultrafine grains boundaries. It is revealed that the occurrence of bimodal grain size distributions causes the increasing of UFG alloys ductility, but decreasing of the tensile strength. The increasing of fine precipitations concentration not only causes the hardening but increasing of ductility of UFG alloys with bimodal grain size distribution. This research carried out in 2014-2015 was supported by grant from ``The Tomsk State University Academic D.I. Mendeleev Fund Program''.
Systematic and simulation-free coarse graining of homopolymer melts: a relative-entropy-based study.
Yang, Delian; Wang, Qiang
2015-09-28
We applied the systematic and simulation-free strategy proposed in our previous work (D. Yang and Q. Wang, J. Chem. Phys., 2015, 142, 054905) to the relative-entropy-based (RE-based) coarse graining of homopolymer melts. RE-based coarse graining provides a quantitative measure of the coarse-graining performance and can be used to select the appropriate analytic functional forms of the pair potentials between coarse-grained (CG) segments, which are more convenient to use than the tabulated (numerical) CG potentials obtained from structure-based coarse graining. In our general coarse-graining strategy for homopolymer melts using the RE framework proposed here, the bonding and non-bonded CG potentials are coupled and need to be solved simultaneously. Taking the hard-core Gaussian thread model (K. S. Schweizer and J. G. Curro, Chem. Phys., 1990, 149, 105) as the original system, we performed RE-based coarse graining using the polymer reference interaction site model theory under the assumption that the intrachain segment pair correlation functions of CG systems are the same as those in the original system, which de-couples the bonding and non-bonded CG potentials and simplifies our calculations (that is, we only calculated the latter). We compared the performance of various analytic functional forms of non-bonded CG pair potential and closures for CG systems in RE-based coarse graining, as well as the structural and thermodynamic properties of original and CG systems at various coarse-graining levels. Our results obtained from RE-based coarse graining are also compared with those from structure-based coarse graining.
Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics.
Erban, Radek
2016-02-01
Molecular dynamics (MD) simulations of ions (K + , Na + , Ca 2+ and Cl - ) in aqueous solutions are investigated. Water is described using the SPC/E model. A stochastic coarse-grained description for ion behaviour is presented and parametrized using MD simulations. It is given as a system of coupled stochastic and ordinary differential equations, describing the ion position, velocity and acceleration. The stochastic coarse-grained model provides an intermediate description between all-atom MD simulations and Brownian dynamics (BD) models. It is used to develop a multiscale method which uses all-atom MD simulations in parts of the computational domain and (less detailed) BD simulations in the remainder of the domain.
Coarse-graining errors and numerical optimization using a relative entropy framework
NASA Astrophysics Data System (ADS)
Chaimovich, Aviel; Shell, M. Scott
2011-03-01
The ability to generate accurate coarse-grained models from reference fully atomic (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex molecular systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, Srel, that measures the information lost upon coarse-graining. Here, we develop a broad theoretical framework for this methodology and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodology and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theoretical considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Farrell, Kathryn, E-mail: kfarrell@ices.utexas.edu; Oden, J. Tinsley, E-mail: oden@ices.utexas.edu; Faghihi, Danial, E-mail: danial@ices.utexas.edu
A general adaptive modeling algorithm for selection and validation of coarse-grained models of atomistic systems is presented. A Bayesian framework is developed to address uncertainties in parameters, data, and model selection. Algorithms for computing output sensitivities to parameter variances, model evidence and posterior model plausibilities for given data, and for computing what are referred to as Occam Categories in reference to a rough measure of model simplicity, make up components of the overall approach. Computational results are provided for representative applications.
Stark, Austin C.; Andrews, Casey T.
2013-01-01
Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods – especially with regard to using them to model, for example, intracellular environments – is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields. PMID:24223529
Stark, Austin C; Andrews, Casey T; Elcock, Adrian H
2013-09-10
Coarse-grained (CG) simulation methods are now widely used to model the structure and dynamics of large biomolecular systems. One important issue for using such methods - especially with regard to using them to model, for example, intracellular environments - is to demonstrate that they can reproduce experimental data on the thermodynamics of protein-protein interactions in aqueous solutions. To examine this issue, we describe here simulations performed using the popular coarse-grained MARTINI force field, aimed at computing the thermodynamics of lysozyme and chymotrypsinogen self-interactions in aqueous solution. Using molecular dynamics simulations to compute potentials of mean force between a pair of protein molecules, we show that the original parameterization of the MARTINI force field is likely to significantly overestimate the strength of protein-protein interactions to the extent that the computed osmotic second virial coefficients are orders of magnitude more negative than experimental estimates. We then show that a simple down-scaling of the van der Waals parameters that describe the interactions between protein pseudo-atoms can bring the simulated thermodynamics into much closer agreement with experiment. Overall, the work shows that it is feasible to test explicit-solvent CG force fields directly against thermodynamic data for proteins in aqueous solutions, and highlights the potential usefulness of osmotic second virial coefficient measurements for fully parameterizing such force fields.
Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma
Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan
2014-01-01
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470
A coarse-grained model to study calcium activation of the cardiac thin filament
NASA Astrophysics Data System (ADS)
Zhang, Jing; Schwartz, Steven
2015-03-01
Familial hypertrophic cardiomyopathy (FHC) is one of the most common heart disease caused by genetic mutations. Cardiac muscle contraction and relaxation involve regulation of crossbridge binding to the cardiac thin filament, which regulates actomyosin interactions through calcium-dependent alterations in the dynamics of cardiac troponin (cTn) and tropomyosin (Tm). An atomistic model of cTn complex interacting with Tm has been studied by our group. A more realistic model requires the inclusion of the dynamics of actin filament, which is almost 6 times larger than cTn and Tm in terms of atom numbers, and extensive sampling of the model becomes very resource-demanding. By using physics-based protein united-residue force field, we introduce a coarse-grained model to study the calcium activation of the thin filament resulting from cTn's allosteric regulation of Tm dynamics on actin. The time scale is much longer than that of all-atom molecular dynamics simulation because of the reduction of the degrees of freedom. The coarse-grained model is a good template for studying cardiac thin filament mutations that cause FHC, and reduces the cost of computational resources.
Grid computing in large pharmaceutical molecular modeling.
Claus, Brian L; Johnson, Stephen R
2008-07-01
Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.
Multiscale equation-free algorithms for molecular dynamics
NASA Astrophysics Data System (ADS)
Abi Mansour, Andrew
Molecular dynamics is a physics-based computational tool that has been widely employed to study the dynamics and structure of macromolecules and their assemblies at the atomic scale. However, the efficiency of molecular dynamics simulation is limited because of the broad spectrum of timescales involved. To overcome this limitation, an equation-free algorithm is presented for simulating these systems using a multiscale model cast in terms of atomistic and coarse-grained variables. Both variables are evolved in time in such a way that the cross-talk between short and long scales is preserved. In this way, the coarse-grained variables guide the evolution of the atom-resolved states, while the latter provide the Newtonian physics for the former. While the atomistic variables are evolved using short molecular dynamics runs, time advancement at the coarse-grained level is achieved with a scheme that uses information from past and future states of the system while accounting for both the stochastic and deterministic features of the coarse-grained dynamics. To complete the multiscale cycle, an atom-resolved state consistent with the updated coarse-grained variables is recovered using algorithms from mathematical optimization. This multiscale paradigm is extended to nanofluidics using concepts from hydrodynamics, and it is demonstrated for macromolecular and nanofluidic systems. A toolkit is developed for prototyping these algorithms, which are then implemented within the GROMACS simulation package and released as an open source multiscale simulator.
Coarse-graining errors and numerical optimization using a relative entropy framework.
Chaimovich, Aviel; Shell, M Scott
2011-03-07
The ability to generate accurate coarse-grained models from reference fully atomic (or otherwise "first-principles") ones has become an important component in modeling the behavior of complex molecular systems with large length and time scales. We recently proposed a novel coarse-graining approach based upon variational minimization of a configuration-space functional called the relative entropy, S(rel), that measures the information lost upon coarse-graining. Here, we develop a broad theoretical framework for this methodology and numerical strategies for its use in practical coarse-graining settings. In particular, we show that the relative entropy offers tight control over the errors due to coarse-graining in arbitrary microscopic properties, and suggests a systematic approach to reducing them. We also describe fundamental connections between this optimization methodology and other coarse-graining strategies like inverse Monte Carlo, force matching, energy matching, and variational mean-field theory. We suggest several new numerical approaches to its minimization that provide new coarse-graining strategies. Finally, we demonstrate the application of these theoretical considerations and algorithms to a simple, instructive system and characterize convergence and errors within the relative entropy framework. © 2011 American Institute of Physics.
Atomistic and coarse-grained computer simulations of raft-like lipid mixtures.
Pandit, Sagar A; Scott, H Larry
2007-01-01
Computer modeling can provide insights into the existence, structure, size, and thermodynamic stability of localized raft-like regions in membranes. However, the challenges in the construction and simulation of accurate models of heterogeneous membranes are great. The primary obstacle in modeling the lateral organization within a membrane is the relatively slow lateral diffusion rate for lipid molecules. Microsecond or longer time-scales are needed to fully model the formation and stability of a raft in a membra ne. Atomistic simulations currently are not able to reach this scale, but they do provide quantitative information on the intermolecular forces and correlations that are involved in lateral organization. In this chapter, the steps needed to carry out and analyze atomistic simulations of hydrated lipid bilayers having heterogeneous composition are outlined. It is then shown how the data from a molecular dynamics simulation can be used to construct a coarse-grained model for the heterogeneous bilayer that can predict the lateral organization and stability of rafts at up to millisecond time-scales.
Protocols for efficient simulations of long-time protein dynamics using coarse-grained CABS model.
Jamroz, Michal; Kolinski, Andrzej; Kmiecik, Sebastian
2014-01-01
Coarse-grained (CG) modeling is a well-acknowledged simulation approach for getting insight into long-time scale protein folding events at reasonable computational cost. Depending on the design of a CG model, the simulation protocols vary from highly case-specific-requiring user-defined assumptions about the folding scenario-to more sophisticated blind prediction methods for which only a protein sequence is required. Here we describe the framework protocol for the simulations of long-term dynamics of globular proteins, with the use of the CABS CG protein model and sequence data. The simulations can start from a random or a selected (e.g., native) structure. The described protocol has been validated using experimental data for protein folding model systems-the prediction results agreed well with the experimental results.
CG2AA: backmapping protein coarse-grained structures.
Lombardi, Leandro E; Martí, Marcelo A; Capece, Luciana
2016-04-15
Coarse grain (CG) models allow long-scale simulations with a much lower computational cost than that of all-atom simulations. However, the absence of atomistic detail impedes the analysis of specific atomic interactions that are determinant in most interesting biomolecular processes. In order to study these phenomena, it is necessary to reconstruct the atomistic structure from the CG representation. This structure can be analyzed by itself or be used as an onset for atomistic molecular dynamics simulations. In this work, we present a computer program that accurately reconstructs the atomistic structure from a CG model for proteins, using a simple geometrical algorithm. The software is free and available online at http://www.ic.fcen.uba.ar/cg2aa/cg2aa.py Supplementary data are available at Bioinformatics online. lula@qi.fcen.uba.ar. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
A test of systematic coarse-graining of molecular dynamics simulations: Thermodynamic properties
NASA Astrophysics Data System (ADS)
Fu, Chia-Chun; Kulkarni, Pandurang M.; Scott Shell, M.; Gary Leal, L.
2012-10-01
Coarse-graining (CG) techniques have recently attracted great interest for providing descriptions at a mesoscopic level of resolution that preserve fluid thermodynamic and transport behaviors with a reduced number of degrees of freedom and hence less computational effort. One fundamental question arises: how well and to what extent can a "bottom-up" developed mesoscale model recover the physical properties of a molecular scale system? To answer this question, we explore systematically the properties of a CG model that is developed to represent an intermediate mesoscale model between the atomistic and continuum scales. This CG model aims to reduce the computational cost relative to a full atomistic simulation, and we assess to what extent it is possible to preserve both the thermodynamic and transport properties of an underlying reference all-atom Lennard-Jones (LJ) system. In this paper, only the thermodynamic properties are considered in detail. The transport properties will be examined in subsequent work. To coarse-grain, we first use the iterative Boltzmann inversion (IBI) to determine a CG potential for a (1-ϕ)N mesoscale particle system, where ϕ is the degree of coarse-graining, so as to reproduce the radial distribution function (RDF) of an N atomic particle system. Even though the uniqueness theorem guarantees a one to one relationship between the RDF and an effective pairwise potential, we find that RDFs are insensitive to the long-range part of the IBI-determined potentials, which provides some significant flexibility in further matching other properties. We then propose a reformulation of IBI as a robust minimization procedure that enables simultaneous matching of the RDF and the fluid pressure. We find that this new method mainly changes the attractive tail region of the CG potentials, and it improves the isothermal compressibility relative to pure IBI. We also find that there are optimal interaction cutoff lengths for the CG system, as a function of ϕ, that are required to attain an adequate potential while maintaining computational speedup. To demonstrate the universality of the method, we test a range of state points for the LJ liquid as well as several LJ chain fluids.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vögele, Martin; Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt a. M.; Holm, Christian
2015-12-28
We present simulations of aqueous polyelectrolyte complexes with new MARTINI models for the charged polymers poly(styrene sulfonate) and poly(diallyldimethylammonium). Our coarse-grained polyelectrolyte models allow us to study large length and long time scales with regard to chemical details and thermodynamic properties. The results are compared to the outcomes of previous atomistic molecular dynamics simulations and verify that electrostatic properties are reproduced by our MARTINI coarse-grained approach with reasonable accuracy. Structural similarity between the atomistic and the coarse-grained results is indicated by a comparison between the pair radial distribution functions and the cumulative number of surrounding particles. Our coarse-grained models aremore » able to quantitatively reproduce previous findings like the correct charge compensation mechanism and a reduced dielectric constant of water. These results can be interpreted as the underlying reason for the stability of polyelectrolyte multilayers and complexes and validate the robustness of the proposed models.« less
2015-07-01
grained simulations of the formation of meso-segregated microstructure and its interaction with the shockwave is analyzed in the present work. It is...help identify these phenomena and processes, meso-scale coarse-grained simulations of the formation of meso-segregated microstructure and its...of shockwave-induced hard-domain densification. Keywords: Polyurea; Meso-scale; Coarse-grained simulations ; Shockwave attenuation; shockwave
Consistent integration of experimental and ab initio data into molecular and coarse-grained models
NASA Astrophysics Data System (ADS)
Vlcek, Lukas
As computer simulations are increasingly used to complement or replace experiments, highly accurate descriptions of physical systems at different time and length scales are required to achieve realistic predictions. The questions of how to objectively measure model quality in relation to reference experimental or ab initio data, and how to transition seamlessly between different levels of resolution are therefore of prime interest. To address these issues, we use the concept of statistical distance to define a measure of similarity between statistical mechanical systems, i.e., a model and its target, and show that its minimization leads to general convergence of the systems' measurable properties. Through systematic coarse-graining, we arrive at appropriate expressions for optimization loss functions consistently incorporating microscopic ab initio data as well as macroscopic experimental data. The design of coarse-grained and multiscale models is then based on factoring the model system partition function into terms describing the system at different resolution levels. The optimization algorithm takes advantage of thermodynamic perturbation expressions for fast exploration of the model parameter space, enabling us to scan millions of parameter combinations per hour on a single CPU. The robustness and generality of the new model optimization framework and its efficient implementation are illustrated on selected examples including aqueous solutions, magnetic systems, and metal alloys.
Coarse-graining using the relative entropy and simplex-based optimization methods in VOTCA
NASA Astrophysics Data System (ADS)
Rühle, Victor; Jochum, Mara; Koschke, Konstantin; Aluru, N. R.; Kremer, Kurt; Mashayak, S. Y.; Junghans, Christoph
2014-03-01
Coarse-grained (CG) simulations are an important tool to investigate systems on larger time and length scales. Several methods for systematic coarse-graining were developed, varying in complexity and the property of interest. Thus, the question arises which method best suits a specific class of system and desired application. The Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) provides a uniform platform for coarse-graining methods and allows for their direct comparison. We present recent advances of VOTCA, namely the implementation of the relative entropy method and downhill simplex optimization for coarse-graining. The methods are illustrated by coarse-graining SPC/E bulk water and a water-methanol mixture. Both CG models reproduce the pair distributions accurately. SYM is supported by AFOSR under grant 11157642 and by NSF under grant 1264282. CJ was supported in part by the NSF PHY11-25915 at KITP. K. Koschke acknowledges funding by the Nestle Research Center.
NASA Astrophysics Data System (ADS)
Poursina, Mohammad; Anderson, Kurt S.
2014-08-01
This paper presents a novel algorithm to approximate the long-range electrostatic potential field in the Cartesian coordinates applicable to 3D coarse-grained simulations of biopolymers. In such models, coarse-grained clusters are formed via treating groups of atoms as rigid and/or flexible bodies connected together via kinematic joints. Therefore, multibody dynamic techniques are used to form and solve the equations of motion of such coarse-grained systems. In this article, the approximations for the potential fields due to the interaction between a highly negatively/positively charged pseudo-atom and charged particles, as well as the interaction between clusters of charged particles, are presented. These approximations are expressed in terms of physical and geometrical properties of the bodies such as the entire charge, the location of the center of charge, and the pseudo-inertia tensor about the center of charge of the clusters. Further, a novel substructuring scheme is introduced to implement the presented far-field potential evaluations in a binary tree framework as opposed to the existing quadtree and octree strategies of implementing fast multipole method. Using the presented Lagrangian grids, the electrostatic potential is recursively calculated via sweeping two passes: assembly and disassembly. In the assembly pass, adjacent charged bodies are combined together to form new clusters. Then, the potential field of each cluster due to its interaction with faraway resulting clusters is recursively calculated in the disassembly pass. The method is highly compatible with multibody dynamic schemes to model coarse-grained biopolymers. Since the proposed method takes advantage of constant physical and geometrical properties of rigid clusters, improvement in the overall computational cost is observed comparing to the tradition application of fast multipole method.
NASA Astrophysics Data System (ADS)
Schöberl, Markus; Zabaras, Nicholas; Koutsourelakis, Phaedon-Stelios
2017-03-01
We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method [1] and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extended to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo - Expectation-Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schöberl, Markus, E-mail: m.schoeberl@tum.de; Zabaras, Nicholas; Department of Aerospace and Mechanical Engineering, University of Notre Dame, 365 Fitzpatrick Hall, Notre Dame, IN 46556
We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extendedmore » to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo – Expectation–Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.« less
Coarse-Grained and Atomistic Modeling of Polyimides
NASA Technical Reports Server (NTRS)
Clancy, Thomas C.; Hinkley, Jeffrey A.
2004-01-01
A coarse-grained model for a set of three polyimide isomers is developed. Each polyimide is comprised of BPDA (3,3,4,4' - biphenyltetracarboxylic dianhydride) and one of three APB isomers: 1,3-bis(4-aminophenoxy)benzene, 1,4-bis(4-aminophenoxy)benzene or 1,3-bis(3-aminophenoxy)benzene. The coarse-grained model is constructed as a series of linked vectors following the contour of the polymer backbone. Beads located at the midpoint of each vector define centers for long range interaction energy between monomer subunits. A bulk simulation of each coarse-grained polyimide model is performed with a dynamic Monte Carlo procedure. These coarsegrained models are then reverse-mapped to fully atomistic models. The coarse-grained models show the expected trends in decreasing chain dimensions with increasing meta linkage in the APB section of the repeat unit, although these differences were minor due to the relatively short chains simulated here. Considerable differences are seen among the dynamic Monte Carlo properties of the three polyimide isomers. Decreasing relaxation times are seen with increasing meta linkage in the APB section of the repeat unit.
NASA Astrophysics Data System (ADS)
Chen, Xiongyu; Verma, Rahul; Espinoza, D. Nicolas; Prodanović, Maša.
2018-01-01
This work uses X-ray computed micro-tomography (μCT) to monitor xenon hydrate growth in a sandpack under the excess gas condition. The μCT images give pore-scale hydrate distribution and pore habit in space and time. We use the lattice Boltzmann method to calculate gas relative permeability (krg) as a function of hydrate saturation (Shyd) in the pore structure of the experimental hydrate-bearing sand retrieved from μCT data. The results suggest the krg - Shyd data fit well a new model krg = (1-Shyd)·exp(-4.95·Shyd) rather than the simple Corey model. In addition, we calculate krg-Shyd curves using digital models of hydrate-bearing sand based on idealized grain-attaching, coarse pore-filling, and dispersed pore-filling hydrate habits. Our pore-scale measurements and modeling show that the krg-Shyd curves are similar regardless of whether hydrate crystals develop grain-attaching or coarse pore-filling habits. The dispersed pore filling habit exhibits much lower gas relative permeability than the other two, but it is not observed in the experiment and not compatible with Ostwald ripening mechanisms. We find that a single grain-shape factor can be used in the Carman-Kozeny equation to calculate krg-Shyd data with known porosity and average grain diameter, suggesting it is a useful model for hydrate-bearing sand.
A combined coarse-grained and all-atom simulation of TRPV1 channel gating and heat activation
Qin, Feng
2015-01-01
The transient receptor potential (TRP) channels act as key sensors of various chemical and physical stimuli in eukaryotic cells. Despite years of study, the molecular mechanisms of TRP channel activation remain unclear. To elucidate the structural, dynamic, and energetic basis of gating in TRPV1 (a founding member of the TRPV subfamily), we performed coarse-grained modeling and all-atom molecular dynamics (MD) simulation based on the recently solved high resolution structures of the open and closed form of TRPV1. Our coarse-grained normal mode analysis captures two key modes of collective motions involved in the TRPV1 gating transition, featuring a quaternary twist motion of the transmembrane domains (TMDs) relative to the intracellular domains (ICDs). Our transition pathway modeling predicts a sequence of structural movements that propagate from the ICDs to the TMDs via key interface domains (including the membrane proximal domain and the C-terminal domain), leading to sequential opening of the selectivity filter followed by the lower gate in the channel pore (confirmed by modeling conformational changes induced by the activation of ICDs). The above findings of coarse-grained modeling are robust to perturbation by lipids. Finally, our MD simulation of the ICD identifies key residues that contribute differently to the nonpolar energy of the open and closed state, and these residues are predicted to control the temperature sensitivity of TRPV1 gating. These computational predictions offer new insights to the mechanism for heat activation of TRPV1 gating, and will guide our future electrophysiology and mutagenesis studies. PMID:25918362
NASA Astrophysics Data System (ADS)
Li, Zhen; Bian, Xin; Yang, Xiu; Karniadakis, George Em
2016-07-01
We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of a star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models cannot be selected arbitrarily. If the free parameters are properly defined, the reverse CG procedure also yields an accurate effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces the many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.
Li, Zhen; Bian, Xin; Yang, Xiu; Karniadakis, George Em
2016-07-28
We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of a star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models cannot be selected arbitrarily. If the free parameters are properly defined, the reverse CG procedure also yields an accurate effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces the many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.
2012-08-01
paper, we will first briefly discuss our recent results, using coarse-grained bead - spring model , on the dependence of failure stress and failure...length of the resin strands. In the coarse-grained model used here the polymer network is treated as a bead - spring system. To create highly cross...simulations of Thermosets We have used a coarse-grained bead - spring model to study the dependence of the mechanical properties of thermosets on chain
Web-Based Computational Chemistry Education with CHARMMing II: Coarse-Grained Protein Folding
Schalk, Vinushka; Lerner, Michael G.; Woodcock, H. Lee; Brooks, Bernard R.
2014-01-01
A lesson utilizing a coarse-grained (CG) G-like model has been implemented into the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org) to the Chemistry at HARvard Macromolecular Mechanics (CHARMM) molecular simulation package. While widely used to model various biophysical processes, such as protein folding and aggregation, CG models can also serve as an educational tool because they can provide qualitative descriptions of complex biophysical phenomena for a relatively cheap computational cost. As a proof of concept, this lesson demonstrates the construction of a CG model of a small globular protein, its simulation via Langevin dynamics, and the analysis of the resulting data. This lesson makes connections between modern molecular simulation techniques and topics commonly presented in an advanced undergraduate lecture on physical chemistry. It culminates in a straightforward analysis of a short dynamics trajectory of a small fast folding globular protein; we briefly describe the thermodynamic properties that can be calculated from this analysis. The assumptions inherent in the model and the data analysis are laid out in a clear, concise manner, and the techniques used are consistent with those employed by specialists in the field of CG modeling. One of the major tasks in building the G-like model is determining the relative strength of the nonbonded interactions between coarse-grained sites. New functionality has been added to CHARMMing to facilitate this process. The implementation of these features into CHARMMing helps automate many of the tedious aspects of constructing a CG G model. The CG model builder and its accompanying lesson should be a valuable tool to chemistry students, teachers, and modelers in the field. PMID:25058338
Web-based computational chemistry education with CHARMMing II: Coarse-grained protein folding.
Pickard, Frank C; Miller, Benjamin T; Schalk, Vinushka; Lerner, Michael G; Woodcock, H Lee; Brooks, Bernard R
2014-07-01
A lesson utilizing a coarse-grained (CG) Gō-like model has been implemented into the CHARMM INterface and Graphics (CHARMMing) web portal (www.charmming.org) to the Chemistry at HARvard Macromolecular Mechanics (CHARMM) molecular simulation package. While widely used to model various biophysical processes, such as protein folding and aggregation, CG models can also serve as an educational tool because they can provide qualitative descriptions of complex biophysical phenomena for a relatively cheap computational cost. As a proof of concept, this lesson demonstrates the construction of a CG model of a small globular protein, its simulation via Langevin dynamics, and the analysis of the resulting data. This lesson makes connections between modern molecular simulation techniques and topics commonly presented in an advanced undergraduate lecture on physical chemistry. It culminates in a straightforward analysis of a short dynamics trajectory of a small fast folding globular protein; we briefly describe the thermodynamic properties that can be calculated from this analysis. The assumptions inherent in the model and the data analysis are laid out in a clear, concise manner, and the techniques used are consistent with those employed by specialists in the field of CG modeling. One of the major tasks in building the Gō-like model is determining the relative strength of the nonbonded interactions between coarse-grained sites. New functionality has been added to CHARMMing to facilitate this process. The implementation of these features into CHARMMing helps automate many of the tedious aspects of constructing a CG Gō model. The CG model builder and its accompanying lesson should be a valuable tool to chemistry students, teachers, and modelers in the field.
Jamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, Sebastian
2013-01-08
It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution.
Highly Coarse-Grained Representations of Transmembrane Proteins
2017-01-01
Numerous biomolecules and biomolecular complexes, including transmembrane proteins (TMPs), are symmetric or at least have approximate symmetries. Highly coarse-grained models of such biomolecules, aiming at capturing the essential structural and dynamical properties on resolution levels coarser than the residue scale, must preserve the underlying symmetry. However, making these models obey the correct physics is in general not straightforward, especially at the highly coarse-grained resolution where multiple (∼3–30 in the current study) amino acid residues are represented by a single coarse-grained site. In this paper, we propose a simple and fast method of coarse-graining TMPs obeying this condition. The procedure involves partitioning transmembrane domains into contiguous segments of equal length along the primary sequence. For the coarsest (lowest-resolution) mappings, it turns out to be most important to satisfy the symmetry in a coarse-grained model. As the resolution is increased to capture more detail, however, it becomes gradually more important to match modular repeats in the secondary structure (such as helix-loop repeats) instead. A set of eight TMPs of various complexity, functionality, structural topology, and internal symmetry, representing different classes of TMPs (ion channels, transporters, receptors, adhesion, and invasion proteins), has been examined. The present approach can be generalized to other systems possessing exact or approximate symmetry, allowing for reliable and fast creation of multiscale, highly coarse-grained mappings of large biomolecular assemblies. PMID:28043122
Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM)
NASA Astrophysics Data System (ADS)
Sinitskiy, Anton V.; Voth, Gregory A.
2018-01-01
Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.
Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM).
Sinitskiy, Anton V; Voth, Gregory A
2018-01-07
Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.
NASA Astrophysics Data System (ADS)
Izvekov, Sergei
2017-03-01
We consider the generalized Langevin equations of motion describing exactly the particle-based coarse-grained dynamics in the classical microscopic ensemble that were derived recently within the Mori-Zwanzig formalism based on new projection operators [S. Izvekov, J. Chem. Phys. 138(13), 134106 (2013)]. The fundamental difference between the new family of projection operators and the standard Zwanzig projection operator used in the past to derive the coarse-grained equations of motion is that the new operators average out the explicit irrelevant trajectories leading to the possibility of solving the projected dynamics exactly. We clarify the definition of the projection operators and revisit the formalism to compute the projected dynamics exactly for the microscopic system in equilibrium. The resulting expression for the projected force is in the form of a "generalized additive fluctuating force" describing the departure of the generalized microscopic force associated with the coarse-grained coordinate from its projection. Starting with this key expression, we formulate a new exact formula for the memory function in terms of microscopic and coarse-grained conservative forces. We conclude by studying two independent limiting cases of practical importance: the Markov limit (vanishing correlations of projected force) and the limit of weak dependence of the memory function on the particle momenta. We present computationally affordable expressions which can be efficiently evaluated from standard molecular dynamics simulations.
Nonlinear evolution of coarse-grained quantum systems with generalized purity constraints
NASA Astrophysics Data System (ADS)
Burić, Nikola
2010-12-01
Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant fluctuation, and the coarse-grained pure states correspond to the generalized coherent, i.e. generalized nonentangled states. Open system model of the coarse-graining is discussed. It is shown that in this model and in the weak coupling limit the constrained dynamical equations coincide with an equation for pointer states, based on Hilbert-Schmidt distance, that was previously suggested in the context of the decoherence theory.
Koehl, Patrice; Poitevin, Frédéric; Navaza, Rafael; Delarue, Marc
2017-03-14
Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.
Glass transition temperature of polymer nano-composites with polymer and filler interactions
NASA Astrophysics Data System (ADS)
Hagita, Katsumi; Takano, Hiroshi; Doi, Masao; Morita, Hiroshi
2012-02-01
We systematically studied versatile coarse-grained model (bead spring model) to describe filled polymer nano-composites for coarse-grained (Kremer-Grest model) molecular dynamics simulations. This model consists of long polymers, crosslink, and fillers. We used the hollow structure as the filler to describe rigid spherical fillers with small computing costs. Our filler model consists of surface particles of icosahedra fullerene structure C320 and a repulsive force from the center of the filler is applied to the surface particles in order to make a sphere and rigid. The filler's diameter is 12 times of beads of the polymers. As the first test of our model, we study temperature dependence of volumes of periodic boundary conditions under constant pressures through NPT constant Andersen algorithm. It is found that Glass transition temperature (Tg) decrease with increasing filler's volume fraction for the case of repulsive interaction between polymer and fillers and Tg weakly increase for attractive interaction.
Coarse-Grained Structural Modeling of Molecular Motors Using Multibody Dynamics
Parker, David; Bryant, Zev; Delp, Scott L.
2010-01-01
Experimental and computational approaches are needed to uncover the mechanisms by which molecular motors convert chemical energy into mechanical work. In this article, we describe methods and software to generate structurally realistic models of molecular motor conformations compatible with experimental data from different sources. Coarse-grained models of molecular structures are constructed by combining groups of atoms into a system of rigid bodies connected by joints. Contacts between rigid bodies enforce excluded volume constraints, and spring potentials model system elasticity. This simplified representation allows the conformations of complex molecular motors to be simulated interactively, providing a tool for hypothesis building and quantitative comparisons between models and experiments. In an example calculation, we have used the software to construct atomically detailed models of the myosin V molecular motor bound to its actin track. The software is available at www.simtk.org. PMID:20428469
High-Resolution Coarse-Grained Modeling Using Oriented Coarse-Grained Sites.
Haxton, Thomas K
2015-03-10
We introduce a method to bring nearly atomistic resolution to coarse-grained models, and we apply the method to proteins. Using a small number of coarse-grained sites (about one per eight atoms) but assigning an independent three-dimensional orientation to each site, we preferentially integrate out stiff degrees of freedom (bond lengths and angles, as well as dihedral angles in rings) that are accurately approximated by their average values, while retaining soft degrees of freedom (unconstrained dihedral angles) mostly responsible for conformational variability. We demonstrate that our scheme retains nearly atomistic resolution by mapping all experimental protein configurations in the Protein Data Bank onto coarse-grained configurations and then analytically backmapping those configurations back to all-atom configurations. This roundtrip mapping throws away all information associated with the eliminated (stiff) degrees of freedom except for their average values, which we use to construct optimal backmapping functions. Despite the 4:1 reduction in the number of degrees of freedom, we find that heavy atoms move only 0.051 Å on average during the roundtrip mapping, while hydrogens move 0.179 Å on average, an unprecedented combination of efficiency and accuracy among coarse-grained protein models. We discuss the advantages of such a high-resolution model for parametrizing effective interactions and accurately calculating observables through direct or multiscale simulations.
NASA Astrophysics Data System (ADS)
Kawaguchi, Kazutomo; Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Nagao, Hidemi
2018-03-01
We present a simple coarse-grained model of the effective interaction for charged amino acid residues, such as Glu and Lys, in a water solvent. The free-energy profile as a function of the distance between two charged amino acid side-chain analogues in an explicit water solvent is calculated with all-atom molecular dynamics simulation and thermodynamic integration method. The calculated free-energy profile is applied to the coarse-grained potential of the effective interaction between two amino acid residues. The Langevin dynamics simulations with our coarse-grained potential are performed for association of a small protein complex, GCN4-pLI tetramer. The tetramer conformation reproduced by our coarse-grained model is similar to the X-ray crystallographic structure. We show that the effective interaction between charged amino acid residues stabilises association and orientation of protein complex. We also investigate the association pathways of GCN4-pLI tetramer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhen; Bian, Xin; Yang, Xiu
We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics basedmore » on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models are not interchangeable. If the free parameters are properly selected, the reverse CG procedure also yields an effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu
We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of a star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamicsmore » based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models cannot be selected arbitrarily. If the free parameters are properly defined, the reverse CG procedure also yields an accurate effective potential. Moreover, we explain how an aggressive coarse-graining procedure introduces the many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.« less
Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.
Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R
2015-12-01
The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.
NASA Astrophysics Data System (ADS)
Katsoulakis, Markos A.; Vlachos, Dionisios G.
2003-11-01
We derive a hierarchy of successively coarse-grained stochastic processes and associated coarse-grained Monte Carlo (CGMC) algorithms directly from the microscopic processes as approximations in larger length scales for the case of diffusion of interacting particles on a lattice. This hierarchy of models spans length scales between microscopic and mesoscopic, satisfies a detailed balance, and gives self-consistent fluctuation mechanisms whose noise is asymptotically identical to the microscopic MC. Rigorous, detailed asymptotics justify and clarify these connections. Gradient continuous time microscopic MC and CGMC simulations are compared under far from equilibrium conditions to illustrate the validity of our theory and delineate the errors obtained by rigorous asymptotics. Information theory estimates are employed for the first time to provide rigorous error estimates between the solutions of microscopic MC and CGMC, describing the loss of information during the coarse-graining process. Simulations under periodic boundary conditions are used to verify the information theory error estimates. It is shown that coarse-graining in space leads also to coarse-graining in time by q2, where q is the level of coarse-graining, and overcomes in part the hydrodynamic slowdown. Operation counting and CGMC simulations demonstrate significant CPU savings in continuous time MC simulations that vary from q3 for short potentials to q4 for long potentials. Finally, connections of the new coarse-grained stochastic processes to stochastic mesoscopic and Cahn-Hilliard-Cook models are made.
2007-11-05
limits of what is considered practical when applying all-atom molecular - dynamics simulation methods. Lattice models provide computationally robust...of expectation values from the density of states. All-atom molecular - dynamics simulations provide the most rigorous sampling method to generate con... molecular - dynamics simulations of protein folding,6–9 reported studies of computing a heat capacity or other calorimetric observables have been limited to
Preparation of Entangled Polymer Melts of Various Architecture for Coarse-Grained Models
2011-09-01
Simulator ( LAMMPS ). This report presents a theory overview and a manual how to use the method. 15. SUBJECT TERMS Ammunition, coarse-grained model...polymer builder, LAMMPS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 26 19a. NAME OF RESPONSIBLE PERSON...scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ). Gel is an in house written C program of coarse- grained polymer builder, and LAMMPS is
STOCK: Structure mapper and online coarse-graining kit for molecular simulations
Bevc, Staš; Junghans, Christoph; Praprotnik, Matej
2015-03-15
We present a web toolkit STructure mapper and Online Coarse-graining Kit for setting up coarse-grained molecular simulations. The kit consists of two tools: structure mapping and Boltzmann inversion tools. The aim of the first tool is to define a molecular mapping from high, e.g. all-atom, to low, i.e. coarse-grained, resolution. Using a graphical user interface it generates input files, which are compatible with standard coarse-graining packages, e.g. VOTCA and DL_CGMAP. Our second tool generates effective potentials for coarse-grained simulations preserving the structural properties, e.g. radial distribution functions, of the underlying higher resolution model. The required distribution functions can be providedmore » by any simulation package. Simulations are performed on a local machine and only the distributions are uploaded to the server. The applicability of the toolkit is validated by mapping atomistic pentane and polyalanine molecules to a coarse-grained representation. Effective potentials are derived for systems of TIP3P (transferable intermolecular potential 3 point) water molecules and salt solution. The presented coarse-graining web toolkit is available at http://stock.cmm.ki.si.« less
Coarse-grained models of key self-assembly processes in HIV-1
NASA Astrophysics Data System (ADS)
Grime, John
Computational molecular simulations can elucidate microscopic information that is inaccessible to conventional experimental techniques. However, many processes occur over time and length scales that are beyond the current capabilities of atomic-resolution molecular dynamics (MD). One such process is the self-assembly of the HIV-1 viral capsid, a biological structure that is crucial to viral infectivity. The nucleation and growth of capsid structures requires the interaction of large numbers of capsid proteins within a complicated molecular environment. Coarse-grained (CG) models, where degrees of freedom are removed to produce more computationally efficient models, can in principle access large-scale phenomena such as the nucleation and growth of HIV-1 capsid lattice. We report here studies of the self-assembly behaviors of a CG model of HIV-1 capsid protein, including the influence of the local molecular environment on nucleation and growth processes. Our results suggest a multi-stage process, involving several characteristic structures, eventually producing metastable capsid lattice morphologies that are amenable to subsequent capsid dissociation in order to transmit the viral infection.
Coarse grained modeling of transport properties in monoclonal antibody solution
NASA Astrophysics Data System (ADS)
Swan, James; Wang, Gang
Monoclonal antibodies and their derivatives represent the fastest growing segment of the bio pharmaceutical industry. For many applications such as novel cancer therapies, high concentration, sub-cutaneous injections of these protein solutions are desired. However, depending on the peptide sequence within the antibody, such high concentration formulations can be too viscous to inject via human derived force alone. Understanding how heterogenous charge distribution and hydrophobicity within the antibodies leads to high viscosities is crucial to their future application. In this talk, we explore a coarse grained computational model of therapeutically relevant monoclonal antibodies that accounts for electrostatic, dispersion and hydrodynamic interactions between suspended antibodies to predict assembly and transport properties in concentrated antibody solutions. We explain the high viscosities observed in many experimental studies of the same biologics.
A Hybrid Coarse-graining Approach for Lipid Bilayers at Large Length and Time Scales
Ayton, Gary S.; Voth, Gregory A.
2009-01-01
A hybrid analytic-systematic (HAS) coarse-grained (CG) lipid model is developed and employed in a large-scale simulation of a liposome. The methodology is termed hybrid analyticsystematic as one component of the interaction between CG sites is variationally determined from the multiscale coarse-graining (MS-CG) methodology, while the remaining component utilizes an analytic potential. The systematic component models the in-plane center of mass interaction of the lipids as determined from an atomistic-level MD simulation of a bilayer. The analytic component is based on the well known Gay-Berne ellipsoid of revolution liquid crystal model, and is designed to model the highly anisotropic interactions at a highly coarse-grained level. The HAS CG approach is the first step in an “aggressive” CG methodology designed to model multi-component biological membranes at very large length and timescales. PMID:19281167
Hinckley, Daniel M.; Freeman, Gordon S.; Whitmer, Jonathan K.; de Pablo, Juan J.
2013-01-01
A new 3-Site-Per-Nucleotide coarse-grained model for DNA is presented. The model includes anisotropic potentials between bases involved in base stacking and base pair interactions that enable the description of relevant structural properties, including the major and minor grooves. In an improvement over available coarse-grained models, the correct persistence length is recovered for both ssDNA and dsDNA, allowing for simulation of non-canonical structures such as hairpins. DNA melting temperatures, measured for duplexes and hairpins by integrating over free energy surfaces generated using metadynamics simulations, are shown to be in quantitative agreement with experiment for a variety of sequences and conditions. Hybridization rate constants, calculated using forward-flux sampling, are also shown to be in good agreement with experiment. The coarse-grained model presented here is suitable for use in biological and engineering applications, including nucleosome positioning and DNA-templated engineering. PMID:24116642
Henrich, Oliver; Gutiérrez Fosado, Yair Augusto; Curk, Tine; Ouldridge, Thomas E
2018-05-10
During the last decade coarse-grained nucleotide models have emerged that allow us to study DNA and RNA on unprecedented time and length scales. Among them is oxDNA, a coarse-grained, sequence-specific model that captures the hybridisation transition of DNA and many structural properties of single- and double-stranded DNA. oxDNA was previously only available as standalone software, but has now been implemented into the popular LAMMPS molecular dynamics code. This article describes the new implementation and analyses its parallel performance. Practical applications are presented that focus on single-stranded DNA, an area of research which has been so far under-investigated. The LAMMPS implementation of oxDNA lowers the entry barrier for using the oxDNA model significantly, facilitates future code development and interfacing with existing LAMMPS functionality as well as other coarse-grained and atomistic DNA models.
Fluctuations of the partition function in the generalized random energy model with external field
NASA Astrophysics Data System (ADS)
Bovier, Anton; Klimovsky, Anton
2008-12-01
We study Derrida's generalized random energy model (GREM) in the presence of uniform external field. We compute the fluctuations of the ground state and of the partition function in the thermodynamic limit for all admissible values of parameters. We find that the fluctuations are described by a hierarchical structure which is obtained by a certain coarse graining of the initial hierarchical structure of the GREM with external field. We provide an explicit formula for the free energy of the model. We also derive some large deviation results providing an expression for the free energy in a class of models with Gaussian Hamiltonians and external field. Finally, we prove that the coarse-grained parts of the system emerging in the thermodynamic limit tend to have a certain optimal magnetization, as prescribed by the strength of the external field and by parameters of the GREM.
Local-feature analysis for automated coarse-graining of bulk-polymer molecular dynamics simulations.
Xue, Y; Ludovice, P J; Grover, M A
2012-12-01
A method for automated coarse-graining of bulk polymers is presented, using the data-mining tool of local feature analysis. Most existing methods for polymer coarse-graining define superatoms based on their covalent bonding topology along the polymer backbone, but here superatoms are defined based only on their correlated motions, as observed in molecular dynamics simulations. Correlated atomic motions are identified in the simulation data using local feature analysis, between atoms in the same or in different polymer chains. Groups of highly correlated atoms constitute the superatoms in the coarse-graining scheme, and the positions of their seed coordinates are then projected forward in time. Based on only the seed positions, local feature analysis enables the full reconstruction of all atomic positions. This reconstruction suggests an iterative scheme to reduce the computation of the simulations to initialize another short molecular dynamic simulation, identify new superatoms, and again project forward in time.
Variable-free exploration of stochastic models: a gene regulatory network example.
Erban, Radek; Frewen, Thomas A; Wang, Xiao; Elston, Timothy C; Coifman, Ronald; Nadler, Boaz; Kevrekidis, Ioannis G
2007-04-21
Finding coarse-grained, low-dimensional descriptions is an important task in the analysis of complex, stochastic models of gene regulatory networks. This task involves (a) identifying observables that best describe the state of these complex systems and (b) characterizing the dynamics of the observables. In a previous paper [R. Erban et al., J. Chem. Phys. 124, 084106 (2006)] the authors assumed that good observables were known a priori, and presented an equation-free approach to approximate coarse-grained quantities (i.e., effective drift and diffusion coefficients) that characterize the long-time behavior of the observables. Here we use diffusion maps [R. Coifman et al., Proc. Natl. Acad. Sci. U.S.A. 102, 7426 (2005)] to extract appropriate observables ("reduction coordinates") in an automated fashion; these involve the leading eigenvectors of a weighted Laplacian on a graph constructed from network simulation data. We present lifting and restriction procedures for translating between physical variables and these data-based observables. These procedures allow us to perform equation-free, coarse-grained computations characterizing the long-term dynamics through the design and processing of short bursts of stochastic simulation initialized at appropriate values of the data-based observables.
Coarse-grained, foldable, physical model of the polypeptide chain.
Chakraborty, Promita; Zuckermann, Ronald N
2013-08-13
Although nonflexible, scaled molecular models like Pauling-Corey's and its descendants have made significant contributions in structural biology research and pedagogy, recent technical advances in 3D printing and electronics make it possible to go one step further in designing physical models of biomacromolecules: to make them conformationally dynamic. We report here the design, construction, and validation of a flexible, scaled, physical model of the polypeptide chain, which accurately reproduces the bond rotational degrees of freedom in the peptide backbone. The coarse-grained backbone model consists of repeating amide and α-carbon units, connected by mechanical bonds (corresponding to ϕ and ψ) that include realistic barriers to rotation that closely approximate those found at the molecular scale. Longer-range hydrogen-bonding interactions are also incorporated, allowing the chain to readily fold into stable secondary structures. The model is easily constructed with readily obtainable parts and promises to be a tremendous educational aid to the intuitive understanding of chain folding as the basis for macromolecular structure. Furthermore, this physical model can serve as the basis for linking tangible biomacromolecular models directly to the vast array of existing computational tools to provide an enhanced and interactive human-computer interface.
Finite Dimensional Approximations for Continuum Multiscale Problems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berlyand, Leonid
2017-01-24
The completed research project concerns the development of novel computational techniques for modeling nonlinear multiscale physical and biological phenomena. Specifically, it addresses the theoretical development and applications of the homogenization theory (coarse graining) approach to calculation of the effective properties of highly heterogenous biological and bio-inspired materials with many spatial scales and nonlinear behavior. This theory studies properties of strongly heterogeneous media in problems arising in materials science, geoscience, biology, etc. Modeling of such media raises fundamental mathematical questions, primarily in partial differential equations (PDEs) and calculus of variations, the subject of the PI’s research. The focus of completed researchmore » was on mathematical models of biological and bio-inspired materials with the common theme of multiscale analysis and coarse grain computational techniques. Biological and bio-inspired materials offer the unique ability to create environmentally clean functional materials used for energy conversion and storage. These materials are intrinsically complex, with hierarchical organization occurring on many nested length and time scales. The potential to rationally design and tailor the properties of these materials for broad energy applications has been hampered by the lack of computational techniques, which are able to bridge from the molecular to the macroscopic scale. The project addressed the challenge of computational treatments of such complex materials by the development of a synergistic approach that combines innovative multiscale modeling/analysis techniques with high performance computing.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Braun, Daniel; Boresch, Stefan; Steinhauser, Othmar
Long-term molecular dynamics simulations are used to compare the single particle dipole reorientation time, the diffusion constant, the viscosity, and the frequency-dependent dielectric constant of the coarse-grained big multipole water (BMW) model to two common atomistic three-point water models, SPC/E and TIP3P. In particular, the agreement between the calculated viscosity of BMW and the experimental viscosity of water is satisfactory. We also discuss contradictory values for the static dielectric properties reported in the literature. Employing molecular hydrodynamics, we show that the viscosity can be computed from single particle dynamics, circumventing the slow convergence of the standard approaches. Furthermore, our datamore » indicate that the Kivelson relation connecting single particle and collective reorientation time holds true for all systems investigated. Since simulations with coarse-grained force fields often employ extremely large time steps, we also investigate the influence of time step on dynamical properties. We observe a systematic acceleration of system dynamics when increasing the time step. Carefully monitoring energy/temperature conservation is found to be a sufficient criterion for the reliable calculation of dynamical properties. By contrast, recommended criteria based on the ratio of fluctuations of total vs. kinetic energy are not sensitive enough.« less
Chng, Choon-Peng; Yang, Lee-Wei
2008-01-01
Molecular dynamics (MD) simulation has remained the most indispensable tool in studying equilibrium/non-equilibrium conformational dynamics since its advent 30 years ago. With advances in spectroscopy accompanying solved biocomplexes in growing sizes, sampling their dynamics that occur at biologically interesting spatial/temporal scales becomes computationally intractable; this motivated the use of coarse-grained (CG) approaches. CG-MD models are used to study folding and conformational transitions in reduced resolution and can employ enlarged time steps due to the absence of some of the fastest motions in the system. The Boltzmann-Inversion technique, heavily used in parameterizing these models, provides a smoothed-out effective potential on which molecular conformation evolves at a faster pace thus stretching simulations into tens of microseconds. As a result, a complete catalytic cycle of HIV-1 protease or the assembly of lipid-protein mixtures could be investigated by CG-MD to gain biological insights. In this review, we survey the theories developed in recent years, which are categorized into Folding-based and Molecular-Mechanics-based. In addition, physical bases in the selection of CG beads/time-step, the choice of effective potentials, representation of solvent, and restoration of molecular representations back to their atomic details are systematically discussed. PMID:19812774
Comparative Investigation of Normal Modes and Molecular Dynamics of Hepatitis C NS5B Protein
NASA Astrophysics Data System (ADS)
Asafi, M. S.; Yildirim, A.; Tekpinar, M.
2016-04-01
Understanding dynamics of proteins has many practical implications in terms of finding a cure for many protein related diseases. Normal mode analysis and molecular dynamics methods are widely used physics-based computational methods for investigating dynamics of proteins. In this work, we studied dynamics of Hepatitis C NS5B protein with molecular dynamics and normal mode analysis. Principal components obtained from a 100 nanoseconds molecular dynamics simulation show good overlaps with normal modes calculated with a coarse-grained elastic network model. Coarse-grained normal mode analysis takes at least an order of magnitude shorter time. Encouraged by this good overlaps and short computation times, we analyzed further low frequency normal modes of Hepatitis C NS5B. Motion directions and average spatial fluctuations have been analyzed in detail. Finally, biological implications of these motions in drug design efforts against Hepatitis C infections have been elaborated.
Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS
NASA Astrophysics Data System (ADS)
Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan
2016-11-01
Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiencies have been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume. This work is funded by NSF under Grant DMS-1222550.
Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS
NASA Astrophysics Data System (ADS)
Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan
Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiency has been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume.
McCarty, J; Clark, A J; Copperman, J; Guenza, M G
2014-05-28
Structural and thermodynamic consistency of coarse-graining models across multiple length scales is essential for the predictive role of multi-scale modeling and molecular dynamic simulations that use mesoscale descriptions. Our approach is a coarse-grained model based on integral equation theory, which can represent polymer chains at variable levels of chemical details. The model is analytical and depends on molecular and thermodynamic parameters of the system under study, as well as on the direct correlation function in the k → 0 limit, c0. A numerical solution to the PRISM integral equations is used to determine c0, by adjusting the value of the effective hard sphere diameter, dHS, to agree with the predicted equation of state. This single quantity parameterizes the coarse-grained potential, which is used to perform mesoscale simulations that are directly compared with atomistic-level simulations of the same system. We test our coarse-graining formalism by comparing structural correlations, isothermal compressibility, equation of state, Helmholtz and Gibbs free energies, and potential energy and entropy using both united atom and coarse-grained descriptions. We find quantitative agreement between the analytical formalism for the thermodynamic properties, and the results of Molecular Dynamics simulations, independent of the chosen level of representation. In the mesoscale description, the potential energy of the soft-particle interaction becomes a free energy in the coarse-grained coordinates which preserves the excess free energy from an ideal gas across all levels of description. The structural consistency between the united-atom and mesoscale descriptions means the relative entropy between descriptions has been minimized without any variational optimization parameters. The approach is general and applicable to any polymeric system in different thermodynamic conditions.
NASA Astrophysics Data System (ADS)
Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac
2016-10-01
Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.
Resolution-Adapted All-Atomic and Coarse-Grained Model for Biomolecular Simulations.
Shen, Lin; Hu, Hao
2014-06-10
We develop here an adaptive multiresolution method for the simulation of complex heterogeneous systems such as the protein molecules. The target molecular system is described with the atomistic structure while maintaining concurrently a mapping to the coarse-grained models. The theoretical model, or force field, used to describe the interactions between two sites is automatically adjusted in the simulation processes according to the interaction distance/strength. Therefore, all-atomic, coarse-grained, or mixed all-atomic and coarse-grained models would be used together to describe the interactions between a group of atoms and its surroundings. Because the choice of theory is made on the force field level while the sampling is always carried out in the atomic space, the new adaptive method preserves naturally the atomic structure and thermodynamic properties of the entire system throughout the simulation processes. The new method will be very useful in many biomolecular simulations where atomistic details are critically needed.
