Bulletin of the American Physical Society
APS March Meeting 2017
Volume 62, Number 4
Monday–Friday, March 13–17, 2017; New Orleans, Louisiana
Session F26: Advances in Molecular Dynamics Simulation: From Atomistic to Coarse Grained Models - IIIFocus
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Sponsoring Units: DCP Chair: Angel Garcia, Los Alamos National Laboratory Room: 289 |
Tuesday, March 14, 2017 11:15AM - 11:51AM |
F26.00001: Variationally optimal selection of slow coordinates and reaction coordinates in macromolecular systems Invited Speaker: Frank Noe To efficiently simulate and generate understanding from simulations of complex macromolecular systems, the concept of slow collective coordinates or reaction coordinates is of fundamental importance. Here we will introduce variational approaches to approximate the slow coordinates and the reaction coordinates between selected end-states given MD simulations of the macromolecular system and a (possibly large) basis set of candidate coordinates. We will then discuss how to select physically intuitive order paremeters that are good surrogates of this variationally optimal result. These result can be used in order to construct Markov state models or other models of the stationary and kinetics properties, in order to parametrize low-dimensional / coarse-grained model of the dynamics. [Preview Abstract] |
Tuesday, March 14, 2017 11:51AM - 12:03PM |
F26.00002: Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS Szu-Pei Fu, Yuan-Nan Young, Zhangli Peng, Hongyan Yuan 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 $4\sim6$ nm so that there is only one particle in the thickness direction. Yuan {\it 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. [Preview Abstract] |
Tuesday, March 14, 2017 12:03PM - 12:15PM |
F26.00003: Improving density functional tight binding predictions of free energy surfaces for peptide condensation reactions in solution Matthew Kroonblawd, Nir Goldman First principles molecular dynamics using highly accurate density functional theory (DFT) is a common tool for predicting chemistry, but the accessible time and space scales are often orders of magnitude beyond the resolution of experiments. Semi-empirical methods such as density functional tight binding (DFTB) offer up to a thousand-fold reduction in required CPU hours and can approach experimental scales. However, standard DFTB parameter sets lack good transferability and calibration for a particular system is usually necessary. Force matching the pairwise repulsive energy term in DFTB to short DFT trajectories can improve the former's accuracy for chemistry that is fast relative to DFT simulation times (\textless 10 ps), but the effects on slow chemistry and the free energy surface are not well-known. We present a force matching approach to increase the accuracy of DFTB predictions for free energy surfaces. Accelerated sampling techniques are combined with path collective variables to generate the reference DFT data set and validate fitted DFTB potentials without a priori knowledge of transition states. Accuracy of force-matched DFTB free energy surfaces is assessed for slow peptide-forming reactions by direct comparison to DFT results for particular paths. Extensions to model prebiotic chemistry under shock conditions are discussed. [Preview Abstract] |
Tuesday, March 14, 2017 12:15PM - 12:51PM |
F26.00004: Increasing the power of accelerated molecular dynamics methods and plans to exploit the coming exascale Invited Speaker: Arthur Voter Many important materials processes take place on time scales that far exceed the roughly one microsecond accessible to molecular dynamics simulation. Typically, this long-time evolution is characterized by a succession of thermally activated infrequent events involving defects in the material. In the accelerated molecular dynamics (AMD) methodology, known characteristics of infrequent-event systems are exploited to make reactive events take place more frequently, in a dynamically correct way. For certain processes, this approach has been remarkably successful, offering a view of complex dynamical evolution on time scales of microseconds, milliseconds, and sometimes beyond. We have recently made advances in all three of the basic AMD methods (hyperdynamics, parallel replica dynamics, and temperature accelerated dynamics (TAD)), exploiting both algorithmic advances and novel parallelization approaches. I will describe these advances, present some examples of our latest results, and discuss what should be possible when exascale computing arrives in roughly five years. [Preview Abstract] |
Tuesday, March 14, 2017 12:51PM - 1:03PM |