Relative entropy as a universal metric for multiscale errors
NASA Astrophysics Data System (ADS)
Chaimovich, Aviel; Shell, M. Scott
2010-06-01
We show that the relative entropy, Srel , suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and generally links it to errors associated with coarse graining. We consider two simple case studies substantiating these results, and suggest that Srel has important ramifications for evaluating and designing coarse-grained models.
Relative entropy as a universal metric for multiscale errors.
Chaimovich, Aviel; Shell, M Scott
2010-06-01
We show that the relative entropy, Srel, suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and generally links it to errors associated with coarse graining. We consider two simple case studies substantiating these results, and suggest that Srel has important ramifications for evaluating and designing coarse-grained models.
New Coarse-Grained Model and Its Implementation in Simulations of Graphene Assemblies.
Shang, Jun-Jun; Yang, Qing-Sheng; Liu, Xia
2017-08-08
Graphene is a one-atom thick layer of carbon atoms arranged in a hexagonal pattern, which makes it the strongest material in the world. The Tersoff potential is a suitable potential for simulating the mechanical behavior of the complex covalently bonded system of graphene. In this paper, we describe a new coarse-grained (CG) potential, TersoffCG, which is based on the function form of the Tersoff potential. The TersoffCG applies to a CG model of graphene that uses the same hexagonal pattern as the atomistic model. The parameters of the TersoffCG potential are determined using structural feature and potential-energy fitting between the CG model and the atomic model. The modeling process of graphene is highly simplified using the present CG model as it avoids the necessity to define bonds/angles/dihedrals connectivity. What is more, the present CG model provides a new perspective of coarse-graining scheme for crystal structures of nanomaterials. The structural changes and mechanical properties of multilayer graphene were calculated using the new potential. Furthermore, a CG model of a graphene aerogel was built in a specific form of assembly. The chemical bonding in the joints of graphene-aerogel forms automatically during the energy relaxation process. The compressive and recover test of the graphene aerogel was reproduced to study its high elasticity. Our computational examples show that the TersoffCG potential can be used for simulations of graphene and its assemblies, which have many applications in areas of environmental protection, aerospace engineering, and others.
Adaptive resolution simulation of an atomistic protein in MARTINI water
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J., E-mail: s.j.marrink@rug.nl
2014-02-07
We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecularmore » dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.« less
Adaptive resolution simulation of an atomistic protein in MARTINI water.
Zavadlav, Julija; Melo, Manuel Nuno; Marrink, Siewert J; Praprotnik, Matej
2014-02-07
We present an adaptive resolution simulation of protein G in multiscale water. We couple atomistic water around the protein with mesoscopic water, where four water molecules are represented with one coarse-grained bead, farther away. We circumvent the difficulties that arise from coupling to the coarse-grained model via a 4-to-1 molecule coarse-grain mapping by using bundled water models, i.e., we restrict the relative movement of water molecules that are mapped to the same coarse-grained bead employing harmonic springs. The water molecules change their resolution from four molecules to one coarse-grained particle and vice versa adaptively on-the-fly. Having performed 15 ns long molecular dynamics simulations, we observe within our error bars no differences between structural (e.g., root-mean-squared deviation and fluctuations of backbone atoms, radius of gyration, the stability of native contacts and secondary structure, and the solvent accessible surface area) and dynamical properties of the protein in the adaptive resolution approach compared to the fully atomistically solvated model. Our multiscale model is compatible with the widely used MARTINI force field and will therefore significantly enhance the scope of biomolecular simulations.
Darré, Leonardo; Machado, Matías Rodrigo; Brandner, Astrid Febe; González, Humberto Carlos; Ferreira, Sebastián; Pantano, Sergio
2015-02-10
Modeling of macromolecular structures and interactions represents an important challenge for computational biology, involving different time and length scales. However, this task can be facilitated through the use of coarse-grained (CG) models, which reduce the number of degrees of freedom and allow efficient exploration of complex conformational spaces. This article presents a new CG protein model named SIRAH, developed to work with explicit solvent and to capture sequence, temperature, and ionic strength effects in a topologically unbiased manner. SIRAH is implemented in GROMACS, and interactions are calculated using a standard pairwise Hamiltonian for classical molecular dynamics simulations. We present a set of simulations that test the capability of SIRAH to produce a qualitatively correct solvation on different amino acids, hydrophilic/hydrophobic interactions, and long-range electrostatic recognition leading to spontaneous association of unstructured peptides and stable structures of single polypeptides and protein-protein complexes.
Mixing coarse-grained and fine-grained water in molecular dynamics simulations of a single system.
Riniker, Sereina; van Gunsteren, Wilfred F
2012-07-28
The use of a supra-molecular coarse-grained (CG) model for liquid water as solvent in molecular dynamics simulations of biomolecules represented at the fine-grained (FG) atomic level of modelling may reduce the computational effort by one or two orders of magnitude. However, even if the pure FG model and the pure CG model represent the properties of the particular substance of interest rather well, their application in a hybrid FG/CG system containing varying ratios of FG versus CG particles is highly non-trivial, because it requires an appropriate balance between FG-FG, FG-CG, and CG-CG energies, and FG and CG entropies. Here, the properties of liquid water are used to calibrate the FG-CG interactions for the simple-point-charge water model at the FG level and a recently proposed supra-molecular water model at the CG level that represents five water molecules by one CG bead containing two interaction sites. Only two parameters are needed to reproduce different thermodynamic and dielectric properties of liquid water at physiological temperature and pressure for various mole fractions of CG water in FG water. The parametrisation strategy for the FG-CG interactions is simple and can be easily transferred to interactions between atomistic biomolecules and CG water.
Elcock, Adrian H.
2013-01-01
Inclusion of hydrodynamic interactions (HIs) is essential in simulations of biological macromolecules that treat the solvent implicitly if the macromolecules are to exhibit correct translational and rotational diffusion. The present work describes the development and testing of a simple approach aimed at allowing more rapid computation of HIs in coarse-grained Brownian dynamics simulations of systems that contain large numbers of flexible macromolecules. The method combines a complete treatment of intramolecular HIs with an approximate treatment of the intermolecular HIs which assumes that the molecules are effectively spherical; all of the HIs are calculated at the Rotne-Prager-Yamakawa level of theory. When combined with Fixman’s Chebyshev polynomial method for calculating correlated random displacements, the proposed method provides an approach that is simple to program but sufficiently fast that it makes it computationally viable to include HIs in large-scale simulations. Test calculations performed on very coarse-grained models of the pyruvate dehydrogenase (PDH) E2 complex and on oligomers of ParM (ranging in size from 1 to 20 monomers) indicate that the method reproduces the translational diffusion behavior seen in more complete HI simulations surprisingly well; the method performs less well at capturing rotational diffusion but its discrepancies diminish with increasing size of the simulated assembly. Simulations of residue-level models of two tetrameric protein models demonstrate that the method also works well when more structurally detailed models are used in the simulations. Finally, test simulations of systems containing up to 1024 coarse-grained PDH molecules indicate that the proposed method rapidly becomes more efficient than the conventional BD approach in which correlated random displacements are obtained via a Cholesky decomposition of the complete diffusion tensor. PMID:23914146
Mechanical response of two polyimides through coarse-grained molecular dynamics simulations
NASA Astrophysics Data System (ADS)
Sudarkodi, V.; Sooraj, K.; Nair, Nisanth N.; Basu, Sumit; Parandekar, Priya V.; Sinha, Nishant K.; Prakash, Om; Tsotsis, Tom
2018-03-01
Coarse-grained molecular dynamics (MD) simulations allow us to predict the mechanical responses of polymers, starting merely with a description of their molecular architectures. It is interesting to ask whether, given two competing molecular architectures, coarse-grained MD simulations can predict the differences that can be expected in their mechanical responses. We have studied two crosslinked polyimides PMR15 and HFPE52—both used in high- temperature applications—to assess whether the subtle differences in their uniaxial stress-strain responses, revealed by experiments, can be reproduced by carefully coarse-grained MD models. The coarse graining procedure for PMR15 is outlined in this work, while the coarse grain forcefields for HFPE52 are borrowed from an earlier one (Pandiyan et al 2015 Macromol. Theory Simul. 24 513-20). We show that the stress-strain responses of both these polyimides are qualitatively reproduced, and important insights into their deformation and failure mechanisms are obtained. More importantly, the differences in the molecular architecture between the polyimides carry over to the differences in the stress-strain responses in a manner that parallels the experimental results. A critical assessment of the successes and shortcomings of predicting mechanical responses through coarse-grained MD simulations has been made.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hinckley, Daniel M.; Freeman, Gordon S.; Whitmer, Jonathan K.
2013-10-14
A new 3-Site-Per-Nucleotide coarse-grained model for DNA is presented. The model includes anisotropic potentials between bases involved in base stacking and base pair interactions that enable the description of relevant structural properties, including the major and minor grooves. In an improvement over available coarse-grained models, the correct persistence length is recovered for both ssDNA and dsDNA, allowing for simulation of non-canonical structures such as hairpins. DNA melting temperatures, measured for duplexes and hairpins by integrating over free energy surfaces generated using metadynamics simulations, are shown to be in quantitative agreement with experiment for a variety of sequences and conditions. Hybridizationmore » rate constants, calculated using forward-flux sampling, are also shown to be in good agreement with experiment. The coarse-grained model presented here is suitable for use in biological and engineering applications, including nucleosome positioning and DNA-templated engineering.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cao, Zhen; Voth, Gregory A., E-mail: gavoth@uchicago.edu
It is essential to be able to systematically construct coarse-grained (CG) models that can efficiently and accurately reproduce key properties of higher-resolution models such as all-atom. To fulfill this goal, a mapping operator is needed to transform the higher-resolution configuration to a CG configuration. Certain mapping operators, however, may lose information related to the underlying electrostatic properties. In this paper, a new mapping operator based on the centers of charge of CG sites is proposed to address this issue. Four example systems are chosen to demonstrate this concept. Within the multiscale coarse-graining framework, CG models that use this mapping operatormore » are found to better reproduce the structural correlations of atomistic models. The present work also demonstrates the flexibility of the mapping operator and the robustness of the force matching method. For instance, important functional groups can be isolated and emphasized in the CG model.« less
Structural properties of thiophenes investigated with simulations of a coarse-grained model
NASA Astrophysics Data System (ADS)
Luettmer-Strathmann, Jutta; Almutairi, Amani
Thiophenes have important applications in organic electronics, energy conversion, and storage. The interfacial layer of an organic semiconductor in contact with a metal electrode has important effects on the performance of thin-film devices. However, the structure of this layer is not easy to model. In recent work, we developed a coarse-grained model for alpha-oligothiophenes in the bulk and near gold surfaces. We describe the molecules as linear chains of bonded, discotic particles with Gay-Berne potential interactions between non-bonded ellipsoids. In this work, we investigate structural properties of thiophenes with simulations of our coarse-grained model.
Gradients estimation from random points with volumetric tensor in turbulence
NASA Astrophysics Data System (ADS)
Watanabe, Tomoaki; Nagata, Koji
2017-12-01
We present an estimation method of fully-resolved/coarse-grained gradients from randomly distributed points in turbulence. The method is based on a linear approximation of spatial gradients expressed with the volumetric tensor, which is a 3 × 3 matrix determined by a geometric distribution of the points. The coarse grained gradient can be considered as a low pass filtered gradient, whose cutoff is estimated with the eigenvalues of the volumetric tensor. The present method, the volumetric tensor approximation, is tested for velocity and passive scalar gradients in incompressible planar jet and mixing layer. Comparison with a finite difference approximation on a Cartesian grid shows that the volumetric tensor approximation computes the coarse grained gradients fairly well at a moderate computational cost under various conditions of spatial distributions of points. We also show that imposing the solenoidal condition improves the accuracy of the present method for solenoidal vectors, such as a velocity vector in incompressible flows, especially when the number of the points is not large. The volumetric tensor approximation with 4 points poorly estimates the gradient because of anisotropic distribution of the points. Increasing the number of points from 4 significantly improves the accuracy. Although the coarse grained gradient changes with the cutoff length, the volumetric tensor approximation yields the coarse grained gradient whose magnitude is close to the one obtained by the finite difference. We also show that the velocity gradient estimated with the present method well captures the turbulence characteristics such as local flow topology, amplification of enstrophy and strain, and energy transfer across scales.
Insights into DNA-mediated interparticle interactions from a coarse-grained model
NASA Astrophysics Data System (ADS)
Ding, Yajun; Mittal, Jeetain
2014-11-01
DNA-functionalized particles have great potential for the design of complex self-assembled materials. The major hurdle in realizing crystal structures from DNA-functionalized particles is expected to be kinetic barriers that trap the system in metastable amorphous states. Therefore, it is vital to explore the molecular details of particle assembly processes in order to understand the underlying mechanisms. Molecular simulations based on coarse-grained models can provide a convenient route to explore these details. Most of the currently available coarse-grained models of DNA-functionalized particles ignore key chemical and structural details of DNA behavior. These models therefore are limited in scope for studying experimental phenomena. In this paper, we present a new coarse-grained model of DNA-functionalized particles which incorporates some of the desired features of DNA behavior. The coarse-grained DNA model used here provides explicit DNA representation (at the nucleotide level) and complementary interactions between Watson-Crick base pairs, which lead to the formation of single-stranded hairpin and double-stranded DNA. Aggregation between multiple complementary strands is also prevented in our model. We study interactions between two DNA-functionalized particles as a function of DNA grafting density, lengths of the hybridizing and non-hybridizing parts of DNA, and temperature. The calculated free energies as a function of pair distance between particles qualitatively resemble experimental measurements of DNA-mediated pair interactions.
Development of a Coarse-grained Model of Polypeptoids for Studying Self-assembly in Solution
NASA Astrophysics Data System (ADS)
Du, Pu; Rick, Steven; Kumar, Revati
Polypeptoid, a class of highly tunable biomimetic analogues of peptides, are used as a prototypical model system to study self-assembly. The focus of this work is to glean insight into the effect of electrostatic and other non-covalent secondary interactions on the self-assembly of sequence-defined polypeptoids, with different charged and uncharged side groups, in solution that will complement experiments. Atomistic (AA) molecular dynamics simulation can provide a complete description of self-assembly of polypeptoid systems. However, the long simulation length and time scales needed for these processes require the development of a computationally cheaper alternative, namely coarse-grained (CG) models. A CG model for studying polypeptoid micellar interactions is being developed, parameterized on atomistic simulations, using a hybridized approach involving the OPLS-UA force filed and the Stillinger-Weber (SW) potential form. The development of the model as well as the results from the simulations on the self-assembly as function of polypeptoid chemical structure and sequences will be presented.
Moving beyond Watson-Crick models of coarse grained DNA dynamics.
Linak, Margaret C; Tourdot, Richard; Dorfman, Kevin D
2011-11-28
DNA produces a wide range of structures in addition to the canonical B-form of double-stranded DNA. Some of these structures are stabilized by Hoogsteen bonds. We developed an experimentally parameterized, coarse-grained model that incorporates such bonds. The model reproduces many of the microscopic features of double-stranded DNA and captures the experimental melting curves for a number of short DNA hairpins, even when the open state forms complicated secondary structures. We demonstrate the utility of the model by simulating the folding of a thrombin aptamer, which contains G-quartets, and strand invasion during triplex formation. Our results highlight the importance of including Hoogsteen bonding in coarse-grained models of DNA.
Quantitative comparison of alternative methods for coarse-graining biological networks
Bowman, Gregory R.; Meng, Luming; Huang, Xuhui
2013-01-01
Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models that are most faithful to the original set of states. We find that the Bayesian agglomerative clustering engine and the hierarchical Nyström expansion graph (HNEG) typically provide the best performance. Surprisingly, the original Perron cluster cluster analysis (PCCA) method often provides the next best results, outperforming the newer PCCA+ method and the most probable paths algorithm. We also show that the differences between the models are qualitatively significant, rather than being minor shifts in the boundaries between states. The performance of the methods correlates well with the entropy of the resulting coarse-grainings, suggesting that finding states with more similar populations (i.e., avoiding low population states that may just be noise) gives better results. PMID:24089717
Coarse-Grained Molecular Monte Carlo Simulations of Liquid Crystal-Nanoparticle Mixtures
NASA Astrophysics Data System (ADS)
Neufeld, Ryan; Kimaev, Grigoriy; Fu, Fred; Abukhdeir, Nasser M.
Coarse-grained intermolecular potentials have proven capable of capturing essential details of interactions between complex molecules, while substantially reducing the number of degrees of freedom of the system under study. In the domain of liquid crystals, the Gay-Berne (GB) potential has been successfully used to model the behavior of rod-like and disk-like mesogens. However, only ellipsoid-like interaction potentials can be described with GB, making it a poor fit for many real-world mesogens. In this work, the results of Monte Carlo simulations of liquid crystal domains using the Zewdie-Corner (ZC) potential are presented. The ZC potential is constructed from an orthogonal series of basis functions, allowing for potentials of essentially arbitrary shapes to be modeled. We also present simulations of mixtures of liquid crystalline mesogens with nanoparticles. Experimentally these mixtures have been observed to exhibit microphase separation and formation of long-range networks under some conditions. This highlights the need for a coarse-grained approach which can capture salient details on the molecular scale while simulating sufficiently large domains to observe these phenomena. We compare the phase behavior of our simulations with that of a recently presented continuum theory. This work was made possible by the Natural Sciences and Engineering Research Council of Canada and Compute Ontario.
Coarse Grained Model for Biological Simulations: Recent Refinements and Validation
Vicatos, Spyridon; Rychkova, Anna; Mukherjee, Shayantani; Warshel, Arieh
2014-01-01
Exploring the free energy landscape of proteins and modeling the corresponding functional aspects presents a major challenge for computer simulation approaches. This challenge is due to the complexity of the landscape and the enormous computer time needed for converging simulations. The use of various simplified coarse grained (CG) models offers an effective way of sampling the landscape, but most current models are not expected to give a reliable description of protein stability and functional aspects. The main problem is associated with insufficient focus on the electrostatic features of the model. In this respect our recent CG model offers significant advantage as it has been refined while focusing on its electrostatic free energy. Here we review the current state of our model, describing recent refinement, extensions and validation studies while focusing on demonstrating key applications. These include studies of protein stability, extending the model to include membranes and electrolytes and electrodes as well as studies of voltage activated proteins, protein insertion trough the translocon, the action of molecular motors and even the coupling of the stalled ribosome and the translocon. Our example illustrates the general potential of our approach in overcoming major challenges in studies of structure function correlation in proteins and large macromolecular complexes. PMID:25050439
Quantum theory of multiscale coarse-graining.
Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A
2018-03-14
Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.
Variational Approach to Monte Carlo Renormalization Group
NASA Astrophysics Data System (ADS)
Wu, Yantao; Car, Roberto
2017-12-01
We present a Monte Carlo method for computing the renormalized coupling constants and the critical exponents within renormalization theory. The scheme, which derives from a variational principle, overcomes critical slowing down, by means of a bias potential that renders the coarse grained variables uncorrelated. The two-dimensional Ising model is used to illustrate the method.
Kirchheimer, Bernhard; Schinkel, Christoph C F; Dellinger, Agnes S; Klatt, Simone; Moser, Dietmar; Winkler, Manuela; Lenoir, Jonathan; Caccianiga, Marco; Guisan, Antoine; Nieto-Lugilde, Diego; Svenning, Jens-Christian; Thuiller, Wilfried; Vittoz, Pascal; Willner, Wolfgang; Zimmermann, Niklaus E; Hörandl, Elvira; Dullinger, Stefan
2016-03-22
Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. European Alps. We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100 × 100 m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2 × 2 m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations. All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole-range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine-grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse-grained data. Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse-grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.
Lin, Zhixiong; Riniker, Sereina; van Gunsteren, Wilfred F
2013-03-12
Atomistic molecular dynamics simulations of peptides or proteins in aqueous solution are still limited to the multi-nanosecond time scale and multi-nanometer range by computational cost. Combining atomic solutes with a supramolecular solvent model in hybrid fine-grained/coarse-grained (FG/CG) simulations allows atomic detail in the region of interest while being computationally more efficient. We used enveloping distribution sampling (EDS) to calculate the free enthalpy differences between different helical conformations, i.e., α-, π-, and 310-helices, of an atomic level FG alanine deca-peptide solvated in a supramolecular CG water solvent. The free enthalpy differences obtained show that by replacing the FG solvent by the CG solvent, the π-helix is destabilized with respect to the α-helix by about 2.5 kJ mol(-1), and the 310-helix is stabilized with respect to the α-helix by about 9 kJ mol(-1). In addition, the dynamics of the peptide becomes faster. By introducing a FG water layer of 0.8 nm around the peptide, both thermodynamic and dynamic properties are recovered, while the hybrid FG/CG simulations are still four times more efficient than the atomistic simulations, even when the cutoff radius for the nonbonded interactions is increased from 1.4 to 2.0 nm. Hence, the hybrid FG/CG model, which yields an appropriate balance between reduced accuracy and enhanced computational speed, is very suitable for molecular dynamics simulation investigations of biomolecules.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu
2015-12-28
The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF.more » We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.« less
Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales
Ayton, Gary S.; Lyman, Edward
2014-01-01
An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037
Supercoil Formation During DNA Melting
NASA Astrophysics Data System (ADS)
Sayar, Mehmet; Avsaroglu, Baris; Kabakcioglu, Alkan
2009-03-01
Supercoil formation plays a key role in determining the structure-function relationship in DNA. Biological and technological processes, such as protein synthesis, polymerase chain reaction, and microarrays relys on separation of the two strands in DNA, which is coupled to the unwinding of the supercoiled structure. This problem has been studied theoretically via Peyrard-Bishop and Poland-Scheraga type models, which include a simple representation of the DNA structural properties. In recent years, computational models, which provide a more realtistic representaion of DNA molecule, have been used to study the melting behavior of short DNA chains. Here, we will present a new coarse-grained model of DNA which is capable of simulating sufficiently long DNA chains for studying the supercoil formation during melting, without sacrificing the local structural properties. Our coarse-grained model successfully reproduces the local geometry of the DNA molecule, such as the 3'-5' directionality, major-minor groove structure, and the helical pitch. We will present our initial results on the dynamics of supercoiling during DNA melting.
Altwaijry, Nojood A; Baron, Michael; Wright, David W; Coveney, Peter V; Townsend-Nicholson, Andrea
2017-05-09
The accurate identification of the specific points of interaction between G protein-coupled receptor (GPCR) oligomers is essential for the design of receptor ligands targeting oligomeric receptor targets. A coarse-grained molecular dynamics computer simulation approach would provide a compelling means of identifying these specific protein-protein interactions and could be applied both for known oligomers of interest and as a high-throughput screen to identify novel oligomeric targets. However, to be effective, this in silico modeling must provide accurate, precise, and reproducible information. This has been achieved recently in numerous biological systems using an ensemble-based all-atom molecular dynamics approach. In this study, we describe an equivalent methodology for ensemble-based coarse-grained simulations. We report the performance of this method when applied to four different GPCRs known to oligomerize using error analysis to determine the ensemble size and individual replica simulation time required. Our measurements of distance between residues shown to be involved in oligomerization of the fifth transmembrane domain from the adenosine A 2A receptor are in very good agreement with the existing biophysical data and provide information about the nature of the contact interface that cannot be determined experimentally. Calculations of distance between rhodopsin, CXCR4, and β 1 AR transmembrane domains reported to form contact points in homodimers correlate well with the corresponding measurements obtained from experimental structural data, providing an ability to predict contact interfaces computationally. Interestingly, error analysis enables identification of noninteracting regions. Our results confirm that GPCR interactions can be reliably predicted using this novel methodology.
Generalized Quantum Theory of Bianchi IX Cosmologies
NASA Astrophysics Data System (ADS)
Craig, David; Hartle, James
2003-04-01
We apply sum-over-histories generalized quantum theory to the closed homogeneous minisuperspace Bianchi IX cosmological model. We sketch how the probabilities in decoherent sets of alternative, coarse-grained histories of this model universe are calculated. We consider in particular, the probabilities for classical evolution in a suitable coarse-graining. For a restricted class of initial conditions and coarse grainings we exhibit the approximate decoherence of alternative histories in which the universe behaves classically and those in which it does not, illustrating the prediction that these universes will evolve in an approximately classical manner with a probability near unity.
An ellipsoid-chain model for conjugated polymer solutions
NASA Astrophysics Data System (ADS)
Lee, Cheng K.; Hua, Chi C.; Chen, Show A.
2012-02-01
We propose an ellipsoid-chain model which may be routinely parameterized to capture large-scale properties of semiflexible, amphiphilic conjugated polymers in various solvent media. The model naturally utilizes the defect locations as pivotal centers connecting adjacent ellipsoids (each currently representing ten monomer units), and a variant umbrella-sampling scheme is employed to construct the potentials of mean force (PMF) for specific solvent media using atomistic dynamics data and simplex optimization. The performances, both efficacy and efficiency, of the model are thoroughly evaluated by comparing the simulation results on long, single-chain (i.e., 300-mer) structures with those from two existing, finer-grained models for a standard conjugated polymer (i.e., poly(2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenylenevinylene) or MEH-PPV) in two distinct solvents (i.e., chloroform or toluene) as well as a hybrid, binary-solvent medium (i.e., chloroform/toluene = 1:1 in number density). The coarse-grained Monte Carlo (CGMC) simulation of the ellipsoid-chain model is shown to be the most efficient—about 300 times faster than the coarse-grained molecular dynamics (CGMD) simulation of the finest CG model that employs explicit solvents—in capturing elementary single-chain structures for both single-solvent media, and is a few times faster than the coarse-grained Langevin dynamics (CGLD) simulation of another implicit-solvent polymer model with a slightly greater coarse-graining level than in the CGMD simulation. For the binary-solvent system considered, however, both of the two implicit-solvent schemes (i.e., CGMC and CGLD) fail to capture the effects of conspicuous concentration fluctuations near the polymer-solvent interface, arising from a pronounced coupling between the solvent molecules and different parts of the polymer. Essential physical implications are elaborated on the success as well as the failure of the two implicit-solvent CG schemes under varying solvent conditions. Within the ellipsoid-chain model, the impact of synthesized defects on local segmental ordering as well as bulk chain conformation is also scrutinized, and essential consequences in practical applications discussed. In future perspectives, we remark on strategy that takes advantage of the coordination among various CG models and simulation schemes to warrant computational efficiency and accuracy, with the anticipated capability of simulating larger-scale, many-chain aggregate systems.
NASA Astrophysics Data System (ADS)
Li, Tao; Li, Tuan-Jie
2018-04-01
The analysis of grain-size distribution enables us to decipher sediment transport processes and understand the causal relations between dynamic processes and grain-size distributions. In the present study, grain sizes were measured from surface sediments collected in the Pearl River Estuary and its adjacent coastal areas. End-member modeling analysis attempts to unmix the grain sizes into geologically meaningful populations. Six grain-size end-members were identified. Their dominant modes are 0 Φ, 1.5 Φ, 2.75 Φ, 4.5 Φ, 7 Φ, and 8 Φ, corresponding to coarse sand, medium sand, fine sand, very coarse silt, silt, and clay, respectively. The spatial distributions of the six end-members are influenced by sediment transport and depositional processes. The two coarsest end-members (coarse sand and medium sand) may reflect relict sediments deposited during the last glacial period. The fine sand end-member would be difficult to transport under fair weather conditions, and likely indicates storm deposits. The three remaining fine-grained end-members (very coarse silt, silt, and clay) are recognized as suspended particles transported by saltwater intrusion via the flood tidal current, the Guangdong Coastal Current, and riverine outflow. The grain-size trend analysis shows distinct transport patterns for the three fine-grained end-members. The landward transport of the very coarse silt end-member occurs in the eastern part of the estuary, the seaward transport of the silt end-member occurs in the western part, and the east-west transport of the clay end-member occurs in the coastal areas. The results show that grain-size end-member modeling analysis in combination with sediment trend analysis help to better understand sediment transport patterns and the associated transport mechanisms.
Coarse-Grained Molecular Models of Water: A Review
Hadley, Kevin R.; McCabe, Clare
2012-01-01
Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems that involve large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger timesteps can be used and much longer simulation times can be studied. CG simulations are widely used to study systems of biological importance that are beyond the reach of atomistic simulation, necessitating a computationally efficient and accurate CG model for water. In this review, we discuss the methods used for developing CG water models and the relative advantages and disadvantages of the resulting models. In general, CG water models differ with regards to how many waters each CG group or bead represents, whether analytical or tabular potentials have been used to describe the interactions, and how the model incorporates electrostatic interactions. Finally, how the models are parameterized depends on their application, so, while some are fitted to experimental properties such as surface tension and density, others are fitted to radial distribution functions extracted from atomistic simulations. PMID:22904601
Bedload transport over run-of-river dams, Delaware, U.S.A.
NASA Astrophysics Data System (ADS)
Pearson, Adam J.; Pizzuto, Jim
2015-11-01
We document the detailed morphology and bed sediment size distribution of a stream channel upstream and downstream of a 200-year-old run-of-river dam on the Red Clay Creek, a fifth order stream in the Piedmont of northern Delaware, and combine these data with HEC-RAS modeling and bedload transport computations. We hypothesize that coarse bed material can be carried through run-of-river impoundments before they completely fill with sediment, and we explore mechanisms to facilitate this transport. Only 25% of the accommodation space in our study site is filled with sediment, and maximum water depths are approximately equal to the dam height. All grain-size fractions present upstream of the impoundment are also present throughout the impoundment. A characteristic coarse-grained sloping ramp leads from the floor of the impoundment to the crest of the dam. A 2.3-m-deep plunge pool has been excavated below the dam, followed immediately downstream by a mid-channel bar composed of coarse bed material similar in size distribution to the bed material of the impoundment. The mid-channel bar stores 1472 m3 of sediment, exceeding the volume excavated from the plunge pool by a factor of 2.8. These field observations are typical of five other sites nearby and suggest that all bed material grain-size fractions supplied from upstream can be transported through the impoundment, up the sloping ramp, and over the top of the dam. Sediment transport computations suggest that all grain sizes are in transport upstream and within the impoundment at all discharges with return periods from 1 to 50 years. Our computations suggest that transport of coarse bed material through the impoundment is facilitated by its smooth, sandy bed. Model results suggest that the impoundment is currently aggrading at 0.26 m/year, but bed elevations may be recovering after recent scour from a series of large floods during water year 2011-2012. We propose that impoundments upstream of these run-of-river dams behave as long pools that adjust their bed elevation and texture to transport the load supplied by the watershed, rather than as impounded reservoirs with little bed material transport capacity. Scour may only occur during episodic high flows, followed by aggradation during periods of low flow.
NASA Astrophysics Data System (ADS)
Richter, Martin; Fingerhut, Benjamin P.
2017-06-01
The description of non-Markovian effects imposed by low frequency bath modes poses a persistent challenge for path integral based approaches like the iterative quasi-adiabatic propagator path integral (iQUAPI) method. We present a novel approximate method, termed mask assisted coarse graining of influence coefficients (MACGIC)-iQUAPI, that offers appealing computational savings due to substantial reduction of considered path segments for propagation. The method relies on an efficient path segment merging procedure via an intermediate coarse grained representation of Feynman-Vernon influence coefficients that exploits physical properties of system decoherence. The MACGIC-iQUAPI method allows us to access the regime of biological significant long-time bath memory on the order of hundred propagation time steps while retaining convergence to iQUAPI results. Numerical performance is demonstrated for a set of benchmark problems that cover bath assisted long range electron transfer, the transition from coherent to incoherent dynamics in a prototypical molecular dimer and excitation energy transfer in a 24-state model of the Fenna-Matthews-Olson trimer complex where in all cases excellent agreement with numerically exact reference data is obtained.
Messer, Benjamin M.; Roca, Maite; Chu, Zhen T.; Vicatos, Spyridon; Kilshtain, Alexandra Vardi; Warshel, Arieh
2009-01-01
Evaluating the free energy landscape of proteins and the corresponding functional aspects presents a major challenge for computer simulation approaches. This challenge is due to the complexity of the landscape and the enormous computer time needed for converging simulations. The use of simplified coarse grained (CG) folding models offers an effective way of sampling the landscape but such a treatment, however, may not give the correct description of the effect of the actual protein residues. A general way around this problem that has been put forward in our early work (Fan et al, Theor Chem Acc (1999) 103:77-80) uses the CG model as a reference potential for free energy calculations of different properties of the explicit model. This method is refined and extended here, focusing on improving the electrostatic treatment and on demonstrating key applications. This application includes: evaluation of changes of folding energy upon mutations, calculations of transition states binding free energies (which are crucial for rational enzyme design), evaluation of catalytic landscape and simulation of the time dependent responses to pH changes. Furthermore, the general potential of our approach in overcoming major challenges in studies of structure function correlation in proteins is discussed. PMID:20052756
Entropic elasticity based coarse-grained model of lipid membranes
NASA Astrophysics Data System (ADS)
Feng, Shuo; Hu, Yucai; Liang, Haiyi
2018-04-01
Various models for lipid bilayer membranes have been presented to investigate their morphologies. Among them, the aggressive coarse-grained models, where the membrane is represented by a single layer of particles, are computationally efficient and of practical importance for simulating membrane dynamics at the microscopic scale. In these models, soft potentials between particle pairs are used to maintain the fluidity of membranes, but the underlying mechanism of the softening requires further clarification. We have analyzed the membrane area decrease due to thermal fluctuations, and the results demonstrate that the intraparticle part of entropic elasticity is responsible for the softening of the potential. Based on the stretching response of the membrane, a bottom-up model is developed with an entropic effect explicitly involved. The model reproduces several essential properties of the lipid membrane, including the fluid state and a plateau in the stretching curve. In addition, the area compressibility modulus, bending rigidity, and spontaneous curvature display linear dependence on model parameters. As a demonstration, we have investigated the closure and morphology evolution of membrane systems driven by spontaneous curvature, and vesicle shapes observed experimentally are faithfully reproduced.
A new algorithm for construction of coarse-grained sites of large biomolecules.
Li, Min; Zhang, John Z H; Xia, Fei
2016-04-05
The development of coarse-grained (CG) models for large biomolecules remains a challenge in multiscale simulations, including a rigorous definition of CG representations for them. In this work, we proposed a new stepwise optimization imposed with the boundary-constraint (SOBC) algorithm to construct the CG sites of large biomolecules, based on the s cheme of essential dynamics CG. By means of SOBC, we can rigorously derive the CG representations of biomolecules with less computational cost. The SOBC is particularly efficient for the CG definition of large systems with thousands of residues. The resulted CG sites can be parameterized as a CG model using the normal mode analysis based fluctuation matching method. Through normal mode analysis, the obtained modes of CG model can accurately reflect the functionally related slow motions of biomolecules. The SOBC algorithm can be used for the construction of CG sites of large biomolecules such as F-actin and for the study of mechanical properties of biomaterials. © 2015 Wiley Periodicals, Inc.
Tools for Material Design and Selection
NASA Astrophysics Data System (ADS)
Wehage, Kristopher
The present thesis focuses on applications of numerical methods to create tools for material characterization, design and selection. The tools generated in this work incorporate a variety of programming concepts, from digital image analysis, geometry, optimization, and parallel programming to data-mining, databases and web design. The first portion of the thesis focuses on methods for characterizing clustering in bimodal 5083 Aluminum alloys created by cryomilling and powder metallurgy. The bimodal samples analyzed in the present work contain a mixture of a coarse grain phase, with a grain size on the order of several microns, and an ultra-fine grain phase, with a grain size on the order of 200 nm. The mixing of the two phases is not homogeneous and clustering is observed. To investigate clustering in these bimodal materials, various microstructures were created experimentally by conventional cryomilling, Hot Isostatic Pressing (HIP), Extrusion, Dual-Mode Dynamic Forging (DMDF) and a new 'Gradient' cryomilling process. Two techniques for quantitative clustering analysis are presented, formulated and implemented. The first technique, the Area Disorder function, provides a metric of the quality of coarse grain dispersion in an ultra-fine grain matrix and the second technique, the Two-Point Correlation function, provides a metric of long and short range spatial arrangements of the two phases, as well as an indication of the mean feature size in any direction. The two techniques are implemented on digital images created by Scanning Electron Microscopy (SEM) and Electron Backscatter Detection (EBSD) of the microstructures. To investigate structure--property relationships through modeling and simulation, strategies for generating synthetic microstructures are discussed and a computer program that generates randomized microstructures with desired configurations of clustering described by the Area Disorder Function is formulated and presented. In the computer program, two-dimensional microstructures are generated by Random Sequential Adsorption (RSA) of voxelized ellipses representing the coarse grain phase. A simulated annealing algorithm is used to geometrically optimize the placement of the ellipses in the model to achieve varying user-defined configurations of spatial arrangement of the coarse grains. During the simulated annealing process, the ellipses are allowed to overlap up to a specified threshold, allowing triple junctions to form in the model. Once the simulated annealing process is complete, the remaining space is populated by smaller ellipses representing the ultra-fine grain phase. Uniform random orientations are assigned to the grains. The program generates text files that can be imported in to Crystal Plasticity Finite Element Analysis Software for stress analysis. Finally, numerical methods and programming are applied to current issues in green engineering and hazard assessment. To understand hazards associated with materials and select safer alternatives, engineers and designers need access to up-to-date hazard information. However, hazard information comes from many disparate sources and aggregating, interpreting and taking action on the wealth of data is not trivial. In light of these challenges, a Framework for Automated Hazard Assessment based on the GreenScreen list translator is presented. The framework consists of a computer program that automatically extracts data from the GHS-Japan hazard database, loads the data into a machine-readable JSON format, transforms the JSON document in to a GreenScreen JSON document using the GreenScreen List Translator v1.2 and performs GreenScreen Benchmark scoring on the material. The GreenScreen JSON documents are then uploaded to a document storage system to allow human operators to search for, modify or add additional hazard information via a web interface.
Zhang, Yuwei; Cao, Zexing; Zhang, John Zenghui; Xia, Fei
2017-02-27
Construction of coarse-grained (CG) models for large biomolecules used for multiscale simulations demands a rigorous definition of CG sites for them. Several coarse-graining methods such as the simulated annealing and steepest descent (SASD) based on the essential dynamics coarse-graining (ED-CG) or the stepwise local iterative optimization (SLIO) based on the fluctuation maximization coarse-graining (FM-CG), were developed to do it. However, the practical applications of these methods such as SASD based on ED-CG are subject to limitations because they are too expensive. In this work, we extend the applicability of ED-CG by combining it with the SLIO algorithm. A comprehensive comparison of optimized results and accuracy of various algorithms based on ED-CG show that SLIO is the fastest as well as the most accurate algorithm among them. ED-CG combined with SLIO could give converged results as the number of CG sites increases, which demonstrates that it is another efficient method for coarse-graining large biomolecules. The construction of CG sites for Ras protein by using MD fluctuations demonstrates that the CG sites derived from FM-CG can reflect the fluctuation properties of secondary structures in Ras accurately.
Electrostatic interactions in soft particle systems: mesoscale simulations of ionic liquids.
Wang, Yong-Lei; Zhu, You-Liang; Lu, Zhong-Yuan; Laaksonen, Aatto
2018-05-21
Computer simulations provide a unique insight into the microscopic details, molecular interactions and dynamic behavior responsible for many distinct physicochemical properties of ionic liquids. Due to the sluggish and heterogeneous dynamics and the long-ranged nanostructured nature of ionic liquids, coarse-grained meso-scale simulations provide an indispensable complement to detailed first-principles calculations and atomistic simulations allowing studies over extended length and time scales with a modest computational cost. Here, we present extensive coarse-grained simulations on a series of ionic liquids of the 1-alkyl-3-methylimidazolium (alkyl = butyl, heptyl-, and decyl-) family with Cl, [BF4], and [PF6] counterions. Liquid densities, microstructures, translational diffusion coefficients, and re-orientational motion of these model ionic liquid systems have been systematically studied over a wide temperature range. The addition of neutral beads in cationic models leads to a transition of liquid morphologies from dispersed apolar beads in a polar framework to that characterized by bi-continuous sponge-like interpenetrating networks in liquid matrices. Translational diffusion coefficients of both cations and anions decrease upon lengthening of the neutral chains in the cationic models and by enlarging molecular sizes of the anionic groups. Similar features are observed in re-orientational motion and time scales of different cationic models within the studied temperature range. The comparison of the liquid properties of the ionic systems with their neutral counterparts indicates that the distinctive microstructures and dynamical quantities of the model ionic liquid systems are intrinsically related to Coulombic interactions. Finally, we compared the computational efficiencies of three linearly scaling O(N log N) Ewald summation methods, the particle-particle particle-mesh method, the particle-mesh Ewald summation method, and the Ewald summation method based on a non-uniform fast Fourier transform technique, to calculate electrostatic interactions. Coarse-grained simulations were performed using the GALAMOST and the GROMACS packages and hardware efficiently utilizing graphics processing units on a set of extended [1-decyl-3-methylimidazolium][BF4] ionic liquid systems of up to 131 072 ion pairs.
NASA Astrophysics Data System (ADS)
Siettos, C. I.; Gear, C. W.; Kevrekidis, I. G.
2012-08-01
We show how the equation-free approach can be exploited to enable agent-based simulators to perform system-level computations such as bifurcation, stability analysis and controller design. We illustrate these tasks through an event-driven agent-based model describing the dynamic behaviour of many interacting investors in the presence of mimesis. Using short bursts of appropriately initialized runs of the detailed, agent-based simulator, we construct the coarse-grained bifurcation diagram of the (expected) density of agents and investigate the stability of its multiple solution branches. When the mimetic coupling between agents becomes strong enough, the stable stationary state loses its stability at a coarse turning point bifurcation. We also demonstrate how the framework can be used to design a wash-out dynamic controller that stabilizes open-loop unstable stationary states even under model uncertainty.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Na; Zhang, Peng; Kang, Wei
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less
Lu, Liqiang; Gopalan, Balaji; Benyahia, Sofiane
2017-06-21
Several discrete particle methods exist in the open literature to simulate fluidized bed systems, such as discrete element method (DEM), time driven hard sphere (TDHS), coarse-grained particle method (CGPM), coarse grained hard sphere (CGHS), and multi-phase particle-in-cell (MP-PIC). These different approaches usually solve the fluid phase in a Eulerian fixed frame of reference and the particle phase using the Lagrangian method. The first difference between these models lies in tracking either real particles or lumped parcels. The second difference is in the treatment of particle-particle interactions: by calculating collision forces (DEM and CGPM), using momentum conservation laws (TDHS and CGHS),more » or based on particle stress model (MP-PIC). These major model differences lead to a wide range of results accuracy and computation speed. However, these models have never been compared directly using the same experimental dataset. In this research, a small-scale fluidized bed is simulated with these methods using the same open-source code MFIX. The results indicate that modeling the particle-particle collision by TDHS increases the computation speed while maintaining good accuracy. Also, lumping few particles in a parcel increases the computation speed with little loss in accuracy. However, modeling particle-particle interactions with solids stress leads to a big loss in accuracy with a little increase in computation speed. The MP-PIC method predicts an unphysical particle-particle overlap, which results in incorrect voidage distribution and incorrect overall bed hydrodynamics. Based on this study, we recommend using the CGHS method for fluidized bed simulations due to its computational speed that rivals that of MPPIC while maintaining a much better accuracy.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Liqiang; Gopalan, Balaji; Benyahia, Sofiane
Several discrete particle methods exist in the open literature to simulate fluidized bed systems, such as discrete element method (DEM), time driven hard sphere (TDHS), coarse-grained particle method (CGPM), coarse grained hard sphere (CGHS), and multi-phase particle-in-cell (MP-PIC). These different approaches usually solve the fluid phase in a Eulerian fixed frame of reference and the particle phase using the Lagrangian method. The first difference between these models lies in tracking either real particles or lumped parcels. The second difference is in the treatment of particle-particle interactions: by calculating collision forces (DEM and CGPM), using momentum conservation laws (TDHS and CGHS),more » or based on particle stress model (MP-PIC). These major model differences lead to a wide range of results accuracy and computation speed. However, these models have never been compared directly using the same experimental dataset. In this research, a small-scale fluidized bed is simulated with these methods using the same open-source code MFIX. The results indicate that modeling the particle-particle collision by TDHS increases the computation speed while maintaining good accuracy. Also, lumping few particles in a parcel increases the computation speed with little loss in accuracy. However, modeling particle-particle interactions with solids stress leads to a big loss in accuracy with a little increase in computation speed. The MP-PIC method predicts an unphysical particle-particle overlap, which results in incorrect voidage distribution and incorrect overall bed hydrodynamics. Based on this study, we recommend using the CGHS method for fluidized bed simulations due to its computational speed that rivals that of MPPIC while maintaining a much better accuracy.« less
Yoo, Jejoong; Jackson, Meyer B.; Cui, Qiang
2013-01-01
To establish the validity of continuum mechanics models quantitatively for the analysis of membrane remodeling processes, we compare the shape and energies of the membrane fusion pore predicted by coarse-grained (MARTINI) and continuum mechanics models. The results at these distinct levels of resolution give surprisingly consistent descriptions for the shape of the fusion pore, and the deviation between the continuum and coarse-grained models becomes notable only when the radius of curvature approaches the thickness of a monolayer. Although slow relaxation beyond microseconds is observed in different perturbative simulations, the key structural features (e.g., dimension and shape of the fusion pore near the pore center) are consistent among independent simulations. These observations provide solid support for the use of coarse-grained and continuum models in the analysis of membrane remodeling. The combined coarse-grained and continuum analysis confirms the recent prediction of continuum models that the fusion pore is a metastable structure and that its optimal shape is neither toroidal nor catenoidal. Moreover, our results help reveal a new, to our knowledge, bowing feature in which the bilayers close to the pore axis separate more from one another than those at greater distances from the pore axis; bowing helps reduce the curvature and therefore stabilizes the fusion pore structure. The spread of the bilayer deformations over distances of hundreds of nanometers and the substantial reduction in energy of fusion pore formation provided by this spread indicate that membrane fusion can be enhanced by allowing a larger area of membrane to participate and be deformed. PMID:23442963
Miller, Thomas F.
2017-01-01
We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 μs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency. PMID:28328943
NASA Astrophysics Data System (ADS)
Markina, A.; Ivanov, V.; Komarov, P.; Khokhlov, A.; Tung, S.-H.
2016-11-01
We propose a coarse-grained model for studying the effects of adding bile salt to lecithin organosols by means of computer simulation. This model allows us to reveal the mechanisms of experimentally observed increasing of viscosity upon increasing the bile salt concentration. We show that increasing the bile salt to lecithin molar ratio induces the growth of elongated micelles of ellipsoidal and cylindrical shape due to incorporation of disklike bile salt molecules. These wormlike micelles can entangle into transient network displaying perceptible viscoelastic properties.
2017-01-01
The accurate identification of the specific points of interaction between G protein-coupled receptor (GPCR) oligomers is essential for the design of receptor ligands targeting oligomeric receptor targets. A coarse-grained molecular dynamics computer simulation approach would provide a compelling means of identifying these specific protein–protein interactions and could be applied both for known oligomers of interest and as a high-throughput screen to identify novel oligomeric targets. However, to be effective, this in silico modeling must provide accurate, precise, and reproducible information. This has been achieved recently in numerous biological systems using an ensemble-based all-atom molecular dynamics approach. In this study, we describe an equivalent methodology for ensemble-based coarse-grained simulations. We report the performance of this method when applied to four different GPCRs known to oligomerize using error analysis to determine the ensemble size and individual replica simulation time required. Our measurements of distance between residues shown to be involved in oligomerization of the fifth transmembrane domain from the adenosine A2A receptor are in very good agreement with the existing biophysical data and provide information about the nature of the contact interface that cannot be determined experimentally. Calculations of distance between rhodopsin, CXCR4, and β1AR transmembrane domains reported to form contact points in homodimers correlate well with the corresponding measurements obtained from experimental structural data, providing an ability to predict contact interfaces computationally. Interestingly, error analysis enables identification of noninteracting regions. Our results confirm that GPCR interactions can be reliably predicted using this novel methodology. PMID:28383913
Multiscale Simulation and Modeling of Multilayer Heteroepitactic Growth of C60 on Pentacene.
Acevedo, Yaset M; Cantrell, Rebecca A; Berard, Philip G; Koch, Donald L; Clancy, Paulette
2016-03-29
We apply multiscale methods to describe the strained growth of multiple layers of C60 on a thin film of pentacene. We study this growth in the presence of a monolayer pentacene step to compare our simulations to recent experimental studies by Breuer and Witte of submonolayer growth in the presence of monolayer steps. The molecular-level details of this organic semiconductor interface have ramifications on the macroscale structural and electronic behavior of this system and allow us to describe several unexplained experimental observations for this system. The growth of a C60 thin film on a pentacene surface is complicated by the differing crystal habits of the two component species, leading to heteroepitactical growth. In order to probe this growth, we use three computational methods that offer different approaches to coarse-graining the system and differing degrees of computational efficiency. We present a new, efficient reaction-diffusion continuum model for 2D systems whose results compare well with mesoscale kinetic Monte Carlo (KMC) results for submonolayer growth. KMC extends our ability to simulate multiple layers but requires a library of predefined rates for event transitions. Coarse-grained molecular dynamics (CGMD) circumvents KMC's need for predefined lattices, allowing defects and grain boundaries to provide a more realistic thin film morphology. For multilayer growth, in this particularly suitable candidate for coarse-graining, CGMD is a preferable approach to KMC. Combining the results from these three methods, we show that the lattice strain induced by heteroepitactical growth promotes 3D growth and the creation of defects in the first monolayer. The CGMD results are consistent with experimental results on the same system by Conrad et al. and by Breuer and Witte in which C60 aggregates change from a 2D structure at low temperature to 3D clusters along the pentacene step edges at higher temperatures.
Coarse-grained hydrodynamics from correlation functions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Palmer, Bruce
This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configuration from a molecular dynamics simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilbrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is applied to some simple hydrodynamic cases to determine the feasibility of applying this to realistic nanoscale systems.
Coarse-grained modeling of crystal growth and polymorphism of a model pharmaceutical molecule.
Mandal, Taraknath; Marson, Ryan L; Larson, Ronald G
2016-10-04
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 P2 1 ) was predicted which is different from the experimentally known crystal structure (orthorhombic, space group Pna2 1 ). 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.
Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi
2014-03-01
We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Atomistic to continuum modeling of solidification microstructures
Karma, Alain; Tourret, Damien
2015-09-26
We summarize recent advances in modeling of solidification microstructures using computational methods that bridge atomistic to continuum scales. We first discuss progress in atomistic modeling of equilibrium and non-equilibrium solid–liquid interface properties influencing microstructure formation, as well as interface coalescence phenomena influencing the late stages of solidification. The latter is relevant in the context of hot tearing reviewed in the article by M. Rappaz in this issue. We then discuss progress to model microstructures on a continuum scale using phase-field methods. We focus on selected examples in which modeling of 3D cellular and dendritic microstructures has been directly linked tomore » experimental observations. Finally, we discuss a recently introduced coarse-grained dendritic needle network approach to simulate the formation of well-developed dendritic microstructures. The approach reliably bridges the well-separated scales traditionally simulated by phase-field and grain structure models, hence opening new avenues for quantitative modeling of complex intra- and inter-grain dynamical interactions on a grain scale.« less
Genheden, Samuel
2017-10-01
We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.
NASA Astrophysics Data System (ADS)
Genheden, Samuel
2017-10-01
We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.
de Oliveira, Tiago E.; Netz, Paulo A.; Kremer, Kurt; ...
2016-05-03
We present a coarse-graining strategy that we test for aqueous mixtures. The method uses pair-wise cumulative coordination as a target function within an iterative Boltzmann inversion (IBI) like protocol. We name this method coordination iterative Boltzmann inversion (C–IBI). While the underlying coarse-grained model is still structure based and, thus, preserves pair-wise solution structure, our method also reproduces solvation thermodynamics of binary and/or ternary mixtures. In addition, we observe much faster convergence within C–IBI compared to IBI. To validate the robustness, we apply C–IBI to study test cases of solvation thermodynamics of aqueous urea and a triglycine solvation in aqueous urea.
Computational Investigation of Effects of Grain Size on Ballistic Performance of Copper
NASA Astrophysics Data System (ADS)
He, Ge; Dou, Yangqing; Guo, Xiang; Liu, Yucheng
2018-01-01
Numerical simulations were conducted to compare ballistic performance and penetration mechanism of copper (Cu) with four representative grain sizes. Ballistic limit velocities for coarse-grained (CG) copper (grain size ≈ 90 µm), regular copper (grain size ≈ 30 µm), fine-grained (FG) copper (grain size ≈ 890 nm), and ultrafine-grained (UG) copper (grain size ≈ 200 nm) were determined for the first time through the simulations. It was found that the copper with reduced grain size would offer higher strength and better ductility, and therefore renders improved ballistic performance than the CG and regular copper. High speed impact and penetration behavior of the FG and UG copper was also compared with the CG coppers strengthened by nanotwinned (NT) regions. The comparison results showed the impact and penetration resistance of UG copper is comparable to the CG copper strengthened by NT regions with the minimum twin spacing. Therefore, besides the NT-strengthened copper, the single phase copper with nanoscale grain size could also be a strong candidate material for better ballistic protection. A computational modeling and simulation framework was proposed for this study, in which Johnson-Cook (JC) constitutive model is used to predict the plastic deformation of Cu; the JC damage model is to capture the penetration and fragmentation behavior of Cu; Bao-Wierzbicki (B-W) failure criterion defines the material's failure mechanisms; and temperature increase during this adiabatic penetration process is given by the Taylor-Quinney method.
A highly coarse-grained model to simulate entangled polymer melts.
Zhu, You-Liang; Liu, Hong; Lu, Zhong-Yuan
2012-04-14
We introduce a highly coarse-grained model to simulate the entangled polymer melts. In this model, a polymer chain is taken as a single coarse-grained particle, and the creation and annihilation of entanglements are regarded as stochastic events in proper time intervals according to certain rules and possibilities. We build the relationship between the probability of appearance of an entanglement between any pair of neighboring chains at a given time interval and the rate of variation of entanglements which describes the concurrence of birth and death of entanglements. The probability of disappearance of entanglements is tuned to keep the total entanglement number around the target value. This useful model can reflect many characteristics of entanglements and macroscopic properties of polymer melts. As an illustration, we apply this model to simulate the polyethylene melt of C(1000)H(2002) at 450 K and further validate this model by comparing to experimental data and other simulation results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chremos, Alexandros, E-mail: achremos@imperial.ac.uk; Nikoubashman, Arash, E-mail: arashn@princeton.edu; Panagiotopoulos, Athanassios Z.
In this contribution, we develop a coarse-graining methodology for mapping specific block copolymer systems to bead-spring particle-based models. We map the constituent Kuhn segments to Lennard-Jones particles, and establish a semi-empirical correlation between the experimentally determined Flory-Huggins parameter χ and the interaction of the model potential. For these purposes, we have performed an extensive set of isobaric–isothermal Monte Carlo simulations of binary mixtures of Lennard-Jones particles with the same size but with asymmetric energetic parameters. The phase behavior of these monomeric mixtures is then extended to chains with finite sizes through theoretical considerations. Such a top-down coarse-graining approach is importantmore » from a computational point of view, since many characteristic features of block copolymer systems are on time and length scales which are still inaccessible through fully atomistic simulations. We demonstrate the applicability of our method for generating parameters by reproducing the morphology diagram of a specific diblock copolymer, namely, poly(styrene-b-methyl methacrylate), which has been extensively studied in experiments.« less
Unconstrained Structure Formation in Coarse-Grained Protein Simulations
NASA Astrophysics Data System (ADS)
Bereau, Tristan
The ability of proteins to fold into well-defined structures forms the basis of a wide variety of biochemical functions in and out of the cell membrane. Many of these processes, however, operate at time- and length-scales that are currently unattainable by all-atom computer simulations. To cope with this difficulty, increasingly more accurate and sophisticated coarse-grained models are currently being developed. In the present thesis, we introduce a solvent-free coarse-grained model for proteins. Proteins are modeled by four beads per amino acid, providing enough backbone resolution to allow for accurate sampling of local conformations. It relies on simple interactions that emphasize structure, such as hydrogen bonds and hydrophobicity. Realistic alpha/beta content is achieved by including an effective nearest-neighbor dipolar interaction. Parameters are tuned to reproduce both local conformations and tertiary structures. By studying both helical and extended conformations we make sure the force field is not biased towards any particular secondary structure. Without any further adjustments or bias a realistic oligopeptide aggregation scenario is observed. The model is subsequently applied to various biophysical problems: (i) kinetics of folding of two model peptides, (ii) large-scale amyloid-beta oligomerization, and (iii) protein folding cooperativity. The last topic---defined by the nature of the finite-size thermodynamic transition exhibited upon folding---was investigated from a microcanonical perspective: the accurate evaluation of the density of states can unambiguously characterize the nature of the transition, unlike its corresponding canonical analysis. Extending the results of lattice simulations and theoretical models, we find that it is the interplay between secondary structure and the loss of non-native tertiary contacts which determines the nature of the transition. Finally, we combine the peptide model with a high-resolution, solvent-free, lipid model. The lipid force field was systematically tuned to reproduce the structural and mechanical properties of phosphatidylcholine bilayers. The two models were cross-parametrized against atomistic potential of mean force curves for the insertion of single amino acid side chains into a bilayer. Coarse-grained transmembrane protein simulations were then compared with experiments and atomistic simulations to validate the force field. The transferability of the two models across amino acid sequences and lipid species permits the investigation of a wide variety of scenarios, while the absence of explicit solvent allows for studies of large-scale phenomena.
NASA Astrophysics Data System (ADS)
Pandey, Ras; Kuang, Zhifeng; Farmer, Barry; Kim, Sang; Naik, Rajesh
2012-02-01
Recently, Kim et al. [1] have found that peptides P1: HSSYWYAFNNKT and P2: EPLQLKM bind selectively to graphene surfaces and edges respectively which are critical in modulating both the mechanical as well as electronic transport properties of graphene. Such distinctions in binding sites (edge versus surface) observed in electron micrographs were verified by computer simulation by an all-atomic model that captures the pi-pi bonding. We propose a hierarchical approach that involves input from the all-atom Molecular Dynamics (MD) study (with atomistic detail) into a coarse-grained Monte Carlo simulation to extend this study further to a larger scale. The binding energy of a free amino acid with the graphene sheet from all-atom simulation is used in the interaction parameter for the coarse-grained approach. Peptide chain executes its stochastic motion with the Metropolis algorithm. We investigate a number of local and global physical quantities and find that peptide P1 is likely to bind more strongly to graphene sheet than P2 and that it is anchored by three residues ^4Y^5W^6Y. [1] S.N. Kim et al J. Am. Chem. Soc. 133, 14480 (2011).
Distributions of experimental protein structures on coarse-grained free energy landscapes
Liu, Jie; Jernigan, Robert L.
2015-01-01
Predicting conformational changes of proteins is needed in order to fully comprehend functional mechanisms. With the large number of available structures in sets of related proteins, it is now possible to directly visualize the clusters of conformations and their conformational transitions through the use of principal component analysis. The most striking observation about the distributions of the structures along the principal components is their highly non-uniform distributions. In this work, we use principal component analysis of experimental structures of 50 diverse proteins to extract the most important directions of their motions, sample structures along these directions, and estimate their free energy landscapes by combining knowledge-based potentials and entropy computed from elastic network models. When these resulting motions are visualized upon their coarse-grained free energy landscapes, the basis for conformational pathways becomes readily apparent. Using three well-studied proteins, T4 lysozyme, serum albumin, and sarco-endoplasmic reticular Ca2+ adenosine triphosphatase (SERCA), as examples, we show that such free energy landscapes of conformational changes provide meaningful insights into the functional dynamics and suggest transition pathways between different conformational states. As a further example, we also show that Monte Carlo simulations on the coarse-grained landscape of HIV-1 protease can directly yield pathways for force-driven conformational changes. PMID:26723638
The role of structural parameters in DNA cyclization
Alexandrov, Ludmil B.; Bishop, Alan R.; Rasmussen, Kim O.; ...
2016-02-04
The intrinsic bendability of DNA plays an important role with relevance for myriad of essential cellular mechanisms. The flexibility of a DNA fragment can be experimentally and computationally examined by its propensity for cyclization, quantified by the Jacobson-Stockmayer J factor. In this paper, we use a well-established coarse-grained three-dimensional model of DNA and seven distinct sets of experimentally and computationally derived conformational parameters of the double helix to evaluate the role of structural parameters in calculating DNA cyclization.
LocalMove: computing on-lattice fits for biopolymers
Ponty, Y.; Istrate, R.; Porcelli, E.; Clote, P.
2008-01-01
Given an input Protein Data Bank file (PDB) for a protein or RNA molecule, LocalMove is a web server that determines an on-lattice representation for the input biomolecule. The web server implements a Markov Chain Monte-Carlo algorithm with simulated annealing to compute an approximate fit for either the coarse-grain model or backbone model on either the cubic or face-centered cubic lattice. LocalMove returns a PDB file as output, as well as dynamic movie of 3D images of intermediate conformations during the computation. The LocalMove server is publicly available at http://bioinformatics.bc.edu/clotelab/localmove/. PMID:18556754
Systematic coarse-grained modeling of complexation between small interfering RNA and polycations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wei, Zonghui; Luijten, Erik, E-mail: luijten@northwestern.edu; Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208
All-atom molecular dynamics simulations can provide insight into the properties of polymeric gene-delivery carriers by elucidating their interactions and detailed binding patterns with nucleic acids. However, to explore nanoparticle formation through complexation of these polymers and nucleic acids and study their behavior at experimentally relevant time and length scales, a reliable coarse-grained model is needed. Here, we systematically develop such a model for the complexation of small interfering RNA (siRNA) and grafted polyethyleneimine copolymers, a promising candidate for siRNA delivery. We compare the predictions of this model with all-atom simulations and demonstrate that it is capable of reproducing detailed bindingmore » patterns, charge characteristics, and water release kinetics. Since the coarse-grained model accelerates the simulations by one to two orders of magnitude, it will make it possible to quantitatively investigate nanoparticle formation involving multiple siRNA molecules and cationic copolymers.« less
Coarse graining flow of spin foam intertwiners
NASA Astrophysics Data System (ADS)
Dittrich, Bianca; Schnetter, Erik; Seth, Cameron J.; Steinhaus, Sebastian
2016-12-01
Simplicity constraints play a crucial role in the construction of spin foam models, yet their effective behavior on larger scales is scarcely explored. In this article we introduce intertwiner and spin net models for the quantum group SU (2 )k×SU (2 )k, which implement the simplicity constraints analogous to four-dimensional Euclidean spin foam models, namely the Barrett-Crane (BC) and the Engle-Pereira-Rovelli-Livine/Freidel-Krasnov (EPRL/FK) model. These models are numerically coarse grained via tensor network renormalization, allowing us to trace the flow of simplicity constraints to larger scales. In order to perform these simulations we have substantially adapted tensor network algorithms, which we discuss in detail as they can be of use in other contexts. The BC and the EPRL/FK model behave very differently under coarse graining: While the unique BC intertwiner model is a fixed point and therefore constitutes a two-dimensional topological phase, BC spin net models flow away from the initial simplicity constraints and converge to several different topological phases. Most of these phases correspond to decoupling spin foam vertices; however we find also a new phase in which this is not the case, and in which a nontrivial version of the simplicity constraints holds. The coarse graining flow of the BC spin net models indicates furthermore that the transitions between these phases are not of second order. The EPRL/FK model by contrast reveals a far more intricate and complex dynamics. We observe an immediate flow away from the original simplicity constraints; however, with the truncation employed here, the models generically do not converge to a fixed point. The results show that the imposition of simplicity constraints can indeed lead to interesting and also very complex dynamics. Thus we need to further develop coarse graining tools to efficiently study the large scale behavior of spin foam models, in particular for the EPRL/FK model.
HIGH-FIDELITY SIMULATION-DRIVEN MODEL DEVELOPMENT FOR COARSE-GRAINED COMPUTATIONAL FLUID DYNAMICS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hanna, Botros N.; Dinh, Nam T.; Bolotnov, Igor A.
Nuclear reactor safety analysis requires identifying various credible accident scenarios and determining their consequences. For a full-scale nuclear power plant system behavior, it is impossible to obtain sufficient experimental data for a broad range of risk-significant accident scenarios. In single-phase flow convective problems, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide us with high fidelity results when physical data are unavailable. However, these methods are computationally expensive and cannot be afforded for simulation of long transient scenarios in nuclear accidents despite extraordinary advances in high performance scientific computing over the past decades. The major issue is themore » inability to make the transient computation parallel, thus making number of time steps required in high-fidelity methods unaffordable for long transients. In this work, we propose to apply a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. This approach aims to develop a statistical surrogate model instead of the deterministic SGS model. We chose to start with a turbulent natural convection case with volumetric heating in a horizontal fluid layer with a rigid, insulated lower boundary and isothermal (cold) upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a molten corium pool during a severe nuclear reactor accident, as well as in containment mixing and passive cooling. The presented approach demonstrates how to create a correction for the CG-CFD solution by modifying the energy balance equation. A global correction for the temperature equation proves to achieve a significant improvement to the prediction of steady state temperature distribution through the fluid layer.« less
Coarse-Grained Molecular Dynamics Simulations of Membrane-Trehalose Interactions.
Kapla, Jon; Stevensson, Baltzar; Maliniak, Arnold
2016-09-15
It is well established that trehalose (TRH) affects the physical properties of lipid bilayers and stabilizes biological membranes. We present molecular dynamics (MD) computer simulations to investigate the interactions between lipid membranes formed by 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and TRH. Both atomistic and coarse-grained (CG) interaction models were employed, and the coarse graining of DMPC leads to a reduction in the acyl chain length corresponding to a 1,2-dilauroyl-sn-glycero-3-phosphocholine lipid (DLPC). Several modifications of the Martini interaction model, used for CG simulations, were implemented, resulting in different potentials of mean force (PMFs) for DMPC bilayer-TRH interactions. These PMFs were subsequently used in a simple two-site analytical model for the description of sugar binding at the membrane interface. In contrast to that in atomistic MD simulations, the binding in the CG model was not in agreement with the two-site model. Our interpretation is that the interaction balance, involving water, TRH, and lipids, in the CG systems needs further tuning of the force-field parameters. The area per lipid is only weakly affected by TRH concentration, whereas the compressibility modulus related to the fluctuations of the membrane increases with an increase in TRH content. In agreement with experimental findings, the bending modulus is not affected by the inclusion of TRH. The important aspects of lipid bilayer interactions with biomolecules are membrane curvature generation and sensing. In the present investigation, membrane curvature is generated by artificial buckling of the bilayer in one dimension. It turns out that TRH prefers the regions with the highest curvature, which enables the most favorable situation for lipid-sugar interactions.
DNA nanotechnology: understanding and optimisation through simulation
NASA Astrophysics Data System (ADS)
Ouldridge, Thomas E.
2015-01-01
DNA nanotechnology promises to provide controllable self-assembly on the nanoscale, allowing for the design of static structures, dynamic machines and computational architectures. In this article, I review the state-of-the art of DNA nanotechnology, highlighting the need for a more detailed understanding of the key processes, both in terms of theoretical modelling and experimental characterisation. I then consider coarse-grained models of DNA, mesoscale descriptions that have the potential to provide great insight into the operation of DNA nanotechnology if they are well designed. In particular, I discuss a number of nanotechnological systems that have been studied with oxDNA, a recently developed coarse-grained model, highlighting the subtle interplay of kinetic, thermodynamic and mechanical factors that can determine behaviour. Finally, new results highlighting the importance of mechanical tension in the operation of a two-footed walker are presented, demonstrating that recovery from an unintended 'overstepped' configuration can be accelerated by three to four orders of magnitude by application of a moderate tension to the walker's track. More generally, the walker illustrates the possibility of biasing strand-displacement processes to affect the overall rate.
PaLaCe: A Coarse-Grain Protein Model for Studying Mechanical Properties.
Pasi, Marco; Lavery, Richard; Ceres, Nicoletta
2013-01-08
We present a coarse-grain protein model PaLaCe (Pasi-Lavery-Ceres) that has been developed principally to allow fast computational studies of protein mechanics and to clarify the links between mechanics and function. PaLaCe uses a two-tier protein representation with one to three pseudoatoms representing each amino acid for the main nonbonded interactions, combined with atomic-scale peptide groups and some side chain atoms to allow the explicit representation of backbone hydrogen bonds and to simplify the treatment of bonded interactions. The PaLaCe force field is composed of physics-based terms, parametrized using Boltzmann inversion of conformational probability distributions derived from a protein structure data set, and iteratively refined to reproduce the experimental distributions. PaLaCe has been implemented in the MMTK simulation package and can be used for energy minimization, normal mode calculations, and molecular or stochastic dynamics. We present simulations with PaLaCe that test its ability to maintain stable structures for folded proteins, reproduce their dynamic fluctuations, and correctly model large-scale, force-induced conformational changes.
NASA Astrophysics Data System (ADS)
Ervik, Åsmund; Serratos, Guadalupe Jiménez; Müller, Erich A.
2017-03-01
We describe here raaSAFT, a Python code that enables the setup and running of coarse-grained molecular dynamics simulations in a systematic and efficient manner. The code is built on top of the popular HOOMD-blue code, and as such harnesses the computational power of GPUs. The methodology makes use of the SAFT- γ Mie force field, so the resulting coarse grained pair potentials are both closely linked to and consistent with the macroscopic thermodynamic properties of the simulated fluid. In raaSAFT both homonuclear and heteronuclear models are implemented for a wide range of compounds spanning from linear alkanes, to more complicated fluids such as water and alcohols, all the way up to nonionic surfactants and models of asphaltenes and resins. Adding new compounds as well as new features is made straightforward by the modularity of the code. To demonstrate the ease-of-use of raaSAFT, we give a detailed walkthrough of how to simulate liquid-liquid equilibrium of a hydrocarbon with water. We describe in detail how both homonuclear and heteronuclear compounds are implemented. To demonstrate the performance and versatility of raaSAFT, we simulate a large polymer-solvent mixture with 300 polystyrene molecules dissolved in 42 700 molecules of heptane, reproducing the experimentally observed temperature-dependent solubility of polystyrene. For this case we obtain a speedup of more than three orders of magnitude as compared to atomistically-detailed simulations.
Multiscale modeling and simulation for nano/micro materials
NASA Astrophysics Data System (ADS)
Wang, Xianqiao
Continuum description and atomic description used to be two distinct methods in the community of modeling and simulations. Science and technology have become so advanced that our understanding of many physical phenomena involves the concepts of both. So our goal now is to build a bridge to make atoms and continua communicate with each other. Micromorphic theory (MMT) envisions a material body as a continuous collection of deformable particles; each possesses finite size and inner structure. It is considered as the most successful top-down formulation of a two-level continuum model to bridge the gap between the micro level and macro level. Therefore MMT can be expected to unveil many new classes of physical phenomena that fall beyond classical field theories. In this work, the constitutive equations for generalized Micromorphic thermoviscoelastic solid and generalized Micromorphic fluid have been formulated. To enlarge the domain of applicability of MMT, from nano, micro to macro, we take a bottom-up approach to re-derive the generalized atomistic field theory (AFT) comprehensively and completely and establish the relationship between AFT and MMT. Finite element (FE) method is then implemented to pursue the numerical solutions of the governing equations derived in AFT. When the finest mesh is used, i.e., the size of FE mesh is equal to the lattice constant of the material, the computational model becomes identical to molecular dynamics simulation. When a coarse mesh is used, the resulting model is a coarse-grained model, the majority of the degrees of freedom are eliminated and the computational cost is largely reduced. When the coarse mesh and finest mesh exist concurrently, i.e., the finest mesh is used in the critical regions and the coarser mesh is used in the far field, it leads naturally to a concurrent atomistic/continuum model. Atomic scale, coarse-grained scale and concurrent atomistic/continuum simulations have demonstrated the potential capability of AFT to simulate most grand challenging problems in nano/micro physics, and shown that AFT has the advantages of both atomic model and MMT. Therefore, AFT has accomplished the mission to bridge the gap between continuum mechanics and atomic physics.
Thermodynamic forces in coarse-grained simulations
NASA Astrophysics Data System (ADS)
Noid, William
Atomically detailed molecular dynamics simulations have profoundly advanced our understanding of the structure and interactions in soft condensed phases. Nevertheless, despite dramatic advances in the methodology and resources for simulating atomically detailed models, low-resolution coarse-grained (CG) models play a central and rapidly growing role in science. CG models not only empower researchers to investigate phenomena beyond the scope of atomically detailed simulations, but also to precisely tailor models for specific phenomena. However, in contrast to atomically detailed simulations, which evolve on a potential energy surface, CG simulations should evolve on a free energy surface. Therefore, the forces in CG models should reflect the thermodynamic information that has been eliminated from the CG configuration space. As a consequence of these thermodynamic forces, CG models often demonstrate limited transferability and, moreover, rarely provide an accurate description of both structural and thermodynamic properties. In this talk, I will present a framework that clarifies the origin and impact of these thermodynamic forces. Additionally, I will present computational methods for quantifying these forces and incorporating their effects into CG MD simulations. As time allows, I will demonstrate applications of this framework for liquids, polymers, and interfaces. We gratefully acknowledge the support of the National Science Foundation via CHE 1565631.
Das, Payel; Matysiak, Silvina; Clementi, Cecilia
2005-01-01
Coarse-grained models have been extremely valuable in promoting our understanding of protein folding. However, the quantitative accuracy of existing simplified models is strongly hindered either from the complete removal of frustration (as in the widely used Gō-like models) or from the compromise with the minimal frustration principle and/or realistic protein geometry (as in the simple on-lattice models). We present a coarse-grained model that “naturally” incorporates sequence details and energetic frustration into an overall minimally frustrated folding landscape. The model is coupled with an optimization procedure to design the parameters of the protein Hamiltonian to fold into a desired native structure. The application to the study of src-Src homology 3 domain shows that this coarse-grained model contains the main physical-chemical ingredients that are responsible for shaping the folding landscape of this protein. The results illustrate the importance of nonnative interactions and energetic heterogeneity for a quantitative characterization of folding mechanisms. PMID:16006532
NASA Astrophysics Data System (ADS)
He, Yi; Liwo, Adam; Scheraga, Harold A.
2015-12-01
Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.
Folding and stability of helical bundle proteins from coarse-grained models.
Kapoor, Abhijeet; Travesset, Alex
2013-07-01
We develop a coarse-grained model where solvent is considered implicitly, electrostatics are included as short-range interactions, and side-chains are coarse-grained to a single bead. The model depends on three main parameters: hydrophobic, electrostatic, and side-chain hydrogen bond strength. The parameters are determined by considering three level of approximations and characterizing the folding for three selected proteins (training set). Nine additional proteins (containing up to 126 residues) as well as mutated versions (test set) are folded with the given parameters. In all folding simulations, the initial state is a random coil configuration. Besides the native state, some proteins fold into an additional state differing in the topology (structure of the helical bundle). We discuss the stability of the native states, and compare the dynamics of our model to all atom molecular dynamics simulations as well as some general properties on the interactions governing folding dynamics. Copyright © 2013 Wiley Periodicals, Inc.
Stringent and efficient assessment of boson-sampling devices.
Tichy, Malte C; Mayer, Klaus; Buchleitner, Andreas; Mølmer, Klaus
2014-07-11
Boson sampling holds the potential to experimentally falsify the extended Church-Turing thesis. The computational hardness of boson sampling, however, complicates the certification that an experimental device yields correct results in the regime in which it outmatches classical computers. To certify a boson sampler, one needs to verify quantum predictions and rule out models that yield these predictions without true many-boson interference. We show that a semiclassical model for many-boson propagation reproduces coarse-grained observables that are proposed as witnesses of boson sampling. A test based on Fourier matrices is demonstrated to falsify physically plausible alternatives to coherent many-boson propagation.
Learning To Fold Proteins Using Energy Landscape Theory
Schafer, N.P.; Kim, B.L.; Zheng, W.; Wolynes, P.G.
2014-01-01
This review is a tutorial for scientists interested in the problem of protein structure prediction, particularly those interested in using coarse-grained molecular dynamics models that are optimized using lessons learned from the energy landscape theory of protein folding. We also present a review of the results of the AMH/AMC/AMW/AWSEM family of coarse-grained molecular dynamics protein folding models to illustrate the points covered in the first part of the article. Accurate coarse-grained structure prediction models can be used to investigate a wide range of conceptual and mechanistic issues outside of protein structure prediction; specifically, the paper concludes by reviewing how AWSEM has in recent years been able to elucidate questions related to the unusual kinetic behavior of artificially designed proteins, multidomain protein misfolding, and the initial stages of protein aggregation. PMID:25308991
NASA Astrophysics Data System (ADS)
Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Kawaguchi, Kazutomo; Nagao, Hidemi
2018-03-01
We present a simple coarse-grained model with the molecular crowding effect in solvent to investigate the structure and dynamics of protein complexes including association and/or dissociation processes and investigate some physical properties such as the structure and the reaction rate from the viewpoint of the hydrophobic intermolecular interactions of protein complex. In the present coarse-grained model, a function depending upon the density of hydrophobic amino acid residues in a binding area of the complex is introduced, and the function involves the molecular crowding effect for the intermolecular interactions of hydrophobic amino acid residues between proteins. We propose a hydrophobic intermolecular potential energy between proteins by using the density-dependent function. The present coarse-grained model is applied to the complex of cytochrome f and plastocyanin by using the Langevin dynamics simulation to investigate some physical properties such as the complex structure, the electron transfer reaction rate constant from plastocyanin to cytochrome f and so on. We find that for proceeding the electron transfer reaction, the distance between metals in their active sites is necessary within about 18 Å. We discuss some typical complex structures formed in the present simulation in relation to the molecular crowding effect on hydrophobic interactions.
An accurate coarse-grained model for chitosan polysaccharides in aqueous solution.
Tsereteli, Levan; Grafmüller, Andrea
2017-01-01
Computational models can provide detailed information about molecular conformations and interactions in solution, which is currently inaccessible by other means in many cases. Here we describe an efficient and precise coarse-grained model for long polysaccharides in aqueous solution at different physico-chemical conditions such as pH and ionic strength. The Model is carefully constructed based on all-atom simulations of small saccharides and metadynamics sampling of the dihedral angles in the glycosidic links, which represent the most flexible degrees of freedom of the polysaccharides. The model is validated against experimental data for Chitosan molecules in solution with various degree of deacetylation, and is shown to closely reproduce the available experimental data. For long polymers, subtle differences of the free energy maps of the glycosidic links are found to significantly affect the measurable polymer properties. Therefore, for titratable monomers the free energy maps of the corresponding links are updated according to the current charge of the monomers. We then characterize the microscopic and mesoscopic structural properties of large chitosan polysaccharides in solution for a wide range of solvent pH and ionic strength, and investigate the effect of polymer length and degree and pattern of deacetylation on the polymer properties.
An accurate coarse-grained model for chitosan polysaccharides in aqueous solution
Tsereteli, Levan
2017-01-01
Computational models can provide detailed information about molecular conformations and interactions in solution, which is currently inaccessible by other means in many cases. Here we describe an efficient and precise coarse-grained model for long polysaccharides in aqueous solution at different physico-chemical conditions such as pH and ionic strength. The Model is carefully constructed based on all-atom simulations of small saccharides and metadynamics sampling of the dihedral angles in the glycosidic links, which represent the most flexible degrees of freedom of the polysaccharides. The model is validated against experimental data for Chitosan molecules in solution with various degree of deacetylation, and is shown to closely reproduce the available experimental data. For long polymers, subtle differences of the free energy maps of the glycosidic links are found to significantly affect the measurable polymer properties. Therefore, for titratable monomers the free energy maps of the corresponding links are updated according to the current charge of the monomers. We then characterize the microscopic and mesoscopic structural properties of large chitosan polysaccharides in solution for a wide range of solvent pH and ionic strength, and investigate the effect of polymer length and degree and pattern of deacetylation on the polymer properties. PMID:28732036
PSO-Assisted Development of New Transferable Coarse-Grained Water Models.
Bejagam, Karteek K; Singh, Samrendra; An, Yaxin; Berry, Carter; Deshmukh, Sanket A
2018-02-15
We have employed two-to-one mapping scheme to develop three coarse-grained (CG) water models, namely, 1-, 2-, and 3-site CG models. Here, for the first time, particle swarm optimization (PSO) and gradient descent methods were coupled to optimize the force-field parameters of the CG models to reproduce the density, self-diffusion coefficient, and dielectric constant of real water at 300 K. The CG MD simulations of these new models conducted with various timesteps, for different system sizes, and at a range of different temperatures are able to predict the density, self-diffusion coefficient, dielectric constant, surface tension, heat of vaporization, hydration free energy, and isothermal compressibility of real water with excellent accuracy. The 1-site model is ∼3 and ∼4.5 times computationally more efficient than 2- and 3-site models, respectively. To utilize the speed of 1-site model and electrostatic interactions offered by 2- and 3-site models, CG MD simulations of 1:1 combination of 1- and 2-/3-site models were performed at 300 K. These mixture simulations could also predict the properties of real water with good accuracy. Two new CG models of benzene, consisting of beads with and without partial charges, were developed. All three water models showed good capacity to solvate these benzene models.
Munn, M.D.; Waite, I.R.; Larsen, D.P.; Herlihy, A.T.
2009-01-01
The objective of this study was to determine the relative influence of reach-specific habitat variables and geographic location on benthic invertebrate assemblages within six ecoregions across the Western USA. This study included 417 sites from six ecoregions. A total of 301 taxa were collected with the highest richness associated with ecoregions dominated by streams with coarse substrate (19-29 taxa per site). Lowest richness (seven to eight taxa per site) was associated with ecoregions dominated by fine-grain substrate. Principle component analysis (PCA) on reach-scale habitat separated the six ecoregions into those in high-gradient mountainous areas (Coast Range, Cascades, and Southern Rockies) and those in lower-gradient ecoregions (Central Great Plains and Central California Valley). Nonmetric multidimensional scaling (NMS) models performed best in ecoregions dominated by coarse-grain substrate and high taxa richness, along with coarse-grain substrates sites combined from multiple ecoregions regardless of location. In contrast, ecoregions or site combinations dominated by fine-grain substrate had poor model performance (high stress). Four NMS models showed that geographic location (i.e. latitude and longitude) was important for: (1) all ecoregions combined, (2) all sites dominated by coarse-grain sub strate combined, (3) Cascades Ecoregion, and (4) Columbia Ecoregion. Local factors (i.e. substrate or water temperature) seem to be overriding factors controlling invertebrate composition across the West, regardless of geographic location. ?? The Author(s) 2008.
Multiscale approach to the determination of the photoactive yellow protein signaling state ensemble.
A Rohrdanz, Mary; Zheng, Wenwei; Lambeth, Bradley; Vreede, Jocelyne; Clementi, Cecilia
2014-10-01
The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.
Optimization of Analytical Potentials for Coarse-Grained Biopolymer Models.
Mereghetti, Paolo; Maccari, Giuseppe; Spampinato, Giulia Lia Beatrice; Tozzini, Valentina
2016-08-25
The increasing trend in the recent literature on coarse grained (CG) models testifies their impact in the study of complex systems. However, the CG model landscape is variegated: even considering a given resolution level, the force fields are very heterogeneous and optimized with very different parametrization procedures. Along the road for standardization of CG models for biopolymers, here we describe a strategy to aid building and optimization of statistics based analytical force fields and its implementation in the software package AsParaGS (Assisted Parameterization platform for coarse Grained modelS). Our method is based on the use and optimization of analytical potentials, optimized by targeting internal variables statistical distributions by means of the combination of different algorithms (i.e., relative entropy driven stochastic exploration of the parameter space and iterative Boltzmann inversion). This allows designing a custom model that endows the force field terms with a physically sound meaning. Furthermore, the level of transferability and accuracy can be tuned through the choice of statistical data set composition. The method-illustrated by means of applications to helical polypeptides-also involves the analysis of two and three variable distributions, and allows handling issues related to the FF term correlations. AsParaGS is interfaced with general-purpose molecular dynamics codes and currently implements the "minimalist" subclass of CG models (i.e., one bead per amino acid, Cα based). Extensions to nucleic acids and different levels of coarse graining are in the course.
Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.
2013-01-01
Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887
NASA Astrophysics Data System (ADS)
Fitrasari, Dian; Purqon, Acep
2017-07-01
Proteins play important roles in body metabolism. However, to reveal hydration effects, it is cost computing especially for all-atom calculation. Coarse-grained method is one of potential solution to reduce the calculation and computable in longer timescale. Furthermore, the protein of Azurin is interesting protein and potentially applicable to cancer medicine for the stability property reason. We investigate the effects of hydration on Azurin, the conformation and the stabilities. Furthermore, we analyze the free-energy of the conformation system to find the favorable structure using free energy perturbation (FEP) calculation. Our calculation results show that free energy value of azurin is -136.9 kJ/mol. It shows a good agreement with experimental results with relative error index remained at 0.07%.
Rathnayaka, C M; Karunasena, H C P; Senadeera, W; Gu, Y T
2018-03-14
Numerical modelling has gained popularity in many science and engineering streams due to the economic feasibility and advanced analytical features compared to conventional experimental and theoretical models. Food drying is one of the areas where numerical modelling is increasingly applied to improve drying process performance and product quality. This investigation applies a three dimensional (3-D) Smoothed Particle Hydrodynamics (SPH) and Coarse-Grained (CG) numerical approach to predict the morphological changes of different categories of food-plant cells such as apple, grape, potato and carrot during drying. To validate the model predictions, experimental findings from in-house experimental procedures (for apple) and sources of literature (for grape, potato and carrot) have been utilised. The subsequent comaprison indicate that the model predictions demonstrate a reasonable agreement with the experimental findings, both qualitatively and quantitatively. In this numerical model, a higher computational accuracy has been maintained by limiting the consistency error below 1% for all four cell types. The proposed meshfree-based approach is well-equipped to predict the morphological changes of plant cellular structure over a wide range of moisture contents (10% to 100% dry basis). Compared to the previous 2-D meshfree-based models developed for plant cell drying, the proposed model can draw more useful insights on the morphological behaviour due to the 3-D nature of the model. In addition, the proposed computational modelling approach has a high potential to be used as a comprehensive tool in many other tissue morphology related investigations.
Entanglement renormalization and gauge symmetry
NASA Astrophysics Data System (ADS)
Tagliacozzo, L.; Vidal, G.
2011-03-01
A lattice gauge theory is described by a redundantly large vector space that is subject to local constraints and can be regarded as the low-energy limit of an extended lattice model with a local symmetry. We propose a numerical coarse-graining scheme to produce low-energy, effective descriptions of lattice models with a local symmetry such that the local symmetry is exactly preserved during coarse-graining. Our approach results in a variational ansatz for the ground state(s) and low-energy excitations of such models and, by extension, of lattice gauge theories. This ansatz incorporates the local symmetry in its structure and exploits it to obtain a significant reduction of computational costs. We test the approach in the context of a Z2 lattice gauge theory formulated as the low-energy theory of a specific regime of the toric code with a magnetic field, for lattices with up to 16×16 sites (162×2=512 spins) on a torus. We reproduce the well-known ground-state phase diagram of the model, consisting of a deconfined and spin-polarized phases separated by a continuous quantum phase transition, and obtain accurate estimates of energy gaps, ground-state fidelities, Wilson loops, and several other quantities.
NASA Astrophysics Data System (ADS)
Spiriti, Justin; Zuckerman, Daniel M.
2015-12-01
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.
Path-space variational inference for non-equilibrium coarse-grained systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harmandaris, Vagelis, E-mail: harman@uoc.gr; Institute of Applied and Computational Mathematics; Kalligiannaki, Evangelia, E-mail: ekalligian@tem.uoc.gr
In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirelymore » data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.« less
Software Testing and Verification in Climate Model Development
NASA Technical Reports Server (NTRS)
Clune, Thomas L.; Rood, RIchard B.
2011-01-01
Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.
Structure and thermodynamics of core-softened models for alcohols
DOE Office of Scientific and Technical Information (OSTI.GOV)
Munaò, Gianmarco, E-mail: gmunao@unime.it; Urbic, Tomaz
The phase behavior and the fluid structure of coarse-grain models for alcohols are studied by means of reference interaction site model (RISM) theory and Monte Carlo simulations. Specifically, we model ethanol and 1-propanol as linear rigid chains constituted by three (trimers) and four (tetramers) partially fused spheres, respectively. Thermodynamic properties of these models are examined in the RISM context, by employing closed formulæ for the calculation of free energy and pressure. Gas-liquid coexistence curves for trimers and tetramers are reported and compared with already existing data for a dimer model of methanol. Critical temperatures slightly increase with the number ofmore » CH{sub 2} groups in the chain, while critical pressures and densities decrease. Such a behavior qualitatively reproduces the trend observed in experiments on methanol, ethanol, and 1-propanol and suggests that our coarse-grain models, despite their simplicity, can reproduce the essential features of the phase behavior of such alcohols. The fluid structure of these models is investigated by computing radial distribution function g{sub ij}(r) and static structure factor S{sub ij}(k); the latter shows the presence of a low−k peak at intermediate-high packing fractions and low temperatures, suggesting the presence of aggregates for both trimers and tetramers.« less
An implicit divalent counterion force field for RNA molecular dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Henke, Paul S.; Mak, Chi H., E-mail: cmak@usc.edu; Center of Applied Mathematical Sciences, University of Southern California, Los Angeles, California 90089
How to properly account for polyvalent counterions in a molecular dynamics simulation of polyelectrolytes such as nucleic acids remains an open question. Not only do counterions such as Mg{sup 2+} screen electrostatic interactions, they also produce attractive intrachain interactions that stabilize secondary and tertiary structures. Here, we show how a simple force field derived from a recently reported implicit counterion model can be integrated into a molecular dynamics simulation for RNAs to realistically reproduce key structural details of both single-stranded and base-paired RNA constructs. This divalent counterion model is computationally efficient. It works with existing atomistic force fields, or coarse-grainedmore » models may be tuned to work with it. We provide optimized parameters for a coarse-grained RNA model that takes advantage of this new counterion force field. Using the new model, we illustrate how the structural flexibility of RNA two-way junctions is modified under different salt conditions.« less
Chen, Tao; Chan, Hue Sun
2014-04-14
Local-nonlocal coupling is an organizational principle in protein folding. It envisions a cooperative energetic interplay between local conformational preferences and favorable nonlocal contacts. Previous theoretical studies by our group showed that two classes of native-centric coarse-grained models can capture the experimentally observed high degrees of protein folding cooperativity and diversity in folding rates. These models either embody an explicit local-nonlocal coupling mechanism or incorporate desolvation barriers in the models' pairwise interactions. Here a conceptual connection is made between these two paradigmatic coarse-grained interaction schemes by showing that desolvation barriers enhance local-nonlocal coupling. Furthermore, we find that a class of coarse-grained protein models with a single-site representation of sidechains also increases local-nonlocal coupling relative to mainchain models without sidechains. Enhanced local-nonlocal coupling generally leads to higher folding cooperativity and chevron plots with more linear folding arms. For the sidechain models studied, the chevron plot simulated with entirely native-centric intrachain interactions behaves very similarly to the corresponding chevron plots simulated with interactions that are partly modulated by sequence- and denaturant-dependent transfer free energies. In these essentially native-centric models, the mild chevron rollovers in the simulated folding arm are caused by occasionally populated intermediates as well as the movement of the unfolded and putative folding transition states. The strength and limitation of the models are analyzed by comparison with experiment. New formulations of sidechain models that may provide a physical account for nonnative interactions are also explored.
Molecular Simulation Studies of Covalently and Ionically Grafted Nanoparticles
NASA Astrophysics Data System (ADS)
Hong, Bingbing
Solvent-free covalently- or ionically-grafted nanoparticles (CGNs and IGNs) are a new class of organic-inorganic hybrid composite materials exhibiting fluid-like behaviors around room temperature. With similar structures to prior systems, e.g. nanocomposites, neutral or charged colloids, ionic liquids, etc, CGNs and IGNs inherit the functionality of inorganic nanopariticles, the facile processibility of polymers, as well as conductivity and nonvolatility from their constituent materials. In spite of the extensive prior experimental research having covered synthesis and measurements of thermal and dynamic properties, little progress in understanding of these new materials at the molecular level has been achieved, because of the lack of simulation work in this new area. Atomistic and coarse-grained molecular dynamics simulations have been performed in this thesis to investigate the thermodynamics, structure, and dynamics of these systems and to seek predictive methods predictable for their properties. Starting from poly(ethylene oxide) oligomers (PEO) melts, we established atomistic models based on united-atom representations of methylene. The Green-Kubo and Einstein-Helfand formulas were used to calculate the transport properties. The simulations generate densities, viscosities, diffusivities, in good agreement with experimental data. The chain-length dependence of the transport properties suggests that neither Rouse nor reptation models are applicable in the short-chain regime investigated. Coupled with thermodynamic integration methods, the models give good predictions of pressure-composition-density relations for CO 2 + PEO oligomers. Water effects on the Henry's constant of CO 2 in PEO have also been investigated. The dependence of the calculated Henry's constants on the weight percentage of water falls on a temperature-dependent master curve, irrespective of PEO chain length. CGNs are modeled by the inclusion of solid-sphere nanoparticles into the atomistic oligomers. The calculated viscosities from Green-Kubo relationships and temperature extrapolation are of the same order of magnitude as experimental values, but show a smaller activation energy relative to real CGNs systems. Grafted systems have higher viscosities, smaller diffusion coefficients, and slower chain dynamics than the ungrafted counterparts - nanocomposites - at high temperatures. At lower temperatures, grafted systems exhibit faster dynamics for both nanoparticles and chains relative to ungrafted systems, because of lower aggregation of nanoparticles and enhanced correlations between nanoparticles and chains. This agrees with the experimental observation that the new materials have liquid-like behavior in the absence of a solvent. To lower the simulated temperatures into the experimental range, we established a coarse-grained CGNs model by matching structural distribution functions to atomistic simulation data. In contrast with linear polymer systems, for which coarse-graining always accelerate dynamics, coarse-graining of grafted nanoparticles can either accelerate or slowdown the core motions, depending on the length of the grafted chains. This can be qualitatively predicted by a simple transition-state theory. Similar atomistic models to CGNs were developed for IGNs, with ammonium counterions described by an explicit-hydrogen way; these were in turn compared with "generic" coarse-grained IGNs. The elimination of chemical details in the coarse-grained models does not bring in qualitative changes to the radial distribution functions and diffusion of atomistic IGNs, but saves considerable simulation resources and make simulations near room temperatures affordable. The chain counterions in both atomistic and coarse-grained models are mobile, moving from site to site and from nanoparticle to nanoparticle. At the same temperature and the same core volume fractions, the nanoparticle diffusivities in coarse-grained IGNs are slower by a factor ten than the cores of CGNs. The coarse-grained IGNs models are later used to investigate the system dynamics through analysis of the dependence on temperature and structural parameters of the transport properties (self-diffusion coefficients, viscosities and conductivities). Further, migration kinetics of oligomeric counterions is analyzed in a manner analogous to unimer exchange between micellar aggregates. The counterion migrations follow the "double-core" mechanism and are kinetically controlled by neighboring-core collisions. (Abstract shortened by UMI.)
Refining the treatment of membrane proteins by coarse-grained models.
Vorobyov, Igor; Kim, Ilsoo; Chu, Zhen T; Warshel, Arieh
2016-01-01
Obtaining a quantitative description of the membrane proteins stability is crucial for understanding many biological processes. However the advance in this direction has remained a major challenge for both experimental studies and molecular modeling. One of the possible directions is the use of coarse-grained models but such models must be carefully calibrated and validated. Here we use a recent progress in benchmark studies on the energetics of amino acid residue and peptide membrane insertion and membrane protein stability in refining our previously developed coarse-grained model (Vicatos et al., Proteins 2014;82:1168). Our refined model parameters were fitted and/or tested to reproduce water/membrane partitioning energetics of amino acid side chains and a couple of model peptides. This new model provides a reasonable agreement with experiment for absolute folding free energies of several β-barrel membrane proteins as well as effects of point mutations on a relative stability for one of those proteins, OmpLA. The consideration and ranking of different rotameric states for a mutated residue was found to be essential to achieve satisfactory agreement with the reference data. © 2015 Wiley Periodicals, Inc.
Coarse-grained hydrodynamics from correlation functions
NASA Astrophysics Data System (ADS)
Palmer, Bruce
2018-02-01
This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.
SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.
Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M
2016-04-20
RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
NASA Astrophysics Data System (ADS)
Erez, Mattan; Dally, William J.
Stream processors, like other multi core architectures partition their functional units and storage into multiple processing elements. In contrast to typical architectures, which contain symmetric general-purpose cores and a cache hierarchy, stream processors have a significantly leaner design. Stream processors are specifically designed for the stream execution model, in which applications have large amounts of explicit parallel computation, structured and predictable control, and memory accesses that can be performed at a coarse granularity. Applications in the streaming model are expressed in a gather-compute-scatter form, yielding programs with explicit control over transferring data to and from on-chip memory. Relying on these characteristics, which are common to many media processing and scientific computing applications, stream architectures redefine the boundary between software and hardware responsibilities with software bearing much of the complexity required to manage concurrency, locality, and latency tolerance. Thus, stream processors have minimal control consisting of fetching medium- and coarse-grained instructions and executing them directly on the many ALUs. Moreover, the on-chip storage hierarchy of stream processors is under explicit software control, as is all communication, eliminating the need for complex reactive hardware mechanisms.
Packing of sidechains in low-resolution models for proteins.
Keskin, O; Bahar, I
1998-01-01
Atomic level rotamer libraries for sidechains in proteins have been proposed by several groups. Conformations of side groups in coarse-grained models, on the other hand, have not yet been analyzed, although low resolution approaches are the only efficient way to explore global structural features. A residue-specific backbone-dependent library for sidechain isomers, compatible with a coarse-grained model, is proposed. The isomeric states are utilized in packing sidechains of known backbone structures. Sidechain positions are predicted with a root-mean-square deviation (r.m.s.d.) of 2.40 A with respect to crystal structure for 50 test proteins. The rmsd for core residues is 1.60 A and decreases to 1.35 A when conformational correlations and directional effects in inter-residue couplings are considered. An automated method for assigning sidechain positions in coarse-grained model proteins is proposed and made available on the internet; the method accounts satisfactorily for sidechain packing, particularly in the core.
Ramanan, B; Holmes, W M; Sloan, W T; Phoenix, V R
2012-01-03
Quantifying nanoparticle (NP) transport inside saturated porous geological media is imperative for understanding their fate in a range of natural and engineered water systems. While most studies focus upon finer grained systems representative of soils and aquifers, very few examine coarse-grained systems representative of riverbeds and gravel based sustainable urban drainage systems. In this study, we investigated the potential of magnetic resonance imaging (MRI) to image transport behaviors of nanoparticles (NPs) through a saturated coarse-grained system. MRI successfully imaged the transport of superparamagnetic NPs, inside a porous column composed of quartz gravel using T(2)-weighted images. A calibration protocol was then used to convert T(2)-weighted images into spatially resolved quantitative concentration maps of NPs at different time intervals. Averaged concentration profiles of NPs clearly illustrates that transport of a positively charged amine-functionalized NP within the column was slower compared to that of a negatively charged carboxyl-functionalized NP, due to electrostatic attraction between positively charged NP and negatively charged quartz grains. Concentration profiles of NPs were then compared with those of a convection-dispersion model to estimate coefficients of dispersivity and retardation. For the amine functionalized NPs (which exhibited inhibited transport), a better model fit was obtained when permanent attachment (deposition) was incorporated into the model as opposed to nonpermanent attachment (retardation). This technology can be used to further explore transport processes of NPs inside coarse-grained porous media, either by using the wide range of commercially available (super)paramagnetically tagged NPs or by using custom-made tagged NPs.
Multi-scale coarse-graining of non-conservative interactions in molecular liquids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Izvekov, Sergei, E-mail: sergiy.izvyekov.civ@mail.mil; Rice, Betsy M.
2014-03-14
A new bottom-up procedure for constructing non-conservative (dissipative and stochastic) interactions for dissipative particle dynamics (DPD) models is described and applied to perform hierarchical coarse-graining of a polar molecular liquid (nitromethane). The distant-dependent radial and shear frictions in functional-free form are derived consistently with a chosen form for conservative interactions by matching two-body force-velocity and three-body velocity-velocity correlations along the microscopic trajectories of the centroids of Voronoi cells (clusters), which represent the dissipative particles within the DPD description. The Voronoi tessellation is achieved by application of the K-means clustering algorithm at regular time intervals. Consistently with a notion of many-bodymore » DPD, the conservative interactions are determined through the multi-scale coarse-graining (MS-CG) method, which naturally implements a pairwise decomposition of the microscopic free energy. A hierarchy of MS-CG/DPD models starting with one molecule per Voronoi cell and up to 64 molecules per cell is derived. The radial contribution to the friction appears to be dominant for all models. As the Voronoi cell sizes increase, the dissipative forces rapidly become confined to the first coordination shell. For Voronoi cells of two and more molecules the time dependence of the velocity autocorrelation function becomes monotonic and well reproduced by the respective MS-CG/DPD models. A comparative analysis of force and velocity correlations in the atomistic and CG ensembles indicates Markovian behavior with as low as two molecules per dissipative particle. The models with one and two molecules per Voronoi cell yield transport properties (diffusion and shear viscosity) that are in good agreement with the atomistic data. The coarser models produce slower dynamics that can be appreciably attributed to unaccounted dissipation introduced by regular Voronoi re-partitioning as well as by larger numerical errors in mapping out the dissipative forces. The framework presented herein can be used to develop computational models of real liquids which are capable of bridging the atomistic and mesoscopic scales.« less
Coarse-graining and self-dissimilarity of complex networks
NASA Astrophysics Data System (ADS)
Itzkovitz, Shalev; Levitt, Reuven; Kashtan, Nadav; Milo, Ron; Itzkovitz, Michael; Alon, Uri
2005-01-01
Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units as connectivity patterns which can serve as the nodes of a coarse-grained network and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit module made of many gates. We apply our approach also to a mammalian protein signal-transduction network, to find a simplified coarse-grained network with three main signaling channels that resemble multi-layered perceptrons made of cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are “self-dissimilar,” with different network motifs at each level. The present approach may be used to simplify a variety of directed and nondirected, natural and designed networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Wenjun, E-mail: wjzheng@buffalo.edu; Glenn, Paul
2015-01-21
The Bacteriophage T4 Lysozyme (T4L) is a prototype modular protein comprised of an N-terminal and a C-domain domain, which was extensively studied to understand the folding/unfolding mechanism of modular proteins. To offer detailed structural and dynamic insights to the folded-state stability and the mechanical unfolding behaviors of T4L, we have performed extensive equilibrium and steered molecular dynamics simulations of both the wild-type (WT) and a circular permutation (CP) variant of T4L using all-atom and coarse-grained force fields. Our all-atom and coarse-grained simulations of the folded state have consistently found greater stability of the C-domain than the N-domain in isolation, whichmore » is in agreement with past thermostatic studies of T4L. While the all-atom simulation cannot fully explain the mechanical unfolding behaviors of the WT and the CP variant observed in an optical tweezers study, the coarse-grained simulations based on the Go model or a modified elastic network model (mENM) are in qualitative agreement with the experimental finding of greater unfolding cooperativity in the WT than the CP variant. Interestingly, the two coarse-grained models predict different structural mechanisms for the observed change in cooperativity between the WT and the CP variant—while the Go model predicts minor modification of the unfolding pathways by circular permutation (i.e., preserving the general order that the N-domain unfolds before the C-domain), the mENM predicts a dramatic change in unfolding pathways (e.g., different order of N/C-domain unfolding in the WT and the CP variant). Based on our simulations, we have analyzed the limitations of and the key differences between these models and offered testable predictions for future experiments to resolve the structural mechanism for cooperative folding/unfolding of T4L.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pulupa, Joan; Rachh, Manas; Tomasini, Michael D.
The phenylalanine-glycine–repeat nucleoporins (FG-Nups), which occupy the lumen of the nuclear pore complex (NPC), are critical for transport between the nucleus and cytosol. Although NPCs differ in composition across species, they are largely conserved in organization and function. Transport through the pore is on the millisecond timescale. Here, to explore the dynamics of nucleoporins on this timescale, we use coarse-grained computational simulations. These simulations generate predictions that can be experimentally tested to distinguish between proposed mechanisms of transport. Our model reflects the conserved structure of the NPC, in which FG-Nup filaments extend into the lumen and anchor along the interiormore » of the channel. The lengths of the filaments in our model are based on the known characteristics of yeast FG-Nups. The FG-repeat sites also bind to each other, and we vary this association over several orders of magnitude and run 100-ms simulations for each value. The autocorrelation functions of the orientation of the simulated FG-Nups are compared with in vivo anisotropy data. We observe that FG-Nups reptate back and forth through the NPC at timescales commensurate with experimental measurements of the speed of cargo transport through the NPC. Our results are consistent with models of transport where FG-Nup filaments are free to move across the central channel of the NPC, possibly informing how cargo might transverse the NPC.« less
Pulupa, Joan; Rachh, Manas; Tomasini, Michael D.; ...
2017-09-08
The phenylalanine-glycine–repeat nucleoporins (FG-Nups), which occupy the lumen of the nuclear pore complex (NPC), are critical for transport between the nucleus and cytosol. Although NPCs differ in composition across species, they are largely conserved in organization and function. Transport through the pore is on the millisecond timescale. Here, to explore the dynamics of nucleoporins on this timescale, we use coarse-grained computational simulations. These simulations generate predictions that can be experimentally tested to distinguish between proposed mechanisms of transport. Our model reflects the conserved structure of the NPC, in which FG-Nup filaments extend into the lumen and anchor along the interiormore » of the channel. The lengths of the filaments in our model are based on the known characteristics of yeast FG-Nups. The FG-repeat sites also bind to each other, and we vary this association over several orders of magnitude and run 100-ms simulations for each value. The autocorrelation functions of the orientation of the simulated FG-Nups are compared with in vivo anisotropy data. We observe that FG-Nups reptate back and forth through the NPC at timescales commensurate with experimental measurements of the speed of cargo transport through the NPC. Our results are consistent with models of transport where FG-Nup filaments are free to move across the central channel of the NPC, possibly informing how cargo might transverse the NPC.« less
NASA Astrophysics Data System (ADS)
Menichetti, Roberto; Kanekal, Kiran H.; Kremer, Kurt; Bereau, Tristan
2017-09-01
The partitioning of small molecules in cell membranes—a key parameter for pharmaceutical applications—typically relies on experimentally available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics-based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400 000 compounds. The potential of mean force hereby becomes an easily accessible quantity—already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.
Particle-based membrane model for mesoscopic simulation of cellular dynamics
NASA Astrophysics Data System (ADS)
Sadeghi, Mohsen; Weikl, Thomas R.; Noé, Frank
2018-01-01
We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on interacting and reacting particles, each representing a coarse patch of a lipid monolayer. Particle interactions include nearest-neighbor bond-stretching and angle-bending and are parameterized so as to reproduce the local membrane mechanics given by the Helfrich energy density over a range of relevant curvatures. In-plane fluidity is implemented with Monte Carlo bond-flipping moves. The physical accuracy of the model is verified by five tests: (i) Power spectrum analysis of equilibrium thermal undulations is used to verify that the particle-based representation correctly captures the dynamics predicted by the continuum model of fluid membranes. (ii) It is verified that the input bending stiffness, against which the potential parameters are optimized, is accurately recovered. (iii) Isothermal area compressibility modulus of the membrane is calculated and is shown to be tunable to reproduce available values for different lipid bilayers, independent of the bending rigidity. (iv) Simulation of two-dimensional shear flow under a gravity force is employed to measure the effective in-plane viscosity of the membrane model and show the possibility of modeling membranes with specified viscosities. (v) Interaction of the bilayer membrane with a spherical nanoparticle is modeled as a test case for large membrane deformations and budding involved in cellular processes such as endocytosis. The results are shown to coincide well with the predicted behavior of continuum models, and the membrane model successfully mimics the expected budding behavior. We expect our model to be of high practical usability for ultra coarse-grained molecular dynamics or particle-based reaction-diffusion simulations of biological systems.
Santos, Andrés; López de Haro, Mariano; Fiumara, Giacomo; Saija, Franz
2015-06-14
The relevance of neglecting three- and four-body interactions in the coarse-grained version of the Asakura-Oosawa model is examined. A mapping between the first few virial coefficients of the binary nonadditive hard-sphere mixture representative of this model and those arising from the coarse-grained (pairwise) depletion potential approximation allows for a quantitative evaluation of the effect of such interactions. This turns out to be especially important for large size ratios and large reservoir polymer packing fractions.
Coarse-grained protein-protein stiffnesses and dynamics from all-atom simulations
NASA Astrophysics Data System (ADS)
Hicks, Stephen D.; Henley, C. L.
2010-03-01
Large protein assemblies, such as virus capsids, may be coarse-grained as a set of rigid units linked by generalized (rotational and stretching) harmonic springs. We present an ab initio method to obtain the elastic parameters and overdamped dynamics for these springs from all-atom molecular-dynamics simulations of one pair of units at a time. The computed relaxation times of this pair give a consistency check for the simulation, and we can also find the corrective force needed to null systematic drifts. As a first application we predict the stiffness of an HIV capsid layer and the relaxation time for its breathing mode.
Coarse Graining to Investigate Membrane Induced Peptide Folding of Anticancer Peptides
NASA Astrophysics Data System (ADS)
Ganesan, Sai; Xu, Hongcheng; Matysiak, Silvina
Information about membrane induced peptide folding mechanisms using all-atom molecular dynamics simulations is a challenge due to time and length scale issues.We recently developed a low resolution Water Explicit Polarizable PROtein coarse-grained Model by adding oppositely charged dummy particles inside protein backbone beads.These two dummy particles represent a fluctuating dipole,thus introducing structural polarization into the coarse-grained model.With this model,we were able to achieve significant α- β secondary structure content de novo,without any added bias.We extended the model to zwitterionic and anionic lipids,by adding oppositely charged dummy particles inside polar beads, to capture the ability of the head group region to form hydrogen bonds.We use zwitterionic POPC and anionic POPS as our model lipids, and a cationic anticancer peptide,SVS1,as our model peptide.We have characterized the driving forces for SVS1 folding on lipid bilayers with varying anionic and zwitterionic lipid compositions.Based on our results, dipolar interactions between peptide backbone and lipid head groups contribute to stabilize folded conformations.Cooperativity in folding is induced by both intra peptide and membrane-peptide interaction.
Hybrid parallel computing architecture for multiview phase shifting
NASA Astrophysics Data System (ADS)
Zhong, Kai; Li, Zhongwei; Zhou, Xiaohui; Shi, Yusheng; Wang, Congjun
2014-11-01
The multiview phase-shifting method shows its powerful capability in achieving high resolution three-dimensional (3-D) shape measurement. Unfortunately, this ability results in very high computation costs and 3-D computations have to be processed offline. To realize real-time 3-D shape measurement, a hybrid parallel computing architecture is proposed for multiview phase shifting. In this architecture, the central processing unit can co-operate with the graphic processing unit (GPU) to achieve hybrid parallel computing. The high computation cost procedures, including lens distortion rectification, phase computation, correspondence, and 3-D reconstruction, are implemented in GPU, and a three-layer kernel function model is designed to simultaneously realize coarse-grained and fine-grained paralleling computing. Experimental results verify that the developed system can perform 50 fps (frame per second) real-time 3-D measurement with 260 K 3-D points per frame. A speedup of up to 180 times is obtained for the performance of the proposed technique using a NVIDIA GT560Ti graphics card rather than a sequential C in a 3.4 GHZ Inter Core i7 3770.
A dynamic subgrid scale model for Large Eddy Simulations based on the Mori-Zwanzig formalism
NASA Astrophysics Data System (ADS)
Parish, Eric J.; Duraisamy, Karthik
2017-11-01
The development of reduced models for complex multiscale problems remains one of the principal challenges in computational physics. The optimal prediction framework of Chorin et al. [1], which is a reformulation of the Mori-Zwanzig (M-Z) formalism of non-equilibrium statistical mechanics, provides a framework for the development of mathematically-derived reduced models of dynamical systems. Several promising models have emerged from the optimal prediction community and have found application in molecular dynamics and turbulent flows. In this work, a new M-Z-based closure model that addresses some of the deficiencies of existing methods is developed. The model is constructed by exploiting similarities between two levels of coarse-graining via the Germano identity of fluid mechanics and by assuming that memory effects have a finite temporal support. The appeal of the proposed model, which will be referred to as the 'dynamic-MZ-τ' model, is that it is parameter-free and has a structural form imposed by the mathematics of the coarse-graining process (rather than the phenomenological assumptions made by the modeler, such as in classical subgrid scale models). To promote the applicability of M-Z models in general, two procedures are presented to compute the resulting model form, helping to bypass the tedious error-prone algebra that has proven to be a hindrance to the construction of M-Z-based models for complex dynamical systems. While the new formulation is applicable to the solution of general partial differential equations, demonstrations are presented in the context of Large Eddy Simulation closures for the Burgers equation, decaying homogeneous turbulence, and turbulent channel flow. The performance of the model and validity of the underlying assumptions are investigated in detail.
Workload Characterization of CFD Applications Using Partial Differential Equation Solvers
NASA Technical Reports Server (NTRS)
Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)
1998-01-01
Workload characterization is used for modeling and evaluating of computing systems at different levels of detail. We present workload characterization for a class of Computational Fluid Dynamics (CFD) applications that solve Partial Differential Equations (PDEs). This workload characterization focuses on three high performance computing platforms: SGI Origin2000, EBM SP-2, a cluster of Intel Pentium Pro bases PCs. We execute extensive measurement-based experiments on these platforms to gather statistics of system resource usage, which results in workload characterization. Our workload characterization approach yields a coarse-grain resource utilization behavior that is being applied for performance modeling and evaluation of distributed high performance metacomputing systems. In addition, this study enhances our understanding of interactions between PDE solver workloads and high performance computing platforms and is useful for tuning these applications.
Wei, Dongshan; Wang, Feng
2010-08-28
The damped-short-range-interaction (DSRI) method is proposed to mimic coarse-grained simulations by propagating an atomistic scale system on a smoothed potential energy surface. The DSRI method has the benefit of enhanced sampling provided by a typical coarse-grained simulation without the need to perform coarse-graining. Our method was used to simulate liquid water, alanine dipeptide folding, and the self-assembly of dimyristoylphosphatidylcholine lipid. In each case, our method appreciably accelerated the dynamics without significantly changing the free energy surface. Additional insights from DSRI simulations and the promise of coupling our DSRI method with Hamiltonian replica-exchange molecular dynamics are discussed.
NASA Astrophysics Data System (ADS)
Wei, Dongshan; Wang, Feng
2010-08-01
The damped-short-range-interaction (DSRI) method is proposed to mimic coarse-grained simulations by propagating an atomistic scale system on a smoothed potential energy surface. The DSRI method has the benefit of enhanced sampling provided by a typical coarse-grained simulation without the need to perform coarse-graining. Our method was used to simulate liquid water, alanine dipeptide folding, and the self-assembly of dimyristoylphosphatidylcholine lipid. In each case, our method appreciably accelerated the dynamics without significantly changing the free energy surface. Additional insights from DSRI simulations and the promise of coupling our DSRI method with Hamiltonian replica-exchange molecular dynamics are discussed.
Sterpone, Fabio; Melchionna, Simone; Tuffery, Pierre; Pasquali, Samuela; Mousseau, Normand; Cragnolini, Tristan; Chebaro, Yassmine; Saint-Pierre, Jean-Francois; Kalimeri, Maria; Barducci, Alessandro; Laurin, Yohan; Tek, Alex; Baaden, Marc; Nguyen, Phuong Hoang; Derreumaux, Philippe
2015-01-01
The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows studying single protein properties, DNA/RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the on-going developments. PMID:24759934
NASA Astrophysics Data System (ADS)
Wang, Jinxiang; Yang, Rui; Jiang, Li; Wang, Xiaoxu; Zhou, Nan
2013-11-01
Nanocrystalline (NC) copper was fabricated by severe plastic deformation of coarse-grained copper at a high strain rate under explosive loading. The feasibility of grain refinement under different explosive loading and the influence of overall temperature rise on grain refinement under impact compression were studied in this paper. The calculation model for the macroscopic temperature rise was established according to the adiabatic shock compression theory. The calculation model for coarse-grained copper was established by the Voronoi method and the microscopic temperature rise resulted from severe plastic deformation of grains was calculated by ANSYS/ls-dyna finite element software. The results show that it is feasible to fabricate NC copper by explosively dynamic deformation of coarse-grained copper and the average grain size of the NC copper can be controlled between 200˜400 nm. The whole temperature rise would increase with the increasing explosive thickness. Ammonium nitrate fuel oil explosive was adopted and five different thicknesses of the explosive, which are 20 mm, 25 mm, 30 mm, 35 mm, 45 mm, respectively, with the same diameter using 20 mm to the fly plate were adopted. The maximum macro and micro temperature rise is up to 532.4 K, 143.4 K, respectively, which has no great effect on grain refinement due to the whole temperature rise that is lower than grain growth temperature according to the high pressure melting theory.
Holliday Junction Thermodynamics and Structure: Coarse-Grained Simulations and Experiments
NASA Astrophysics Data System (ADS)
Wang, Wujie; Nocka, Laura M.; Wiemann, Brianne Z.; Hinckley, Daniel M.; Mukerji, Ishita; Starr, Francis W.
2016-03-01
Holliday junctions play a central role in genetic recombination, DNA repair and other cellular processes. We combine simulations and experiments to evaluate the ability of the 3SPN.2 model, a coarse-grained representation designed to mimic B-DNA, to predict the properties of DNA Holliday junctions. The model reproduces many experimentally determined aspects of junction structure and stability, including the temperature dependence of melting on salt concentration, the bias between open and stacked conformations, the relative populations of conformers at high salt concentration, and the inter-duplex angle (IDA) between arms. We also obtain a close correspondence between the junction structure evaluated by all-atom and coarse-grained simulations. We predict that, for salt concentrations at physiological and higher levels, the populations of the stacked conformers are independent of salt concentration, and directly observe proposed tetrahedral intermediate sub-states implicated in conformational transitions. Our findings demonstrate that the 3SPN.2 model captures junction properties that are inaccessible to all-atom studies, opening the possibility to simulate complex aspects of junction behavior.
On the Effect of Sphere-Overlap on Super Coarse-Grained Models of Protein Assemblies
NASA Astrophysics Data System (ADS)
Degiacomi, Matteo T.
2018-05-01
Ion mobility mass spectrometry (IM/MS) can provide structural information on intact protein complexes. Such data, including connectivity and collision cross sections (CCS) of assemblies' subunits, can in turn be used as a guide to produce representative super coarse-grained models. These models are constituted by ensembles of overlapping spheres, each representing a protein subunit. A model is considered plausible if the CCS and sphere-overlap levels of its subunits fall within predetermined confidence intervals. While the first is determined by experimental error, the latter is based on a statistical analysis on a range of protein dimers. Here, we first propose a new expression to describe the overlap between two spheres. Then we analyze the effect of specific overlap cutoff choices on the precision and accuracy of super coarse-grained models. Finally, we propose a method to determine overlap cutoff levels on a per-case scenario, based on collected CCS data, and show that it can be applied to the characterization of the assembly topology of symmetrical homo-multimers. [Figure not available: see fulltext.
Parallel Calculation of Sensitivity Derivatives for Aircraft Design using Automatic Differentiation
NASA Technical Reports Server (NTRS)
Bischof, c. H.; Green, L. L.; Haigler, K. J.; Knauff, T. L., Jr.
1994-01-01
Sensitivity derivative (SD) calculation via automatic differentiation (AD) typical of that required for the aerodynamic design of a transport-type aircraft is considered. Two ways of computing SD via code generated by the ADIFOR automatic differentiation tool are compared for efficiency and applicability to problems involving large numbers of design variables. A vector implementation on a Cray Y-MP computer is compared with a coarse-grained parallel implementation on an IBM SP1 computer, employing a Fortran M wrapper. The SD are computed for a swept transport wing in turbulent, transonic flow; the number of geometric design variables varies from 1 to 60 with coupling between a wing grid generation program and a state-of-the-art, 3-D computational fluid dynamics program, both augmented for derivative computation via AD. For a small number of design variables, the Cray Y-MP implementation is much faster. As the number of design variables grows, however, the IBM SP1 becomes an attractive alternative in terms of compute speed, job turnaround time, and total memory available for solutions with large numbers of design variables. The coarse-grained parallel implementation also can be moved easily to a network of workstations.
Physics-based statistical learning approach to mesoscopic model selection.
Taverniers, Søren; Haut, Terry S; Barros, Kipton; Alexander, Francis J; Lookman, Turab
2015-11-01
In materials science and many other research areas, models are frequently inferred without considering their generalization to unseen data. We apply statistical learning using cross-validation to obtain an optimally predictive coarse-grained description of a two-dimensional kinetic nearest-neighbor Ising model with Glauber dynamics (GD) based on the stochastic Ginzburg-Landau equation (sGLE). The latter is learned from GD "training" data using a log-likelihood analysis, and its predictive ability for various complexities of the model is tested on GD "test" data independent of the data used to train the model on. Using two different error metrics, we perform a detailed analysis of the error between magnetization time trajectories simulated using the learned sGLE coarse-grained description and those obtained using the GD model. We show that both for equilibrium and out-of-equilibrium GD training trajectories, the standard phenomenological description using a quartic free energy does not always yield the most predictive coarse-grained model. Moreover, increasing the amount of training data can shift the optimal model complexity to higher values. Our results are promising in that they pave the way for the use of statistical learning as a general tool for materials modeling and discovery.
Scalable parallel communications
NASA Technical Reports Server (NTRS)
Maly, K.; Khanna, S.; Overstreet, C. M.; Mukkamala, R.; Zubair, M.; Sekhar, Y. S.; Foudriat, E. C.
1992-01-01
Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups.
Sediment sorting at a side channel bifurcation
NASA Astrophysics Data System (ADS)
van Denderen, Pepijn; Schielen, Ralph; Hulscher, Suzanne
2017-04-01
Side channels have been constructed to reduce the flood risk and to increase the ecological value of the river. In various Dutch side channels large aggradation in these channels occurred after construction. Measurements show that the grain size of the deposited sediment in the side channel is smaller than the grain size found on the bed of the main channel. This suggest that sorting occurs at the bifurcation of the side channel. The objective is to reproduce with a 2D morphological model the fining of the bed in the side channel and to study the effect of the sediment sorting on morphodynamic development of the side channel. We use a 2D Delft3D model with two sediment fractions. The first fraction corresponds with the grain size that can be found on the bed of the main channel and the second fraction corresponds with the grain size found in the side channel. With the numerical model we compute several side channel configurations in which we vary the length and the width of the side channel, and the curvature of the upstream channel. From these computations we can derive the equilibrium state and the time scale of the morphodynamic development of the side channel. Preliminary results show that even when a simple sediment transport relation is used, like Engelund & Hansen, more fine sediment enters the side channel than coarse sediment. This is as expected, and is probably related to the bed slope effects which are a function of the Shields parameter. It is expected that by adding a sill at the entrance of the side channel the slope effect increases. This might reduce the amount of coarse sediment which enters the side channel even more. It is unclear whether the model used is able to reproduce the effect of such a sill correctly as modelling a sill and reproducing the correct hydrodynamic and morphodynamic behaviour is not straightforward in a 2D model. Acknowledgements: This research is funded by STW, part of the Dutch Organization for Scientific Research under grant number P12-P14 (RiverCare Perspective Programme) project number 13516.
Han, Wei; Schulten, Klaus
2012-01-01
PACE, a hybrid force field which couples united-atom protein models with coarse-grained (CG) solvent, has been further optimized, aiming to improve itse ciency for folding simulations. Backbone hydration parameters have been re-optimized based on hydration free energies of polyalanyl peptides through atomistic simulations. Also, atomistic partial charges from all-atom force fields were combined with PACE in order to provide a more realistic description of interactions between charged groups. Using replica exchange molecular dynamics (REMD), ab initio folding using the new PACE has been achieved for seven small proteins (16 – 23 residues) with different structural motifs. Experimental data about folded states, such as their stability at room temperature, melting point and NMR NOE constraints, were also well reproduced. Moreover, a systematic comparison of folding kinetics at room temperature has been made with experiments, through standard MD simulations, showing that the new PACE may speed up the actual folding kinetics 5-10 times. Together with the computational speedup benefited from coarse-graining, the force field provides opportunities to study folding mechanisms. In particular, we used the new PACE to fold a 73-residue protein, 3D, in multiple 10 – 30 μs simulations, to its native states (Cα RMSD ~ 0.34 nm). Our results suggest the potential applicability of the new PACE for the study of folding and dynamics of proteins. PMID:23204949
Ahmed, Aqeel; Villinger, Saskia; Gohlke, Holger
2010-12-01
A large-scale comparison of essential dynamics (ED) modes from molecular dynamic simulations and normal modes from coarse-grained normal mode methods (CGNM) was performed on a dataset of 335 proteins. As CGNM methods, the elastic network model (ENM) and the rigid cluster normal mode analysis (RCNMA) were used. Low-frequency normal modes from ENM correlate very well with ED modes in terms of directions of motions and relative amplitudes of motions. Notably, a similar performance was found if normal modes from RCNMA were used, despite a higher level of coarse graining. On average, the space spanned by the first quarter of ENM modes describes 84% of the space spanned by the five ED modes. Furthermore, no prominent differences for ED and CGNM modes among different protein structure classes (CATH classification) were found. This demonstrates the general potential of CGNM approaches for describing intrinsic motions of proteins with little computational cost. For selected cases, CGNM modes were found to be more robust among proteins that have the same topology or are of the same homologous superfamily than ED modes. In view of recent evidence regarding evolutionary conservation of vibrational dynamics, this suggests that ED modes, in some cases, might not be representative of the underlying dynamics that are characteristic of a whole family, probably due to insufficient sampling of some of the family members by MD. Copyright © 2010 Wiley-Liss, Inc.
Xu, Yinlin; Ma, Qianli D Y; Schmitt, Daniel T; Bernaola-Galván, Pedro; Ivanov, Plamen Ch
2011-11-01
We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences.
Xu, Yinlin; Ma, Qianli D.Y.; Schmitt, Daniel T.; Bernaola-Galván, Pedro; Ivanov, Plamen Ch.
2014-01-01
We investigate how various coarse-graining (signal quantization) methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis. Specifically, for coarse-graining in the magnitude of a signal, we consider (i) the Floor, (ii) the Symmetry and (iii) the Centro-Symmetry coarse-graining methods. We find that for anti-correlated signals coarse-graining in the magnitude leads to a crossover to random behavior at large scales, and that with increasing the width of the coarse-graining partition interval Δ, this crossover moves to intermediate and small scales. In contrast, the scaling of positively correlated signals is less affected by the coarse-graining, with no observable changes when Δ < 1, while for Δ > 1 a crossover appears at small scales and moves to intermediate and large scales with increasing Δ. For very rough coarse-graining (Δ > 3) based on the Floor and Symmetry methods, the position of the crossover stabilizes, in contrast to the Centro-Symmetry method where the crossover continuously moves across scales and leads to a random behavior at all scales; thus indicating a much stronger effect of the Centro-Symmetry compared to the Floor and the Symmetry method. For coarse-graining in time, where data points are averaged in non-overlapping time windows, we find that the scaling for both anti-correlated and positively correlated signals is practically preserved. The results of our simulations are useful for the correct interpretation of the correlation and scaling properties of symbolic sequences. PMID:25392599
The grain-size lineup: A test of a novel eyewitness identification procedure.
Horry, Ruth; Brewer, Neil; Weber, Nathan
2016-04-01
When making a memorial judgment, respondents can regulate their accuracy by adjusting the precision, or grain size, of their responses. In many circumstances, coarse-grained responses are less informative, but more likely to be accurate, than fine-grained responses. This study describes a novel eyewitness identification procedure, the grain-size lineup, in which participants eliminated any number of individuals from the lineup, creating a choice set of variable size. A decision was considered to be fine-grained if no more than 1 individual was left in the choice set or coarse-grained if more than 1 individual was left in the choice set. Participants (N = 384) watched 2 high-quality or low-quality videotaped mock crimes and then completed 4 standard simultaneous lineups or 4 grain-size lineups (2 target-present and 2 target-absent). There was some evidence of strategic regulation of grain size, as the most difficult lineup was associated with a greater proportion of coarse-grained responses than the other lineups. However, the grain-size lineup did not outperform the standard simultaneous lineup. Fine-grained suspect identifications were no more diagnostic than suspect identifications from standard lineups, whereas coarse-grained suspect identifications carried little probative value. Participants were generally reluctant to provide coarse-grained responses, which may have hampered the utility of the procedure. For a grain-size approach to be useful, participants may need to be trained or instructed to use the coarse-grained option effectively. (c) 2016 APA, all rights reserved).
Bertalan, Tom; Wu, Yan; Laing, Carlo; Gear, C. William; Kevrekidis, Ioannis G.
2017-01-01
Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and ultimately design. Here, we propose and illustrate a systematic and powerful approach to obtaining good collective coarse-grained observables—variables successfully summarizing the detailed state of such networks. Finding such variables can naturally lead to successful reduced dynamic models for the networks. The main premise enabling our approach is the assumption that the behavior of a node in the network depends (after a short initial transient) on the node identity: a set of descriptors that quantify the node properties, whether intrinsic (e.g., parameters in the node evolution equations) or structural (imparted to the node by its connectivity in the particular network structure). The approach creates a natural link with modeling and “computational enabling technology” developed in the context of Uncertainty Quantification. In our case, however, we will not focus on ensembles of different realizations of a problem, each with parameters randomly selected from a distribution. We will instead study many coupled heterogeneous units, each characterized by randomly assigned (heterogeneous) parameter value(s). One could then coin the term Heterogeneity Quantification for this approach, which we illustrate through a model dynamic network consisting of coupled oscillators with one intrinsic heterogeneity (oscillator individual frequency) and one structural heterogeneity (oscillator degree in the undirected network). The computational implementation of the approach, its shortcomings and possible extensions are also discussed. PMID:28659781
Edgeworth streaming model for redshift space distortions
NASA Astrophysics Data System (ADS)
Uhlemann, Cora; Kopp, Michael; Haugg, Thomas
2015-09-01
We derive the Edgeworth streaming model (ESM) for the redshift space correlation function starting from an arbitrary distribution function for biased tracers of dark matter by considering its two-point statistics and show that it reduces to the Gaussian streaming model (GSM) when neglecting non-Gaussianities. We test the accuracy of the GSM and ESM independent of perturbation theory using the Horizon Run 2 N -body halo catalog. While the monopole of the redshift space halo correlation function is well described by the GSM, higher multipoles improve upon including the leading order non-Gaussian correction in the ESM: the GSM quadrupole breaks down on scales below 30 Mpc /h whereas the ESM stays accurate to 2% within statistical errors down to 10 Mpc /h . To predict the scale-dependent functions entering the streaming model we employ convolution Lagrangian perturbation theory (CLPT) based on the dust model and local Lagrangian bias. Since dark matter halos carry an intrinsic length scale given by their Lagrangian radius, we extend CLPT to the coarse-grained dust model and consider two different smoothing approaches operating in Eulerian and Lagrangian space, respectively. The coarse graining in Eulerian space features modified fluid dynamics different from dust while the coarse graining in Lagrangian space is performed in the initial conditions with subsequent single-streaming dust dynamics, implemented by smoothing the initial power spectrum in the spirit of the truncated Zel'dovich approximation. Finally, we compare the predictions of the different coarse-grained models for the streaming model ingredients to N -body measurements and comment on the proper choice of both the tracer distribution function and the smoothing scale. Since the perturbative methods we considered are not yet accurate enough on small scales, the GSM is sufficient when applied to perturbation theory.
DOE Office of Scientific and Technical Information (OSTI.GOV)
D’Adamo, Giuseppe, E-mail: giuseppe.dadamo@sissa.it; Pelissetto, Andrea, E-mail: andrea.pelissetto@roma1.infn.it; Pierleoni, Carlo, E-mail: carlo.pierleoni@aquila.infn.it
2014-12-28
A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach, groups of monomers are mapped onto a single pseudoatom (a blob) and the effective blob-blob interactions are obtained by requiring the model to reproduce some large-scale structural properties in the zero-density limit. We show that an accurate parametrization of the polymer-colloid interactions is obtained by simply introducing pair potentials between blobs and colloids. For the coarse-grained (CG) model in which polymers are modelled as four-blob chains (tetramers), the pair potentials are determined by means of the iterative Boltzmannmore » inversion scheme, taking full-monomer (FM) pair correlation functions at zero-density as targets. For a larger number n of blobs, pair potentials are determined by using a simple transferability assumption based on the polymer self-similarity. We validate the model by comparing its predictions with full-monomer results for the interfacial properties of polymer solutions in the presence of a single colloid and for thermodynamic and structural properties in the homogeneous phase at finite polymer and colloid density. The tetramer model is quite accurate for q ≲ 1 (q=R{sup ^}{sub g}/R{sub c}, where R{sup ^}{sub g} is the zero-density polymer radius of gyration and R{sub c} is the colloid radius) and reasonably good also for q = 2. For q = 2, an accurate coarse-grained description is obtained by using the n = 10 blob model. We also compare our results with those obtained by using single-blob models with state-dependent potentials.« less
Quasi-coarse-grained dynamics: modelling of metallic materials at mesoscales
NASA Astrophysics Data System (ADS)
Dongare, Avinash M.
2014-12-01
A computationally efficient modelling method called quasi-coarse-grained dynamics (QCGD) is developed to expand the capabilities of molecular dynamics (MD) simulations to model behaviour of metallic materials at the mesoscales. This mesoscale method is based on solving the equations of motion for a chosen set of representative atoms from an atomistic microstructure and using scaling relationships for the atomic-scale interatomic potentials in MD simulations to define the interactions between representative atoms. The scaling relationships retain the atomic-scale degrees of freedom and therefore energetics of the representative atoms as would be predicted in MD simulations. The total energetics of the system is retained by scaling the energetics and the atomic-scale degrees of freedom of these representative atoms to account for the missing atoms in the microstructure. This scaling of the energetics renders improved time steps for the QCGD simulations. The success of the QCGD method is demonstrated by the prediction of the structural energetics, high-temperature thermodynamics, deformation behaviour of interfaces, phase transformation behaviour, plastic deformation behaviour, heat generation during plastic deformation, as well as the wave propagation behaviour, as would be predicted using MD simulations for a reduced number of representative atoms. The reduced number of atoms and the improved time steps enables the modelling of metallic materials at the mesoscale in extreme environments.
Modeling global changes induced by local perturbations to the HIV-1 capsid.
Bergman, Shana; Lezon, Timothy R
2017-01-01
The HIV-1 capsid is a conical protein shell made up of hexamers and pentamers of the capsid protein. The capsid houses the viral genome and replication machinery, and its opening, or uncoating, within the host cell marks a critical step in the HIV-1 lifecycle. Binding of host factors such as TRIM5α and cyclophilin A (CypA) can alter the capsid's stability, accelerating or delaying the onset of uncoating and disrupting infectivity. We employ coarse-grained computational modeling to investigate the effects of point mutations and host factor binding on HIV-1 capsid stability. We find that the largest fluctuations occur in the low-curvature regions of the capsid, and that its structural dynamics are affected by perturbations at the inter-hexamer interfaces and near the CypA binding loop, suggesting roles for these features in capsid stability. Our models show that linking capsid proteins across hexamers attenuates vibration in the low-curvature regions of the capsid, but that linking within hexamers does not. These results indicate a possible mechanism through which CypA binding alters capsid stability and highlight the utility of coarse-grained network modeling for understanding capsid mechanics. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Chen, Po-Chia; Hologne, Maggy; Walker, Olivier
2017-03-02
Rotational diffusion (D rot ) is a fundamental property of biomolecules that contains information about molecular dimensions and solute-solvent interactions. While ab initio D rot prediction can be achieved by explicit all-atom molecular dynamics simulations, this is hindered by both computational expense and limitations in water models. We propose coarse-grained force fields as a complementary solution, and show that the MARTINI force field with elastic networks is sufficient to compute D rot in >10 proteins spanning 5-157 kDa. We also adopt a quaternion-based approach that computes D rot orientation directly from autocorrelations of best-fit rotations as used in, e.g., RMSD algorithms. Over 2 μs trajectories, isotropic MARTINI+EN tumbling replicates experimental values to within 10-20%, with convergence analyses suggesting a minimum sampling of >50 × τ theor to achieve sufficient precision. Transient fluctuations in anisotropic tumbling cause decreased precision in predictions of axisymmetric anisotropy and rhombicity, the latter of which cannot be precisely evaluated within 2000 × τ theor for GB3. Thus, we encourage reporting of axial decompositions D x , D y , D z to ease comparability between experiment and simulation. Where protein disorder is absent, we observe close replication of MARTINI+EN D rot orientations versus CHARMM22*/TIP3p and experimental data. This work anticipates the ab initio prediction of NMR-relaxation by combining coarse-grained global motions with all-atom local motions.
NASA Astrophysics Data System (ADS)
Maierová, Petra; Lexa, Ondrej; Jeřábek, Petr; Schulmann, Karel; Franěk, Jan
2017-05-01
Most of granulite terrains worldwide are characterized by large mean grain sizes of 1 mm or more. An important exception are the high-pressure felsic granulites in the Bohemian Massif, the European Variscan belt. There, recrystallization of original coarse-grained ternary feldspar led to formation of a fine-grained (∼100 μm) mixed matrix dominated by plagioclase and K-feldspar. This change occurred at temperatures of ∼850 °C and was probably caused by chemically induced decomposition related to slight cooling and enhanced by deformation during continental collision. The resulting microstructure shows indications of diffusion creep assisted by melt-enhanced grain-boundary sliding. Further on, minor coarsening occurred associated with deformation by dislocation creep and aggregation of mineral phases. Using a thermodynamics-based model of grain size evolution we show that stability of the fine-grained microstructure crucially depends on Zener pinning in the two-phase mineral matrix. Pinning efficiently hinders grain growth, and the small grain size that resulted from the ternary feldspar decomposition can be stable even at high temperatures. The late switch from the grain-size-sensitive creep to dislocation creep is rather difficult to explain by temperature and strain rate (or stress) changes only. However, a simple incorporation of melt solidification can successfully simulate this behavior. Alternatively, the switch and the associated grain size growth can be related to mineral phase aggregation at lower pressure-temperature conditions resulting into a decrease of pinning efficiency. This study suggests that the fine grain size of the Bohemian granulites, in contrast to the common coarse-grained type, stems from abrupt recrystallization during the high-pressure high-temperature conditions, and pinning in the fine-grained matrix. Such a process may in some cases significantly and suddenly reduce the strength of the lower continental crust and allow for its efficient redistribution.
Truccolo, Wilson
2017-01-01
This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics (“order parameters”) inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. PMID:28336305
Truccolo, Wilson
2016-11-01
This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.
A rapid solvent accessible surface area estimator for coarse grained molecular simulations.
Wei, Shuai; Brooks, Charles L; Frank, Aaron T
2017-06-05
The rapid and accurate calculation of solvent accessible surface area (SASA) is extremely useful in the energetic analysis of biomolecules. For example, SASA models can be used to estimate the transfer free energy associated with biophysical processes, and when combined with coarse-grained simulations, can be particularly useful for accounting for solvation effects within the framework of implicit solvent models. In such cases, a fast and accurate, residue-wise SASA predictor is highly desirable. Here, we develop a predictive model that estimates SASAs based on Cα-only protein structures. Through an extensive comparison between this method and a comparable method, POPS-R, we demonstrate that our new method, Protein-C α Solvent Accessibilities or PCASA, shows better performance, especially for unfolded conformations of proteins. We anticipate that this model will be quite useful in the efficient inclusion of SASA-based solvent free energy estimations in coarse-grained protein folding simulations. PCASA is made freely available to the academic community at https://github.com/atfrank/PCASA. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Loeffler, Troy David; Chan, Henry; Narayanan, Badri; Cherukara, Mathew J; Gray, Stephen K; Sankaranarayanan, Subramanian K R S
2018-06-20
Coarse-grained molecular dynamics (MD) simulations represent a powerful approach to simulate longer time scale and larger length scale phenomena than those accessible to all-atom models. The gain in efficiency, however, comes at the cost of atomistic details. The reverse transformation, also known as back-mapping, of coarse grained beads into their atomistic constituents represents a major challenge. Most existing approaches are limited to specific molecules or specific force-fields and often rely on running a long time atomistic MD of the back-mapped configuration to arrive at an optimal solution. Such approaches are problematic when dealing with systems with high diffusion barriers. Here, we introduce a new extension of the configurational-bias-Monte-Carlo (CBMC) algorithm, which we term the crystalline-configurational-bias-Monte-Carlo (C-CBMC) algortihm, that allows rapid and efficient conversion of a coarse-grained model back into its atomistic representation. Although the method is generic, we use a coarse-grained water model as a representative example and demonstrate the back-mapping or reverse transformation for model systems ranging from the ice-liquid water interface to amorphous and crystalline ice configurations. A series of simulations using the TIP4P/Ice model are performed to compare the new CBMC method to several other standard Monte Carlo and Molecular Dynamics based back-mapping techniques. In all the cases, the C-CBMC algorithm is able to find optimal hydrogen bonded configuration many thousand evaluations/steps sooner than the other methods compared within this paper. For crystalline ice structures such as a hexagonal, cubic, and cubic-hexagonal stacking disorder structures, the C-CBMC was able to find structures that were between 0.05 and 0.1 eV/water molecule lower in energy than the ground state energies predicted by the other methods. Detailed analysis of the atomistic structures show a significantly better global hydrogen positioning when contrasted with the existing simpler back-mapping methods. Our results demonstrate the efficiency and efficacy of our new back-mapping approach, especially for crystalline systems where simple force-field based relaxations have a tendency to get trapped in local minima.
Coarse-graining as a downward causation mechanism
NASA Astrophysics Data System (ADS)
Flack, Jessica C.
2017-11-01
Downward causation is the controversial idea that `higher' levels of organization can causally influence behaviour at `lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks. This article is part of the themed issue 'Reconceptualizing the origins of life'.
Coarse-graining as a downward causation mechanism
2017-01-01
Downward causation is the controversial idea that ‘higher’ levels of organization can causally influence behaviour at ‘lower’ levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks. This article is part of the themed issue ‘Reconceptualizing the origins of life’. PMID:29133440
On the representability problem and the physical meaning of coarse-grained models
NASA Astrophysics Data System (ADS)
Wagner, Jacob W.; Dama, James F.; Durumeric, Aleksander E. P.; Voth, Gregory A.
2016-07-01
In coarse-grained (CG) models where certain fine-grained (FG, i.e., atomistic resolution) observables are not directly represented, one can nonetheless identify indirect the CG observables that capture the FG observable's dependence on CG coordinates. Often, in these cases it appears that a CG observable can be defined by analogy to an all-atom or FG observable, but the similarity is misleading and significantly undermines the interpretation of both bottom-up and top-down CG models. Such problems emerge especially clearly in the framework of the systematic bottom-up CG modeling, where a direct and transparent correspondence between FG and CG variables establishes precise conditions for consistency between CG observables and underlying FG models. Here we present and investigate these representability challenges and illustrate them via the bottom-up conceptual framework for several simple analytically tractable polymer models. The examples provide special focus on the observables of configurational internal energy, entropy, and pressure, which have been at the root of controversy in the CG literature, as well as discuss observables that would seem to be entirely missing in the CG representation but can nonetheless be correlated with CG behavior. Though we investigate these problems in the framework of systematic coarse-graining, the lessons apply to top-down CG modeling also, with crucial implications for simulation at constant pressure and surface tension and for the interpretations of structural and thermodynamic correlations for comparison to experiment.
A distributed Clips implementation: dClips
NASA Technical Reports Server (NTRS)
Li, Y. Philip
1993-01-01
A distributed version of the Clips language, dClips, was implemented on top of two existing generic distributed messaging systems to show that: (1) it is easy to create a coarse-grained parallel programming environment out of an existing language if a high level messaging system is used; and (2) the computing model of a parallel programming environment can be changed easily if we change the underlying messaging system. dClips processes were first connected with a simple master-slave model. A client-server model with intercommunicating agents was later implemented. The concept of service broker is being investigated.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Enciso, Marta, E-mail: m.enciso@latrobe.edu.au; Schütte, Christof, E-mail: schuette@zib.de; Zuse Institute Berlin, Berlin
We employ a recently developed coarse-grained model for peptides and proteins where the effect of pH is automatically included. We explore the effect of pH in the aggregation process of the amyloidogenic peptide KTVIIE and two related sequences, using three different pH environments. Simulations using large systems (24 peptides chains per box) allow us to describe the formation of realistic peptide aggregates. We evaluate the thermodynamic and kinetic implications of changes in sequence and pH upon peptide aggregation, and we discuss how a minimalistic coarse-grained model can account for these details.
Extrapolation to Nonequilibrium from Coarse-Grained Response Theory
NASA Astrophysics Data System (ADS)
Basu, Urna; Helden, Laurent; Krüger, Matthias
2018-05-01
Nonlinear response theory, in contrast to linear cases, involves (dynamical) details, and this makes application to many-body systems challenging. From the microscopic starting point we obtain an exact response theory for a small number of coarse-grained degrees of freedom. With it, an extrapolation scheme uses near-equilibrium measurements to predict far-from-equilibrium properties (here, second order responses). Because it does not involve system details, this approach can be applied to many-body systems. It is illustrated in a four-state model and in the near critical Ising model.
de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-12-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.
NASA Astrophysics Data System (ADS)
de la Cruz, Roberto; Guerrero, Pilar; Calvo, Juan; Alarcón, Tomás
2017-12-01
The development of hybrid methodologies is of current interest in both multi-scale modelling and stochastic reaction-diffusion systems regarding their applications to biology. We formulate a hybrid method for stochastic multi-scale models of cells populations that extends the remit of existing hybrid methods for reaction-diffusion systems. Such method is developed for a stochastic multi-scale model of tumour growth, i.e. population-dynamical models which account for the effects of intrinsic noise affecting both the number of cells and the intracellular dynamics. In order to formulate this method, we develop a coarse-grained approximation for both the full stochastic model and its mean-field limit. Such approximation involves averaging out the age-structure (which accounts for the multi-scale nature of the model) by assuming that the age distribution of the population settles onto equilibrium very fast. We then couple the coarse-grained mean-field model to the full stochastic multi-scale model. By doing so, within the mean-field region, we are neglecting noise in both cell numbers (population) and their birth rates (structure). This implies that, in addition to the issues that arise in stochastic-reaction diffusion systems, we need to account for the age-structure of the population when attempting to couple both descriptions. We exploit our coarse-graining model so that, within the mean-field region, the age-distribution is in equilibrium and we know its explicit form. This allows us to couple both domains consistently, as upon transference of cells from the mean-field to the stochastic region, we sample the equilibrium age distribution. Furthermore, our method allows us to investigate the effects of intracellular noise, i.e. fluctuations of the birth rate, on collective properties such as travelling wave velocity. We show that the combination of population and birth-rate noise gives rise to large fluctuations of the birth rate in the region at the leading edge of front, which cannot be accounted for by the coarse-grained model. Such fluctuations have non-trivial effects on the wave velocity. Beyond the development of a new hybrid method, we thus conclude that birth-rate fluctuations are central to a quantitatively accurate description of invasive phenomena such as tumour growth.
Star polymers as unit cells for coarse-graining cross-linked networks
NASA Astrophysics Data System (ADS)
Molotilin, Taras Y.; Maduar, Salim R.; Vinogradova, Olga I.
2018-03-01
Reducing the complexity of cross-linked polymer networks by preserving their main macroscale properties is key to understanding them, and a crucial issue is to relate individual properties of the polymer constituents to those of the reduced network. Here we study polymer networks in a good solvent, by considering star polymers as their unit elements, and first quantify the interaction between their centers of masses. We then reduce the complexity of a network by replacing sets of its bridged star polymers by equivalent effective soft particles with dense cores. Our coarse graining allows us to approximate complex polymer networks by much simpler ones, keeping their relevant mechanical properties, as illustrated in computer experiments.
Adhesion between a rutile surface and a polyimide: a coarse grained molecular dynamics study
NASA Astrophysics Data System (ADS)
Kumar, Arun; Sudarkodi, V.; Parandekar, Priya V.; Sinha, Nishant K.; Prakash, Om; Nair, Nisanth N.; Basu, Sumit
2018-04-01
Titanium, due to its high strength to weight ratio and polyimides, due to their excellent thermal stability are being increasingly used in aerospace applications. We investigate the bonding between a (110) rutile substrate and a popular commercial polyimide, PMR-15, starting from the known atomic structure of the rutile substrate and the architecture of the polymer. First, the long PMR-15 molecule is divided into four fragments and an all-atom non-bonded forcefield governing the interaction between PMR-15 and a rutile substrate is developed. To this end, parameters of Buckingham potential for interaction between each atom in the fragments and the rutile surface are fitted, so as to ensure that the sum of non-bonded and electrostatic interaction energy between the substrate and a large number of configurations of each fragment, calculated by the quantum mechanical route and obtained from the fitted potential, is closely matched. Further, two coarse grained models of PMR-15 are developed—one for interaction between two coarse grained PMR-15 molecules and another for that between a coarse grained PMR-15 and the rutile substrate. Molecular dynamics simulations with the coarse grained models yields a traction separation law—a very useful tool for conducting continuum level finite element simulations of rutile-PMR-15 joints—governing the normal separation of a PMR-15 block from a flat rutile substrate. Moreover, detailed information about the affinity of various fragments to the substrate are also obtained. In fact, though the separation energy between rutile and PMR-15 turns out to be rather low, our analysis—with merely the molecular architecture of the polyimide as the starting point—provides a scheme for in-silico prediction of adhesion energies for new polyimide formulations.
Ruiz-Morales, Yosadara; Romero-Martínez, Ascención
2018-04-12
The first critical micelle concentration (CMC) of the ionic surfactant sodium dodecyl sulfate (SDS) in diluted aqueous solution has been determined at room temperature from the investigation of the bulk viscosity, at several concentrations of SDS, by means of coarse-grain molecular dynamics simulations. The coarse-grained model molecules at the mesoscale level are adopted. The bulk viscosity of SDS was calculated at several millimolar concentrations of SDS in water using the MARTINI force field by means of NVT shear Mesocite molecular dynamics. The definition of each bead in the MARTINI force field is established, as well as their radius, volume, and mass. The effect of the size of the simulation box on the obtained CMC has been investigated, as well as the effect of the number of SDS molecules, in the simulations, on the formation of aggregates. The CMC, which was obtained from a graph of the calculated viscosities versus concentration, is in good agreement with the reported experimental data and does not depend on the size of the box used in the simulation. The formation of a spherical micelle-like aggregate is observed, where the dodecyl sulfate tails point inward and the heads point outward the aggregation micelle, in accordance with experimental observations. The advantage of using coarse-grain molecular dynamics is the possibility of treating explicitly charged beads, applying a shear flow for viscosity calculation, and processing much larger spatial and temporal scales than atomistic molecular dynamics can. Furthermore, the CMC of SDS obtained with the coarse-grained model is in much better agreement with the experimental value than the value obtained with atomistic simulations.
Spontaneous adsorption of coiled-coil model peptides K and E to a mixed lipid bilayer.
Pluhackova, Kristyna; Wassenaar, Tsjerk A; Kirsch, Sonja; Böckmann, Rainer A
2015-03-26
A molecular description of the lipid-protein interactions underlying the adsorption of proteins to membranes is crucial for understanding, for example, the specificity of adsorption or the binding strength of a protein to a bilayer, or for characterizing protein-induced changes of membrane properties. In this paper, we extend an automated in silico assay (DAFT) for binding studies and apply it to characterize the adsorption of the model fusion peptides E and K to a mixed phospholipid/cholesterol membrane using coarse-grained molecular dynamics simulations. In addition, we couple the coarse-grained protocol to reverse transformation to atomistic resolution, thereby allowing to study molecular interactions with high detail. The experimentally observed differential binding of the peptides E and K to membranes, as well as the increased binding affinity of helical over unstructered peptides, could be well reproduced using the polarizable Martini coarse-grained (CG) force field. Binding to neutral membranes is shown to be dominated by initial binding of the positively charged N-terminus to the phospholipid headgroup region, followed by membrane surface-aligned insertion of the peptide at the interface between the hydrophobic core of the membrane and its polar headgroup region. Both coarse-grained and atomistic simulations confirm a before hypothesized snorkeling of lysine side chains for the membrane-bound state of the peptide K. Cholesterol was found to be enriched in peptide vicinity, which is probably of importance for the mechanism of membrane fusion. The applied sequential multiscale method, using coarse-grained simulations for the slow adsorption process of peptides to membranes followed by backward transformation to atomistic detail and subsequent atomistic simulations of the preformed peptide-lipid complexes, is shown to be a versatile approach to study the interactions of peptides or proteins with biomembranes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leonard, T.; Lander, B.; Seifert, U.
2013-11-28
We discuss the stochastic thermodynamics of systems that are described by a time-dependent density field, for example, simple liquids and colloidal suspensions. For a time-dependent change of external parameters, we show that the Jarzynski relation connecting work with the change of free energy holds if the time evolution of the density follows the Kawasaki-Dean equation. Specifically, we study the work distributions for the compression and expansion of a two-dimensional colloidal model suspension implementing a practical coarse-graining scheme of the microscopic particle positions. We demonstrate that even if coarse-grained dynamics and density functional do not match, the fluctuation relations for themore » work still hold albeit for a different, apparent, change of free energy.« less
Homopolyrotaxanes and Homopolyrotaxane Networks of PEO
NASA Technical Reports Server (NTRS)
Pugh, Coleen; Mattice, Wayne
2005-01-01
In order to identify the optimum size of macrocrown ether for threading, we first investigated the size and shape of simple crown ethers in the melt at 373 K, and their extent of threading with PEO in the melt using coarse-grained Monte Carlo simulations on the 2nnd (second nearest neighbor diamond) lattice, which is a high coordination lattice whose coarse-grained chains can be reverse mapped into fully atomistic models in continuous space.
Cyclic hardening behavior of extruded ZK60 magnesium alloy with different grain sizes
NASA Astrophysics Data System (ADS)
Zhang, Lixin; Zhang, Wencong; Chen, Wenzhen; Wang, Wenke
2018-04-01
Montonic and fully reversed strain-controlled cyclic deformation experiments were conducted on extruded ZK60 magnesium alloy with two different grain sizes in ambient air. Results revealed that the hardening rates of the ZK60 magnesium alloy rods with fine grain and coarse grain in the monotonic deformation and the fully reversed strain-controlled cyclic deformation were opposite along the extrusion direction. Electron Backscatter Diffration analysis revealed that fine grains were more easily rotated than coarse grains under the cyclic deformation. Under the twinning and detwinning process of the cyclic deformation at a large strain amplitude, the coarse grained ZK60 magnesium alloys were more prone to tension twinning {10-12}<10-11> and more residual twins were observed. Texture hardening of coarse grained magnesium alloy was more obvious in cyclic defromation than fine-grained magnesium alloy.
Systematic methods for defining coarse-grained maps in large biomolecules.
Zhang, Zhiyong
2015-01-01
Large biomolecules are involved in many important biological processes. It would be difficult to use large-scale atomistic molecular dynamics (MD) simulations to study the functional motions of these systems because of the computational expense. Therefore various coarse-grained (CG) approaches have attracted rapidly growing interest, which enable simulations of large biomolecules over longer effective timescales than all-atom MD simulations. The first issue in CG modeling is to construct CG maps from atomic structures. In this chapter, we review the recent development of a novel and systematic method for constructing CG representations of arbitrarily complex biomolecules, in order to preserve large-scale and functionally relevant essential dynamics (ED) at the CG level. In this ED-CG scheme, the essential dynamics can be characterized by principal component analysis (PCA) on a structural ensemble, or elastic network model (ENM) of a single atomic structure. Validation and applications of the method cover various biological systems, such as multi-domain proteins, protein complexes, and even biomolecular machines. The results demonstrate that the ED-CG method may serve as a very useful tool for identifying functional dynamics of large biomolecules at the CG level.
Analysis of Gas-Particle Flows through Multi-Scale Simulations
NASA Astrophysics Data System (ADS)
Gu, Yile
Multi-scale structures are inherent in gas-solid flows, which render the modeling efforts challenging. On one hand, detailed simulations where the fine structures are resolved and particle properties can be directly specified can account for complex flow behaviors, but they are too computationally expensive to apply for larger systems. On the other hand, coarse-grained simulations demand much less computations but they necessitate constitutive models which are often not readily available for given particle properties. The present study focuses on addressing this issue, as it seeks to provide a general framework through which one can obtain the required constitutive models from detailed simulations. To demonstrate the viability of this general framework in which closures can be proposed for different particle properties, we focus on the van der Waals force of interaction between particles. We start with Computational Fluid Dynamics (CFD) - Discrete Element Method (DEM) simulations where the fine structures are resolved and van der Waals force between particles can be directly specified, and obtain closures for stress and drag that are required for coarse-grained simulations. Specifically, we develop a new cohesion model that appropriately accounts for van der Waals force between particles to be used for CFD-DEM simulations. We then validate this cohesion model and the CFD-DEM approach by showing that it can qualitatively capture experimental results where the addition of small particles to gas fluidization reduces bubble sizes. Based on the DEM and CFD-DEM simulation results, we propose stress models that account for the van der Waals force between particles. Finally, we apply machine learning, specifically neural networks, to obtain a drag model that captures the effects from fine structures and inter-particle cohesion. We show that this novel approach using neural networks, which can be readily applied for other closures other than drag here, can take advantage of the large amount of data generated from simulations, and therefore offer superior modeling performance over traditional approaches.
Coarse-grained molecular dynamics simulation of water diffusion in the presence of carbon nanotubes.
Lado Touriño, Isabel; Naranjo, Arisbel Cerpa; Negri, Viviana; Cerdán, Sebastián; Ballesteros, Paloma
2015-11-01
Computational modeling of the translational diffusion of water molecules in anisotropic environments entails vital relevance to understand correctly the information contained in the magnetic resonance images weighted in diffusion (DWI) and of the diffusion tensor images (DTI). In the present work we investigated the validity, strengths and weaknesses of a coarse-grained (CG) model based on the MARTINI force field to simulate water diffusion in a medium containing carbon nanotubes (CNTs) as models of anisotropic water diffusion behavior. We show that water diffusion outside the nanotubes follows Ficḱs law, while water diffusion inside the nanotubes is not described by a Ficḱs behavior. We report on the influence on water diffusion of various parameters such as length and concentration of CNTs, comparing the CG results with those obtained from the more accurate classic force field calculation, like the all-atom approach. Calculated water diffusion coefficients decreased in the presence of nanotubes in a concentration dependent manner. We also observed smaller water diffusion coefficients for longer CNTs. Using the CG methodology we were able to demonstrate anisotropic diffusion of water inside the nanotube scaffold, but we could not prove anisotropy in the surrounding medium, suggesting that grouping several water molecules in a single diffusing unit may affect the diffusional anisotropy calculated. The methodologies investigated in this work represent a first step towards the study of more complex models, including anisotropic cohorts of CNTs or even neuronal axons, with reasonable savings in computation time. Copyright © 2015 Elsevier Inc. All rights reserved.
Song, Bin; Molinero, Valeria
2013-08-07
Hydrophobic interactions are responsible for water-driven processes such as protein folding and self-assembly of biomolecules. Microscopic theories and molecular simulations have been used to study association of a pair of methanes in water, the paradigmatic example of hydrophobic attraction, and determined that entropy is the driving force for the association of the methane pair, while the enthalpy disfavors it. An open question is to which extent coarse-grained water models can still produce correct thermodynamic and structural signatures of hydrophobic interaction. In this work, we investigate the hydrophobic interaction between a methane pair in water at temperatures from 260 to 340 K through molecular dynamics simulations with the coarse-grained monatomic water model mW. We find that the coarse-grained model correctly represents the free energy of association of the methane pair, the temperature dependence of free energy, and the positive change in entropy and enthalpy upon association. We investigate the relationship between thermodynamic signatures and structural order of water through the analysis of the spatial distribution of the density, energy, and tetrahedral order parameter Qt of water. The simulations reveal an enhancement of tetrahedral order in the region between the first and second hydration shells of the methane molecules. The increase in tetrahedral order, however, is far from what would be expected for a clathrate-like or ice-like shell around the solutes. This work shows that the mW water model reproduces the key signatures of hydrophobic interaction without long ranged electrostatics or the need to be re-parameterized for different thermodynamic states. These characteristics, and its hundred-fold increase in efficiency with respect to atomistic models, make mW a promising water model for studying water-driven hydrophobic processes in more complex systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less
Generalized quantum theory of recollapsing homogeneous cosmologies
NASA Astrophysics Data System (ADS)
Craig, David; Hartle, James B.
2004-06-01
A sum-over-histories generalized quantum theory is developed for homogeneous minisuperspace type A Bianchi cosmological models, focusing on the particular example of the classically recollapsing Bianchi type-IX universe. The decoherence functional for such universes is exhibited. We show how the probabilities of decoherent sets of alternative, coarse-grained histories of these model universes can be calculated. We consider in particular the probabilities for classical evolution defined by a suitable coarse graining. For a restricted class of initial conditions and coarse grainings we exhibit the approximate decoherence of alternative histories in which the universe behaves classically and those in which it does not. For these situations we show that the probability is near unity for the universe to recontract classically if it expands classically. We also determine the relative probabilities of quasiclassical trajectories for initial states of WKB form, recovering for such states a precise form of the familiar heuristic “JṡdΣ” rule of quantum cosmology, as well as a generalization of this rule to generic initial states.
Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent
NASA Astrophysics Data System (ADS)
Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu
2011-10-01
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.
TMFF-A Two-Bead Multipole Force Field for Coarse-Grained Molecular Dynamics Simulation of Protein.
Li, Min; Liu, Fengjiao; Zhang, John Z H
2016-12-13
Coarse-grained (CG) models are desirable for studying large and complex biological systems. In this paper, we propose a new two-bead multipole force field (TMFF) in which electric multipoles up to the quadrupole are included in the CG force field. The inclusion of electric multipoles in the proposed CG force field enables a more realistic description of the anisotropic electrostatic interactions in the protein system and, thus, provides an improvement over the standard isotropic two-bead CG models. In order to test the accuracy of the new CG force field model, extensive molecular dynamics simulations were carried out for a series of benchmark protein systems. These simulation studies showed that the TMFF model can realistically reproduce the structural and dynamical properties of proteins, as demonstrated by the close agreement of the CG results with those from the corresponding all-atom simulations in terms of root-mean-square deviations (RMSDs) and root-mean-square fluctuations (RMSFs) of the protein backbones. The current two-bead model is highly coarse-grained and is 50-fold more efficient than all-atom method in MD simulation of proteins in explicit water.
An exactly solvable coarse-grained model for species diversity
NASA Astrophysics Data System (ADS)
Suweis, Samir; Rinaldo, Andrea; Maritan, Amos
2012-07-01
We present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology.
Prediction of purification of biopharmeceuticals with molecular dynamics
NASA Astrophysics Data System (ADS)
Ustach, Vincent; Faller, Roland
Purification of biopharmeceuticals remains the most expensive part of protein-based drug production. In ion exchange chromatography (IEX), prediction of the elution ionic strength of host cell and target proteins has the potential to reduce the parameter space for scale-up of protein production. The complex shape and charge distribution of proteins and pores complicates predictions of the interactions in these systems. All-atom molecular dynamics methods are beyond the scope of computational limits for mass transport regimes. We present a coarse-grained model for proteins for prediction of elution pH and ionic strength. By extending the raspberry model for colloid particles to surface shapes and charge distributions of proteins, we can reproduce the behavior of proteins in IEX. The average charge states of titratatable amino acid residues at relevant pH values are determined by extrapolation from all-atom molecular dynamics at pH 7. The pH specific all-atom electrostatic field is then mapped onto the coarse-grained surface beads of the raspberry particle. The hydrodynamics are reproduced with the lattice-Boltzmann scheme. This combination of methods allows very long simulation times. The model is being validated for known elution procedures by comparing the data with experiments. Defense Threat Reduction Agency (Grant Number HDTRA1-15-1-0054).
KOSMOS: a universal morph server for nucleic acids, proteins and their complexes.
Seo, Sangjae; Kim, Moon Ki
2012-07-01
KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sarkar, Avik; Milioli, Fernando E.; Ozarkar, Shailesh
2016-10-01
The accuracy of fluidized-bed CFD predictions using the two-fluid model can be improved significantly, even when using coarse grids, by replacing the microscopic kinetic-theory-based closures with coarse-grained constitutive models. These coarse-grained constitutive relationships, called filtered models, account for the unresolved gas-particle structures (clusters and bubbles) via sub-grid corrections. Following the previous 2-D approaches of Igci et al. [AIChE J., 54(6), 1431-1448, 2008] and Milioli et al. [AIChE J., 59(9), 3265-3275, 2013], new filtered models are constructed from highly-resolved 3-D simulations of gas-particle flows. Although qualitatively similar to the older 2-D models, the new 3-D relationships exhibit noticeable quantitative and functionalmore » differences. In particular, the filtered stresses are strongly dependent on the gas-particle slip velocity. Closures for the filtered inter-phase drag, gas- and solids-phase pressures and viscosities are reported. A new model for solids stress anisotropy is also presented. These new filtered 3-D constitutive relationships are better suited to practical coarse-grid 3-D simulations of large, commercial-scale devices.« less
Reconciling transport models across scales: The role of volume exclusion
NASA Astrophysics Data System (ADS)
Taylor, P. R.; Yates, C. A.; Simpson, M. J.; Baker, R. E.
2015-10-01
Diffusive transport is a universal phenomenon, throughout both biological and physical sciences, and models of diffusion are routinely used to interrogate diffusion-driven processes. However, most models neglect to take into account the role of volume exclusion, which can significantly alter diffusive transport, particularly within biological systems where the diffusing particles might occupy a significant fraction of the available space. In this work we use a random walk approach to provide a means to reconcile models that incorporate crowding effects on different spatial scales. Our work demonstrates that coarse-grained models incorporating simplified descriptions of excluded volume can be used in many circumstances, but that care must be taken in pushing the coarse-graining process too far.
Khatri, Bhavin S.; Goldstein, Richard A.
2015-01-01
Speciation is fundamental to understanding the huge diversity of life on Earth. Although still controversial, empirical evidence suggests that the rate of speciation is larger for smaller populations. Here, we explore a biophysical model of speciation by developing a simple coarse-grained theory of transcription factor-DNA binding and how their co-evolution in two geographically isolated lineages leads to incompatibilities. To develop a tractable analytical theory, we derive a Smoluchowski equation for the dynamics of binding energy evolution that accounts for the fact that natural selection acts on phenotypes, but variation arises from mutations in sequences; the Smoluchowski equation includes selection due to both gradients in fitness and gradients in sequence entropy, which is the logarithm of the number of sequences that correspond to a particular binding energy. This simple consideration predicts that smaller populations develop incompatibilities more quickly in the weak mutation regime; this trend arises as sequence entropy poises smaller populations closer to incompatible regions of phenotype space. These results suggest a generic coarse-grained approach to evolutionary stochastic dynamics, allowing realistic modelling at the phenotypic level. PMID:25936759
The balance between keystone clustering and bed roughness in experimental step-pool stabilization
NASA Astrophysics Data System (ADS)
Johnson, J. P.
2016-12-01
Predicting how mountain channels will respond to environmental perturbations such as floods requires an improved quantitative understanding of morphodynamic feedbacks among bed topography, surface grain size and sediment sorting. In boulder-rich gravel streams, transport and sorting often lead to the development of step pool morphologies, which are expressed both in bed topography and coarse grain clustering. Bed stability is difficult to measure, and is sometimes inferred from the presence of step pools. I use scaled flume experiments to explore feedbacks among surface grain sizes, coarse grain clustering, bed roughness and hydraulic roughness during progressive bed stabilization and over a range of sediment transport rates. While grain clusters are sometimes identified by subjective interpretation, I quantify the degree of coarse surface grain clustering using spatial statistics, including a novel normalization of Ripley's K function. This approach is objective and provides information on the strength of clustering over a range of length scales. Flume experiments start with an initial bed surface with a broad grain size distribution and spatially random positions. Flow causes the bed surface to progressively stabilize in response to erosion, surface coarsening, roughening and grain reorganization. At 95% confidence, many but not all beds stabilized with coarse grains becoming more clustered than complete spatial randomness (CSR). I observe a tradeoff between topographic roughness and clustering. Beds that stabilized with higher degrees of coarse-grain clustering were topographically smoother, and vice-versa. Initial conditions influenced the degree of clustering at stability: Beds that happened to have fewer initial coarse grains had more coarse grain reorganization during stabilization, leading to more clustering. Finally, regressions demonstrate that clustering statistics actually predict hydraulic roughness significantly better than does D84 (the size at which 84% of grains are smaller). In the experimental data, the spatial organization of surface grains is a stronger control on flow characteristics than the size of surface grains.
Predicting RNA 3D structure using a coarse-grain helix-centered model
Kerpedjiev, Peter; Höner zu Siederdissen, Christian; Hofacker, Ivo L.
2015-01-01
A 3D model of RNA structure can provide information about its function and regulation that is not possible with just the sequence or secondary structure. Current models suffer from low accuracy and long running times and either neglect or presume knowledge of the long-range interactions which stabilize the tertiary structure. Our coarse-grained, helix-based, tertiary structure model operates with only a few degrees of freedom compared with all-atom models while preserving the ability to sample tertiary structures given a secondary structure. It strikes a balance between the precision of an all-atom tertiary structure model and the simplicity and effectiveness of a secondary structure representation. It provides a simplified tool for exploring global arrangements of helices and loops within RNA structures. We provide an example of a novel energy function relying only on the positions of stems and loops. We show that coupling our model to this energy function produces predictions as good as or better than the current state of the art tools. We propose that given the wide range of conformational space that needs to be explored, a coarse-grain approach can explore more conformations in less iterations than an all-atom model coupled to a fine-grain energy function. Finally, we emphasize the overarching theme of providing an ensemble of predicted structures, something which our tool excels at, rather than providing a handful of the lowest energy structures. PMID:25904133
NASA Astrophysics Data System (ADS)
Zeidman, Benjamin D.; Lu, Ning; Wu, David T.
2016-05-01
The effects of path-dependent wetting and drying manifest themselves in many types of physical systems, including nanomaterials, biological systems, and porous media such as soil. It is desirable to better understand how these hysteretic macroscopic properties result from a complex interplay between gasses, liquids, and solids at the pore scale. Coarse-Grained Monte Carlo (CGMC) is an appealing approach to model these phenomena in complex pore spaces, including ones determined experimentally. We present two-dimensional CGMC simulations of wetting and drying in two systems with pore spaces determined by sections from micro X-ray computed tomography: a system of randomly distributed spheres and a system of Ottawa sand. Results for the phase distribution, water uptake, and matric suction when corrected for extending to three dimensions show excellent agreement with experimental measurements on the same systems. This supports the hypothesis that CGMC can generate metastable configurations representative of experimental hysteresis and can also be used to predict hysteretic constitutive properties of particular experimental systems, given pore space images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zeidman, Benjamin D.; Lu, Ning; Wu, David T., E-mail: dwu@mines.edu
2016-05-07
The effects of path-dependent wetting and drying manifest themselves in many types of physical systems, including nanomaterials, biological systems, and porous media such as soil. It is desirable to better understand how these hysteretic macroscopic properties result from a complex interplay between gasses, liquids, and solids at the pore scale. Coarse-Grained Monte Carlo (CGMC) is an appealing approach to model these phenomena in complex pore spaces, including ones determined experimentally. We present two-dimensional CGMC simulations of wetting and drying in two systems with pore spaces determined by sections from micro X-ray computed tomography: a system of randomly distributed spheres andmore » a system of Ottawa sand. Results for the phase distribution, water uptake, and matric suction when corrected for extending to three dimensions show excellent agreement with experimental measurements on the same systems. This supports the hypothesis that CGMC can generate metastable configurations representative of experimental hysteresis and can also be used to predict hysteretic constitutive properties of particular experimental systems, given pore space images.« less
In silico assembly and nanomechanical characterization of carbon nanotube buckypaper.
Cranford, Steven W; Buehler, Markus J
2010-07-02
Carbon nanotube sheets or films, also known as 'buckypaper', have been proposed for use in actuating, structural and filtration systems, based in part on their unique and robust mechanical properties. Computational modeling of such a fibrous nanostructure is hindered by both the random arrangement of the constituent elements as well as the time- and length-scales accessible to atomistic level molecular dynamics modeling. Here we present a novel in silico assembly procedure based on a coarse-grain model of carbon nanotubes, used to attain a representative mesoscopic buckypaper model that circumvents the need for probabilistic approaches. By variation in assembly parameters, including the initial nanotube density and ratio of nanotube type (single- and double-walled), the porosity of the resulting buckypaper can be varied threefold, from approximately 0.3 to 0.9. Further, through simulation of nanoindentation, the Young's modulus is shown to be tunable through manipulation of nanotube type and density over a range of approximately 0.2-3.1 GPa, in good agreement with experimental findings of the modulus of assembled carbon nanotube films. In addition to carbon nanotubes, the coarse-grain model and assembly process can be adapted for other fibrous nanostructures such as electrospun polymeric composites, high performance nonwoven ballistic materials, or fibrous protein aggregates, facilitating the development and characterization of novel nanomaterials and composites as well as the analysis of biological materials such as protein fiber films and bulk structures.
Stochastic entangled chain dynamics of dense polymer solutions.
Kivotides, Demosthenes; Wilkin, S Louise; Theofanous, Theo G
2010-10-14
We propose an adjustable-parameter-free, entangled chain dynamics model of dense polymer solutions. The model includes the self-consistent dynamics of molecular chains and solvent by describing the former via coarse-grained polymer dynamics that incorporate hydrodynamic interaction effects, and the latter via the forced Stokes equation. Real chain elasticity is modeled via the inclusion of a Pincus regime in the polymer's force-extension curve. Excluded volume effects are taken into account via the combined action of coarse-grained intermolecular potentials and explicit geometric tracking of chain entanglements. We demonstrate that entanglements are responsible for a new (compared to phantom chain dynamics), slow relaxation mode whose characteristic time scale agrees very well with experiment. Similarly good agreement between theory and experiment is also obtained for the equilibrium chain size. We develop methods for the solution of the model in periodic flow domains and apply them to the computation of entangled polymer solutions in equilibrium. We show that the number of entanglements Π agrees well with the number of entanglements expected on the basis of tube theory, satisfactorily reproducing the latter's scaling of Π with the polymer volume fraction φ. Our model predicts diminishing chain size with concentration, thus vindicating Flory's suggestion of excluded volume effects screening in dense solutions. The predicted scaling of chain size with φ is consistent with the heuristic, Flory theory based value.
In silico assembly and nanomechanical characterization of carbon nanotube buckypaper
NASA Astrophysics Data System (ADS)
Cranford, Steven W.; Buehler, Markus J.
2010-07-01
Carbon nanotube sheets or films, also known as 'buckypaper', have been proposed for use in actuating, structural and filtration systems, based in part on their unique and robust mechanical properties. Computational modeling of such a fibrous nanostructure is hindered by both the random arrangement of the constituent elements as well as the time- and length-scales accessible to atomistic level molecular dynamics modeling. Here we present a novel in silico assembly procedure based on a coarse-grain model of carbon nanotubes, used to attain a representative mesoscopic buckypaper model that circumvents the need for probabilistic approaches. By variation in assembly parameters, including the initial nanotube density and ratio of nanotube type (single- and double-walled), the porosity of the resulting buckypaper can be varied threefold, from approximately 0.3 to 0.9. Further, through simulation of nanoindentation, the Young's modulus is shown to be tunable through manipulation of nanotube type and density over a range of approximately 0.2-3.1 GPa, in good agreement with experimental findings of the modulus of assembled carbon nanotube films. In addition to carbon nanotubes, the coarse-grain model and assembly process can be adapted for other fibrous nanostructures such as electrospun polymeric composites, high performance nonwoven ballistic materials, or fibrous protein aggregates, facilitating the development and characterization of novel nanomaterials and composites as well as the analysis of biological materials such as protein fiber films and bulk structures.
Interwell Connectivity Evaluation Using Injection and Production Fluctuation Data
NASA Astrophysics Data System (ADS)
Shang, Barry Zhongqi
The development of multiscale methods for computational simulation of biophysical systems represents a significant challenge. Effective computational models that bridge physical insights obtained from atomistic simulations and experimental findings are lacking. An accurate passing of information between these scales would enable: (1) an improved physical understanding of structure-function relationships, and (2) enhanced rational strategies for molecular engineering and materials design. Two approaches are described in this dissertation to facilitate these multiscale goals. In Part I, we develop a lattice kinetic Monte Carlo model to simulate cellulose decomposition by cellulase enzymes and to understand the effects of spatial confinement on enzyme kinetics. An enhanced mechanistic understanding of this reaction system could enhance the design of cellulose bioconversion technologies for renewable and sustainable energy. Using our model, we simulate the reaction up to experimental conversion times of days, while simultaneously capturing the microscopic kinetic behaviors. Therefore, the influence of molecular-scale kinetics on the macroscopic conversion rate is made transparent. The inclusion of spatial constraints in the kinetic model represents a significant advance over classical mass-action models commonly used to describe this reaction system. We find that restrictions due to enzyme jamming and substrate heterogeneity at the molecular level play a dominate role in limiting cellulose conversion. We identify that the key rate limitations are the slow rates of enzyme complexation with glucan chains and the competition between enzyme processivity and jamming. We show that the kinetics of complexation, which involves extraction of a glucan chain end from the cellulose surface and threading through the enzyme active site, occurs slowly on the order of hours, while intrinsic hydrolytic bond cleavage occurs on the order of seconds. We also elucidate the subtle trade-off between processivity and jamming. Highly processive enzymes cleave a large fraction of a glucan chain during each processive run but are prone to jamming at obstacles. Less processive enzymes avoid jamming but cleave only a small fraction of a chain. Optimizing this trade-off maximizes the cellulose conversion rate. We also elucidate the molecular-scale kinetic origins for synergy among cellulases in enzyme mixtures. In contrast to the currently accepted theory, we show that the ability of an endoglucanase to increase the concentration of chain ends for exoglucanases is insufficient for synergy to occur. Rather, endoglucanases must enhance the rate of complexation between exoglucanases and the newly created chain ends. This enhancement occurs when the endoglucanase is able to partially decrystallize the cellulose surface. We show generally that the driving forces for complexation and jamming, which govern the kinetics of pure exoglucanases, also control the degree of synergy in endo-exo mixtures. In Part II, we focus our attention on a different multiscale problem. This challenge is the development of coarse-grained models from atomistic models to access larger length- and time-scales in a simulation. This problem is difficult because it requires a delicate balance between maintaining (1) physical simplicity in the coarse-grained model and (2) physical consistency with the atomistic model. To achieve these goals, we develop a scheme to coarse-grain an atomistic fluid model into a fluctuating hydrodynamics (FHD) model. The FHD model describes the solvent as a field of fluctuating mass, momentum, and energy densities. The dynamics of the fluid are governed by continuum balance equations and fluctuation-dissipation relations based on the constitutive transport laws. The incorporation of both macroscopic transport and microscopic fluctuation phenomena could provide richer physical insight into the behaviors of biophysical systems driven by hydrodynamic fluctuations, such as hydrophobic assembly and crystal nucleation. We further extend our coarse-graining method by developing an interfacial FHD model using information obtained from simulations of an atomistic liquid-vapor interface. We illustrate that a phenomenological Ginzburg-Landau free energy employed in the FHD model can effectively represent the attractive molecular interactions of the atomistic model, which give rise to phase separation. For argon and water, we show that the interfacial FHD model can reproduce the compressibility, surface tension, and capillary wave spectrum of the atomistic model. Via this approach, simulations that explore the coupling between hydrodynamic fluctuations and phase equilibria with molecular-scale consistency are now possible. In both Parts I and II, the emerging theme is that the combination of bottom-up coarse graining and top-down phenomenology is essential for enabling a multiscale approach to remain physically consistent with molecular-scale interactions while simultaneously capturing the collective macroscopic behaviors. This hybrid strategy enables the resulting computational models to be both physically insightful and practically meaningful. (Abstract shortened by UMI.).
Transport of Chemotactic Bacteria in Porous Media with Structured Heterogeneity
NASA Astrophysics Data System (ADS)
Ford, R. M.; Wang, M.; Liu, J.; Long, T.
2008-12-01
Chemical contaminants that become trapped in low permeability zones (e.g. clay lenses) are difficult to remediate using conventional pump-and-treat approaches. Chemotactic bacteria that are transported by groundwater through more permeable regions may migrate toward these less permeable zones in response to chemical gradients created by contaminant diffusion from the low permeability source, thereby enhancing the remediation process by directing bacteria to the contaminants they degrade. What effect does the heterogeneity associated with coarse- and fine-grained layers that are characteristic of natural groundwater environments have on the transport of microorganisms and their chemotactic response? To address this question experiments were conducted over a range of scales from a single capillary tube to a laboratory- scale column in both static and flowing systems with and without chemoattractant gradients. In static capillary assays, motile bacteria accumulated at the interface between an aqueous solution and a suspension of agarose particulates. In microfluidic devices with an array of staggered cylinders, chemotactic bacteria migrated transverse to flow in response to a chemoattractant gradient. In sand columns packed with a coarse-grained core and surrounded by a fine-grained annulus, chemotactic bacteria migrated preferentially toward a chemoattractant source along the centerline. Mathematical models and computer simulations were developed to analyze the experimental observations in terms of transport parameters from the advection- disperson-sorption equation.
On the representability problem and the physical meaning of coarse-grained models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wagner, Jacob W.; Dama, James F.; Durumeric, Aleksander E. P.
2016-07-28
In coarse-grained (CG) models where certain fine-grained (FG, i.e., atomistic resolution) observables are not directly represented, one can nonetheless identify indirect the CG observables that capture the FG observable’s dependence on CG coordinates. Often, in these cases it appears that a CG observable can be defined by analogy to an all-atom or FG observable, but the similarity is misleading and significantly undermines the interpretation of both bottom-up and top-down CG models. Such problems emerge especially clearly in the framework of the systematic bottom-up CG modeling, where a direct and transparent correspondence between FG and CG variables establishes precise conditions formore » consistency between CG observables and underlying FG models. Here we present and investigate these representability challenges and illustrate them via the bottom-up conceptual framework for several simple analytically tractable polymer models. The examples provide special focus on the observables of configurational internal energy, entropy, and pressure, which have been at the root of controversy in the CG literature, as well as discuss observables that would seem to be entirely missing in the CG representation but can nonetheless be correlated with CG behavior. Though we investigate these problems in the framework of systematic coarse-graining, the lessons apply to top-down CG modeling also, with crucial implications for simulation at constant pressure and surface tension and for the interpretations of structural and thermodynamic correlations for comparison to experiment.« less
NASA Astrophysics Data System (ADS)
Jiang, Feng; Gu, Qing; Hao, Huizhen; Li, Na; Wang, Bingqian; Hu, Xiumian
2018-06-01
Automatic grain segmentation of sandstone is to partition mineral grains into separate regions in the thin section, which is the first step for computer aided mineral identification and sandstone classification. The sandstone microscopic images contain a large number of mixed mineral grains where differences among adjacent grains, i.e., quartz, feldspar and lithic grains, are usually ambiguous, which make grain segmentation difficult. In this paper, we take advantage of multi-angle cross-polarized microscopic images and propose a method for grain segmentation with high accuracy. The method consists of two stages, in the first stage, we enhance the SLIC (Simple Linear Iterative Clustering) algorithm, named MSLIC, to make use of multi-angle images and segment the images as boundary adherent superpixels. In the second stage, we propose the region merging technique which combines the coarse merging and fine merging algorithms. The coarse merging merges the adjacent superpixels with less evident boundaries, and the fine merging merges the ambiguous superpixels using the spatial enhanced fuzzy clustering. Experiments are designed on 9 sets of multi-angle cross-polarized images taken from the three major types of sandstones. The results demonstrate both the effectiveness and potential of the proposed method, comparing to the available segmentation methods.
Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely
2013-02-05
The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.
Multidisciplinary Optimization Methods for Aircraft Preliminary Design
NASA Technical Reports Server (NTRS)
Kroo, Ilan; Altus, Steve; Braun, Robert; Gage, Peter; Sobieski, Ian
1994-01-01
This paper describes a research program aimed at improved methods for multidisciplinary design and optimization of large-scale aeronautical systems. The research involves new approaches to system decomposition, interdisciplinary communication, and methods of exploiting coarse-grained parallelism for analysis and optimization. A new architecture, that involves a tight coupling between optimization and analysis, is intended to improve efficiency while simplifying the structure of multidisciplinary, computation-intensive design problems involving many analysis disciplines and perhaps hundreds of design variables. Work in two areas is described here: system decomposition using compatibility constraints to simplify the analysis structure and take advantage of coarse-grained parallelism; and collaborative optimization, a decomposition of the optimization process to permit parallel design and to simplify interdisciplinary communication requirements.
Dynamics in entangled polyethylene melts using coarse-grained models
NASA Astrophysics Data System (ADS)
Peters, Brandon L.; Grest, Gary S.; Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora
Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion on multiple length scales. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using polyethylene (PE) as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion (iBi) with 2-6 methyl groups per CG bead from all fully atomistic melt simulations for short chains. While the iBi methods produces non-bonded potentials which give excellent agreement for the atomistic and CG pair correlation functions, the pressure P = 100-500MPa for the CG model. Correcting for potential so P 0 leads to non-bonded models with slightly smaller effective diameter and much deeper minimum. However, both the pressure and non-pressure corrected CG models give similar results for mean squared displacement (MSD) and the stress auto correlation function G(t) for PE melts above the melting point. The time rescaling factor between CG and atomistic models is found to be nearly the same for both CG models. Transferability of potential for different temperatures was tested by comparing the MSD and G(t) for potentials generated at different temperatures.
Weak Galilean invariance as a selection principle for coarse-grained diffusive models.
Cairoli, Andrea; Klages, Rainer; Baule, Adrian
2018-05-29
How does the mathematical description of a system change in different reference frames? Galilei first addressed this fundamental question by formulating the famous principle of Galilean invariance. It prescribes that the equations of motion of closed systems remain the same in different inertial frames related by Galilean transformations, thus imposing strong constraints on the dynamical rules. However, real world systems are often described by coarse-grained models integrating complex internal and external interactions indistinguishably as friction and stochastic forces. Since Galilean invariance is then violated, there is seemingly no alternative principle to assess a priori the physical consistency of a given stochastic model in different inertial frames. Here, starting from the Kac-Zwanzig Hamiltonian model generating Brownian motion, we show how Galilean invariance is broken during the coarse-graining procedure when deriving stochastic equations. Our analysis leads to a set of rules characterizing systems in different inertial frames that have to be satisfied by general stochastic models, which we call "weak Galilean invariance." Several well-known stochastic processes are invariant in these terms, except the continuous-time random walk for which we derive the correct invariant description. Our results are particularly relevant for the modeling of biological systems, as they provide a theoretical principle to select physically consistent stochastic models before a validation against experimental data.
The mechanical behavior of metal alloys with grain size distribution in a wide range of strain rates
NASA Astrophysics Data System (ADS)
Skripnyak, V. A.; Skripnyak, V. V.; Skripnyak, E. G.
2017-12-01
The paper discusses a multiscale simulation approach for the construction of grain structure of metals and alloys, providing high tensile strength with ductility. This work compares the mechanical behavior of light alloys and the influence of the grain size distribution in a wide range of strain rates. The influence of the grain size distribution on the inelastic deformation and fracture of aluminium and magnesium alloys is investigated by computer simulations in a wide range of strain rates. It is shown that the yield stress depends on the logarithm of the normalized strain rate for light alloys with a bimodal grain distribution and coarse-grained structure.
Role of Grain Boundaries under Long-Time Radiation
NASA Astrophysics Data System (ADS)
Zhu, Yichao; Luo, Jing; Guo, Xu; Xiang, Yang; Chapman, Stephen Jonathan
2018-06-01
Materials containing a high proportion of grain boundaries offer significant potential for the development of radiation-resistant structural materials. However, a proper understanding of the connection between the radiation-induced microstructural behavior of a grain boundary and its impact at long natural time scales is still missing. In this Letter, point defect absorption at interfaces is summarized by a jump Robin-type condition at a coarse-grained level, wherein the role of interface microstructure is effectively taken into account. Then a concise formula linking the sink strength of a polycrystalline aggregate with its grain size is introduced and is well compared with experimental observation. Based on the derived model, a coarse-grained formulation incorporating the coupled evolution of grain boundaries and point defects is proposed, so as to underpin the study of long-time morphological evolution of grains induced by irradiation. Our simulation results suggest that the presence of point defect sources within a grain further accelerates its shrinking process, and radiation tends to trigger the extension of twin boundary sections.
Na, Hyuntae; Song, Guang
2015-07-01
In a recent work we developed a method for deriving accurate simplified models that capture the essentials of conventional all-atom NMA and identified two best simplified models: ssNMA and eANM, both of which have a significantly higher correlation with NMA in mean square fluctuation calculations than existing elastic network models such as ANM and ANMr2, a variant of ANM that uses the inverse of the squared separation distances as spring constants. Here, we examine closely how the performance of these elastic network models depends on various factors, namely, the presence of hydrogen atoms in the model, the quality of input structures, and the effect of crystal packing. The study reveals the strengths and limitations of these models. Our results indicate that ssNMA and eANM are the best fine-grained elastic network models but their performance is sensitive to the quality of input structures. When the quality of input structures is poor, ANMr2 is a good alternative for computing mean-square fluctuations while ANM model is a good alternative for obtaining normal modes. © 2015 Wiley Periodicals, Inc.
Reproductive Potential of Salmon Spawning Substrates Inferred from Grain Size and Fish Length
NASA Astrophysics Data System (ADS)
Riebe, C. S.; Sklar, L. S.; Overstreet, B. T.; Wooster, J. K.; Bellugi, D. G.
2014-12-01
The river restoration industry spends millions of dollars every year on improving salmon spawning in riverbeds where sediment is too big for fish to move and thus use during redd building. However, few studies have addressed the question of how big is too big in salmon spawning substrates. Hence managers have had little quantitative basis for gauging the amount of spawning habitat in coarse-bedded rivers. Moreover, the scientific framework has remained weak for restoration projects that seek to improve spawning conditions. To overcome these limitations, we developed a physically based, field-calibrated model for the fraction of the bed that is fine-grained enough to support spawning by fish of a given size. Model inputs are fish length and easy-to-measure indices of bed-surface grain size. Model outputs include the number of redds and eggs the substrate can accommodate when flow depth, temperature, and other environmental factors are not limiting. The mechanistic framework of the model captures the biophysical limits on sediment movement and the space limitations on redd building and egg deposition in riverbeds. We explored the parameter space of the model and found a previously unrecognized tradeoff in salmon size: bigger fish can move larger sediment and thus use more riverbed area for spawning; they also tend to have higher fecundity, and so can deposit more eggs per redd; however, because redd area increases with fish length, the number of eggs a substrate can accommodate is highest for moderate-sized fish. One implication of this tradeoff is that differences in grain size may help regulate river-to-river differences in salmon size. Thus, our model suggests that population diversity and, by extension, species resilience are linked to lithologic, geomorphic, and climatic factors that determine grain size in rivers. We cast the model into easy-to-use look-up tables, charts, and computer applications, including a JavaScript app that works on tablets and mobile phones. We explain how these tools can be used in a new, mechanistic approach to assessing spawning substrates and optimizing gravel augmentation projects in coarse-bedded rivers.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heinemann, Thomas, E-mail: thomas.heinemann@tu-berlin.de; Klapp, Sabine H. L., E-mail: klapp@physik.tu-berlin.de; Palczynski, Karol, E-mail: karol.palczynski@helmholtz-berlin.de
We present an approach for calculating coarse-grained angle-resolved effective pair potentials for uniaxial molecules. For integrating out the intramolecular degrees of freedom we apply umbrella sampling and steered dynamics techniques in atomistically-resolved molecular dynamics (MD) computer simulations. Throughout this study we focus on disk-like molecules such as coronene. To develop the methods we focus on integrating out the van der Waals and intramolecular interactions, while electrostatic charge contributions are neglected. The resulting coarse-grained pair potential reveals a strong temperature and angle dependence. In the next step we fit the numerical data with various Gay-Berne-like potentials to be used in moremore » efficient simulations on larger scales. The quality of the resulting coarse-grained results is evaluated by comparing their pair and many-body structure as well as some thermodynamic quantities self-consistently to the outcome of atomistic MD simulations of many-particle systems. We find that angle-resolved potentials are essential not only to accurately describe crystal structures but also for fluid systems where simple isotropic potentials start to fail already for low to moderate packing fractions. Further, in describing these states it is crucial to take into account the pronounced temperature dependence arising in selected pair configurations due to bending fluctuations.« less
Kelp, cobbles, and currents: Biologic reduction of coarse grain entrainment stress
Masteller, Claire C; Finnegan, Noah J; Warrick, Jonathan; Miller, Ian M.
2015-01-01
Models quantifying the onset of sediment motion do not typically account for the effect of biotic processes because they are difficult to isolate and quantify in relation to physical processes. Here we investigate an example of the interaction of kelp (Order Laminariales) and coarse sediment transport in the coastal zone, where it is possible to directly quantify and test its effect. Kelp is ubiquitous along rocky coastlines and the impact on ecosystems has been well studied. We develop a physical model to explore the reduction in critical shear stress of large cobbles colonized by Nereocystis luetkeana, or bull kelp. Observations of coarse sediment motion at a site in the Strait of Juan de Fuca (northwest United States–Canada boundary channel) confirm the model prediction and show that kelp reduces the critical stress required for transport of a given grain size by as much as 92%, enabling annual coarse sediment transport rates comparable to those of fluvial systems. We demonstrate that biology is fundamental to the physical processes that shape the coastal zone in this setting.
Gray, Alan; Harlen, Oliver G; Harris, Sarah A; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J; Pearson, Arwen R; Read, Daniel J; Richardson, Robin A
2015-01-01
Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.
Automated optimization of water-water interaction parameters for a coarse-grained model.
Fogarty, Joseph C; Chiu, See-Wing; Kirby, Peter; Jakobsson, Eric; Pandit, Sagar A
2014-02-13
We have developed an automated parameter optimization software framework (ParOpt) that implements the Nelder-Mead simplex algorithm and applied it to a coarse-grained polarizable water model. The model employs a tabulated, modified Morse potential with decoupled short- and long-range interactions incorporating four water molecules per interaction site. Polarizability is introduced by the addition of a harmonic angle term defined among three charged points within each bead. The target function for parameter optimization was based on the experimental density, surface tension, electric field permittivity, and diffusion coefficient. The model was validated by comparison of statistical quantities with experimental observation. We found very good performance of the optimization procedure and good agreement of the model with experiment.
Magma Mixing: Magmatic Enclaves in Morne Micotrin, Dominica
NASA Astrophysics Data System (ADS)
Hickernell, S.; Frey, H. M.; Manon, M. R. F.; Waters, L. E.
2017-12-01
Magmatic enclaves in volcanic rocks provide direct evidence of magma mingling/mixing within a magma reservoir and may reinvigorate the system and trigger eruption, as documented at the Soufriere Hills in Montserrat. Lava domes on the neighboring island of Dominica also contain multiple enclave populations and may be evidence for similar magma chamber processes. The central dome of Micotrin is at the head of the Roseau Valley, which was filled with 3 km3 of pyroclastic deposits from eruptions spanning 65 - 25 ka. There appear to be two distinct types of enclaves in the crystal-rich Micotrin andesites (60 wt% SiO2), fine-grained and coarse-grained. Fine-grained mafic enclaves (52 wt% SiO2) vary in size from 1 to 15 cm in diameter, whereas the coarse-grained enclaves are generally larger and range from 3-20 cm. Fine-grained enclaves are saturated in plag (35%) + opx (35%) + cpx (20%) + oxides (10%). Average pyroxenes are 0.01 to 0.02 cm in size, whereas plagioclase averages 0.05 cm and up to 0.1 cm. The texture of the fine-grained enclaves is cumulate-like, devoid of microlites and matrix glass. Coarse-grained enclaves lack cpx and have different modal abundances and textures: plag (75%) + opx (10%) + oxides (5%) + plag microlites (10%). Plagioclase are 0.1 cm in size and orthopyroxenes average 0.05 cm. The coarse-grained enclaves are highly vesicular, a notable difference from the host as well as the fine-grained enclaves. The boundaries of both the fine- and coarse-grained enclaves are quite sharp and distinct and there do not appear to be enclave minerals disaggregated in the host rock. Temperatures were determined by two oxides. The fine-grained enclaves had two populations of magnetite, yielding 847 + 21° and 920 + 17°C. The coarse-grained enclave was 890 + 42 °C, but the oxides were extensively exsolved. Plagioclase composition in both coarse and fine-grained samples was comparable, ranging from An50 to An80. Despite compositional similarity the textures of the plagioclase are distinctive. Fine-grained enclave plagioclase has patchy, uneven zoning, whereas coarse-grained enclave plagioclase has oscillatory zoning. The presence of these enclaves indicates that there may be several different magma inputs contributing to the system that is feeding Micotrin, and the injection of these unique magmas may be eruption triggers.
Mutually unbiased coarse-grained measurements of two or more phase-space variables
NASA Astrophysics Data System (ADS)
Paul, E. C.; Walborn, S. P.; Tasca, D. S.; Rudnicki, Łukasz
2018-05-01
Mutual unbiasedness of the eigenstates of phase-space operators—such as position and momentum, or their standard coarse-grained versions—exists only in the limiting case of infinite squeezing. In Phys. Rev. Lett. 120, 040403 (2018), 10.1103/PhysRevLett.120.040403, it was shown that mutual unbiasedness can be recovered for periodic coarse graining of these two operators. Here we investigate mutual unbiasedness of coarse-grained measurements for more than two phase-space variables. We show that mutual unbiasedness can be recovered between periodic coarse graining of any two nonparallel phase-space operators. We illustrate these results through optics experiments, using the fractional Fourier transform to prepare and measure mutually unbiased phase-space variables. The differences between two and three mutually unbiased measurements is discussed. Our results contribute to bridging the gap between continuous and discrete quantum mechanics, and they could be useful in quantum-information protocols.
Space Debris Detection on the HPDP, a Coarse-Grained Reconfigurable Array Architecture for Space
NASA Astrophysics Data System (ADS)
Suarez, Diego Andres; Bretz, Daniel; Helfers, Tim; Weidendorfer, Josef; Utzmann, Jens
2016-08-01
Stream processing, widely used in communications and digital signal processing applications, requires high- throughput data processing that is achieved in most cases using Application-Specific Integrated Circuit (ASIC) designs. Lack of programmability is an issue especially in space applications, which use on-board components with long life-cycles requiring applications updates. To this end, the High Performance Data Processor (HPDP) architecture integrates an array of coarse-grained reconfigurable elements to provide both flexible and efficient computational power suitable for stream-based data processing applications in space. In this work the capabilities of the HPDP architecture are demonstrated with the implementation of a real-time image processing algorithm for space debris detection in a space-based space surveillance system. The implementation challenges and alternatives are described making trade-offs to improve performance at the expense of negligible degradation of detection accuracy. The proposed implementation uses over 99% of the available computational resources. Performance estimations based on simulations show that the HPDP can amply match the application requirements.
NASA Astrophysics Data System (ADS)
Malinverno, Alberto; Goldberg, David S.
2015-07-01
Methane gas hydrates in marine sediments often concentrate in coarse-grained layers surrounded by fine-grained marine muds that are hydrate-free. Methane in these hydrate deposits is typically microbial, and must have migrated from its source as the coarse-grained sediments contain little or no organic matter. In "long-range" migration, fluid flow through permeable layers transports methane from deeper sources into the gas hydrate stability zone (GHSZ). In "short-range" migration, microbial methane is generated within the GHSZ in fine-grained sediments, where small pore sizes inhibit hydrate formation. Dissolved methane can then diffuse into adjacent sand layers, where pore size does not restrict hydrate formation and hydrates can accumulate. Short-range migration has been used to explain hydrate accumulations in sand layers observed in drill sites on the northern Cascadia margin and in the Gulf of Mexico. Here we test the feasibility of short-range migration in two additional locations, where gas hydrates have been found in coarse-grained volcanic ash layers (Site NGHP-01-17, Andaman Sea, Indian Ocean) and turbidite sand beds (Site IODP-C0002, Kumano forearc basin, Nankai Trough, western Pacific). We apply reaction-transport modeling to calculate dissolved methane concentration and gas hydrate amounts resulting from microbial methane generated within the GHSZ. Model results show that short-range migration of microbial methane can explain the overall amounts of methane hydrate observed at the two sites. Short-range migration has been shown to be feasible in diverse margin environments and is likely to be a widespread methane transport mechanism in gas hydrate systems. It only requires a small amount of organic carbon and sediment sequences consisting of thin coarse-grained layers that can concentrate microbial methane generated within thick fine-grained sediment beds; these conditions are common along continental margins around the globe.
Abbott, Lauren J; Stevens, Mark J
2015-12-28
A coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil-globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomistic simulations.
Introduction of a Classical Level in Quantum Theory
NASA Astrophysics Data System (ADS)
Prosperi, G. M.
2016-11-01
In an old paper of our group in Milano a formalism was introduced for the continuous monitoring of a system during a certain interval of time in the framework of a somewhat generalized approach to quantum mechanics (QM). The outcome was a distribution of probability on the space of all the possible continuous histories of a set of quantities to be considered as a kind of coarse grained approximation to some ordinary quantum observables commuting or not. In fact the main aim was the introduction of a classical level in the context of QM, treating formally a set of basic quantities, to be considered as beables in the sense of Bell, as continuously taken under observation. However the effect of such assumption was a permanent modification of the Liouville-von Neumann equation for the statistical operator by the introduction of a dissipative term which is in conflict with basic conservation rules in all reasonable models we had considered. Difficulties were even encountered for a relativistic extension of the formalism. In this paper I propose a modified version of the original formalism which seems to overcome both difficulties. First I study the simple models of an harmonic oscillator and a free scalar field in which a coarse grain position and a coarse grained field respectively are treated as beables. Then I consider the more realistic case of spinor electrodynamics in which only certain coarse grained electric and magnetic fields are introduced as classical variables and no matter related quantities.
Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent
Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu
2011-01-01
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. PMID:22029338
Coarse graining atomistic simulations of plastically deforming amorphous solids
NASA Astrophysics Data System (ADS)
Hinkle, Adam R.; Rycroft, Chris H.; Shields, Michael D.; Falk, Michael L.
2017-05-01
The primary mode of failure in disordered solids results from the formation and persistence of highly localized regions of large plastic strains known as shear bands. Continuum-level field theories capable of predicting this mechanical response rely upon an accurate representation of the initial and evolving states of the amorphous structure. We perform molecular dynamics simulations of a metallic glass and propose a methodology for coarse graining discrete, atomistic quantities, such as the potential energies of the elemental constituents. A strain criterion is established and used to distinguish the coarse-grained degrees-of-freedom inside the emerging shear band from those of the surrounding material. A signal-to-noise ratio provides a means of evaluating the strength of the signal of the shear band as a function of the coarse graining. Finally, we investigate the effect of different coarse graining length scales by comparing a two-dimensional, numerical implementation of the effective-temperature description in the shear transformation zone (STZ) theory with direct molecular dynamics simulations. These comparisons indicate the coarse graining length scale has a lower bound, above which there is a high level of agreement between the atomistics and the STZ theory, and below which the concept of effective temperature breaks down.
Taylor, P. R.; Baker, R. E.; Simpson, M. J.; Yates, C. A.
2016-01-01
Numerous processes across both the physical and biological sciences are driven by diffusion. Partial differential equations are a popular tool for modelling such phenomena deterministically, but it is often necessary to use stochastic models to accurately capture the behaviour of a system, especially when the number of diffusing particles is low. The stochastic models we consider in this paper are ‘compartment-based’: the domain is discretized into compartments, and particles can jump between these compartments. Volume-excluding effects (crowding) can be incorporated by blocking movement with some probability. Recent work has established the connection between fine- and coarse-grained models incorporating volume exclusion, but only for uniform lattices. In this paper, we consider non-uniform, hybrid lattices that incorporate both fine- and coarse-grained regions, and present two different approaches to describe the interface of the regions. We test both techniques in a range of scenarios to establish their accuracy, benchmarking against fine-grained models, and show that the hybrid models developed in this paper can be significantly faster to simulate than the fine-grained models in certain situations and are at least as fast otherwise. PMID:27383421
Coarse gaining of molecular crystals: limitations imposed by molecular flexibility
NASA Astrophysics Data System (ADS)
Picu, Catalin; Pal, Anirban
Molecular crystals include molecular electronics, energetic materials, pharmaceuticals and some food components. In many of these applications the small scale mechanical behavior of the crystal is important such as for example in energetic materials where detonation is induced by the formation of hot spots which are induced thermomechanically, and in pharmaceuticals where phase stability is critical for the biochemical activity of the drug. Accurate modeling of these processes requires resolving the atomistic scale details of the material. However, the cost of these models is very large due to the complexity of the molecules forming the crystal, and some form of coarse graning is necessary. In this study we identify the limitations imposed by the need to accurately capture molecular flexibility on the development of coarse grained models for the energetic molecular crystal RDX. We define guidelines for the definition of coarse grained models that target elastic and plastic crystal scale properties such as elastic constants, thermal expansion, compressibility, the critical stress for the motion of dislocations (Peierls stress) and the stacking fault energy This work was supported by the ARO through Grant W911NF-09-1-0330 and AFRL through Grant FA8651-16-1-0004.
Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.
Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less
Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts
Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.; ...
2016-10-10
Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, R. B.; Dion, S.; Konigslow, K. von
Self-consistent field theory equations are presented that are suitable for use as a coarse-grained model for DNA coated colloids, polymer-grafted nanoparticles and other systems with approximately isotropic interactions. The equations are generalized for arbitrary numbers of chemically distinct colloids. The advantages and limitations of such a coarse-grained approach for DNA coated colloids are discussed, as are similarities with block copolymer self-assembly. In particular, preliminary results for three species self-assembly are presented that parallel results from a two dimensional ABC triblock copolymer phase. The possibility of incorporating crystallization, dynamics, inverse statistical mechanics and multiscale modelling techniques are discussed.
Application of a coarse-grained model for DNA to homo- and heterogeneous melting equilibria
NASA Astrophysics Data System (ADS)
Tito, Nicholas B.; Stubbs, John M.
2010-01-01
Configurational-bias Monte Carlo simulations were carried out on deoxyribonucleic acid (DNA) decamers using a coarse-grained molecular model. The effects of single mutations on the melting transition were investigated as were heterogeneous systems with immobilization of one strand on a surface, both with and without a spacer. The destabilizing effect of an internal mutation is attributed to a lack of cooperativity, which acts through a hydrogen bonding nucleotide's restriction of the conformational freedom of neighboring bases. A surface-oligomer spacer is necessary for duplex stability with the destabilizing effect of the surface coinciding with the volume it excludes.
Coarse grained modeling of directed assembly to form functional nanoporous films
NASA Astrophysics Data System (ADS)
Al Khatib, Amir
A coarse-grained (CG) simulation of polyethylene glycol (PEG) and Polymethylsilsesquixane nanoparticle (PMSSQ) referred to as (NP) at different sizes and concentrations were done using the Martini coarse-grained (CG) force field. The interactions between CG PEG and CG NP were parameterized from the chemical compound of each molecule and based on Martini force field. NP particles migrates to the surface of the substrate in an agreement with the experimental output at high temperature of 800K. This demonstration of nanoparticles-polymer film to direct it to self-assemble a systematically spatial pattern using the substrate surface energy as the key gating parameter. Validation of the model comparing molecular dynamics simulations with experimental data collected from previous study. NP interaction with the substrate at low interactions energy using Lennard-Johns potential were able to direct the NP to self-assemble in a hexagonal shape up to 4 layers above the substrate. This thesis established that substrate surface energy is a key gating parameter to direct the collective behavior of functional nanoparticles to form thin nanoporous films with spatially predetermined optical/dielectric constants.
Monte-Carlo simulations of a coarse-grained model for α-oligothiophenes
NASA Astrophysics Data System (ADS)
Almutairi, Amani; Luettmer-Strathmann, Jutta
The interfacial layer of an organic semiconductor in contact with a metal electrode has important effects on the performance of thin-film devices. However, the structure of this layer is not easy to model. Oligothiophenes are small, π-conjugated molecules with applications in organic electronics that also serve as small-molecule models for polythiophenes. α-hexithiophene (6T) is a six-ring molecule, whose adsorption on noble metal surfaces has been studied extensively (see, e.g., Ref.). In this work, we develop a coarse-grained model for α-oligothiophenes. We describe the molecules as linear chains of bonded, discotic particles with Gay-Berne potential interactions between non-bonded ellipsoids. We perform Monte Carlo simulations to study the structure of isolated and adsorbed molecules
Czaplewski, Cezary; Karczynska, Agnieszka; Sieradzan, Adam K; Liwo, Adam
2018-04-30
A server implementation of the UNRES package (http://www.unres.pl) for coarse-grained simulations of protein structures with the physics-based UNRES model, coined a name UNRES server, is presented. In contrast to most of the protein coarse-grained models, owing to its physics-based origin, the UNRES force field can be used in simulations, including those aimed at protein-structure prediction, without ancillary information from structural databases; however, the implementation includes the possibility of using restraints. Local energy minimization, canonical molecular dynamics simulations, replica exchange and multiplexed replica exchange molecular dynamics simulations can be run with the current UNRES server; the latter are suitable for protein-structure prediction. The user-supplied input includes protein sequence and, optionally, restraints from secondary-structure prediction or small x-ray scattering data, and simulation type and parameters which are selected or typed in. Oligomeric proteins, as well as those containing D-amino-acid residues and disulfide links can be treated. The output is displayed graphically (minimized structures, trajectories, final models, analysis of trajectory/ensembles); however, all output files can be downloaded by the user. The UNRES server can be freely accessed at http://unres-server.chem.ug.edu.pl.
Chaimovich, Aviel; Shell, M Scott
2009-03-28
Recent efforts have attempted to understand many of liquid water's anomalous properties in terms of effective spherically-symmetric pairwise molecular interactions entailing two characteristic length scales (so-called "core-softened" potentials). In this work, we examine the extent to which such simple descriptions of water are representative of the true underlying interactions by extracting coarse-grained potential functions that are optimized to reproduce the behavior of an all-atom model. To perform this optimization, we use a novel procedure based upon minimizing the relative entropy, a quantity that measures the extent to which a coarse-grained configurational ensemble overlaps with a reference all-atom one. We show that the optimized spherically-symmetric water models exhibit notable variations with the state conditions at which they were optimized, reflecting in particular the shifting accessibility of networked hydrogen bonding interactions. Moreover, we find that water's density and diffusivity anomalies are only reproduced when the effective coarse-grained potentials are allowed to vary with state. Our results therefore suggest that no state-independent spherically-symmetric potential can fully capture the interactions responsible for water's unique behavior; rather, the particular way in which the effective interactions vary with temperature and density contributes significantly to anomalous properties.
Comparison of corrosion behavior between coarse grained and nano/ultrafine grained alloy 690
NASA Astrophysics Data System (ADS)
Jinlong, Lv; Tongxiang, Liang; Chen, Wang; Ting, Guo
2016-01-01
The effect of grain refinement on corrosion resistance of alloy 690 was investigated. The electron work function value of coarse grained alloy 690 was higher than that of nano/ultrafine grained one. The grain refinement reduced the electron work function of alloy 690. The passive films formed on coarse grained and nano/ultrafine grained alloy 690 in borate buffer solution were studied by potentiodynamic curves and electrochemical impedance spectroscopy and X-ray photoelectron spectroscopy. The results showed that the grain refinement improved corrosion resistance of alloy 690. This was attributed to the fact that grain refinement promoted the enrichment of Cr2O3 and inhibited Cr(OH)3 in the passive film. More Cr2O3 in passive film could significantly improve the corrosion resistance of the nano/ultrafine grained alloy 690.
Principles of proteome allocation are revealed using proteomic data and genome-scale models
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.
2016-01-01
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205
Principles of proteome allocation are revealed using proteomic data and genome-scale models
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...
2016-11-18
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less
Development of Coarse Grained Models for Long Chain Alkanes
NASA Astrophysics Data System (ADS)
Gyawali, Gaurav; Sternfield, Samuel; Hwang, In Chul; Rick, Steven; Kumar, Revati; Rick Group Team; Kumar Group Team
Modeling aggregation in aqueous solution is a challenge for molecular simulations as it involves long time scales, a range of length scales, and the correct balance of hydrophobic and hydrophilic interactions. We have developed a coarse-grained model fast enough for the rapid testing of molecular structures for their aggregation properties. This model, using the Stillinger-Weber potential, achieves efficiency through a reduction in the number of interaction sites and the use of short-ranged interactions. The model can be two to three orders of magnitude more efficient than conventional all atom simulations, yet through a careful parameterization process and the use of many-body interactions can be remarkably accurate. We have developed models for long chain alkanes in water that reproduce the thermodynamics and structure of water-alkane and liquid alkane systems.
NASA Astrophysics Data System (ADS)
Deng, Liang; Bai, Hanli; Wang, Fang; Xu, Qingxin
2016-06-01
CPU/GPU computing allows scientists to tremendously accelerate their numerical codes. In this paper, we port and optimize a double precision alternating direction implicit (ADI) solver for three-dimensional compressible Navier-Stokes equations from our in-house Computational Fluid Dynamics (CFD) software on heterogeneous platform. First, we implement a full GPU version of the ADI solver to remove a lot of redundant data transfers between CPU and GPU, and then design two fine-grain schemes, namely “one-thread-one-point” and “one-thread-one-line”, to maximize the performance. Second, we present a dual-level parallelization scheme using the CPU/GPU collaborative model to exploit the computational resources of both multi-core CPUs and many-core GPUs within the heterogeneous platform. Finally, considering the fact that memory on a single node becomes inadequate when the simulation size grows, we present a tri-level hybrid programming pattern MPI-OpenMP-CUDA that merges fine-grain parallelism using OpenMP and CUDA threads with coarse-grain parallelism using MPI for inter-node communication. We also propose a strategy to overlap the computation with communication using the advanced features of CUDA and MPI programming. We obtain speedups of 6.0 for the ADI solver on one Tesla M2050 GPU in contrast to two Xeon X5670 CPUs. Scalability tests show that our implementation can offer significant performance improvement on heterogeneous platform.
A Generic Force Field for Protein Coarse-Grained Molecular Dynamics Simulation
Gu, Junfeng; Bai, Fang; Li, Honglin; Wang, Xicheng
2012-01-01
Coarse-grained (CG) force fields have become promising tools for studies of protein behavior, but the balance of speed and accuracy is still a challenge in the research of protein coarse graining methodology. In this work, 20 CG beads have been designed based on the structures of amino acid residues, with which an amino acid can be represented by one or two beads, and a CG solvent model with five water molecules was adopted to ensure the consistence with the protein CG beads. The internal interactions in protein were classified according to the types of the interacting CG beads, and adequate potential functions were chosen and systematically parameterized to fit the energy distributions. The proposed CG force field has been tested on eight proteins, and each protein was simulated for 1000 ns. Even without any extra structure knowledge of the simulated proteins, the Cα root mean square deviations (RMSDs) with respect to their experimental structures are close to those of relatively short time all atom molecular dynamics simulations. However, our coarse grained force field will require further refinement to improve agreement with and persistence of native-like structures. In addition, the root mean square fluctuations (RMSFs) relative to the average structures derived from the simulations show that the conformational fluctuations of the proteins can be sampled. PMID:23203075
Ziegler, Johannes C; Bertrand, Daisy; Lété, Bernard; Grainger, Jonathan
2014-04-01
The present study used a variant of masked priming to track the development of 2 marker effects of orthographic and phonological processing from Grade 1 through Grade 5 in a cross-sectional study. Pseudohomophone (PsH) priming served as a marker for phonological processing, whereas transposed-letter (TL) priming was a marker for coarse-grained orthographic processing. The results revealed a clear developmental picture. First, the PsH priming effect was significant and remained stable across development, suggesting that phonology not only plays an important role in early reading development but continues to exert a robust influence throughout reading development. This finding challenges the view that more advanced readers should rely less on phonological information than younger readers. Second, the TL priming effect increased monotonically with grade level and reading age, which suggests greater reliance on coarse-grained orthographic coding as children become better readers. Thus, TL priming effects seem to be a good marker effect for children's ability to use coarse-grained orthographic coding to speed up direct lexical access in alphabetic languages. The results were predicted by the dual-route model of orthographic processing, which suggests that direct orthographic access is achieved through coarse-grained orthographic coding that tolerates some degree of flexibility in letter order. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Structure-based coarse-graining for inhomogeneous liquid polymer systems.
Fukuda, Motoo; Zhang, Hedong; Ishiguro, Takahiro; Fukuzawa, Kenji; Itoh, Shintaro
2013-08-07
The iterative Boltzmann inversion (IBI) method is used to derive interaction potentials for coarse-grained (CG) systems by matching structural properties of a reference atomistic system. However, because it depends on such thermodynamic conditions as density and pressure of the reference system, the derived CG nonbonded potential is probably not applicable to inhomogeneous systems containing different density regimes. In this paper, we propose a structure-based coarse-graining scheme to devise CG nonbonded potentials that are applicable to different density bulk systems and inhomogeneous systems with interfaces. Similar to the IBI, the radial distribution function (RDF) of a reference atomistic bulk system is used for iteratively refining the CG nonbonded potential. In contrast to the IBI, however, our scheme employs an appropriately estimated initial guess and a small amount of refinement to suppress transfer of the many-body interaction effects included in the reference RDF into the CG nonbonded potential. To demonstrate the application of our approach to inhomogeneous systems, we perform coarse-graining for a liquid perfluoropolyether (PFPE) film coated on a carbon surface. The constructed CG PFPE model favorably reproduces structural and density distribution functions, not only for bulk systems, but also at the liquid-vacuum and liquid-solid interfaces, demonstrating that our CG scheme offers an easy and practical way to accurately determine nonbonded potentials for inhomogeneous systems.
Nelson, Peter A.; McDonald, Richard R.; Nelson, Jonathan M.; Dietrich, William E.
2015-01-01
Riverbeds frequently display a spatial structure where the sediment mixture composing the channel bed has been sorted into discrete patches of similar grain size. Even though patches are a fundamental feature in gravel bed rivers, we have little understanding of how patches form, evolve, and interact. Here we present a two-dimensional morphodynamic model that is used to examine in greater detail the mechanisms responsible for the development of forced bed surface patches and the coevolution of bed morphology and bed surface patchiness. The model computes the depth-averaged channel hydrodynamics, mixed-grain-size sediment transport, and bed evolution by coupling the river morphodynamic model Flow and Sediment Transport with Morphological Evolution of Channels (FaSTMECH) with a transport relation for gravel mixtures and the mixed-grain-size Exner equation using the active layer assumption. To test the model, we use it to simulate a flume experiment in which the bed developed a sequence of alternate bars and temporally and spatially persistent forced patches with a general pattern of coarse bar tops and fine pools. Cross-stream sediment flux causes sediment to be exported off of bars and imported into pools at a rate that balances downstream gradients in the streamwise sediment transport rate, allowing quasi-steady bar-pool topography to persist. The relative importance of lateral gravitational forces on the cross-stream component of sediment transport is a primary control on the amplitude of the bars. Because boundary shear stress declines as flow shoals over the bars, the lateral sediment transport is increasingly size selective and leads to the development of coarse bar tops and fine pools.
Kilinc, Deniz; Demir, Alper
2017-08-01
The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.
NASA Astrophysics Data System (ADS)
Voepel, Hal; Ahmed, Sharif; Hodge, Rebecca; Leyland, Julian; Sear, David
2016-04-01
Uncertainty in bedload estimates for gravel bed rivers is largely driven by our inability to characterize arrangement, orientation and resultant forces of fluvial sediment in river beds. Water working of grains leads to structural differences between areas of the bed through particle sorting, packing, imbrication, mortaring and degree of bed armoring. In this study, non-destructive, micro-focus X-ray computed tomography (CT) imaging in 3D is used to visualize, quantify and assess the internal geometry of sections of a flume bed that have been extracted keeping their fabric intact. Flume experiments were conducted at 1:1 scaling of our prototype river. From the volume, center of mass, points of contact, and protrusion of individual grains derived from 3D scan data we estimate 3D static force properties at the grain-scale such as pivoting angles, buoyancy and gravity forces, and local grain exposure. Here metrics are derived for images from two flume experiments: one with a bed of coarse grains (>4mm) and the other where sand and clay were incorporated into the coarse flume bed. In addition to deriving force networks, comparison of metrics such as critical shear stress, pivot angles, grain distributions, principle axis orientation, and pore space over depth are made. This is the first time bed stability has been studied in 3D using CT scanned images of sediment from the bed surface to depths well into the subsurface. The derived metrics, inter-granular relationships and characterization of bed structures will lead to improved bedload estimates with reduced uncertainty, as well as improved understanding of relationships between sediment structure, grain size distribution and channel topography.
KOSMOS: a universal morph server for nucleic acids, proteins and their complexes
Seo, Sangjae; Kim, Moon Ki
2012-01-01
KOSMOS is the first online morph server to be able to address the structural dynamics of DNA/RNA, proteins and even their complexes, such as ribosomes. The key functions of KOSMOS are the harmonic and anharmonic analyses of macromolecules. In the harmonic analysis, normal mode analysis (NMA) based on an elastic network model (ENM) is performed, yielding vibrational modes and B-factor calculations, which provide insight into the potential biological functions of macromolecules based on their structural features. Anharmonic analysis involving elastic network interpolation (ENI) is used to generate plausible transition pathways between two given conformations by optimizing a topology-oriented cost function that guarantees a smooth transition without steric clashes. The quality of the computed pathways is evaluated based on their various facets, including topology, energy cost and compatibility with the NMA results. There are also two unique features of KOSMOS that distinguish it from other morph servers: (i) the versatility in the coarse-graining methods and (ii) the various connection rules in the ENM. The models enable us to analyze macromolecular dynamics with the maximum degrees of freedom by combining a variety of ENMs from full-atom to coarse-grained, backbone and hybrid models with one connection rule, such as distance-cutoff, number-cutoff or chemical-cutoff. KOSMOS is available at http://bioengineering.skku.ac.kr/kosmos. PMID:22669912
Quantum decimation in Hilbert space: Coarse graining without structure
NASA Astrophysics Data System (ADS)
Singh, Ashmeet; Carroll, Sean M.
2018-03-01
We present a technique to coarse grain quantum states in a finite-dimensional Hilbert space. Our method is distinguished from other approaches by not relying on structures such as a preferred factorization of Hilbert space or a preferred set of operators (local or otherwise) in an associated algebra. Rather, we use the data corresponding to a given set of states, either specified independently or constructed from a single state evolving in time. Our technique is based on principle component analysis (PCA), and the resulting coarse-grained quantum states live in a lower-dimensional Hilbert space whose basis is defined using the underlying (isometric embedding) transformation of the set of fine-grained states we wish to coarse grain. Physically, the transformation can be interpreted to be an "entanglement coarse-graining" scheme that retains most of the global, useful entanglement structure of each state, while needing fewer degrees of freedom for its reconstruction. This scheme could be useful for efficiently describing collections of states whose number is much smaller than the dimension of Hilbert space, or a single state evolving over time.
Coarse graining Escherichia coli chemotaxis: from multi-flagella propulsion to logarithmic sensing.
Curk, Tine; Matthäus, Franziska; Brill-Karniely, Yifat; Dobnikar, Jure
2012-01-01
Various sensing mechanisms in nature can be described by the Weber-Fechner law stating that the response to varying stimuli is proportional to their relative rather than absolute changes. The chemotaxis of bacteria Escherichia coli is an example where such logarithmic sensing enables sensitivity over large range of concentrations. It has recently been experimentally demonstrated that under certain conditions E. coli indeed respond to relative gradients of ligands. We use numerical simulations of bacteria in food gradients to investigate the limits of validity of the logarithmic behavior. We model the chemotactic signaling pathway reactions, couple them to a multi-flagella model for propelling and take the effects of rotational diffusion into account to accurately reproduce the experimental observations of single cell swimming. Using this simulation scheme we analyze the type of response of bacteria subject to exponential ligand profiles and identify the regimes of absolute gradient sensing, relative gradient sensing, and a rotational diffusion dominated regime. We explore dependance of the swimming speed, average run time and the clockwise (CW) bias on ligand variation and derive a small set of relations that define a coarse grained model for bacterial chemotaxis. Simulations based on this coarse grained model compare well with microfluidic experiments on E. coli diffusion in linear and exponential gradients of aspartate.
Sampling saddle points on a free energy surface
NASA Astrophysics Data System (ADS)
Samanta, Amit; Chen, Ming; Yu, Tang-Qing; Tuckerman, Mark; E, Weinan
2014-04-01
Many problems in biology, chemistry, and materials science require knowledge of saddle points on free energy surfaces. These saddle points act as transition states and are the bottlenecks for transitions of the system between different metastable states. For simple systems in which the free energy depends on a few variables, the free energy surface can be precomputed, and saddle points can then be found using existing techniques. For complex systems, where the free energy depends on many degrees of freedom, this is not feasible. In this paper, we develop an algorithm for finding the saddle points on a high-dimensional free energy surface "on-the-fly" without requiring a priori knowledge the free energy function itself. This is done by using the general strategy of the heterogeneous multi-scale method by applying a macro-scale solver, here the gentlest ascent dynamics algorithm, with the needed force and Hessian values computed on-the-fly using a micro-scale model such as molecular dynamics. The algorithm is capable of dealing with problems involving many coarse-grained variables. The utility of the algorithm is illustrated by studying the saddle points associated with (a) the isomerization transition of the alanine dipeptide using two coarse-grained variables, specifically the Ramachandran dihedral angles, and (b) the beta-hairpin structure of the alanine decamer using 20 coarse-grained variables, specifically the full set of Ramachandran angle pairs associated with each residue. For the alanine decamer, we obtain a detailed network showing the connectivity of the minima obtained and the saddle-point structures that connect them, which provides a way to visualize the gross features of the high-dimensional surface.
NASA Astrophysics Data System (ADS)
Pedraza, A.; Kingsley, C.; Marchitto, T. M., Jr.; Lora, J. M.; Pollen, A.; Vollmer, T.; Leithold, E. L.; Mitchell, J.; Tripati, A. K.; Bhattacharya, A.
2017-12-01
Mineral dust accumulation is often causally associated with aridity. However, the relation might not be as straightforward. Consideration of grain sizes and geochemical fingerprinting of the coarse grain fraction will clearly have an impact on how we interpret the sedimentary record of mineral dust in depositional environments e.g. coarse grain fractions of mineral dust would most certainly be transported over relatively short distances and as such in depositional environments, the depositional rate of coarse grains must be determined in order to reliably understand erosional patterns associated with meteorological events (such as frequency of intense wind events such as tornadoes), climatological phenomenon (such as regional droughts) as well as more recently land-use changes. In this study we separate the two size fractions of mineral dust accumulation- fine fraction (typically <4 microns) and coarse fraction (typically >25 microns using grain size analysis from well-studied cores collected from several lake sites distributed across the western southwestern and the Great Plain regions; furthermore we use trace element analysis in each size fraction to identify contributing source regions. We find evidence that the coarser-grain size fraction in the studied lake cores could be of regional origin (and not just local in orgin);. the coarser fraction also appears to be related to intense meteorological events (i.e., the occurrence of cyclones). Analysis is underway to understand the impact of land-use changes on coarse grain fraction
Coarse-grained model of water diffusion and proton conductivity in hydrated polyelectrolyte membrane
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Ming-Tsung; Vishnyakov, Aleksey; Neimark, Alexander V., E-mail: aneimark@rutgers.edu
2016-01-07
Using dissipative particle dynamics (DPD), we simulate nanoscale segregation, water diffusion, and proton conductivity in hydrated sulfonated polystyrene (sPS). We employ a novel model [Lee et al. J. Chem. Theory Comput. 11(9), 4395-4403 (2015)] that incorporates protonation/deprotonation equilibria into DPD simulations. The polymer and water are modeled by coarse-grained beads interacting via short-range soft repulsion and smeared charge electrostatic potentials. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with the base beads representing water and sulfonate anions. Morse bond formation and breakup artificially mimics the Grotthuss mechanism of proton hopping between the bases. Themore » DPD model is parameterized by matching the proton mobility in bulk water, dissociation constant of benzenesulfonic acid, and liquid-liquid equilibrium of water-ethylbenzene solutions. The DPD simulations semi-quantitatively predict nanoscale segregation in the hydrated sPS into hydrophobic and hydrophilic subphases, water self-diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from isolated water clusters to a 3D network. The analysis of hydrophilic subphase connectivity and water diffusion demonstrates the importance of the dynamic percolation effect of formation and breakup of temporary junctions between water clusters. The proposed DPD model qualitatively predicts the ratio of proton to water self-diffusion and its dependence on the hydration level that is in reasonable agreement with experiments.« less
Dynamics of biomolecular processes
NASA Astrophysics Data System (ADS)
Behringer, Hans; Eichhorn, Ralf; Wallin, Stefan
2013-05-01
The last few years have seen enormous progress in the availability of computational resources, so that the size and complexity of physical systems that can be investigated numerically has increased substantially. The physical mechanisms behind the processes creating life, such as those in a living cell, are of foremost interest in biophysical research. A main challenge here is that complexity not only emerges from interactions of many macro-molecular compounds, but is already evident at the level of a single molecule. An exciting recent development in this context is, therefore, that detailed atomistic level characterization of large-scale dynamics of individual bio-macromolecules, such as proteins and DNA, is starting to become feasible in some cases. This has contributed to a better understanding of the molecular mechanisms of, e.g. protein folding and aggregation, as well as DNA dynamics. Nevertheless, simulations of the dynamical behaviour of complex multicomponent cellular processes at an all-atom level will remain beyond reach for the foreseeable future, and may not even be desirable. Ultimate understanding of many biological processes will require the development of methods targeting different time and length scales and, importantly, ways to bridge these in multiscale approaches. At the scientific programme Dynamics of biomolecular processes: from atomistic representations to coarse-grained models held between 27 February and 23 March 2012, and hosted by the Nordic Institute for Theoretical Physics, new modelling approaches and results for particular biological systems were presented and discussed. The programme was attended by around 30 scientists from the Nordic countries and elsewhere. It also included a PhD and postdoc 'winter school', where basic theoretical concepts and techniques of biomolecular modelling and simulations were presented. One to two decades ago, the biomolecular modelling field was dominated by two widely different and largely independent approaches. On the one hand, computationally convenient and highly simplified lattice models were being used to elucidate the fundamental aspects of biomolecular conformational transitions, such as protein folding. On the other hand, these generic coarse-grained approaches were complemented by atomistic representations of the biomolecules. Physico-chemical all-atom models, often with an explicit representation of the surrounding solvent, were applied to specific protein structures to investigate their detailed dynamical behaviour. Today the situation is strikingly different, as was evident during the programme, where several new efforts were presented that try to combine the atomistic and the generic modelling approaches. The aim is to develop coarse-grained models at an intermediate-level resolution that are detailed enough to study specific biomolecular systems, and yet remain computationally efficient. These attempts are accompanied by the emergence of systematic coarse-graining techniques which bridge the physics of different lengths and timescales in a single simulation dynamically by applying appropriate representations of the associated degrees of freedom. Such adaptive resolution schemes represent promising candidates to tackle systems with an intrinsic multiscale nature, such as hierarchical chains and networks of biochemical reactions on a cellular level, calling for a very detailed description on an atomistic particle (or even quantum) level but simultaneously allowing the investigation of large-scale structuring and transport phenomena. The presentations and discussions during the programme also showed that the numerical evidence from (multiscale) simulations needs to be complemented by analytical and theoretical investigations to provide, eventually, a combined and deepened insight into the properties of biomolecular processes. The contributions from this scientific programme published in this issue of Physica Scripta highlight some of these new developments while also addressing related issues, such as the challenge of achieving efficient conformational sampling for chain molecules, and the interaction of nano-particles with biomolecules. The latter topic is especially timely as nano-particles are currently being considered for use as drug delivery devices, and present concerns about the general safety of their use might be resolved (or substantiated) by studies of this kind. This scientific programme and the contributions presented here were made possible by the financial and administrative support of the Nordic Institute for Theoretical Physics.
Andrews, Casey T; Elcock, Adrian H
2014-11-11
We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions-which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)-quantitatively reproduced all of the "target" MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic ( PLoS Comput. Biol. 2014 , 5 , e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP's nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.
2015-01-01
We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions—which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)—quantitatively reproduced all of the “target” MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic (PLoS Comput. Biol.2014, 5, e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP’s nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins. PMID:25400526
NASA Astrophysics Data System (ADS)
Sieradzan, Adam K.; Makowski, Mariusz; Augustynowicz, Antoni; Liwo, Adam
2017-03-01
A general and systematic method for the derivation of the functional expressions for the effective energy terms in coarse-grained force fields of polymer chains is proposed. The method is based on the expansion of the potential of mean force of the system studied in the cluster-cumulant series and expanding the all-atom energy in the Taylor series in the squares of interatomic distances about the squares of the distances between coarse-grained centers, to obtain approximate analytical expressions for the cluster cumulants. The primary degrees of freedom to average about are the angles for collective rotation of the atoms contained in the coarse-grained interaction sites about the respective virtual-bond axes. The approach has been applied to the revision of the virtual-bond-angle, virtual-bond-torsional, and backbone-local-and-electrostatic correlation potentials for the UNited RESidue (UNRES) model of polypeptide chains, demonstrating the strong dependence of the torsional and correlation potentials on virtual-bond angles, not considered in the current UNRES. The theoretical considerations are illustrated with the potentials calculated from the ab initio potential-energy surface of terminally blocked alanine by numerical integration and with the statistical potentials derived from known protein structures. The revised torsional potentials correctly indicate that virtual-bond angles close to 90° result in the preference for the turn and helical structures, while large virtual-bond angles result in the preference for polyproline II and extended backbone geometry. The revised correlation potentials correctly reproduce the preference for the formation of β-sheet structures for large values of virtual-bond angles and for the formation of α-helical structures for virtual-bond angles close to 90°.
Abbott, Lauren J.; Stevens, Mark J.
2015-12-22
In this study, a coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil–globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomisticmore » simulations.« less
Molecular modeling of polycarbonate materials: Glass transition and mechanical properties
NASA Astrophysics Data System (ADS)
Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim
2017-09-01
Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.
2015-01-01
Using the translocation of short, charged cationic oligo-arginine peptides (mono-, di-, and triarginine) from bulk aqueous solution into model DMPC bilayers, we explore the question of the similarity of thermodynamic and structural predictions obtained from molecular dynamics simulations using all-atom and Martini coarse-grain force fields. Specifically, we estimate potentials of mean force associated with translocation using standard all-atom (CHARMM36 lipid) and polarizable and nonpolarizable Martini force fields, as well as a series of modified Martini-based parameter sets. We find that we are able to reproduce qualitative features of potentials of mean force of single amino acid side chain analogues into model bilayers. In particular, modifications of peptide–water and peptide–membrane interactions allow prediction of free energy minima at the bilayer–water interface as obtained with all-atom force fields. In the case of oligo-arginine peptides, the modified parameter sets predict interfacial free energy minima as well as free energy barriers in almost quantitative agreement with all-atom force field based simulations. Interfacial free energy minima predicted by a modified coarse-grained parameter set are −2.51, −4.28, and −5.42 for mono-, di-, and triarginine; corresponding values from all-atom simulations are −0.83, −3.33, and −3.29, respectively, all in units of kcal/mol. We found that a stronger interaction between oligo-arginine and the membrane components and a weaker interaction between oligo-arginine and water are crucial for producing such minima in PMFs using the polarizable CG model. The difference between bulk aqueous and bilayer center states predicted by the modified coarse-grain force field are 11.71, 14.14, and 16.53 kcal/mol, and those by the all-atom model are 6.94, 8.64, and 12.80 kcal/mol; those are of almost the same order of magnitude. Our simulations also demonstrate a remarkable similarity in the structural aspects of the ensemble of configurations generated using the all-atom and coarse-grain force fields. Both resolutions show that oligo-arginine peptides adopt preferential orientations as they translocate into the bilayer. The guiding theme centers on charged groups maintaining coordination with polar and charged bilayer components as well as local water. We also observe similar behaviors related with membrane deformations. PMID:25290376
Hu, Yuan; Sinha, Sudipta Kumar; Patel, Sandeep
2014-10-16
Using the translocation of short, charged cationic oligo-arginine peptides (mono-, di-, and triarginine) from bulk aqueous solution into model DMPC bilayers, we explore the question of the similarity of thermodynamic and structural predictions obtained from molecular dynamics simulations using all-atom and Martini coarse-grain force fields. Specifically, we estimate potentials of mean force associated with translocation using standard all-atom (CHARMM36 lipid) and polarizable and nonpolarizable Martini force fields, as well as a series of modified Martini-based parameter sets. We find that we are able to reproduce qualitative features of potentials of mean force of single amino acid side chain analogues into model bilayers. In particular, modifications of peptide-water and peptide-membrane interactions allow prediction of free energy minima at the bilayer-water interface as obtained with all-atom force fields. In the case of oligo-arginine peptides, the modified parameter sets predict interfacial free energy minima as well as free energy barriers in almost quantitative agreement with all-atom force field based simulations. Interfacial free energy minima predicted by a modified coarse-grained parameter set are -2.51, -4.28, and -5.42 for mono-, di-, and triarginine; corresponding values from all-atom simulations are -0.83, -3.33, and -3.29, respectively, all in units of kcal/mol. We found that a stronger interaction between oligo-arginine and the membrane components and a weaker interaction between oligo-arginine and water are crucial for producing such minima in PMFs using the polarizable CG model. The difference between bulk aqueous and bilayer center states predicted by the modified coarse-grain force field are 11.71, 14.14, and 16.53 kcal/mol, and those by the all-atom model are 6.94, 8.64, and 12.80 kcal/mol; those are of almost the same order of magnitude. Our simulations also demonstrate a remarkable similarity in the structural aspects of the ensemble of configurations generated using the all-atom and coarse-grain force fields. Both resolutions show that oligo-arginine peptides adopt preferential orientations as they translocate into the bilayer. The guiding theme centers on charged groups maintaining coordination with polar and charged bilayer components as well as local water. We also observe similar behaviors related with membrane deformations.
Self-assembly of Spherical Macroions in Solution: A Coarse-grained Molecular Dynamics Study
NASA Astrophysics Data System (ADS)
Liu, Zhuonan; Liu, Tianbo; Tsige, Mesfin
2015-03-01
Macroions (such as polyoxometalates) in solution can form a stable hollow spherical super-molecular structure called blackberry when they have moderate surface charge density and size (1-10 nm). Depending on the surface charge density of macroions, the size of the blackberry can be from 20 to more than 100 nm. Other macroions such as dendrimers can also self-assemble into similar super-molecular structure in solution. Existing theories such as Debye-Hückel and DLVO theories cannot explain this phenomenon and we are not aware of any other theory that can explain this. Previous studies using all-atom Molecular Dynamics simulations have shown identical macroions forming oligomers mediated by counterions. Due to the limitations in all-atom simulation and available computational capabilities, these studies handled only small systems with simple macroions, leading to less conclusive but still relevant results on the self-assembly behavior. To overcome these limitations, in this work large-scale coarse-grained modeling of macroions in solution is used. In order to understand the origin of the attractive force that is responsible for the self-assembly of macroions, different types of macroions in different solution conditions are studied. This work was supported by NSF Grant DMR0847580.
NASA Astrophysics Data System (ADS)
Fattah-alhosseini, Arash; Imantalab, Omid; Attarzadeh, Farid Reza
2016-10-01
Electrochemical behavior of coarse- and nano-grained pure copper were modified and improved to a large extent by the application of cyclic potentiodynamic passivation. The efficacy of this method was evaluated on the basis of grain size which is of great importance in corrosion studies. In this study, the eight passes of accumulative roll bonding process at room temperature were successfully performed to produce nano-grained pure copper. Transmission electron microscopy image indicated that the average grain size reached below 100 nm after eight passes. On the basis of cyclic voltammetry and also the electrochemical tests performed after that, it was revealed that cyclic potentiodynamic passivation had a significant improving effect on the passive behavior of both coarse- and nano-grained samples. In addition, a superior behavior of nano-grained sample in comparison to coarse-grained one was distinguished by its smaller cyclic voltammogram loops, nobler free potentials, larger capacitive arcs in the Nyquist plots, and less charge carrier densities within the passive film.
Grain coarsening in two-dimensional phase-field models with an orientation field
NASA Astrophysics Data System (ADS)
Korbuly, Bálint; Pusztai, Tamás; Henry, Hervé; Plapp, Mathis; Apel, Markus; Gránásy, László
2017-05-01
In the literature, contradictory results have been published regarding the form of the limiting (long-time) grain size distribution (LGSD) that characterizes the late stage grain coarsening in two-dimensional and quasi-two-dimensional polycrystalline systems. While experiments and the phase-field crystal (PFC) model (a simple dynamical density functional theory) indicate a log-normal distribution, other works including theoretical studies based on conventional phase-field simulations that rely on coarse grained fields, like the multi-phase-field (MPF) and orientation field (OF) models, yield significantly different distributions. In a recent work, we have shown that the coarse grained phase-field models (whether MPF or OF) yield very similar limiting size distributions that seem to differ from the theoretical predictions. Herein, we revisit this problem, and demonstrate in the case of OF models [R. Kobayashi, J. A. Warren, and W. C. Carter, Physica D 140, 141 (2000), 10.1016/S0167-2789(00)00023-3; H. Henry, J. Mellenthin, and M. Plapp, Phys. Rev. B 86, 054117 (2012), 10.1103/PhysRevB.86.054117] that an insufficient resolution of the small angle grain boundaries leads to a log-normal distribution close to those seen in the experiments and the molecular scale PFC simulations. Our paper indicates, furthermore, that the LGSD is critically sensitive to the details of the evaluation process, and raises the possibility that the differences among the LGSD results from different sources may originate from differences in the detection of small angle grain boundaries.
NASA Astrophysics Data System (ADS)
Ren, W. W.; Xu, C. G.; Chen, X. L.; Qin, S. X.
2018-05-01
Using high temperature compression experiments, true stress true strain curve of 6082 aluminium alloy were obtained at the temperature 460°C-560°C and the strain rate 0.01 s-1-10 s-1. The effects of deformation temperature and strain rate on the microstructure are investigated; (‑∂lnθ/∂ε) ‑ ε curves are plotted based on σ-ε curve. Critical strains of dynamic recrystallization of 6082 aluminium alloy model were obtained. The results showed lower strain rates were beneficial to increase the volume fraction of recrystallization, the average recrystallized grain size was coarse; High strain rates are beneficial to refine average grain size, the volume fraction of dynamic recrystallized grain is less than that by using low strain rates. High temperature reduced the dislocation density and provided less driving force for recrystallization so that coarse grains remained. Dynamic recrystallization critical strain model and thermal experiment results can effectively predict recrystallization critical point of 6082 aluminium alloy during thermal deformation.
Inferring phenomenological models of Markov processes from data
NASA Astrophysics Data System (ADS)
Rivera, Catalina; Nemenman, Ilya
Microscopically accurate modeling of stochastic dynamics of biochemical networks is hard due to the extremely high dimensionality of the state space of such networks. Here we propose an algorithm for inference of phenomenological, coarse-grained models of Markov processes describing the network dynamics directly from data, without the intermediate step of microscopically accurate modeling. The approach relies on the linear nature of the Chemical Master Equation and uses Bayesian Model Selection for identification of parsimonious models that fit the data. When applied to synthetic data from the Kinetic Proofreading process (KPR), a common mechanism used by cells for increasing specificity of molecular assembly, the algorithm successfully uncovers the known coarse-grained description of the process. This phenomenological description has been notice previously, but this time it is derived in an automated manner by the algorithm. James S. McDonnell Foundation Grant No. 220020321.
Extension of coarse-grained UNRES force field to treat carbon nanotubes.
Sieradzan, Adam K; Mozolewska, Magdalena A
2018-04-26
Carbon nanotubes (CNTs) have recently received considerable attention because of their possible applications in various branches of nanotechnology. For their cogent application, knowledge of their interactions with biological macromolecules, especially proteins, is essential and computer simulations are very useful for such studies. Classical all-atom force fields limit simulation time scale and size of the systems significantly. Therefore, in this work, we implemented CNTs into the coarse-grained UNited RESidue (UNRES) force field. A CNT is represented as a rigid infinite-length cylinder which interacts with a protein through the Kihara potential. Energy conservation in microcanonical coarse-grained molecular dynamics simulations and temperature conservation in canonical simulations with UNRES containing the CNT component have been verified. Subsequently, studies of three proteins, bovine serum albumin (BSA), soybean peroxidase (SBP), and α-chymotrypsin (CT), with and without CNTs, were performed to examine the influence of CNTs on the structure and dynamics of these proteins. It was found that nanotubes bind to these proteins and influence their structure. Our results show that the UNRES force field can be used for further studies of CNT-protein systems with 3-4 order of magnitude larger timescale than using regular all-atom force fields. Graphical abstract Bovine serum albumin (BSA), soybean peroxidase (SBP), and α-chymotrypsin (CT), with and without CNTsᅟ.
Angle-resolved effective potentials for disk-shaped molecules
NASA Astrophysics Data System (ADS)
Heinemann, Thomas; Palczynski, Karol; Dzubiella, Joachim; Klapp, Sabine H. L.
2014-12-01
We present an approach for calculating coarse-grained angle-resolved effective pair potentials for uniaxial molecules. For integrating out the intramolecular degrees of freedom we apply umbrella sampling and steered dynamics techniques in atomistically-resolved molecular dynamics (MD) computer simulations. Throughout this study we focus on disk-like molecules such as coronene. To develop the methods we focus on integrating out the van der Waals and intramolecular interactions, while electrostatic charge contributions are neglected. The resulting coarse-grained pair potential reveals a strong temperature and angle dependence. In the next step we fit the numerical data with various Gay-Berne-like potentials to be used in more efficient simulations on larger scales. The quality of the resulting coarse-grained results is evaluated by comparing their pair and many-body structure as well as some thermodynamic quantities self-consistently to the outcome of atomistic MD simulations of many-particle systems. We find that angle-resolved potentials are essential not only to accurately describe crystal structures but also for fluid systems where simple isotropic potentials start to fail already for low to moderate packing fractions. Further, in describing these states it is crucial to take into account the pronounced temperature dependence arising in selected pair configurations due to bending fluctuations.
Meeker, G.P.
1995-01-01
Many coarse-grained calcium- aluminum-rich inclusions (CAIs) contain features that are inconsistent with equilibrium liquid crystallization models of origin. Spinel-free islands (SFIs) in spinel-rich cores of Type B CAIs are examples of such features. One model previously proposed for the origin of Allende 5241, a Type B1 CAI containing SFIs, involves the capture and assimilation of xenoliths by a liquid droplet in the solar nebula (El Goresy et al, 1985; MacPherson et al 1989). This study reports new textural and chemical zoning data from 5241 and identifies previously unrecognized chemical zoning patterns in the melilite mantle and in a SFI. -from Author
Inverse Coarse-Graining: A New Tool for Molecular Design
2010-12-16
simulations. When compared with the more general multiscale coarse-graining (MS-CG) method, the EF-CG method retains the transferable part of the CG...Y.; Yan, T.; Voth, G. A., A Multiscale coarse-graining study of liquid/vacuum interface of room-temperature ionic liquids with alkyl substituents of...Energetic Room Temperature Ionic Liquid 1-Hydroxyethyl-4Amino-1, 2, 4-Triazolium Nitrate (HEATN). J. Phys. Chem. B 2008, 112, 3121-3131. 6. Liu, P
NASA Technical Reports Server (NTRS)
Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri
2014-01-01
A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.
Investigation of the mechanism for penetration of low density lipoprotein into the arterial wall
NASA Astrophysics Data System (ADS)
Glukhova, O. E.; Zyktin, A. A.; Slepchenkov, M. M.
2018-02-01
Currently, the pathology of the cardiovascular system is an extremely urgent problem of fundamental and clinical medicine. These diseases are caused, mainly, by atherosclerotic changes in the wall of blood vessels. The predominant role in the development of atherosclerosis is attributed to the penetration of various kinds of lipoproteins into the arterial intima. In this paper, we in silico investigated the dynamics of the penetration of low density lipoprotein (LDL) through the intercellular gap using molecular modeling methods. The simulation was carried out in the GROMACS software package using a coarse-grained MARTINI model. During investigation we carried out the LDL self-assembly for the first time. The coarse-grained model of LDL was collected from the following molecules: POPC (phosphatidylcholine) - 630 molecules, LPC (lysophosphatidylcholine) - 80 molecules CHOL (cholesterol) - 600 molecules CHYO (cholesteryl oleate) - 1600 molecules TOG (glycerol trioleate) 180 Molecules. The coarse-grained model of the intercellular endothelial gap was based on a model of lipid bilayer consisting of DPPC phospholipids and cholesterol in a percentage ratio of 70% and 30%, respectively. Based on the obtained results, we can predict the mechanism of LDL diffusion. Lipoproteins can be deformed so as to pass through narrow gaps. Our investigations open the way for the research of the behavior dynamics of LDL moving with the blood flow rate when interacting with the intercellular gaps of the endothelial layer of the vessel inner wall.
NASA Astrophysics Data System (ADS)
Bellemans, Aurélie; Parente, Alessandro; Magin, Thierry
2018-04-01
The present work introduces a novel approach for obtaining reduced chemistry representations of large kinetic mechanisms in strong non-equilibrium conditions. The need for accurate reduced-order models arises from compression of large ab initio quantum chemistry databases for their use in fluid codes. The method presented in this paper builds on existing physics-based strategies and proposes a new approach based on the combination of a simple coarse grain model with Principal Component Analysis (PCA). The internal energy levels of the chemical species are regrouped in distinct energy groups with a uniform lumping technique. Following the philosophy of machine learning, PCA is applied on the training data provided by the coarse grain model to find an optimally reduced representation of the full kinetic mechanism. Compared to recently published complex lumping strategies, no expert judgment is required before the application of PCA. In this work, we will demonstrate the benefits of the combined approach, stressing its simplicity, reliability, and accuracy. The technique is demonstrated by reducing the complex quantum N2(g+1Σ) -N(S4u ) database for studying molecular dissociation and excitation in strong non-equilibrium. Starting from detailed kinetics, an accurate reduced model is developed and used to study non-equilibrium properties of the N2(g+1Σ) -N(S4u ) system in shock relaxation simulations.
Yoon, Hongkyu; Oostrom, Mart; Wietsma, Thomas W; Werth, Charles J; Valocchi, Albert J
2009-10-13
The purpose of this work is to identify the mechanisms that govern the removal of carbon tetrachloride (CT) during soil vapor extraction (SVE) by comparing numerical and analytical model simulations with a detailed data set from a well-defined intermediate-scale flow cell experiment. The flow cell was packed with a fine-grained sand layer embedded in a coarse-grained sand matrix. A total of 499 mL CT was injected at the top of the flow cell and allowed to redistribute in the variably saturated system. A dual-energy gamma radiation system was used to determine the initial NAPL saturation profile in the fine-grained sand layer. Gas concentrations at the outlet of the flow cell and 15 sampling ports inside the flow cell were measured during subsequent CT removal using SVE. Results show that CT mass was removed quickly in coarse-grained sand, followed by a slow removal from the fine-grained sand layer. Consequently, effluent gas concentrations decreased quickly at first, and then started to decrease gradually, resulting in long-term tailing. The long-term tailing was mainly due to diffusion from the fine-grained sand layer to the coarse-grained sand zone. An analytical solution for a one-dimensional advection and a first-order mass transfer model matched the tailing well with two fitting parameters. Given detailed knowledge of the permeability field and initial CT distribution, we were also able to predict the effluent concentration tailing and gas concentration profiles at sampling ports using a numerical simulator assuming equilibrium CT evaporation. The numerical model predictions were accurate within the uncertainty of independently measured or literature derived parameters. This study demonstrates that proper numerical modeling of CT removal through SVE can be achieved using equilibrium evaporation of NAPL if detailed fine-scale knowledge of the CT distribution and physical heterogeneity is incorporated into the model. However, CT removal could also be fit by a first-order mass transfer analytical model, potentially leading to an erroneous conclusion that the long-term tailing in the experiment was kinetically controlled due to rate-limited NAPL evaporation.
Nanoparticle interaction potentials constructed by multiscale computation
NASA Astrophysics Data System (ADS)
Lee, Cheng K.; Hua, Chi C.
2010-06-01
The van der Waals (vdW) potentials governing macroscopic objects have long been formulated in the context of classical theories, such as Hamaker's microscopic theory and Lifshitz's continuum theory. This work addresses the possibility of constructing the vdW interaction potentials of nanoparticle species using multiscale simulation schemes. Amorphous silica nanoparticles were considered as a benchmark example for which a series of (SiO2)n (n being an integer) has been systematically surveyed as the potential candidates of the packing units that reproduce known bulk material properties in atomistic molecular dynamics simulations. This strategy led to the identification of spherical Si6O12 molecules, later utilized as the elementary coarse-grained (CG) particles to compute the pair interaction potentials of silica nanoparticles ranging from 0.62 to 100 nm in diameter. The model nanoparticles so built may, in turn, serve as the children CG particles to construct nanoparticles assuming arbitrary sizes and shapes. Major observations are as follows. The pair interaction potentials for all the investigated spherical silica nanoparticles can be cast into a semiempirical, generalized Lennard-Jones 2α-α potential (α being a size-dependent, large integral number). In its reduced form, we discuss the implied universalities for the vdW potentials governing a certain range of amorphous nanoparticle species as well as how thermodynamic transferability can be fulfilled automatically. In view of future applications with colloidal suspensions, we briefly evaluated the vdW potential in the presence of a "screening" medium mimicking the effects of electrical double layers or grafting materials atop the nanoparticle core. The general observations shed new light on strategies to attain a microscopic control over interparticle attractions. In future perspectives, the proposed multiscale computation scheme shall help bridge the current gap between the modeling of polymer chains and macroscopic objects by introducing molecular models coarse-grained at a similar level so that the interactions between these two can be treated in a consistent and faithful way.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garcia, Andres
Transport and reaction in zeolites and other porous materials, such as mesoporous silica particles, has been a focus of interest in recent years. This is in part due to the possibility of anomalous transport effects (e.g. single-file diffusion) and its impact in the reaction yield in catalytic processes. Computational simulations are often used to study these complex nonequilibrium systems. Computer simulations using Molecular Dynamics (MD) techniques are prohibitive, so instead coarse grained one-dimensional models with the aid of Kinetic Monte Carlo (KMC) simulations are used. Both techniques can be computationally expensive, both time and resource wise. These coarse-grained systems canmore » be exactly described by a set of coupled stochastic master equations, that describe the reaction-diffusion kinetics of the system. The equations can be written exactly, however, coupling between the equations and terms within the equations make it impossible to solve them exactly; approximations must be made. One of the most common methods to obtain approximate solutions is to use Mean Field (MF) theory. MF treatments yield reasonable results at high ratios of reaction rate k to hop rate h of the particles, but fail completely at low k=h due to the over-estimation of fluxes of particles within the pore. We develop a method to estimate fluxes and intrapore diffusivity in simple one- dimensional reaction-diffusion models at high and low k=h, where the pores are coupled to an equilibrated three-dimensional fluid. We thus successfully describe analytically these simple reaction-diffusion one-dimensional systems. Extensions to models considering behavior with long range steric interactions and wider pores require determination of multiple boundary conditions. We give a prescription to estimate the required parameters for these simulations. For one dimensional systems, if single-file diffusion is relaxed, additional parameters to describe particle exchange have to be introduced. We use Langevin Molecular Dynamics (MD) simulations to assess these parameters.« less
Musical structure analysis using similarity matrix and dynamic programming
NASA Astrophysics Data System (ADS)
Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay
2005-10-01
Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
Initial Isotopic Heterogeneities in ZAGAMI: Evidence of a Complex Magmatic History
NASA Technical Reports Server (NTRS)
Nyquist, L. E.; Shih, C.-Y.; Reese, Y. D.
2006-01-01
Interpretations of Zagami s magmatic history range from complex [1,2] to relatively simple [3]. Discordant radiometric ages led to a suggestion that the ages had been reset [4]. In an attempt to identify the mechanism, Rb-Sr isochrons were individually determined for both fine-grained and coarse-grained Zagami [5]. Ages of approx.180 Ma were obtained from both lithologies, but the initial Sr-87/Sr-86 (ISr) of the fine-grained lithology was higher by 8.6+/-0.4 e-units. Recently, a much older age of approx.4 Ga has been advocated [6]. Here, we extend our earlier investigation [5]. Rb-Sr Data: In [5] we applied identical, simplified, procedures to both lithologies to test whether a grain-size dependent process such as thermally-driven subsolidus isotopic reequilibration had caused age-resetting. Minerals were separated only by density. In the present experiment, purer mineral separates were analysed with improved techniques. Combined Rb-Sr results give ages (T) = 166+/-12 Ma and 177+/-9 Ma and I(subSr) = 0.72174+/-9 and 0.72227+/-7 for the coarse-grained and fine-grained lithologies, respectively. ISr in the fine-grained sample is thus higher than in the coarse-grained sample by 7.3+/-1.6 e-units. The results for the coarse-grained lithology are in close agreement with T = 166+/-6 Ma, ISr = 0.72157+/-8 for an adjacent sample [7] and T = 178+/-4 Ma, ISr = 0.72151+/-5 [4, adjusted] for a separate sample. Thus, fine-grained Zagami appears on average to be less typical of the bulk than coarse-grained Zagami.
GUI to Facilitate Research on Biological Damage from Radiation
NASA Technical Reports Server (NTRS)
Cucinotta, Frances A.; Ponomarev, Artem Lvovich
2010-01-01
A graphical-user-interface (GUI) computer program has been developed to facilitate research on the damage caused by highly energetic particles and photons impinging on living organisms. The program brings together, into one computational workspace, computer codes that have been developed over the years, plus codes that will be developed during the foreseeable future, to address diverse aspects of radiation damage. These include codes that implement radiation-track models, codes for biophysical models of breakage of deoxyribonucleic acid (DNA) by radiation, pattern-recognition programs for extracting quantitative information from biological assays, and image-processing programs that aid visualization of DNA breaks. The radiation-track models are based on transport models of interactions of radiation with matter and solution of the Boltzmann transport equation by use of both theoretical and numerical models. The biophysical models of breakage of DNA by radiation include biopolymer coarse-grained and atomistic models of DNA, stochastic- process models of deposition of energy, and Markov-based probabilistic models of placement of double-strand breaks in DNA. The program is designed for use in the NT, 95, 98, 2000, ME, and XP variants of the Windows operating system.
NASA Astrophysics Data System (ADS)
Lyu, Dandan; Li, Shaofan
2017-10-01
Crystal defects have microstructure, and this microstructure should be related to the microstructure of the original crystal. Hence each type of crystals may have similar defects due to the same failure mechanism originated from the same microstructure, if they are under the same loading conditions. In this work, we propose a multiscale crystal defect dynamics (MCDD) model that models defects by considering its intrinsic microstructure derived from the microstructure or material genome of the original perfect crystal. The main novelties of present work are: (1) the discrete exterior calculus and algebraic topology theory are used to construct a scale-up (coarse-grained) dual lattice model for crystal defects, which may represent all possible defect modes inside a crystal; (2) a higher order Cauchy-Born rule (up to the fourth order) is adopted to construct atomistic-informed constitutive relations for various defect process zones, and (3) an hierarchical strain gradient theory based finite element formulation is developed to support an hierarchical multiscale cohesive (process) zone model for various defects in a unified formulation. The efficiency of MCDD computational algorithm allows us to simulate dynamic defect evolution at large scale while taking into account atomistic interaction. The MCDD model has been validated by comparing of the results of MCDD simulations with that of molecular dynamics (MD) in the cases of nanoindentation and uniaxial tension. Numerical simulations have shown that MCDD model can predict dislocation nucleation induced instability and inelastic deformation, and thus it may provide an alternative solution to study crystal plasticity.
Huang, Wenjun; Mandal, Taraknath; Larson, Ronald G
2017-03-06
We present coarse-grained (CG) force fields for hydroxypropyl-methylcellulose acetate succinate (HPMCAS) polymers and the drug molecule phenytoin using a bead/stiff spring model, with each bead representing a HPMCAS monomer or monomer side group (hydroxypropyl acetyl, acetyl, or succinyl) or a single phenytoin ring. We obtain the bonded and nonbonded interaction parameters in our CG model using the RDFs from atomistic simulations of short HPMCAS model oligomers (20-mer) and atomistic simulations of phenytoin molecules. The nonbonded interactions are modeled using a LJ 12-6 potential, with separate parameters for each monomer substitution type, which allows heterogeneous polymer chains to be modeled. The cross interaction terms between the polymer and phenytoin CG beads are obtained explicitly from atomistic level polymer-phenytoin simulations, rather than from mixing rules. We study the solvation behavior of 50-mer and 100-mer polymer chains and find chain-length-dependent aggregation. We also compare the phenytoin CG force field developed in this work with that in Mandal et al. (Soft Matter, 2016, 12, 8246-8255) and conclude both are suitable for studying the interaction between polymer and drug in solvated solid dispersion formulation, in the absence of drug crystallization. Finally, we present simulations of heterogeneous HPMCAS model polymer chains and phenytoin molecules. Polymer and drug form a complex in a short period of simulation time due to strong intermolecular interactions. Moreover, the protonated polymer chains are more effective than deprotonated ones in inhibiting the drug aggregation in the polymer-drug complex.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maier-Kiener, Verena; Schuh, Benjamin; George, Easo P.
A CrMnFeCoNi high-entropy alloy was investigated by nanoindentation from room temperature to 400 °C in the nanocrystalline state and cast plus homogenized coarse-grained state. In the latter case a < 100 >-orientated grain was selected by electron back scatter diffraction for nanoindentation. It was found that hardness decreases more strongly with increasing temperature than Young’s modulus, especially for the coarse-grained state. The modulus of the nanocrystalline state was slightly higher than that of the coarse-grained one. For the coarse-grained sample a strong thermally activated deformation behavior was found up to 100–150 °C, followed by a diminishing thermally activated contribution atmore » higher testing temperatures. For the nanocrystalline state, different temperature dependent deformation mechanisms are proposed. At low temperatures, the governing processes appear to be similar to those in the coarse-grained sample, but with increasing temperature, dislocation-grain boundary interactions likely become more dominant. Finally, at 400 °C, decomposition of the nanocrystalline alloy causes a further reduction in thermal activation. Furthermore, this is rationalized by a reduction of the deformation controlling internal length scale by precipitate formation in conjunction with a diffusional contribution.« less
Numerical Model of Turbulence, Sediment Transport, and Sediment Cover in a Large Canyon-Bound River
NASA Astrophysics Data System (ADS)
Alvarez, L. V.; Schmeeckle, M. W.
2013-12-01
The Colorado River in Grand Canyon is confined by bedrock and coarse-grained sediments. Finer grain sizes are supply limited, and sandbars primarily occur in lateral separation eddies downstream of coarse-grained tributary debris fans. These sandbars are important resources for native fish, recreational boaters, and as a source of aeolian transport preventing the erosion of archaeological resources by gully extension. Relatively accurate prediction of deposition and, especially, erosion of these sandbar beaches has proven difficult using two- and three-dimensional, time-averaged morphodynamic models. We present a parallelized, three-dimensional, turbulence-resolving model using the Detached-Eddy Simulation (DES) technique. DES is a hybrid large eddy simulation (LES) and Reynolds-averaged Navier Stokes (RANS). RANS is applied to the near-bed grid cells, where grid resolution is not sufficient to fully resolve wall turbulence. LES is applied further from the bed and banks. We utilize the Spalart-Allmaras one equation turbulence closure with a rough wall extension. The model resolves large-scale turbulence using DES and simultaneously integrates the suspended sediment advection-diffusion equation. The Smith and McLean suspended sediment boundary condition is used to calculate the upward and downward settling of sediment fluxes in the grid cells attached to the bed. The model calculates the entrainment of five grain sizes at every time step using a mixing layer model. Where the mixing layer depth becomes zero, the net entrainment is zero or negative. As such, the model is able to predict the exposure and burial of bedrock and coarse-grained surfaces by fine-grained sediments. A separate program was written to automatically construct the computational domain between the water surface and a triangulated surface of a digital elevation model of the given river reach. Model results compare favorably with ADCP measurements of flow taken on the Colorado River in Grand Canyon during the High Flow Experiment (HFE) of 2008. The model accurately reproduces the size and position of the major recirculation currents, and the error in velocity magnitude was found to be less than 17% or 0.22 m/s absolute error. The mean deviation of the direction of velocity with respect to the measured velocity was found to be 20 degrees. Large-scale turbulence structures with vorticity predominantly in the vertical direction are produced at the shear layer between the main channel and the separation zone. However, these structures rapidly become three-dimensional with no preferred orientation of vorticity. Surprisingly, cross-stream velocities, into the main recirculation zone just upstream of the point of reattachment and out of the main recirculation region just downstream of the point of separation, are highest near the bed. Lateral separation eddies are more efficient at storing and exporting sediment than previously modeled. The input of sediment to the eddy recirculation zone occurs near the reattachment zone and is relatively continuous in time. While, the export of sediment to the main channel by the return current occurs in pulses. Pulsation of the strength of the return current becomes a key factor to determine the rates of erosion and deposition in the main recirculation zone.
Comparison of iterative inverse coarse-graining methods
NASA Astrophysics Data System (ADS)
Rosenberger, David; Hanke, Martin; van der Vegt, Nico F. A.
2016-10-01
Deriving potentials for coarse-grained Molecular Dynamics (MD) simulations is frequently done by solving an inverse problem. Methods like Iterative Boltzmann Inversion (IBI) or Inverse Monte Carlo (IMC) have been widely used to solve this problem. The solution obtained by application of these methods guarantees a match in the radial distribution function (RDF) between the underlying fine-grained system and the derived coarse-grained system. However, these methods often fail in reproducing thermodynamic properties. To overcome this deficiency, additional thermodynamic constraints such as pressure or Kirkwood-Buff integrals (KBI) may be added to these methods. In this communication we test the ability of these methods to converge to a known solution of the inverse problem. With this goal in mind we have studied a binary mixture of two simple Lennard-Jones (LJ) fluids, in which no actual coarse-graining is performed. We further discuss whether full convergence is actually needed to achieve thermodynamic representability.
Does horizon entropy satisfy a quantum null energy conjecture?
NASA Astrophysics Data System (ADS)
Fu, Zicao; Marolf, Donald
2016-12-01
A modern version of the idea that the area of event horizons gives 4G times an entropy is the Hubeny-Rangamani causal holographic information (CHI) proposal for holographic field theories. Given a region R of a holographic QFTs, CHI computes A/4G on a certain cut of an event horizon in the gravitational dual. The result is naturally interpreted as a coarse-grained entropy for the QFT. CHI is known to be finitely greater than the fine-grained Hubeny-Rangamani-Takayanagi (HRT) entropy when \\partial R lies on a Killing horizon of the QFT spacetime, and in this context satisfies other non-trivial properties expected of an entropy. Here we present evidence that it also satisfies the quantum null energy condition (QNEC), which bounds the second derivative of the entropy of a quantum field theory on one side of a non-expanding null surface by the flux of stress-energy across the surface. In particular, we show CHI to satisfy the QNEC in 1 + 1 holographic CFTs when evaluated in states dual to conical defects in AdS3. This surprising result further supports the idea that CHI defines a useful notion of coarse-grained holographic entropy, and suggests unprecedented bounds on the rate at which bulk horizon generators emerge from a caustic. To supplement our motivation, we include an appendix deriving a corresponding coarse-grained generalized second law for 1 + 1 holographic CFTs perturbatively coupled to dilaton gravity.
A Calculus for Boxes and Traits in a Java-Like Setting
NASA Astrophysics Data System (ADS)
Bettini, Lorenzo; Damiani, Ferruccio; de Luca, Marco; Geilmann, Kathrin; Schäfer, Jan
The box model is a component model for the object-oriented paradigm, that defines components (the boxes) with clear encapsulation boundaries. Having well-defined boundaries is crucial in component-based software development, because it enables to argue about the interference and interaction between a component and its context. In general, boxes contain several objects and inner boxes, of which some are local to the box and cannot be accessed from other boxes and some can be accessible by other boxes. A trait is a set of methods divorced from any class hierarchy. Traits can be composed together to form classes or other traits. We present a calculus for boxes and traits. Traits are units of fine-grained reuse, whereas boxes can be seen as units of coarse-grained reuse. The calculus is equipped with an ownership type system and allows us to combine coarse- and fine-grained reuse of code by maintaining encapsulation of components.
NASA Astrophysics Data System (ADS)
Miura, Yasunari; Sugiyama, Yuki
2017-12-01
We present a general method for analyzing macroscopic collective phenomena observed in many-body systems. For this purpose, we employ diffusion maps, which are one of the dimensionality-reduction techniques, and systematically define a few relevant coarse-grained variables for describing macroscopic phenomena. The time evolution of macroscopic behavior is described as a trajectory in the low-dimensional space constructed by these coarse variables. We apply this method to the analysis of the traffic model, called the optimal velocity model, and reveal a bifurcation structure, which features a transition to the emergence of a moving cluster as a traffic jam.
Molecular dynamics simulation of water in and around carbon nanotubes: A coarse-grained description
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pantawane, Sanwardhini; Choudhury, Niharendu, E-mail: nihcho@barc.gov.in
2016-05-23
In the present study, we intend to investigate behaviour of water in and around hydrophobic open ended carbon nanotubes (CNTs) using a coarse-grained, core-softened model potential for water. The model potential considered here for water has recently been shown to successfully reproduce dynamic, thermodynamic and structural anomalies of water. The epitome of the study is to understand the incarceration of this coarse-grained water in a single-file carbon nanotube. In order to examine the effect of fluid-water van der Waals interaction on the structure of fluid in and around the nanotube, we have simulated three different CNT-water systems with varying degreemore » of solute-water dispersion interaction. The analyses of the radial one-particle density profiles reveal varying degree of permeation and wetting of the CNT interior depending on the degree of fluid-solute attractive van der Waals interaction. A peak in the radial density profile slightly off the nanotube axis signifies a zigzag chain of water molecule around the CNT axis. The average numbers of water molecules inside the CNT have been shown to increase with the increase in fluid-water attractive dispersion interaction.« less
Transport of fine sediment over a coarse, immobile riverbed
Grams, Paul E.; Wilcock, Peter R.
2014-01-01
Sediment transport in cobble-boulder rivers consists mostly of fine sediment moving over a coarse, immobile bed. Transport rate depends on several interrelated factors: boundary shear stress, the grain size and volume of fine sediment, and the configuration of fine sediment into interstitial deposits and bed forms. Existing models do not incorporate all of these factors. Approaches that partition stress face a daunting challenge because most of the boundary shear is exerted on immobile grains. We present an alternative approach that divides the bed into sand patches and interstitial deposits and is well constrained by two clear end-member cases: full sand cover and absence of sand. Entrainment from sand patches is a function of their aerial coverage. Entrainment from interstices among immobile grains is a function of sand elevation relative to the size of the immobile grains. The bed-sand coverage function is used to predict the ratio of the rate of entrainment from a partially covered bed to the rate of entrainment from a completely sand-covered bed, which is determined using a standard sand transport model. We implement the bed-sand coverage function in a morphodynamic routing model and test it against observations of sand bed elevation and suspended sand concentration for conditions of nonuniform fine sediment transport in a large flume with steady uniform flow over immobile hemispheres. The results suggest that this approach may provide a simple and robust method for predicting the transport and migration of fine sediment through rivers with coarse, immobile beds.
2012-08-01
270 350x 650 (25, 26) 2 20 Ni-15Al- 5Cr+C,B,Zr 187 x 187 500x 44 ( 4 , 11) 0.5 40 A. Coarse grain, single phase α- titanium The coarse grained... titanium alloy serves as an instructive example because, as evident in Figure 4 (a), only one triple point and one grain boundary appear in the search...wpafb.af.mil Figure 4 . Crystal orientation maps for the first (left) and second (current) tiles of (a) coarse grained α- Titanium , (b) a 2x2 array of a
Statistical physics approaches to Alzheimer's disease
NASA Astrophysics Data System (ADS)
Peng, Shouyong
Alzheimer's disease (AD) is the most common cause of late life dementia. In the brain of an AD patient, neurons are lost and spatial neuronal organizations (microcolumns) are disrupted. An adequate quantitative analysis of microcolumns requires that we automate the neuron recognition stage in the analysis of microscopic images of human brain tissue. We propose a recognition method based on statistical physics. Specifically, Monte Carlo simulations of an inhomogeneous Potts model are applied for image segmentation. Unlike most traditional methods, this method improves the recognition of overlapped neurons, and thus improves the overall recognition percentage. Although the exact causes of AD are unknown, as experimental advances have revealed the molecular origin of AD, they have continued to support the amyloid cascade hypothesis, which states that early stages of aggregation of amyloid beta (Abeta) peptides lead to neurodegeneration and death. X-ray diffraction studies reveal the common cross-beta structural features of the final stable aggregates-amyloid fibrils. Solid-state NMR studies also reveal structural features for some well-ordered fibrils. But currently there is no feasible experimental technique that can reveal the exact structure or the precise dynamics of assembly and thus help us understand the aggregation mechanism. Computer simulation offers a way to understand the aggregation mechanism on the molecular level. Because traditional all-atom continuous molecular dynamics simulations are not fast enough to investigate the whole aggregation process, we apply coarse-grained models and discrete molecular dynamics methods to increase the simulation speed. First we use a coarse-grained two-bead (two beads per amino acid) model. Simulations show that peptides can aggregate into multilayer beta-sheet structures, which agree with X-ray diffraction experiments. To better represent the secondary structure transition happening during aggregation, we refine the model to four beads per amino acid. Typical essential interactions, such as backbone hydrogen bond, hydrophobic and electrostatic interactions, are incorporated into our model. We study the aggregation of Abeta16-22, a peptide that can aggregate into a well-ordered fibrillar structure in experiments. Our results show that randomly-oriented monomers can aggregate into fibrillar subunits, which agree not only with X-ray diffraction experiments but also with solid-state NMR studies. Our findings demonstrate that coarse-grained models and discrete molecular dynamics simulations can help researchers understand the aggregation mechanism of amyloid peptides.
NASA Astrophysics Data System (ADS)
Vishnyakov, Aleksey; Mao, Runfang; Lee, Ming-Tsung; Neimark, Alexander V.
2018-01-01
We present a coarse-grained model of the acid form of Nafion membrane that explicitly includes proton transport. This model is based on a soft-core bead representation of the polymer implemented into the dissipative particle dynamics (DPD) simulation framework. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with water beads. Morse bond formation and breakup artificially mimics the Grotthuss hopping mechanism of proton transport. The proposed DPD model is parameterized to account for the specifics of the conformations and flexibility of the Nafion backbone and sidechains; it treats electrostatic interactions in the smeared charge approximation. The simulation results qualitatively, and in many respects quantitatively, predict the specifics of nanoscale segregation in the hydrated Nafion membrane into hydrophobic and hydrophilic subphases, water diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from a collection of isolated water clusters to a 3D network of pores filled with water embedded in the hydrophobic matrix. The segregated morphology is characterized in terms of the pore size distribution with the average size growing with hydration from ˜1 to ˜4 nm. Comparison of the predicted water diffusivity with the experimental data taken from different sources shows good agreement at high and moderate hydration and substantial deviation at low hydration, around and below the percolation threshold. This discrepancy is attributed to the dynamic percolation effects of formation and rupture of merging bridges between the water clusters, which become progressively important at low hydration, when the coarse-grained model is unable to mimic the fine structure of water network that includes singe molecule bridges. Selected simulations of water diffusion are performed for the alkali metal substituted membrane which demonstrate the effects of the counter-ions on membrane self-assembly and transport. The hydration dependence of the proton diffusivity reproduces semi-qualitatively the trend of the diverse experimental data, showing a sharp decrease around the percolation threshold. Overall, the proposed model opens up an opportunity to study self-assembly and water and proton transport in polyelectrolytes using computationally efficient DPD simulations, and, with further refinement, it may become a practical tool for theory informed design and optimization of perm-selective and ion-conducting membranes with improved properties.
Sallenger,, Asbury H.
1981-01-01
Swash marks composed entirely of coarse sand are commonly found on coarse-sand beaches. These swash marks are 10 to 30 centimeters in width and a few millimeters to one centimeter in height. Previous observations, mostly on finer-sand beaches, indicate swash marks are seldom over a few millimeters in height and are commonly composed of material readily floated by surface tension (e.g., mica flakes and shell fragments). Swash marks composed of coarse sand have both fining seaward and fining with depth trends in grain size. Apparently, the leading margin of a wave upwash drives a highly concentrated flow of grains in which both grain size and grain velocity decrease with depth. Therefore, large grains are transported at greater velocities than are smaller grains. Thus, at the maximum advance of an upwash, a swash mark is deposited which has the observed fining seaward and fining with depth trends in grain size.
Coarse-grained theory of a realistic tetrahedral liquid model
NASA Astrophysics Data System (ADS)
Procaccia, I.; Regev, I.
2012-02-01
Tetrahedral liquids such as water and silica-melt show unusual thermodynamic behavior such as a density maximum and an increase in specific heat when cooled to low temperatures. Previous work had shown that Monte Carlo and mean-field solutions of a lattice model can exhibit these anomalous properties with or without a phase transition, depending on the values of the different terms in the Hamiltonian. Here we use a somewhat different approach, where we start from a very popular empirical model of tetrahedral liquids —the Stillinger-Weber model— and construct a coarse-grained theory which directly quantifies the local structure of the liquid as a function of volume and temperature. We compare the theory to molecular-dynamics simulations and show that the theory can rationalize the simulation results and the anomalous behavior.
NASA Astrophysics Data System (ADS)
Pizzirusso, Antonio; Brasiello, Antonio; De Nicola, Antonio; Marangoni, Alejandro G.; Milano, Giuseppe
2015-12-01
The first simulation study of the crystallisation of a binary mixture of triglycerides using molecular dynamics simulations is reported. Coarse-grained models of tristearin (SSS) and tripalmitin (PPP) molecules have been considered. The models have been preliminarily tested in the crystallisation of pure SSS and PPP systems. Two different quenching procedures have been tested and their performances have been analysed. The structures obtained from the crystallisation procedures show a high orientation order and a high content of molecules in the tuning fork conformation, comparable with the crystalline α phase. The behaviour of melting temperatures for the α phase of the mixture SSS/PPP obtained from the simulations is in qualitative agreement with the behaviour that was experimentally determined.
Rye, R.O.; Roberts, R.J.; Snyder, W.S.; Lahusen, G.L.; Motica, J.E.
1984-01-01
The Big Mike deposit is a massive sulphide lens entirely within a carbonaceous argillite of the Palaeozoic Havallah pelagic sequence. The massive ore contains two generations of pyrite, a fine- and a coarse-grained variety; framboidal pyrite occurs in the surrounding carbonaceous argillite. Coarse grained pyrite is largely recrystallized fine-grained pyrite and is proportionately more abundant toward the margins of the lens. Chalcopyrite and sphalerite replace fine-grained pyrite and vein-fragmented coarse-grained pyrite. Quartz fills openings in the sulphide fabric. S-isotope data are related to sulphide mineralogy and textures. Isotopically light S in the early fine-grained pyrite was probably derived from framboidal biogenic pyrite. The S-isotope values of the later coarse-grained pyrite and chalcopyrite probably reflect a combination of reduced sea-water sulphate and igneous S. Combined S- and O-isotope and textural data accord with precipitation of fine-grained pyrite from a hydrothermal plume like those at the East Pacific Rise spreading centre at lat. 21oN. The primary material was recystallized and mineralized by later fluids of distinctly different S-isotope composition. -G.J.N.
NASA Astrophysics Data System (ADS)
Li, Chunhua; Lv, Dashuai; Zhang, Lei; Yang, Feng; Wang, Cunxin; Su, Jiguo; Zhang, Yang
2016-07-01
Riboswitches are noncoding mRNA segments that can regulate the gene expression via altering their structures in response to specific metabolite binding. We proposed a coarse-grained Gaussian network model (GNM) to examine the unfolding and folding dynamics of adenosine deaminase (add) A-riboswitch upon the adenine dissociation, in which the RNA is modeled by a nucleotide chain with interaction networks formed by connecting adjoining atomic contacts. It was shown that the adenine binding is critical to the folding of the add A-riboswitch while the removal of the ligand can result in drastic increase of the thermodynamic fluctuations especially in the junction regions between helix domains. Under the assumption that the native contacts with the highest thermodynamic fluctuations break first, the iterative GNM simulations showed that the unfolding process of the adenine-free add A-riboswitch starts with the denature of the terminal helix stem, followed by the loops and junctions involving ligand binding pocket, and then the central helix domains. Despite the simplified coarse-grained modeling, the unfolding dynamics and pathways are shown in close agreement with the results from atomic-level MD simulations and the NMR and single-molecule force spectroscopy experiments. Overall, the study demonstrates a new avenue to investigate the binding and folding dynamics of add A-riboswitch molecule which can be readily extended for other RNA molecules.
On the intrinsic flexibility of the opioid receptor through multiscale modeling approaches
NASA Astrophysics Data System (ADS)
Vercauteren, Daniel; FosséPré, Mathieu; Leherte, Laurence; Laaksonen, Aatto
Numerous releases of G protein-coupled receptors crystalline structures created the opportunity for computational methods to widely explore their dynamics. Here, we study the biological implication of the intrinsic flexibility properties of opioid receptor OR. First, one performed classical all-atom (AA) Molecular Dynamics (MD) simulations of OR in its apo-form. We highlighted that the various degrees of bendability of the α-helices present important consequences on the plasticity of the binding site. Hence, this latter adopts a wide diversity of shape and volume, explaining why OR interacts with very diverse ligands. Then, one introduces a new strategy for parameterizing purely mechanical but precise coarse-grained (CG) elastic network models (ENMs). The CG ENMs reproduced in a high accurate way the flexibility properties of OR versus the AA simulations. At last, one uses network modularization to design multi-grained (MG) models. They represent a novel type of low resolution models, different in nature versus CG models as being true multi-resolution models, i . e ., each MG grouping a different number of residues. The three parts constitute hierarchical and multiscale approach for tackling the flexibility of OR.
NASA Astrophysics Data System (ADS)
Pozharskiy, Dmitry
In recent years a nonlinear, acoustic metamaterial, named granular crystals, has gained prominence due to its high accessibility, both experimentally and computationally. The observation of a wide range of dynamical phenomena in the system, due to its inherent nonlinearities, has suggested its importance in many engineering applications related to wave propagation. In the first part of this dissertation, we explore the nonlinear dynamics of damped-driven granular crystals. In one case, we consider a highly nonlinear setting, also known as a sonic vacuum, and derive a nonlinear analogue of a linear spectrum, corresponding to resonant periodic propagation and antiresonances. Experimental studies confirm the computational findings and the assimilation of experimental data into a numerical model is demonstrated. In the second case, global bifurcations in a precompressed granular crystal are examined, and their involvement in the appearance of chaotic dynamics is demonstrated. Both results highlight the importance of exploring the nonlinear dynamics, to gain insight into how a granular crystal responds to different external excitations. In the second part, we borrow established ideas from coarse-graining of dynamical systems, and extend them to optimization problems. We combine manifold learning algorithms, such as Diffusion Maps, with stochastic optimization methods, such as Simulated Annealing, and show that we can retrieve an ensemble, of few, important parameters that should be explored in detail. This framework can lead to acceleration of convergence when dealing with complex, high-dimensional optimization, and could potentially be applied to design engineered granular crystals.
NASA Astrophysics Data System (ADS)
Pandey, Harsh; Underhill, Patrick T.
2015-11-01
The electrophoretic mobility of molecules such as λ -DNA depends on the conformation of the molecule. It has been shown that electrohydrodynamic interactions between parts of the molecule lead to a mobility that depends on conformation and can explain some experimental observations. We have developed a new coarse-grained model that incorporates these changes of mobility into a bead-spring chain model. Brownian dynamics simulations have been performed using this model. The model reproduces the cross-stream migration that occurs in capillary electrophoresis when pressure-driven flow is applied parallel or antiparallel to the electric field. The model also reproduces the change of mobility when the molecule is stretched significantly in an extensional field. We find that the conformation-dependent mobility can lead to a new type of unraveling of the molecule in strong fields. This occurs when different parts of the molecule have different mobilities and the electric field is large.
Development of DPD coarse-grained models: From bulk to interfacial properties
DOE Office of Scientific and Technical Information (OSTI.GOV)
Solano Canchaya, José G.; Dequidt, Alain, E-mail: alain.dequidt@univ-bpclermont.fr; Goujon, Florent
2016-08-07
A new Bayesian method was recently introduced for developing coarse-grain (CG) force fields for molecular dynamics. The CG models designed for dissipative particle dynamics (DPD) are optimized based on trajectory matching. Here we extend this method to improve transferability across thermodynamic conditions. We demonstrate the capability of the method by developing a CG model of n-pentane from constant-NPT atomistic simulations of bulk liquid phases and we apply the CG-DPD model to the calculation of the surface tension of the liquid-vapor interface over a large range of temperatures. The coexisting densities, vapor pressures, and surface tensions calculated with different CG andmore » atomistic models are compared to experiments. Depending on the database used for the development of the potentials, it is possible to build a CG model which performs very well in the reproduction of the surface tension on the orthobaric curve.« less
Simulating the flow of entangled polymers.
Masubuchi, Yuichi
2014-01-01
To optimize automation for polymer processing, attempts have been made to simulate the flow of entangled polymers. In industry, fluid dynamics simulations with phenomenological constitutive equations have been practically established. However, to account for molecular characteristics, a method to obtain the constitutive relationship from the molecular structure is required. Molecular dynamics simulations with atomic description are not practical for this purpose; accordingly, coarse-grained models with reduced degrees of freedom have been developed. Although the modeling of entanglement is still a challenge, mesoscopic models with a priori settings to reproduce entangled polymer dynamics, such as tube models, have achieved remarkable success. To use the mesoscopic models as staging posts between atomistic and fluid dynamics simulations, studies have been undertaken to establish links from the coarse-grained model to the atomistic and macroscopic simulations. Consequently, integrated simulations from materials chemistry to predict the macroscopic flow in polymer processing are forthcoming.
2011-09-06
Presentation Outline A) Review of Soil Model governing equations B) Development of pedo -transfer functions (terrain database to engineering properties) C...lateral earth pressure) UNCLASSIFIED B) Development of pedo -transfer functions Engineering parameters needed by soil model - compression index - rebound...inches, RCI for fine- grained soils, CI for coarse-grained soils. UNCLASSIFIED Pedo -transfer function • Need to transfer existing terrain database
Decorated tensor network renormalization for lattice gauge theories and spin foam models
NASA Astrophysics Data System (ADS)
Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian
2016-05-01
Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lenz, Dominic A.; Likos, Christos N.; Blaak, Ronald
We pursue the goal of finding real-world examples of macromolecular aggregates that form cluster crystals, which have been predicted on the basis of coarse-grained, ultrasoft pair potentials belonging to a particular mathematical class [B. M. Mladek et al., Phys. Rev. Lett. 46, 045701 (2006)]. For this purpose, we examine in detail the phase behavior and structural properties of model amphiphilic dendrimers of the second generation by means of monomer-resolved computer simulations. On augmenting the density of these systems, a fluid comprised of clusters that contain several overlapping and penetrating macromolecules is spontaneously formed. Upon further compression of the system, amore » transition to multi-occupancy crystals takes place, the thermodynamic stability of which is demonstrated by means of free-energy calculations, and where the FCC is preferred over the BCC-phase. Contrary to predictions for coarse-grained theoretical models in which the particles interact exclusively by effective pair potentials, the internal degrees of freedom of these molecules cause the lattice constant to be density-dependent. Furthermore, the mechanical stability of monodisperse BCC and FCC cluster crystals is restricted to a bounded region in the plane of cluster occupation number versus density. The structural properties of the dendrimers in the dense crystals, including their overall sizes and the distribution of monomers are also thoroughly analyzed.« less
OpenRBC: Redefining the Frontier of Red Blood Cell Simulations at Protein Resolution
NASA Astrophysics Data System (ADS)
Tang, Yu-Hang; Lu, Lu; Li, He; Grinberg, Leopold; Sachdeva, Vipin; Evangelinos, Constantinos; Karniadakis, George
We present a from-scratch development of OpenRBC, a coarse-grained molecular dynamics code, which is capable of performing an unprecedented in silico experiment - simulating an entire mammal red blood cell lipid bilayer and cytoskeleton modeled by 4 million mesoscopic particles - on a single shared memory node. To achieve this, we invented an adaptive spatial searching algorithm to accelerate the computation of short-range pairwise interactions in an extremely sparse 3D space. The algorithm is based on a Voronoi partitioning of the point cloud of coarse-grained particles, and is continuously updated over the course of the simulation. The algorithm enables the construction of a lattice-free cell list, i.e. the key spatial searching data structure in our code, in O (N) time and space space with cells whose position and shape adapts automatically to the local density and curvature. The code implements NUMA/NUCA-aware OpenMP parallelization and achieves perfect scaling with up to hundreds of hardware threads. The code outperforms a legacy solver by more than 8 times in time-to-solution and more than 20 times in problem size, thus providing a new venue for probing the cytomechanics of red blood cells. This work was supported by the Department of Energy (DOE) Collaboratory on Mathematics for Mesoscopic Model- ing of Materials (CM4). YHT acknowledges partial financial support from an IBM Ph.D. Scholarship Award.
Models@Home: distributed computing in bioinformatics using a screensaver based approach.
Krieger, Elmar; Vriend, Gert
2002-02-01
Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.
Valentine, P.C.; Commeau, J.A.
1990-01-01
The Gulf of Maine, an embayment of the New England margin, is floored by shallow, glacially scoured basins that are partly filled with late Pleistocene and Holocene silt and clay containing 0.7 to 1.0 wt percent TiO2 chiefly in the form of silt-size rutile. Much of the rutile in the Gulf of Maine mud probably formed diagenetically in poorly cemented Carboniferous and Triassic coarse-grained sedimentary rocks of Nova Scotia and New Brunswick after the dissolution of titanium-rich detrital minerals (ilmenite, ilmenomagnetite). The diagenesis of rutile in coarse sedimentary rocks (especially arkose and graywacke) followed by erosion, segregation, and deposition (and including recycling of fine-grained rutile from shales) can serve as a model for predicting and prospecting for unconsolidated deposits of fine-grained TiO2. -from Authors
Spirov, Alexander; Holloway, David
2013-07-15
This paper surveys modeling approaches for studying the evolution of gene regulatory networks (GRNs). Modeling of the design or 'wiring' of GRNs has become increasingly common in developmental and medical biology, as a means of quantifying gene-gene interactions, the response to perturbations, and the overall dynamic motifs of networks. Drawing from developments in GRN 'design' modeling, a number of groups are now using simulations to study how GRNs evolve, both for comparative genomics and to uncover general principles of evolutionary processes. Such work can generally be termed evolution in silico. Complementary to these biologically-focused approaches, a now well-established field of computer science is Evolutionary Computations (ECs), in which highly efficient optimization techniques are inspired from evolutionary principles. In surveying biological simulation approaches, we discuss the considerations that must be taken with respect to: (a) the precision and completeness of the data (e.g. are the simulations for very close matches to anatomical data, or are they for more general exploration of evolutionary principles); (b) the level of detail to model (we proceed from 'coarse-grained' evolution of simple gene-gene interactions to 'fine-grained' evolution at the DNA sequence level); (c) to what degree is it important to include the genome's cellular context; and (d) the efficiency of computation. With respect to the latter, we argue that developments in computer science EC offer the means to perform more complete simulation searches, and will lead to more comprehensive biological predictions. Copyright © 2013 Elsevier Inc. All rights reserved.
Effect of physicochemical factors on transport and retention of graphene oxide in saturated media.
Chen, Chong; Shang, Jianying; Zheng, Xiaoli; Zhao, Kang; Yan, Chaorui; Sharma, Prabhakar; Liu, Kesi
2018-05-01
Fate and transport of graphene oxide (GO) have received much attention recently with the increase of GO applications. This study investigated the effect of salt concentration on the transport and retention behavior of GO particles in heterogeneous saturated porous media. Transport experiments were conducted in NaCl solutions with three concentrations (1, 20, and 50 mM) using six structurally packed columns (two homogeneous and four heterogeneous) which were made of fine and coarse grains. The results showed that GO particles had high mobility in all the homogeneous and heterogeneous columns when solution ionic strength (IS) was low. When IS was high, GO particles showed distinct transport ability in six structurally heterogeneous porous media. In homogeneous columns, decreasing ionic strength and increasing grain size increased the mobility of GO. For the column containing coarse-grained channel, the preferential flow path resulted in an early breakthrough of GO, and further larger contact area between coarse and fine grains caused a lower breakthrough peak and a stronger tailing at different IS. In the layered column, there was significant GO retention at coarse-fine grain interface where water flowed from coarse grain to fine grain. Our results indicated that the fate and transport of GO particles in the natural heterogeneous porous media was highly related to the coupled effect of medium structure and salt solution concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.
Simulation of polymer translocation through protein channels
Muthukumar, M.; Kong, C. Y.
2006-01-01
A modeling algorithm is presented to compute simultaneously polymer conformations and ionic current, as single polymer molecules undergo translocation through protein channels. The method is based on a combination of Langevin dynamics for coarse-grained models of polymers and the Poisson–Nernst–Planck formalism for ionic current. For the illustrative example of ssDNA passing through the α-hemolysin pore, vivid details of conformational fluctuations of the polymer inside the vestibule and β-barrel compartments of the protein pore, and their consequent effects on the translocation time and extent of blocked ionic current are presented. In addition to yielding insights into several experimentally reported puzzles, our simulations offer experimental strategies to sequence polymers more efficiently. PMID:16567657
Non-Markovian closure models for large eddy simulations using the Mori-Zwanzig formalism
NASA Astrophysics Data System (ADS)
Parish, Eric J.; Duraisamy, Karthik
2017-01-01
This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from nonequilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbulence. The mechanics of the generalized Langevin equation (GLE) are considered, and insight gained from the orthogonal dynamics equation is used as a starting point for model development. A class of subgrid models is considered which represent nonlocal behavior via a finite memory approximation [Stinis, arXiv:1211.4285 (2012)], the length of which is determined using a heuristic that is related to the spectral radius of the Jacobian of the resolved variables. The resulting models are intimately tied to the underlying numerical resolution and are capable of approximating non-Markovian effects. Numerical experiments on the Burgers equation demonstrate that the M-Z-based models can accurately predict the temporal evolution of the total kinetic energy and the total dissipation rate at varying mesh resolutions. The trajectory of each resolved mode in phase space is accurately predicted for cases where the coarse graining is moderate. Large eddy simulations (LESs) of homogeneous isotropic turbulence and the Taylor-Green Vortex show that the M-Z-based models are able to provide excellent predictions, accurately capturing the subgrid contribution to energy transfer. Last, LESs of fully developed channel flow demonstrate the applicability of M-Z-based models to nondecaying problems. It is notable that the form of the closure is not imposed by the modeler, but is rather derived from the mathematics of the coarse graining, highlighting the potential of M-Z-based techniques to define LES closures.
Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P
2016-09-01
The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.
Ion distributions in electrolyte confined by multiple dielectric interfaces
NASA Astrophysics Data System (ADS)
Jing, Yufei; Zwanikken, Jos W.; Jadhao, Vikram; de La Cruz, Monica
2014-03-01
The distribution of ions at dielectric interfaces between liquids characterized by different dielectric permittivities is crucial to nanoscale assembly processes in many biological and synthetic materials such as cell membranes, colloids and oil-water emulsions. The knowledge of ionic structure of these systems is also exploited in energy storage devices such as double-layer super-capacitors. The presence of multiple dielectric interfaces often complicates computing the desired ionic distributions via simulations or theory. Here, we use coarse-grained models to compute the ionic distributions in a system of electrolyte confined by two planar dielectric interfaces using Car-Parrinello molecular dynamics simulations and liquid state theory. We compute the density profiles for various electrolyte concentrations, stoichiometric ratios and dielectric contrasts. The explanations for the trends in these profiles and discuss their effects on the behavior of the confined charged fluid are also presented.
NASA Astrophysics Data System (ADS)
Cordier, P.; Sun, X.; Taupin, V.; Fressengeas, C.
2016-12-01
Grain boundaries (GBs) are thin material layers where the lattice rotates from one orientation to the next one within a few nanometers. Because they treat these layers as infinitely thin interfaces, large-scale polycrystalline representations fail to describe their structure. Conversely, atomistic representations provide a detailed description of the GBs, but their character remains discrete and not prone to coarse-graining procedures. Continuum descriptions based on kinematic and crystal defect fields defined at interatomic scale are appealing because they can provide smooth and thorough descriptions of GBs, recovering in some sense the atomistic description and potentially serving as a basis for coarse-grained polycrystalline representations. In this work, a crossover between atomistic description and continuous representation of a MgO tilt boundary in polycrystals is set-up to model the periodic arrays of structural units by using dislocation and disclination dipole arrays along GBs. The strain, rotation, curvature, disclination and dislocation density fields are determined in the boundary area by using the discrete atomic positions generated by molecular dynamics simulations. Then, this continuous disclination/dislocation model is used as part of the initial conditions in elasto-plastic continuum mechanics simulations to investigate the shear-coupled boundary migration of tilt boundaries. The present study leads to better understanding of the structure and mechanical architecture of grain boundaries.
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu
2015-12-28
The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while themore » corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.« less
Coarse-graining to the meso and continuum scales with molecular-dynamics-like models
NASA Astrophysics Data System (ADS)
Plimpton, Steve
Many engineering-scale problems that industry or the national labs try to address with particle-based simulations occur at length and time scales well beyond the most optimistic hopes of traditional coarse-graining methods for molecular dynamics (MD), which typically start at the atomic scale and build upward. However classical MD can be viewed as an engine for simulating particles at literally any length or time scale, depending on the models used for individual particles and their interactions. To illustrate I'll highlight several coarse-grained (CG) materials models, some of which are likely familiar to molecular-scale modelers, but others probably not. These include models for water droplet freezing on surfaces, dissipative particle dynamics (DPD) models of explosives where particles have internal state, CG models of nano or colloidal particles in solution, models for aspherical particles, Peridynamics models for fracture, and models of granular materials at the scale of industrial processing. All of these can be implemented as MD-style models for either soft or hard materials; in fact they are all part of our LAMMPS MD package, added either by our group or contributed by collaborators. Unlike most all-atom MD simulations, CG simulations at these scales often involve highly non-uniform particle densities. So I'll also discuss a load-balancing method we've implemented for these kinds of models, which can improve parallel efficiencies. From the physics point-of-view, these models may be viewed as non-traditional or ad hoc. But because they are MD-style simulations, there's an opportunity for physicists to add statistical mechanics rigor to individual models. Or, in keeping with a theme of this session, to devise methods that more accurately bridge models from one scale to the next.
Piedramuelle Limestone in the building heritage of Oviedo, Spain, and adjacent towns.
NASA Astrophysics Data System (ADS)
Cardenes Van den Eynde, Victor; Mateos, Felix Javier; Valdeon, Luis; Rojo, Araceli
2017-04-01
The Piedramuelle limestone has a very important representation in the building heritage of Oviedo, historical capital of Asturias (Spain) and surrounding towns. This argillaceous limestone has been quarried since the High Middle Ages until the beginning of the XX century. The main mineralogical components are carbonates (mainly calcite and sometimes ankerite, 70-90%), quartz (5-15%), terrigenous minerals (6-15%) and iron oxides (<5%). Two different facies, with different constructive uses, can be clearly distinguished depending on the grain size: fine-grained facies and coarse-grained facies. The fine-grained facies has color ranging from red to yellow, slightly higher content in carbonates, higher terrigenous components and a micro crystalline texture. The coarse-grained facies is mainly yellow, with detrital clastic texture. The open porosity is higher for the coarse-grained facies (16-20%), while for the fine-grained facies it ranges between 5 and 15%. The fine-grained facies is more vulnerable to weathering than the coarse-grained one, and it is used in the building heritage mainly for ornamental details, while the coarse-grained one is found in the bigger blocks and ashlars of the buildings. Some of the buildings constructed with Piedramuelle limestone are the Cathedral, the Old University and the Palaces from the XVII and XVIII centuries. The ambiance and historical architecture of Oviedo and adjacent towns is closely linked with the textures and colors of this stone. Nowadays, the Piedramuelle limestone is not exploited anymore, being the quarries exhausted. This represents an issue from a conservation point of view, since there is not a suitable stone for replacement. In order to preserve and maintain the building heritage of these towns, it is very important to prospect and protect the remaining outcrops still able to supply this characteristic stone.
Control over Grain Size in Memory Reporting--with and without Satisficing Knowledge
ERIC Educational Resources Information Center
Ackerman, Rakefet; Goldsmith, Morris
2008-01-01
When answering questions from memory, respondents strategically control the precision or coarseness of their answers. This grain control process is guided by 2 countervailing aims: to be informative and to be correct. Previously, M. Goldsmith, A. Koriat, and A. Weinberg Eliezer (2002) proposed a "satisficing model" in which respondents…
Coarse-grained simulations of cis- and trans-polybutadiene: A bottom-up approach
NASA Astrophysics Data System (ADS)
Lemarchand, Claire A.; Couty, Marc; Rousseau, Bernard
2017-02-01
We apply the dissipative particle dynamics strategy proposed by Hijón et al. [Faraday Discuss. 144, 301-322 (2010)] and based on an exact derivation of the generalized Langevin equation to cis- and trans-1,4-polybutadiene. We prove that it is able to reproduce not only the structural but also the dynamical properties of these polymers without any fitting parameter. A systematic study of the effect of the level of coarse-graining is done on cis-1,4-polybutadiene. We show that as the level of coarse-graining increases, the dynamical properties are better and better reproduced while the structural properties deviate more and more from those calculated in molecular dynamics (MD) simulations. We suggest two reasons for this behavior: the Markovian approximation is better satisfied as the level of coarse-graining increases, while the pair-wise approximation neglects important contributions due to the relative orientation of the beads at large levels of coarse-graining. Finally, we highlight a possible limit of the Markovian approximation: the fact that in constrained simulations, in which the centers-of-mass of the beads are kept constant, the bead rotational dynamics become extremely slow.
Modeling the effect of dune sorting on the river long profile
NASA Astrophysics Data System (ADS)
Blom, A.
2012-12-01
River dunes, which occur in low slope sand bed and sand-gravel bed rivers, generally show a downward coarsening pattern due to grain flows down their avalanche lee faces. These grain flows cause coarse particles to preferentially deposit at lower elevations of the lee face, while fines show a preference for its upper elevations. Before considering the effect of this dune sorting mechanism on the river long profile, let us first have a look at some general trends along the river profile. Tributaries increasing the river's water discharge in streamwise direction also cause a streamwise increase in flow depth. As under subcritical conditions mean dune height generally increases with increasing flow depth, the dune height shows a streamwise increase, as well. This means that also the standard deviation of bedform height increases in streamwise direction, as in earlier work it was found that the standard deviation of bedform height linearly increases with an increasing mean value of bedform height. As a result of this streamwise increase in standard deviation of dune height, the above-mentioned dune sorting then results in a loss of coarse particles to the lower elevations of the bed that are less and even rarely exposed to the flow. This loss of coarse particles to lower elevations thus increases the rate of fining in streamwise direction. As finer material is more easily transported downstream than coarser material, a smaller bed slope is required to transport the same amount of sediment downstream. This means that dune sorting adds to river profile concavity, compared to the combined effect of abrasion, selective transport and tributaries. A Hirano-type mass conservation model is presented that deals with dune sorting. The model includes two active layers: a bedform layer representing the sediment in the bedforms and a coarse layer representing the coarse and less mobile sediment underneath migrating bedforms. The exposure of the coarse layer is governed by the rate of sediment supply from upstream. By definition the sum of the exposure of both layers equals unity. The model accounts for vertical sediment fluxes due to grain flows down the bedform lee face and the formation of a less mobile coarse layer. The model with its vertical sediment fluxes is validated against earlier flume experiments. It deals well with the transition between a plane bed and a bedform-dominated bed. Applying the model to field scale confirms that dune sorting increases river profile concavity.
Entrainment of coarse grains using a discrete particle model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Valyrakis, Manousos, E-mail: Manousos.Valyrakis@glasgow.ac.uk; Arnold, Roger B. Jr.
2014-10-06
Conventional bedload transport models and incipient motion theories relying on a time-averaged boundary shear stress are incapable of accounting for the effects of fluctuating near-bed velocity in turbulent flow and are therefore prone to significant errors. Impulse, the product of an instantaneous force magnitude and its duration, has been recently proposed as an appropriate criterion for quantifying the effects of flow turbulence in removing coarse grains from the bed surface. Here, a discrete particle model (DPM) is used to examine the effects of impulse, representing a single idealized turbulent event, on particle entrainment. The results are classified according to themore » degree of grain movement into the following categories: motion prior to entrainment, initial dislodgement, and energetic displacement. The results indicate that in all three cases the degree of particle motion depends on both the force magnitude and the duration of its application and suggest that the effects of turbulence must be adequately accounted for in order to develop a more accurate method of determining incipient motion. DPM is capable of simulating the dynamics of grain entrainment and is an appropriate tool for further study of the fundamental mechanisms of sediment transport.« less
Relative resolution: A hybrid formalism for fluid mixtures.
Chaimovich, Aviel; Peter, Christine; Kremer, Kurt
2015-12-28
We show here that molecular resolution is inherently hybrid in terms of relative separation. While nearest neighbors are characterized by a fine-grained (geometrically detailed) model, other neighbors are characterized by a coarse-grained (isotropically simplified) model. We notably present an analytical expression for relating the two models via energy conservation. This hybrid framework is correspondingly capable of retrieving the structural and thermal behavior of various multi-component and multi-phase fluids across state space.
Relative resolution: A hybrid formalism for fluid mixtures
NASA Astrophysics Data System (ADS)
Chaimovich, Aviel; Peter, Christine; Kremer, Kurt
2015-12-01
We show here that molecular resolution is inherently hybrid in terms of relative separation. While nearest neighbors are characterized by a fine-grained (geometrically detailed) model, other neighbors are characterized by a coarse-grained (isotropically simplified) model. We notably present an analytical expression for relating the two models via energy conservation. This hybrid framework is correspondingly capable of retrieving the structural and thermal behavior of various multi-component and multi-phase fluids across state space.
Wilczynski, Bartek; Furlong, Eileen E M
2010-04-15
Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.
Pulawski, Wojciech; Jamroz, Michal; Kolinski, Michal; Kolinski, Andrzej; Kmiecik, Sebastian
2016-11-28
The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shendruk, Tyler N., E-mail: tyler.shendruk@physics.ox.ac.uk; Bertrand, Martin; Harden, James L.
2014-12-28
Given the ubiquity of depletion effects in biological and other soft matter systems, it is desirable to have coarse-grained Molecular Dynamics (MD) simulation approaches appropriate for the study of complex systems. This paper examines the use of two common truncated Lennard-Jones (Weeks-Chandler-Andersen (WCA)) potentials to describe a pair of colloidal particles in a thermal bath of depletants. The shifted-WCA model is the steeper of the two repulsive potentials considered, while the combinatorial-WCA model is the softer. It is found that the depletion-induced well depth for the combinatorial-WCA model is significantly deeper than the shifted-WCA model because the resulting overlap ofmore » the colloids yields extra accessible volume for depletants. For both shifted- and combinatorial-WCA simulations, the second virial coefficients and pair potentials between colloids are demonstrated to be well approximated by the Morphometric Thermodynamics (MT) model. This agreement suggests that the presence of depletants can be accurately modelled in MD simulations by implicitly including them through simple, analytical MT forms for depletion-induced interactions. Although both WCA potentials are found to be effective generic coarse-grained simulation approaches for studying depletion effects in complicated soft matter systems, combinatorial-WCA is the more efficient approach as depletion effects are enhanced at lower depletant densities. The findings indicate that for soft matter systems that are better modelled by potentials with some compressibility, predictions from hard-sphere systems could greatly underestimate the magnitude of depletion effects at a given depletant density.« less
Path statistics, memory, and coarse-graining of continuous-time random walks on networks
Kion-Crosby, Willow; Morozov, Alexandre V.
2015-01-01
Continuous-time random walks (CTRWs) on discrete state spaces, ranging from regular lattices to complex networks, are ubiquitous across physics, chemistry, and biology. Models with coarse-grained states (for example, those employed in studies of molecular kinetics) or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics. However, existing methods for analyzing CTRWs on complex energy landscapes do not address these effects. Here we use statistical mechanics of the nonequilibrium path ensemble to characterize first-passage CTRWs on networks with arbitrary connectivity, energy landscape, and waiting time distributions. Our approach can be applied to calculating higher moments (beyond the mean) of path length, time, and action, as well as statistics of any conservative or non-conservative force along a path. For homogeneous networks, we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process with its discrete-time projection. For more general models, we obtain recursion relations, reminiscent of transfer matrix and exact enumeration techniques, to efficiently calculate path statistics numerically. We have implemented our algorithm in PathMAN (Path Matrix Algorithm for Networks), a Python script that users can apply to their model of choice. We demonstrate the algorithm on a few representative examples which underscore the importance of non-exponential distributions, memory, and coarse-graining in CTRWs. PMID:26646868
Correlations in polymer blends: Simulations, perturbation theory, and coarse-grained theory
NASA Astrophysics Data System (ADS)
Chung, Jun Kyung
A thermodynamic perturbation theory of symmetric polymer blends is developed that properly accounts for the correlation in the spatial arrangement of monomers. By expanding the free energy of mixing in powers of a small parameter alpha which controls the incompatibility of two monomer species, we show that the perturbation theory has the form of the original Flory-Huggins theory, to first order in alpha. However, the lattice coordination number in the original theory is replaced by an effective coordination number. A random walk model for the effective coordination number is found to describe Monte Carlo simulation data very well. We also propose a way to estimate Flory-Huggins chi parameter by extrapolating the perturbation theory to the limit of a hypothetical system of infinitely long chains. The first order perturbation theory yields an accurate estimation of chi to first order in alpha. Going to second order, however, turns out to be more involved and an unambiguous determination of the coefficient of alpha2 term is not possible at the moment. Lastly, we test the predictions of a renormalized one-loop theory of fluctuations using two coarse-grained models of symmetric polymer blends at the critical composition. It is found that the theory accurately describes the correlation effect for relatively small values of chiN. In addition, the universality assumption of coarse-grained models is examined and we find results that are supportive of it.
Hyltegren, Kristin; Skepö, Marie
2017-05-15
The adsorbed amount of the polyelectrolyte-like protein histatin 5 on a silica surface depends on the pH and the ionic strength of the solution. Interestingly, an increase in ionic strength affects the adsorbed amount differently depending on the pH of the solution, as shown by ellipsometry measurements (Hyltegren, 2016). We have tested the hypothesis that the same (qualitative) trends can be found also from a coarse-grained model that takes all charge-charge interactions into account within the frameworks of Gouy-Chapman and Debye-Hückel theories. Using the same coarse-grained model as in our previous Monte Carlo study of single protein adsorption (Hyltegren, 2016), simulations of systems with many histatin 5 molecules were performed and then compared with ellipsometry measurements. The strength of the short-ranged attractive interaction between the protein and the surface was varied. The coarse-grained model does not qualitatively reproduce the pH-dependence of the experimentally observed trends in adsorbed amount as a function of ionic strength. However, the simulations cast light on the balance between electrostatic attraction between protein and surface and electrostatic repulsion between adsorbed proteins, the deficiencies of the Langmuir isotherm, and the implications of protein charge regulation in concentrated systems. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Mukherjee, Biswaroop; Peter, Christine; Kremer, Kurt
2017-09-01
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.
NASA Astrophysics Data System (ADS)
Friese, Carmen A.; van der Does, Michèlle; Merkel, Ute; Iversen, Morten H.; Fischer, Gerhard; Stuut, Jan-Berend W.
2016-09-01
The particle sizes of Saharan dust in marine sediment core records have been used frequently as a proxy for trade-wind speed. However, there are still large uncertainties with respect to the seasonality of the particle sizes of deposited Saharan dust off northwestern Africa and the factors influencing this seasonality. We investigated a three-year time-series of grain-size data from two sediment-trap moorings off Cape Blanc, Mauritania and compared them to observed wind-speed and precipitation as well as satellite images. Our results indicate a clear seasonality in the grain-size distributions: during summer the modal grain sizes were generally larger and the sorting was generally less pronounced compared to the winter season. Gravitational settling was the major deposition process during winter. We conclude that the following two mechanisms control the modal grain size of the collected dust during summer: (1) wet deposition causes increased deposition fluxes resulting in coarser modal grain sizes and (2) the development of cold fronts favors the emission and transport of coarse particles off Cape Blanc. Individual dust-storm events throughout the year could be recognized in the traps as anomalously coarse-grained samples. During winter and spring, intense cyclonic dust-storm events in the dust-source region explained the enhanced emission and transport of a larger component of coarse particles off Cape Blanc. The outcome of our study provides important implications for climate modellers and paleo-climatologists.
Coarse-grained simulations of protein-protein association: an energy landscape perspective.
Ravikumar, Krishnakumar M; Huang, Wei; Yang, Sichun
2012-08-22
Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Coarse-Grained Simulations of Protein-Protein Association: An Energy Landscape Perspective
Ravikumar, Krishnakumar M.; Huang, Wei; Yang, Sichun
2012-01-01
Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. PMID:22947945
Calculations of the binding affinities of protein-protein complexes with the fast multipole method
NASA Astrophysics Data System (ADS)
Kim, Bongkeun; Song, Jiming; Song, Xueyu
2010-09-01
In this paper, we used a coarse-grained model at the residue level to calculate the binding free energies of three protein-protein complexes. General formulations to calculate the electrostatic binding free energy and the van der Waals free energy are presented by solving linearized Poisson-Boltzmann equations using the boundary element method in combination with the fast multipole method. The residue level model with the fast multipole method allows us to efficiently investigate how the mutations on the active site of the protein-protein interface affect the changes in binding affinities of protein complexes. Good correlations between the calculated results and the experimental ones indicate that our model can capture the dominant contributions to the protein-protein interactions. At the same time, additional effects on protein binding due to atomic details are also discussed in the context of the limitations of such a coarse-grained model.
Jämbeck, Joakim P M; Eriksson, Emma S E; Laaksonen, Aatto; Lyubartsev, Alexander P; Eriksson, Leif A
2014-01-14
Liposomes are proposed as drug delivery systems and can in principle be designed so as to cohere with specific tissue types or local environments. However, little detail is known about the exact mechanisms for drug delivery and the distributions of drug molecules inside the lipid carrier. In the current work, a coarse-grained (CG) liposome model is developed, consisting of over 2500 lipids, with varying degrees of drug loading. For the drug molecule, we chose hypericin, a natural compound proposed for use in photodynamic therapy, for which a CG model was derived and benchmarked against corresponding atomistic membrane bilayer model simulations. Liposomes with 21-84 hypericin molecules were generated and subjected to 10 microsecond simulations. Distribution of the hypericins, their orientations within the lipid bilayer, and the potential of mean force for transferring a hypericin molecule from the interior aqueous "droplet" through the liposome bilayer are reported herein.
Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling
MacDonald, James T.; Kelley, Lawrence A.; Freemont, Paul S.
2013-01-01
Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using -carbon positions only and sampling conformations with a Monte Carlo simulated annealing based protocol. Backbone atoms were added using a method previously described and then gradient minimised in the Rosetta force field. Despite the CG potential energy function being sequence-independent, the method performed similarly to methods that explicitly use either fragments of known protein backbones with similar sequences or residue-specific /-maps to restrict the search space. The method was also able to predict with sub-Angstrom accuracy two out of seven loops from recently solved crystal structures of proteins with low sequence and structure similarity to previously deposited structures in the PDB. The ability to sample realistic loop conformations directly from a potential energy function enables the incorporation of additional geometric restraints and the use of more advanced sampling methods in a way that is not possible to do easily with fragment replacement methods and also enable multi-scale simulations for protein design and protein structure prediction. These restraints could be derived from experimental data or could be design restraints in the case of computational protein design. C++ source code is available for download from http://www.sbg.bio.ic.ac.uk/phyre2/PD2/. PMID:23824634
Zhang, Peng; Gao, Chao; Zhang, Na; Slepian, Marvin J.; Deng, Yuefan; Bluestein, Danny
2014-01-01
We developed a multiscale particle-based model of platelets, to study the transport dynamics of shear stresses between the surrounding fluid and the platelet membrane. This model facilitates a more accurate prediction of the activation potential of platelets by viscous shear stresses - one of the major mechanisms leading to thrombus formation in cardiovascular diseases and in prosthetic cardiovascular devices. The interface of the model couples coarse-grained molecular dynamics (CGMD) with dissipative particle dynamics (DPD). The CGMD handles individual platelets while the DPD models the macroscopic transport of blood plasma in vessels. A hybrid force field is formulated for establishing a functional interface between the platelet membrane and the surrounding fluid, in which the microstructural changes of platelets may respond to the extracellular viscous shear stresses transferred to them. The interaction between the two systems preserves dynamic properties of the flowing platelets, such as the flipping motion. Using this multiscale particle-based approach, we have further studied the effects of the platelet elastic modulus by comparing the action of the flow-induced shear stresses on rigid and deformable platelet models. The results indicate that neglecting the platelet deformability may overestimate the stress on the platelet membrane, which in turn may lead to erroneous predictions of the platelet activation under viscous shear flow conditions. This particle-based fluid-structure interaction multiscale model offers for the first time a computationally feasible approach for simulating deformable platelets interacting with viscous blood flow, aimed at predicting flow induced platelet activation by using a highly resolved mapping of the stress distribution on the platelet membrane under dynamic flow conditions. PMID:25530818
Computational Study of Uniaxial Deformations in Silica Aerogel Using a Coarse-Grained Model.
Ferreiro-Rangel, Carlos A; Gelb, Lev D
2015-07-09
Simulations of a flexible coarse-grained model are used to study silica aerogels. This model, introduced in a previous study (J. Phys. Chem. C 2007, 111, 15792), consists of spherical particles which interact through weak nonbonded forces and strong interparticle bonds that may form and break during the simulations. Small-deformation simulations are used to determine the elastic moduli of a wide range of material models, and large-deformation simulations are used to probe structural evolution and plastic deformation. Uniaxial deformation at constant transverse pressure is simulated using two methods: a hybrid Monte Carlo approach combining molecular dynamics for the motion of individual particles and stochastic moves for transverse stress equilibration, and isothermal molecular dynamics simulations at fixed Poisson ratio. Reasonable agreement on elastic moduli is obtained except at very low densities. The model aerogels exhibit Poisson ratios between 0.17 and 0.24, with higher-density gels clustered around 0.20, and Young's moduli that vary with aerogel density according to a power-law dependence with an exponent near 3.0. These results are in agreement with reported experimental values. The models are shown to satisfy the expected homogeneous isotropic linear-elastic relationship between bulk and Young's moduli at higher densities, but there are systematic deviations at the lowest densities. Simulations of large compressive and tensile strains indicate that these materials display a ductile-to-brittle transition as the density is increased, and that the tensile strength varies with density according to a power law, with an exponent in reasonable agreement with experiment. Auxetic behavior is observed at large tensile strains in some models. Finally, at maximum tensile stress very few broken bonds are found in the materials, in accord with the theory that only a small fraction of the material structure is actually load-bearing.
A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sinitskiy, Anton V.; Voth, Gregory A., E-mail: gavoth@uchicago.edu
2015-09-07
Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman’s imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionistmore » perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.« less
Krüger, Dennis M; Ahmed, Aqeel; Gohlke, Holger
2012-07-01
The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.
A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals.
Sinitskiy, Anton V; Voth, Gregory A
2015-09-07
Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman's imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.
Shang, Barry Z; Voulgarakis, Nikolaos K; Chu, Jhih-Wei
2012-07-28
This work illustrates that fluctuating hydrodynamics (FHD) simulations can be used to capture the thermodynamic and hydrodynamic responses of molecular fluids at the nanoscale, including those associated with energy and heat transfer. Using all-atom molecular dynamics (MD) trajectories as the reference data, the atomistic coordinates of each snapshot are mapped onto mass, momentum, and energy density fields on Eulerian grids to generate a corresponding field trajectory. The molecular length-scale associated with finite molecule size is explicitly imposed during this coarse-graining by requiring that the variances of density fields scale inversely with the grid volume. From the fluctuations of field variables, the response functions and transport coefficients encoded in the all-atom MD trajectory are computed. By using the extracted fluid properties in FHD simulations, we show that the fluctuations and relaxation of hydrodynamic fields quantitatively match with those observed in the reference all-atom MD trajectory, hence establishing compatibility between the atomistic and field representations. We also show that inclusion of energy transfer in the FHD equations can more accurately capture the thermodynamic and hydrodynamic responses of molecular fluids. The results indicate that the proposed MD-to-FHD mapping with explicit consideration of finite molecule size provides a robust framework for coarse-graining the solution phase of complex molecular systems.
Adiabatic coarse-graining and simulations of stochastic biochemical networks
Sinitsyn, N. A.; Hengartner, Nicolas; Nemenman, Ilya
2009-01-01
We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical networks, which rests on elimination of fast chemical species without a loss of information about mesoscopic, non-Poissonian fluctuations of the slow ones. Our approach is similar to the Born–Oppenheimer approximation in quantum mechanics and follows from the stochastic path integral representation of the cumulant generating function of reaction events. In applications with a small number of chemical reactions, it produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, interpretable representation and can be used for high-accuracy, low-complexity coarse-grained numerical simulations. As an example, we derive the coarse-grained description for a chain of biochemical reactions and show that the coarse-grained and the microscopic simulations agree, but the former is 3 orders of magnitude faster. PMID:19525397
Yoo, Jejoong; Cui, Qiang
2013-01-08
Using both atomistic and coarse-grained (CG) models, we compute the three-dimensional stress field around a gramicidin A (gA) dimer in lipid bilayers that feature different degrees of negative hydrophobic mismatch. The general trends in the computed stress field are similar at the atomistic and CG levels, supporting the use of the CG model for analyzing the mechanical features of protein/lipid/water interfaces. The calculations reveal that the stress field near the protein-lipid interface exhibits a layered structure with both significant repulsive and attractive regions, with the magnitude of the stress reaching 1000 bar in certain regions. Analysis of density profiles and stress field distributions helps highlight the Trp residues at the protein/membrane/water interface as mechanical anchors, suggesting that similar analysis is useful for identifying tension sensors in other membrane proteins, especially membrane proteins involved in mechanosensation. This work fosters a connection between microscopic and continuum mechanics models for proteins in complex environments and makes it possible to test the validity of assumptions commonly made in continuum mechanics models for membrane mediated processes. For example, using the calculated stress field, we estimate the free energy of membrane deformation induced by the hydrophobic mismatch, and the results for regions beyond the annular lipids are in general consistent with relevant experimental data and previous theoretical estimates using elasticity theory. On the other hand, the assumptions of homogeneous material properties for the membrane and a bilayer thickness at the protein/lipid interface being independent of lipid type (e.g., tail length) appear to be oversimplified, highlighting the importance of annular lipids of membrane proteins. Finally, the stress field analysis makes it clear that the effect of even rather severe hydrophobic mismatch propagates to only about two to three lipid layers, thus putting a limit on the range of cooperativity between membrane proteins in crowded cellular membranes. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Using Markov state models to study self-assembly
NASA Astrophysics Data System (ADS)
Perkett, Matthew R.; Hagan, Michael F.
2014-06-01
Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude.
Geochemical evidence for the provenance of aeolian deposits in the Qaidam Basin, Tibetan Plateau
NASA Astrophysics Data System (ADS)
Du, Shisong; Wu, Yongqiu; Tan, Lihua
2018-06-01
The main purpose of this study is to analyse the material source of different grain-size components of dune sand in the Qaidam Basin. We determined the trace and rare earth element (REE) compositions and Sr-Nd isotopic compositions of the coarse (75-500 μm) and fine (<75 μm) fractions of surface sediment samples. The comparison of the immobile trace element and REE compositions, Sr-Nd isotopic compositions and multidimensional scaling (MDS) results of the dune sands with those of different types of sediments in potential source areas revealed the following information. (1) The fine- and coarse-grained fractions of dune sands in the Qaidam Basin exhibit distinctly different elemental concentrations, elemental patterns and characteristic parameters of REE. Moreover, Sr-Nd isotopic differences also exist between different grain-size fractions of aeolian sand, which means that different grain-size fractions of these dune sands have different source areas. (2) The geochemical characteristics of the coarse particles of dune sand exhibit obvious regional heterogeneity and generally record a local origin derived from local fluvial sediments and alluvial/proluvial sediments. The coarse- and fine-grained dune sand in the southern Qaidam Basin mainly came from Kunlun Mountains, whereas the coarse- and fine-grained dune sand in the northeastern Qaidam Basin mainly came from Qilian Mountains. (3) The fine-grained fractions of sediments throughout the entire Qaidam Basin may have been affected by the input of foreign materials from the Tarim Basin.
Volatile elements in Allende inclusions. [Mn, Na and Cl relation to meteorite evolution
NASA Technical Reports Server (NTRS)
Grossman, L.; Ganapathy, R.
1975-01-01
New data are presented on the relatively volatile elements (Mn, Na, and Cl) in coarse- and fine-grained Ca/Al-rich inclusions of different textures and mineralogy in the Allende meteorite. It is shown that the coarse-grained inclusions condensed from the solar nebula at high temperature and contained vanishingly small quantities of volatile elements at that time. Later, volatiles were added to these during the metamorphism of the Allende parent body. The fine-grained inclusions were also affected by the addition of volatiles during this metamorphism but, unlike the coarse-grained ones, they incorporated large amounts of volatiles when they condensed from the solar nebula, accounting for their higher volatile element contents.
NASA Astrophysics Data System (ADS)
Deng, Yu-Feng; Yuan, Feng; Zhou, Taofa; Hollings, Pete; Zhang, Dayu
2018-06-01
The Keketuobie intrusion is situated in the northern part of the West Junggar foldbelt at the southern margin of the Central Asian Orogeic Belt. The intrusion consists of medium- to coarse-grained gabbro, fine-grained gabbro and diorite. Igneous zircons from the medium- to coarse-grained gabbro yielded a LA-ICP-MS U-Pb age of 320.8 ± 5.7 Ma, indicating that the intrusion was emplaced in the Early Carboniferous. The intrusive contact between the medium- to coarse-grained gabbro and the fine-grained gabbro indicates they formed from distinct magma pulses. Magnetite crystals from the fine-grained gabbro have lower V2O3 but higher TiO2 and Al2O3 contents than those of the medium- to coarse-grained gabbro, suggesting that the fine-grained gabbro crystallized in a relatively higher fO2 and temperature magma than the medium- to coarse-grained gabbro. The Keketuobie intrusive rocks are characterized by enriched large ion lithophile elements and depleted high field strength elements relative to N-MORB with restricted (87Sr/86Sr)t ratios (0.70370-0.70400) and εNd(t) values (+5.85 to +6.97). The petrography and geochemistry are comparable to those of subduction-related volcanic rocks. The trace elements and isotopic compositions of the mafic intrusive rocks suggest that the primary magmas were derived from mixing of metasomatized lithospheric mantle and depleted asthenospheric melts, perhaps triggered by slab break-off. The Keketuobie intrusion is younger than adjacent ophiolite sequences, island arc volcanic rocks and porphyry deposits, but predates the post-collisional A-type granites and bimodal volcanic rocks in the district, suggesting that the Keketuobie intrusion likely formed in a syn-collisional setting.
A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma
Ku, S.; Hager, R.; Chang, C. S.; ...
2016-04-01
In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles providemore » scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. In conclusion, the numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.« less
A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ku, S.; Hager, R.; Chang, C. S.
In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles providemore » scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. In conclusion, the numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.« less
A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ku, S., E-mail: sku@pppl.gov; Hager, R.; Chang, C.S.
In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles providemore » scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.« less
Probabilistic Design of a Wind Tunnel Model to Match the Response of a Full-Scale Aircraft
NASA Technical Reports Server (NTRS)
Mason, Brian H.; Stroud, W. Jefferson; Krishnamurthy, T.; Spain, Charles V.; Naser, Ahmad S.
2005-01-01
approach is presented for carrying out the reliability-based design of a plate-like wing that is part of a wind tunnel model. The goal is to design the wind tunnel model to match the stiffness characteristics of the wing box of a flight vehicle while satisfying strength-based risk/reliability requirements that prevents damage to the wind tunnel model and fixtures. The flight vehicle is a modified F/A-18 aircraft. The design problem is solved using reliability-based optimization techniques. The objective function to be minimized is the difference between the displacements of the wind tunnel model and the corresponding displacements of the flight vehicle. The design variables control the thickness distribution of the wind tunnel model. Displacements of the wind tunnel model change with the thickness distribution, while displacements of the flight vehicle are a set of fixed data. The only constraint imposed is that the probability of failure is less than a specified value. Failure is assumed to occur if the stress caused by aerodynamic pressure loading is greater than the specified strength allowable. Two uncertain quantities are considered: the allowable stress and the thickness distribution of the wind tunnel model. Reliability is calculated using Monte Carlo simulation with response surfaces that provide approximate values of stresses. The response surface equations are, in turn, computed from finite element analyses of the wind tunnel model at specified design points. Because the response surface approximations were fit over a small region centered about the current design, the response surfaces were refit periodically as the design variables changed. Coarse-grained parallelism was used to simultaneously perform multiple finite element analyses. Studies carried out in this paper demonstrate that this scheme of using moving response surfaces and coarse-grained computational parallelism reduce the execution time of the Monte Carlo simulation enough to make the design problem tractable. The results of the reliability-based designs performed in this paper show that large decreases in the probability of stress-based failure can be realized with only small sacrifices in the ability of the wind tunnel model to represent the displacements of the full-scale vehicle.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nole, Michael; Daigle, Hugh; Cook, Ann E.
The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1 to 20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two- dimensional and basin-scalemore » three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. As a result, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial.« less
Nole, Michael; Daigle, Hugh; Cook, Ann E.; ...
2017-02-01
The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1 to 20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two- dimensional and basin-scalemore » three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. As a result, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial.« less
Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi
2015-09-07
Photosystem II (PS II) is a protein complex which evolves oxygen and drives charge separation for photosynthesis employing electron and excitation-energy transfer processes over a wide timescale range from picoseconds to milliseconds. While the fluorescence emitted by the antenna pigments of this complex is known as an important indicator of the activity of photosynthesis, its interpretation was difficult because of the complexity of PS II. In this study, an extensive kinetic model which describes the complex and multi-timescale characteristics of PS II is analyzed through the use of the hierarchical coarse-graining method proposed in the authors׳ earlier work. In this coarse-grained analysis, the reaction center (RC) is described by two states, open and closed RCs, both of which consist of oxidized and neutral special pairs being in quasi-equilibrium states. Besides, the PS II model at millisecond scale with three-state RC, which was studied previously, could be derived by suitably adjusting the kinetic parameters of electron transfer between tyrosine and RC. Our novel coarse-grained model of PS II can appropriately explain the light-intensity dependent change of the characteristic patterns of fluorescence induction kinetics from O-J-I-P, which shows two inflection points, J and I, between initial point O and peak point P, to O-J-D-I-P, which shows a dip D between J and I inflection points. Copyright © 2015 Elsevier Ltd. All rights reserved.
Vangaveti, S; Travesset, A
2014-12-28
We present here a method to separate the Stern and diffuse layer in general systems into two regions that can be analyzed separately. The Stern layer can be described in terms of Bjerrum pairing and the diffuse layer in terms of Poisson-Boltzmann theory (monovalent) or strong coupling theory plus a slowly decaying tail (divalent). We consider three anionic phospholipids: phosphatidyl serine, phosphatidic acid, and phosphatidylinositol(4,5)bisphosphate (PIP2), which we describe within a minimal coarse-grained model as a function of ionic concentration. The case of mixed lipid systems is also considered, which shows a high level of binding cooperativity as a function of PIP2 localization. Implications for existing experimental systems of lipid heterogeneities are also discussed.
Coarse-Grained MD Simulations and Protein-Protein Interactions: The Cohesin-Dockerin System.
Hall, Benjamin A; Sansom, Mark S P
2009-09-08
Coarse-grained molecular dynamics (CG-MD) may be applied as part of a multiscale modeling approach to protein-protein interactions. The cohesin-dockerin interaction provides a valuable test system for evaluation of the use of CG-MD, as structural (X-ray) data indicate a dual binding mode for the cohesin-dockerin pair. CG-MD simulations (of 5 μs duration) of the association of cohesin and dockerin identify two distinct binding modes, which resemble those observed in X-ray structures. For each binding mode, ca. 80% of interfacial residues are predicted correctly. Furthermore, each of the binding modes identified by CG-MD is conformationally stable when converted to an atomistic model and used as the basis of a conventional atomistic MD simulation of duration 20 ns.
NASA Astrophysics Data System (ADS)
Vangaveti, S.; Travesset, A.
2014-12-01
We present here a method to separate the Stern and diffuse layer in general systems into two regions that can be analyzed separately. The Stern layer can be described in terms of Bjerrum pairing and the diffuse layer in terms of Poisson-Boltzmann theory (monovalent) or strong coupling theory plus a slowly decaying tail (divalent). We consider three anionic phospholipids: phosphatidyl serine, phosphatidic acid, and phosphatidylinositol(4,5)bisphosphate (PIP2), which we describe within a minimal coarse-grained model as a function of ionic concentration. The case of mixed lipid systems is also considered, which shows a high level of binding cooperativity as a function of PIP2 localization. Implications for existing experimental systems of lipid heterogeneities are also discussed.
Programmable energy landscapes for kinetic control of DNA strand displacement.
Machinek, Robert R F; Ouldridge, Thomas E; Haley, Natalie E C; Bath, Jonathan; Turberfield, Andrew J
2014-11-10
DNA is used to construct synthetic systems that sense, actuate, move and compute. The operation of many dynamic DNA devices depends on toehold-mediated strand displacement, by which one DNA strand displaces another from a duplex. Kinetic control of strand displacement is particularly important in autonomous molecular machinery and molecular computation, in which non-equilibrium systems are controlled through rates of competing processes. Here, we introduce a new method based on the creation of mismatched base pairs as kinetic barriers to strand displacement. Reaction rate constants can be tuned across three orders of magnitude by altering the position of such a defect without significantly changing the stabilities of reactants or products. By modelling reaction free-energy landscapes, we explore the mechanistic basis of this control mechanism. We also demonstrate that oxDNA, a coarse-grained model of DNA, is capable of accurately predicting and explaining the impact of mismatches on displacement kinetics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deichmann, Gregor; Marcon, Valentina; Vegt, Nico F. A. van der, E-mail: vandervegt@csi.tu-darmstadt.de
Molecular simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodynamic properties can be quite accurately represented while the prediction of dynamic properties remains difficult, especially for multi-component systems. In this work, we use constraint molecular dynamics simulations for calculating dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived frommore » fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These molecular liquids are simulated with atomistic molecular dynamics, coarse-grained molecular dynamics, and DPD. We find that the CRW-DPD models reproduce the liquid structure and diffusive dynamics of the liquid systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads containing five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale separation can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics.« less
Performance Characteristics of the Multi-Zone NAS Parallel Benchmarks
NASA Technical Reports Server (NTRS)
Jin, Haoqiang; VanderWijngaart, Rob F.
2003-01-01
We describe a new suite of computational benchmarks that models applications featuring multiple levels of parallelism. Such parallelism is often available in realistic flow computations on systems of grids, but had not previously been captured in bench-marks. The new suite, named NPB Multi-Zone, is extended from the NAS Parallel Benchmarks suite, and involves solving the application benchmarks LU, BT and SP on collections of loosely coupled discretization meshes. The solutions on the meshes are updated independently, but after each time step they exchange boundary value information. This strategy provides relatively easily exploitable coarse-grain parallelism between meshes. Three reference implementations are available: one serial, one hybrid using the Message Passing Interface (MPI) and OpenMP, and another hybrid using a shared memory multi-level programming model (SMP+OpenMP). We examine the effectiveness of hybrid parallelization paradigms in these implementations on three different parallel computers. We also use an empirical formula to investigate the performance characteristics of the multi-zone benchmarks.
2017-08-10
simulation models the conformational plasticity along the helix-forming reaction coordinate was limited by free - energy barriers. By comparison the coarse...revealed. The latter becomes evident in comparing the energy Z-score landscapes , where CHARMM22 simulation shows a manifold of shuttling...solvent simulations of calculating the charging free energy of protein conformations.33 Deviation to the protocol by modification of Born radii
Hennes, M; Schuler, V; Weng, X; Buchwald, J; Demaille, D; Zheng, Y; Vidal, F
2018-04-26
We employ kinetic Monte-Carlo simulations to study the growth process of metal-oxide nanocomposites obtained via sequential pulsed laser deposition. Using Ni-SrTiO3 (Ni-STO) as a model system, we reduce the complexity of the computational problem by choosing a coarse-grained approach mapping Sr, Ti and O atoms onto a single effective STO pseudo-atom species. With this ansatz, we scrutinize the kinetics of the sequential synthesis process, governed by alternating deposition and relaxation steps, and analyze the self-organization propensity of Ni atoms into straight vertically aligned nanowires embedded in the surrounding STO matrix. We finally compare the predictions of our binary toy model with experiments and demonstrate that our computational approach captures fundamental aspects of self-assembled nanowire synthesis. Despite its simplicity, our modeling strategy successfully describes the impact of relevant parameters like the concentration or laser frequency on the final nanoarchitecture of metal-oxide thin films grown via pulsed laser deposition.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Asgharzadeh, H.; Kim, H.S.; Simchi, A., E-mail: simchi@sharif.edu
2013-01-15
An ultrafine-grained Al6063/Al{sub 2}O{sub 3} (0.8 vol.%, 25 nm) nanocomposite was prepared via powder metallurgy route through reactive mechanical alloying and hot powder extrusion. Scanning electron microcopy, transmission electron microscopy, and back scattered electron diffraction analysis showed that the grain structure of the nanocomposite is trimodal and composed of nano-size grains (< 0.1 {mu}m), ultrafine grains (0.1-1 {mu}m), and micron-size grains (> 1 {mu}m) with random orientations. Evaluation of the mechanical properties of the nanocomposite based on the strengthening-mechanism models revealed that the yield strength of the ultrafine-grained nanocomposite is mainly controlled by the high-angle grain boundaries rather than nanometricmore » alumina particles. Hot deformation behavior of the material at different temperatures and strain rates was studied by compression test and compared to coarse-grained Al6063 alloy. The activation energy of the hot deformation process for the nanocomposite was determined to be 291 kJ mol{sup -1}, which is about 64% higher than that of the coarse-grained alloy. Detailed microstructural analysis revealed that dynamic recrystallization is responsible for the observed deformation softening in the ultrafine-grained nanocomposite. - Highlights: Black-Right-Pointing-Pointer The strengthening mechanisms of Al6063/Al{sub 2}O{sub 3} nanocomposite were evaluated. Black-Right-Pointing-Pointer Hot deformation behavior of the nanocomposite was studied. Black-Right-Pointing-Pointer The hot deformation activation energy was determined using consecutive models. Black-Right-Pointing-Pointer The restoration mechanisms and microstructural changes are presented.« less
NASA Astrophysics Data System (ADS)
Salvalaglio, Marco; Backofen, Rainer; Elder, K. R.; Voigt, Axel
2018-05-01
We address a three-dimensional, coarse-grained description of dislocation networks at grain boundaries between rotated crystals. The so-called amplitude expansion of the phase-field crystal model is exploited with the aid of finite element method calculations. This approach allows for the description of microscopic features, such as dislocations, while simultaneously being able to describe length scales that are orders of magnitude larger than the lattice spacing. Moreover, it allows for the direct description of extended defects by means of a scalar order parameter. The versatility of this framework is shown by considering both fcc and bcc lattice symmetries and different rotation axes. First, the specific case of planar, twist grain boundaries is illustrated. The details of the method are reported and the consistency of the results with literature is discussed. Then, the dislocation networks forming at the interface between a spherical, rotated crystal embedded in an unrotated crystalline structure, are shown. Although explicitly accounting for dislocations which lead to an anisotropic shrinkage of the rotated grain, the extension of the spherical grain boundary is found to decrease linearly over time in agreement with the classical theory of grain growth and recent atomistic investigations. It is shown that the results obtained for a system with bcc symmetry agree very well with existing results, validating the methodology. Furthermore, fully original results are shown for fcc lattice symmetry, revealing the generality of the reported observations.
The Prediction of Microstructure Evolution of 6005A Aluminum Alloy in a P-ECAP Extrusion Study
NASA Astrophysics Data System (ADS)
Lei, Shi; Jiu-Ba, Wen; Chang, Ren
2018-05-01
Finite element modeling (FEM) was applied for predicting the recrystallized structure in extruded 6005 aluminum alloy, and simulated results were experimentally validated. First, microstructure evolution of 6005 aluminum alloy during deformation was studied by means of isothermal compression test, where the processing parameters were chosen to reproduce the typical industrial conditions. Second, microstructure evolution was analyzed, and the obtained information was used to fit a dynamic recrystallization model implementing inside the DEFORM-3D FEM code environment. FEM of deformation of 6005 aluminum has been established and validated by microstructure comparison. Finally, the obtained dynamic recrystallization model was applied to tube extrusion by using a portholes-equal channel angular pressing die. The finite element analysis results showed that coarse DRX grains occur in the extruded tube at higher temperature and in the extruded tube at the faster speed of the stem. The test results showed material from the front end of the extruded tube has coarse grains (60 μm) and other extruded tube has finer grains (20 μm).
The Prediction of Microstructure Evolution of 6005A Aluminum Alloy in a P-ECAP Extrusion Study
NASA Astrophysics Data System (ADS)
Lei, Shi; Jiu-Ba, Wen; Chang, Ren
2018-04-01
Finite element modeling (FEM) was applied for predicting the recrystallized structure in extruded 6005 aluminum alloy, and simulated results were experimentally validated. First, microstructure evolution of 6005 aluminum alloy during deformation was studied by means of isothermal compression test, where the processing parameters were chosen to reproduce the typical industrial conditions. Second, microstructure evolution was analyzed, and the obtained information was used to fit a dynamic recrystallization model implementing inside the DEFORM-3D FEM code environment. FEM of deformation of 6005 aluminum has been established and validated by microstructure comparison. Finally, the obtained dynamic recrystallization model was applied to tube extrusion by using a portholes-equal channel angular pressing die. The finite element analysis results showed that coarse DRX grains occur in the extruded tube at higher temperature and in the extruded tube at the faster speed of the stem. The test results showed material from the front end of the extruded tube has coarse grains (60 μm) and other extruded tube has finer grains (20 μm).
Database Dictionary for Ethiopian National Ground-Water Database (ENGDA) Data Fields
2007-01-01
Coarse Sand Fine Sand Fine-Grained Sandstone Fractured Igneous and Metamorphic Rock Gravel Karst Limestone, Dolomite Medium Sand Medium-Grained...Coarse Sand; Fine Sand; Fine-Grained Sandstone; Fractured Igneous and Metamorphic Rock; Gravel; Karst Limestone/ Dolomite ; Medium Sand; Medium...aquifer lithology (rock type; Babcock and other, 2004). - 20 - Data Type: List, 1-character code C Consolidated porous sedimentary I Fractured
Truini, Margot; Beard, L. Sue; Kennedy, Jeffrey; Anning, Dave W.
2013-01-01
We have investigated the hydrogeology of the Hualapai Valley, Detrital Valley, and Sacramento Valley basins of Mohave County in northwestern Arizona to develop a better understanding of groundwater storage within the basin fill aquifers. In our investigation we used geologic maps, well-log data, and geophysical surveys to delineate the sedimentary textures and lithology of the basin fill. We used gravity data to construct a basin geometry model that defines smaller subbasins within the larger basins, and airborne transient-electromagnetic modeled results along with well-log lithology data to infer the subsurface distribution of basin fill within the subbasins. Hydrogeologic units (HGUs) are delineated within the subbasins on the basis of the inferred lithology of saturated basin fill. We used the extent and size of HGUs to estimate groundwater storage to depths of 400 meters (m) below land surface (bls). The basin geometry model for the Hualapai Valley basin consists of three subbasins: the Kingman, Hualapai, and southern Gregg subbasins. In the Kingman subbasin, which is estimated to be 1,200 m deep, saturated basin fill consists of a mixture of fine- to coarse-grained sedimentary deposits. The Hualapai subbasin, which is the largest of the subbasins, contains a thick halite body from about 400 m to about 4,300 m bls. Saturated basin fill overlying the salt body consists predominately of fine-grained older playa deposits. In the southern Gregg subbasin, which is estimated to be 1,400 m deep, saturated basin fill is interpreted to consist primarily of fine- to coarse-grained sedimentary deposits. Groundwater storage to 400 m bls in the Hualapai Valley basin is estimated to be 14.1 cubic kilometers (km3). The basin geometry model for the Detrital Valley basin consists of three subbasins: northern Detrital, central Detrital, and southern Detrital subbasins. The northern and central Detrital subbasins are characterized by a predominance of playa evaporite and fine-grained clastic deposits; evaporite deposits in the northern Detrital subbasin include halite. The northern Detrital subbasin is estimated to be 600 m deep and the middle Detrital subbasin is estimated to be 700 m deep. The southern Detrital subbasin, which is estimated to be 1,500 m deep, is characterized by a mixture of fine- to coarse-grained basin fill deposits. Groundwater storage to 400 m bls in the Detrital Valley basin is estimated to be 9.8 km3. The basin geometry model for the Sacramento Valley basin consists of three subbasins: the Chloride, Golden Valley, and Dutch Flat subbasins. The Chloride subbasin, which is estimated to be 900 m deep, is characterized by fine- to coarse-grained basin fill deposits. In the Golden Valley subbasin, which is elongated north-south, and is estimated to be 1,300 m deep, basin fill includes fine-grained sedimentary deposits overlain by coarse-grained sedimentary deposits in much of the subbasin. The Dutch Flat subbasin is estimated to be 2,600 m deep, and well-log lithologic data suggest that the basin fill consists of interlayers of gravel, sand, and clay. Groundwater storage to 400 m bls in the Sacramento Valley basin is estimated to be 35.1 km3.
2012-03-19
A, Black ME, Baker D, Stoddard BL (2005) Computational thermostabilization of an enzyme . Science 308: 857. 7. Liang HK, Huang CM, Ko MT, Hwang JK...2005) Amino acid coupling patterns in thermophilic proteins. Proteins 59: 58. 8. Das R, Gerstein M (2000) The stability of thermophilic proteins: a study
Geerts, Hugo; Hofmann-Apitius, Martin; Anastasio, Thomas J
2017-11-01
Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to be required for further progress in understanding and treating AD. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
Variational calculation of macrostate transition rates
NASA Astrophysics Data System (ADS)
Ulitsky, Alex; Shalloway, David
1998-08-01
We develop the macrostate variational method (MVM) for computing reaction rates of diffusive conformational transitions in multidimensional systems by a variational coarse-grained "macrostate" decomposition of the Smoluchowski equation. MVM uses multidimensional Gaussian packets to identify and focus computational effort on the "transition region," a localized, self-consistently determined region in conformational space positioned roughly between the macrostates. It also determines the "transition direction" which optimally specifies the projected potential of mean force for mean first-passage time calculations. MVM is complementary to variational transition state theory in that it can efficiently solve multidimensional problems but does not accommodate memory-friction effects. It has been tested on model 1- and 2-dimensional potentials and on the 12-dimensional conformational transition between the isoforms of a microcluster of six-atoms having only van der Waals interactions. Comparison with Brownian dynamics calculations shows that MVM obtains equivalent results at a fraction of the computational cost.
NASA Astrophysics Data System (ADS)
Maio, C. V.; Donnelly, J. P.; Sullivan, R.; Weidman, C. R.; Sheremet, V.
2014-12-01
The brevity of the instrumental record and lack of detailed historical accounts is a limiting factor in our understanding of the relationship between climate change and the frequency and intensity of extreme storm events. This study applied paleotempestologic and hydrographic methods to identify the mechanisms of storm-induced coarse grain deposition and reconstruct a late Holocene storm record within Waquoit Bay, Massachusetts. Three sediment cores (6.0 m, 8.4 m, and 8.2 m) were collected in 3 m of water using a vibracore system. Grain sizes were measured along core to identify coarse grain anomalies that serve as a proxy for past storm events. An historical age model (1620-2011 AD) was developed based on Pb pollution chronomarkers derived from X-Ray Florescence bulk Pb data, equating to a sedimentation rate of 8-8.3 mm/yr (R2 = 0.99). A long-term (4000 to 275 years before present) sedimentation rate of 1.1-1.4 mm/yr (R2 = 0.89) was calculated based on twenty-four continuous flow atomic mass spectrometry 14C ages of marine bivalves. To determine hydrographic conditions within the embayment during storm events current meters and tide gauges were deployed during Hurricane Irene (2011) which measured a storm surge of 88 cm above mean sea level. The buildup of storm water against the landward shoreline resulted in a measured 10 cm/s seaward moving bottom current capable of transporting coarse sand eroded from the adjacent shoreface into the coring site. Modeled surges for eleven modern and historic storm events ranged in height from 0.37 m (2011) to 3.72 m (1635) above mean high water. The WAQ1, WAQ2, and WAQ3 cores recorded a total of 89, 139, and 137 positive anomalies that exceeded the lower threshold and 15, 34, and 12 that exceeded the upper threshold respectively. Events recorded during the historic period coincide with documented storm events. The mean frequency within the three cores applying the lower threshold was 2.6 events per century, while applying the upper threshold was 0.44 events per century. The study has identified a previously understudied transport mechanism for the formation of storm-induced coarse grain horizons and highlighted some of the challenges to utilizing shallow water embayments as sites for storm reconstructions.
Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.
Inoue, Yasuhiro; Adachi, Taiji
2011-07-01
Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cipcigan, Flaviu S., E-mail: flaviu.cipcigan@ed.ac.uk; National Physical Laboratory, Hampton Road, Teddington, Middlesex TW11 0LW; Sokhan, Vlad P.
One key factor that limits the predictive power of molecular dynamics simulations is the accuracy and transferability of the input force field. Force fields are challenged by heterogeneous environments, where electronic responses give rise to biologically important forces such as many-body polarisation and dispersion. The importance of polarisation in the condensed phase was recognised early on, as described by Cochran in 1959 [Philosophical Magazine 4 (1959) 1082–1086] [32]. Currently in molecular simulation, dispersion forces are treated at the two-body level and in the dipole limit, although the importance of three-body terms in the condensed phase was demonstrated by Barker inmore » the 1980s [Phys. Rev. Lett. 57 (1986) 230–233] [72]. One approach for treating both polarisation and dispersion on an equal basis is to coarse grain the electrons surrounding a molecular moiety to a single quantum harmonic oscillator (cf. Hirschfelder, Curtiss and Bird 1954 [The Molecular Theory of Gases and Liquids (1954)] [37]). The approach, when solved in strong coupling beyond the dipole limit, gives a description of long-range forces that includes two- and many-body terms to all orders. In the last decade, the tools necessary to implement the strong coupling limit have been developed, culminating in a transferable model of water with excellent predictive power across the phase diagram. Transferability arises since the environment automatically identifies the important long range interactions, rather than the modeler through a limited set of expressions. Here, we discuss the role of electronic coarse-graining in predictive multiscale materials modelling and describe the first implementation of the method in a general purpose molecular dynamics software: QDO-MD. - Highlights: • Electronic coarse graining unites many-body dispersion and polarisation beyond the dipole limit. • It consists of replacing the electrons of a molecule using a quantum harmonic oscillator, called a Quantum Drude Oscillator. • We present the first general implementation of Quantum Drude Oscillators in the molecular dynamics package QDO-MD. • We highlight the successful construction of a new, transferable molecular model of water: QDO-water. - Graphical abstract:.« less
Karczyńska, Agnieszka S; Czaplewski, Cezary; Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Liwo, Adam
2017-12-05
Molecular simulations restrained to single or multiple templates are commonly used in protein-structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template-restrained canonical molecular dynamics (MD), multiplexed replica-exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse-grained UNRES force field on nine selected proteins, with pseudo-harmonic log-Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non-ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor-quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
A coarse-grained model for DNA origami.
Reshetnikov, Roman V; Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D
2018-02-16
Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version.
A coarse-grained model for DNA origami
Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D
2018-01-01
Abstract Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version. PMID:29267876
Mechanical Properties of a Superalloy Disk with a Dual Grain Structure
NASA Technical Reports Server (NTRS)
Gayda, John; Gabb, Timothy; Kantzos, Peter
2003-01-01
Mechanical properties from an advanced, nickel-base superalloy disk, with a dual grain structure consisting of a fine grain bore and coarse grain rim, were evaluated. The dual grain structure was produced using NASA's low cost Dual Microstructure Heat Treatment (DMHT) process. The results showed the DMHT disk to have a high strength, fatigue resistant bore comparable to a subsolvus (fine grain) heat treated disk, and a creep resistant rim comparable to a supersolvus (coarse grain) heat treated disk. Additional work on subsolvus solutioning before or after the DMHT conversion appears to be a viable avenue for further improvement in disk properties.
Monotonic entropy growth for a nonlinear model of random exchanges.
Apenko, S M
2013-02-01
We present a proof of the monotonic entropy growth for a nonlinear discrete-time model of a random market. This model, based on binary collisions, also may be viewed as a particular case of Ulam's redistribution of energy problem. We represent each step of this dynamics as a combination of two processes. The first one is a linear energy-conserving evolution of the two-particle distribution, for which the entropy growth can be easily verified. The original nonlinear process is actually a result of a specific "coarse graining" of this linear evolution, when after the collision one variable is integrated away. This coarse graining is of the same type as the real space renormalization group transformation and leads to an additional entropy growth. The combination of these two factors produces the required result which is obtained only by means of information theory inequalities.
Isotropic stochastic rotation dynamics
NASA Astrophysics Data System (ADS)
Mühlbauer, Sebastian; Strobl, Severin; Pöschel, Thorsten
2017-12-01
Stochastic rotation dynamics (SRD) is a widely used method for the mesoscopic modeling of complex fluids, such as colloidal suspensions or multiphase flows. In this method, however, the underlying Cartesian grid defining the coarse-grained interaction volumes induces anisotropy. We propose an isotropic, lattice-free variant of stochastic rotation dynamics, termed iSRD. Instead of Cartesian grid cells, we employ randomly distributed spherical interaction volumes. This eliminates the requirement of a grid shift, which is essential in standard SRD to maintain Galilean invariance. We derive analytical expressions for the viscosity and the diffusion coefficient in relation to the model parameters, which show excellent agreement with the results obtained in iSRD simulations. The proposed algorithm is particularly suitable to model systems bound by walls of complex shape, where the domain cannot be meshed uniformly. The presented approach is not limited to SRD but is applicable to any other mesoscopic method, where particles interact within certain coarse-grained volumes.
NASA Astrophysics Data System (ADS)
Orlandi, Javier G.; Casademunt, Jaume
2017-05-01
We introduce a coarse-grained stochastic model for the spontaneous activity of neuronal cultures to explain the phenomenon of noise focusing, which entails localization of the noise activity in excitable networks with metric correlations. The system is modeled as a continuum excitable medium with a state-dependent spatial coupling that accounts for the dynamics of synaptic connections. The most salient feature is the emergence at the mesoscale of a vector field V (r ) , which acts as an advective carrier of the noise. This entails an explicit symmetry breaking of isotropy and homogeneity that stems from the amplification of the quenched fluctuations of the network by the activity avalanches, concomitant with the excitable dynamics. We discuss the microscopic interpretation of V (r ) and propose an explicit construction of it. The coarse-grained model shows excellent agreement with simulations at the network level. The generic nature of the observed phenomena is discussed.
Combining Coarse-Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics
Wabik, Jacek; Kmiecik, Sebastian; Gront, Dominik; Kouza, Maksim; Koliński, Andrzej
2013-01-01
We describe a combination of all-atom simulations with CABS, a well-established coarse-grained protein modeling tool, into a single multiscale protocol. The simulation method has been tested on the C-terminal beta hairpin of protein G, a model system of protein folding. After reconstructing atomistic details, conformations derived from the CABS simulation were subjected to replica-exchange molecular dynamics simulations with OPLS-AA and AMBER99sb force fields in explicit solvent. Such a combination accelerates system convergence several times in comparison with all-atom simulations starting from the extended chain conformation, demonstrated by the analysis of melting curves, the number of native-like conformations as a function of time and secondary structure propagation. The results strongly suggest that the proposed multiscale method could be an efficient and accurate tool for high-resolution studies of protein folding dynamics in larger systems. PMID:23665897
GARN: Sampling RNA 3D Structure Space with Game Theory and Knowledge-Based Scoring Strategies.
Boudard, Mélanie; Bernauer, Julie; Barth, Dominique; Cohen, Johanne; Denise, Alain
2015-01-01
Cellular processes involve large numbers of RNA molecules. The functions of these RNA molecules and their binding to molecular machines are highly dependent on their 3D structures. One of the key challenges in RNA structure prediction and modeling is predicting the spatial arrangement of the various structural elements of RNA. As RNA folding is generally hierarchical, methods involving coarse-grained models hold great promise for this purpose. We present here a novel coarse-grained method for sampling, based on game theory and knowledge-based potentials. This strategy, GARN (Game Algorithm for RNa sampling), is often much faster than previously described techniques and generates large sets of solutions closely resembling the native structure. GARN is thus a suitable starting point for the molecular modeling of large RNAs, particularly those with experimental constraints. GARN is available from: http://garn.lri.fr/.
NASA Astrophysics Data System (ADS)
Hsu, David D.
Due to high nanointerfacial area to volume ratio, the properties of "nanoconfined" polymer thin films, blends, and composites become highly altered compared to their bulk homopolymer analogues. Understanding the structure-property mechanisms underlying this effect is an active area of research. However, despite extensive work, a fundamental framework for predicting the local and system-averaged thermomechanical properties as a function of configuration and polymer species has yet to be established. Towards bridging this gap, here, we present a novel, systematic coarse-graining (CG) method which is able to capture quantitatively, the thermomechanical properties of real polymer systems in bulk and in nanoconfined geometries. This method, which we call thermomechanically consistent coarse-graining (TCCG), is a two-bead-per-monomer CG hybrid approach through which bonded interactions are optimized to match the atomistic structure via the Iterative Boltzmann Inversion method (IBI), and nonbonded interactions are tuned to macroscopic targets through parametric studies. We validate the TCCG method by systematically developing coarse-grain models for a group of five specialized methacrylate-based polymers including poly(methyl methacrylate) (PMMA). Good correlation with bulk all-atom (AA) simulations and experiments is found for the temperature-dependent glass transition temperature (Tg) Flory-Fox scaling relationships, self-diffusion coefficients of liquid monomers, and modulus of elasticity. We apply this TCCG method also to bulk polystyrene (PS) using a comparable coarse-grain CG bead mapping strategy. The model demonstrates chain stiffness commensurate with experiments, and we utilize a density-correction term to improve the transferability of the elastic modulus over a 500 K range. Additionally, PS and PMMA models capture the unexplained, characteristically dissimilar scaling of Tg with the thickness of free-standing films as seen in experiments. Using vibrational density of states (VDOS) analysis, we discover that increasing backbone to sidechain mass ratio in CG models increases the amplitude of sidechain fluctuations associated with flexibility, and suppresses the free-surface Tg-nanoconfinement effect. This uncovers that intrinsic mass distribution and sidechain flexibility differences in the PS and PMMA chemical structure are central to explaining the dissimilarities in their free surface response. PS and PMMA models are subsequently combined in the supported bilayer film configuration to explore the local Tg-nanoconfinement effect associated with different interface types at nanometer resolution. We find that Tg gradients in the interphase regions where chain mobility deviates from the bulk are independent of the film thickness above a critical thickness and add by the principle of superposition below the critical thickness to good approximation. The analytical expressions describing the interphase regions and their interactions demonstrate geometric universality and can be used to derive accurate local and global Tg estimations for complex nanophase blends and nanocomposite configurations. Our studies ascertain the significance of molecular characteristics on nanoconfinement, and highlight the ability for chemistry-specific CG models to explore and predict thermomechanical property modification accompanying interfacial nanoconfinement.
In silico modelling of drug–polymer interactions for pharmaceutical formulations
Ahmad, Samina; Johnston, Blair F.; Mackay, Simon P.; Schatzlein, Andreas G.; Gellert, Paul; Sengupta, Durba; Uchegbu, Ijeoma F.
2010-01-01
Selecting polymers for drug encapsulation in pharmaceutical formulations is usually made after extensive trial and error experiments. To speed up excipient choice procedures, we have explored coarse-grained computer simulations (dissipative particle dynamics (DPD) and coarse-grained molecular dynamics using the MARTINI force field) of polymer–drug interactions to study the encapsulation of prednisolone (log p = 1.6), paracetamol (log p = 0.3) and isoniazid (log p = −1.1) in poly(l-lactic acid) (PLA) controlled release microspheres, as well as the encapsulation of propofol (log p = 4.1) in bioavailability enhancing quaternary ammonium palmitoyl glycol chitosan (GCPQ) micelles. Simulations have been compared with experimental data. DPD simulations, in good correlation with experimental data, correctly revealed that hydrophobic drugs (prednisolone and paracetamol) could be encapsulated within PLA microspheres and predicted the experimentally observed paracetamol encapsulation levels (5–8% of the initial drug level) in 50 mg ml−1 PLA microspheres, but only when initial paracetamol levels exceeded 5 mg ml−1. However, the mesoscale technique was unable to model the hydrophilic drug (isoniazid) encapsulation (4–9% of the initial drug level) which was observed in experiments. Molecular dynamics simulations using the MARTINI force field indicated that the self-assembly of GCPQ is rapid, with propofol residing at the interface between micellar hydrophobic and hydrophilic groups, and that there is a heterogeneous distribution of propofol within the GCPQ micelle population. GCPQ–propofol experiments also revealed a population of relatively empty and drug-filled GCPQ particles. PMID:20519214
Petkevičiūtė, D; Pasi, M; Gonzalez, O; Maddocks, J H
2014-11-10
cgDNA is a package for the prediction of sequence-dependent configuration-space free energies for B-form DNA at the coarse-grain level of rigid bases. For a fragment of any given length and sequence, cgDNA calculates the configuration of the associated free energy minimizer, i.e. the relative positions and orientations of each base, along with a stiffness matrix, which together govern differences in free energies. The model predicts non-local (i.e. beyond base-pair step) sequence dependence of the free energy minimizer. Configurations can be input or output in either the Curves+ definition of the usual helical DNA structural variables, or as a PDB file of coordinates of base atoms. We illustrate the cgDNA package by comparing predictions of free energy minimizers from (a) the cgDNA model, (b) time-averaged atomistic molecular dynamics (or MD) simulations, and (c) NMR or X-ray experimental observation, for (i) the Dickerson-Drew dodecamer and (ii) three oligomers containing A-tracts. The cgDNA predictions are rather close to those of the MD simulations, but many orders of magnitude faster to compute. Both the cgDNA and MD predictions are in reasonable agreement with the available experimental data. Our conclusion is that cgDNA can serve as a highly efficient tool for studying structural variations in B-form DNA over a wide range of sequences. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Lee, Cheng-Kuang; Pao, Chun-Wei
2016-08-17
Solution-processed small-molecule organic solar cells are a promising renewable energy source because of their low production cost, mechanical flexibility, and light weight relative to their pure inorganic counterparts. In this work, we developed a coarse-grained (CG) Gay-Berne ellipsoid molecular simulation model based on atomistic trajectories from all-atom molecular dynamics simulations of smaller system sizes to systematically study the nanomorphology of the SMDPPEH/PCBM/solvent ternary blend during solution processing, including the blade-coating process by applying external shear to the solution. With the significantly reduced overall system degrees of freedom and computational acceleration from GPU, we were able to go well beyond the limitation of conventional all-atom molecular simulations with a system size on the order of hundreds of nanometers with mesoscale molecular detail. Our simulations indicate that, similar to polymer solar cells, the optimal blending ratio in small-molecule organic solar cells must provide the highest specific interfacial area for efficient exciton dissociation, while retaining balanced hole/electron transport pathway percolation. We also reveal that blade-coating processes have a significant impact on nanomorphology. For given donor/acceptor blending ratios, applying an external shear force can effectively promote donor/acceptor phase segregation and stacking in the SMDPPEH domains. The present study demonstrated the capability of an ellipsoid-based coarse-grained model for studying the nanomorphology evolution of small-molecule organic solar cells during solution processing/blade-coating and provided links between fabrication protocols and device nanomorphologies.
Shinoda, Wataru; DeVane, Russell; Klein, Michael L.
2010-01-01
A new coarse-grained (CG) intermolecular force field is presented for a series of zwitterionic lipids. The model is an extension of our previous work on nonionic surfactants and is designed to reproduce experimental surface/interfacial properties as well as distribution functions from all-atom molecular dynamics (MD) simulations. Using simple functional forms, the force field parameters are optimized for multiple lipid molecules, simultaneously. The resulting CG lipid bilayers have reasonable molecular areas, chain order parameters, and elastic properties. The computed surface pressure vs. area (π-A) curve for a DPPC monolayer demonstrates a significant improvement over the previous CG models. The DPPC monolayer has a longer persistence length than a PEG lipid monolayer, exhibiting a long-lived curved monolayer surface under negative tension. The bud ejected from an oversaturated DPPC monolayer has a large bicelle-like structure, which is different from the micellar bud formed from an oversaturated PEG lipid monolayer. We have successfully observed vesicle formation during CG-MD simulations, starting from an aggregate of DMPC molecules. Depending on the aggregate size, the lipid assembly spontaneously transforms into a closed vesicle or a bicelle. None of the various intermediate structures between these extremes seem to be stable. An attempt to observe fusion of two vesicles through the application of an external adhesion force was not successful. The present CG force field also supports stable multi-lamellar DMPC vesicles. PMID:20438090
Sedimentary differentiation of aeolian grains at the White Sands National Monument, New Mexico, USA
NASA Astrophysics Data System (ADS)
Fenton, Lori K.; Bishop, Janice L.; King, Sara; Lafuente, Barbara; Horgan, Briony; Bustos, David; Sarrazin, Philippe
2017-06-01
Gypsum (CaSO4·2H2O) has been identified as a major component of part of Olympia Undae in the northern polar region of Mars, along with the mafic minerals more typical of Martian dune fields. The source and age of the gypsum is disputed, with the proposed explanations having vastly different implications for Mars' geological history. Furthermore, the transport of low density gypsum grains relative to and concurrently with denser grains has yet to be investigated in an aeolian setting. To address this knowledge gap, we performed a field study at White Sands National Monument (WSNM) in New Mexico, USA. Although gypsum dominates the bulk of the dune field, a dolomite-rich [CaMg(CO3)2] transport pathway along the northern border of WSNM provides a suitable analog site to study the transport of gypsum grains relative to the somewhat harder and denser carbonate grains. We collected samples along the stoss slope of a dune and on two coarse-grained ripples at the upwind margin of the dune field where minerals other than gypsum were most common. For comparison, additional samples were taken along the stoss slope of a dune outside the dolomite transport pathway, in the center of the dune field. Visible and near-infrared (VNIR), X-ray powder diffraction (XRD), and Raman analyses of different sample size fractions reveal that dolomite is only prevalent in grains larger than ∼1 mm. Other minerals, most notably calcite, are also present in smaller quantities among the coarse grains. The abundance of these coarse grains, relative to gypsum grains of the same size, drops off sharply at the upwind margin of the dune field. In contrast, gypsum dominated the finer fraction (<∼1 mm) at all sample sites, displaying no spatial variation. Estimates of sediment fluxes indicate that, although mineralogical differentiation of wind-transported grains occurs gradually in creep, the process is much more rapid when winds are strong enough to saltate the ⩾1 mm grains. The observed grain segregation is consistent with the WSNM dune field formative friction velocity (0.39 m/s) proposed by Jerolmack et al. (2011): winds significantly weaker than this value would not lift the large grains into differentiation-inducing saltation, whereas the observed differentiated trend would be obliterated by significantly stronger winds. When applied to Olympia Undae, a similar sediment flux analysis suggests that the strongest winds modeled by the Mars Climate Database (MCD) are consistent with the observed concentration of gypsum at dune crests. Density-driven differentiation in transport should not influence sediment fluxes of finer grains (<1 mm) as strongly on Earth, suggesting that the high ratio of fine gypsum grains to other minerals at WSNM is caused by a relatively high production and/or abrasion rate of gypsum sand. The observed preferential transport of coarse-grained gypsum in the dune field conceals a broader range of coarse-grained minerals present on Alkali Flat, contributing to the problem that mineralogy determined through both remote sensing of dune fields and analysis of dune foresets does not fully represent that of the source regions. Unlike quartz, the concentration of gypsum in WSNM occurs not because it is more resistant to weathering and erosion than other minerals, but rather because it is more readily produced (in the case of finer grains) and transported (in the case of coarser grains) than other minerals present in the region.
Modeling disease transmission near eradication: An equation free approach
NASA Astrophysics Data System (ADS)
Williams, Matthew O.; Proctor, Joshua L.; Kutz, J. Nathan
2015-01-01
Although disease transmission in the near eradication regime is inherently stochastic, deterministic quantities such as the probability of eradication are of interest to policy makers and researchers. Rather than running large ensembles of discrete stochastic simulations over long intervals in time to compute these deterministic quantities, we create a data-driven and deterministic "coarse" model for them using the Equation Free (EF) framework. In lieu of deriving an explicit coarse model, the EF framework approximates any needed information, such as coarse time derivatives, by running short computational experiments. However, the choice of the coarse variables (i.e., the state of the coarse system) is critical if the resulting model is to be accurate. In this manuscript, we propose a set of coarse variables that result in an accurate model in the endemic and near eradication regimes, and demonstrate this on a compartmental model representing the spread of Poliomyelitis. When combined with adaptive time-stepping coarse projective integrators, this approach can yield over a factor of two speedup compared to direct simulation, and due to its lower dimensionality, could be beneficial when conducting systems level tasks such as designing eradication or monitoring campaigns.