F26.00005: On the intrinsic flexibility of the opioid receptor through multiscale modeling approaches Daniel Vercauteren, Mathieu Fossépré, Laurence Leherte, Aatto Laaksonen 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 $\alpha $-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. [Preview Abstract] |
Tuesday, March 14, 2017 1:03PM - 1:15PM |
F26.00006: Scalable and fast concurrent multiscale molecular simulation with predictive parallelization scheme Horacio V. Guzman, Christoph Junghans, Karsten Kreis, Aoife Fogarty, Kurt Kremer, Torsten Stuehn Concurrent multiscale simulation enables the study of molecular systems with different resolutions in specific subdomains of a simulation box. Modeling soft-matter and biological systems in the context of multiscale simulations are challenging research avenues which drive the permanent development of new simulation methods and algorithms. In computational terms, those methods require parallelization schemes that make productive use of computational resources for each simulation and from its genesis. Here, we introduce the dual resolution domain decomposition algorithm that is a combination of a resolution sensitive spatial domain decomposition with an initial sliding subdomain-walls procedure. The algorithm modeling is presented for dual resolution systems in terms of scaling properties as a function of the size of the low-resolution region and the high to low resolutions ratio. The algorithm competences are validated within adaptive resolution simulations, by comparing its scalability and speedup to a spatial domain decomposition. Two representative adaptive resolution simulations have been employed in this work, namely, a biomolecule solvated in water and water in an ideal gas reservoir. [Preview Abstract] |
Tuesday, March 14, 2017 1:15PM - 1:27PM |
F26.00007: Chiral pathways in DNA dinucleotides using gradient optimized refinement along metastable borders Pablo Romano, Marina Guenza We present a study of DNA breathing fluctuations using Markov state models (MSM) with our novel refinement procedure. MSM have become a favored method of building kinetic models, however their accuracy has always depended on using a significant number of microstates, making the method costly. We present a method which optimizes macrostates by refining borders with respect to the gradient along the free energy surface. As the separation between macrostates contains highest discretization errors, this method corrects for any errors produced by limited microstate sampling. Using our refined MSM methods, we investigate DNA breathing fluctuations, thermally induced conformational changes in native B-form DNA. Running several microsecond MD simulations of DNA dinucleotides of varying sequences, to include sequence and polarity effects, we've analyzed using our refined MSM to investigate conformational pathways inherent in the unstacking of DNA bases. Our kinetic analysis has shown preferential chirality in unstacking pathways that may be critical in how proteins interact with single stranded regions of DNA. These breathing dynamics can help elucidate the connection between conformational changes and key mechanisms within protein-DNA recognition. [Preview Abstract] |
Tuesday, March 14, 2017 1:27PM - 1:39PM |
F26.00008: Normal mode analysis on the relaxation of an excited nitromethane molecule in argon bath Luis Rivera-Rivera, Albert Wagner In our previous work [J. Chem. Phys. 142, 014303 (2015)] classical molecular dynamics simulations followed in an Ar bath the relaxation of nitromethane (CH$_{\mathrm{3}}$NO$_{\mathrm{2}})$ instantaneously excited by statistically distributing 50 kcal/mol among all its internal degrees of freedom. The 300 K Ar bath was at pressures of 10 to 400 atm, a range spanning the breakdown of the isolated binary collision approximation. Both rotational and vibrational energies exhibit multi-exponential decay. This study explores mode-specific mechanisms at work in the decay process. With the separation of rotation and vibration developed by Rhee and Kim [J. Chem. Phys. 107, 1394 (1997)], one can show that the vibrational kinetic energy decomposes only into vibrational normal modes while the rotational and Coriolis energies decompose into both vibrational and rotational normal modes. Then the saved CH$_{\mathrm{3}}$NO$_{\mathrm{2\thinspace }}$positions and momenta can be converted into mode-specific energies whose decay over 1000 ps can be monitored. The results identify vibrational and rotational modes that promote/resist energy lost and drive multi-exponential behavior. Increasing pressure can be shown to increasingly interfere with post-collision IVR. [Preview Abstract] |
Tuesday, March 14, 2017 1:39PM - 1:51PM |
F26.00009: Coarse-Graining of Polymer Dynamics via Energy Renormalization Wenjie Xia, Jake Song, Frederick Phelan, Jack Douglas, Sinan Keten 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. [Preview Abstract] |
Tuesday, March 14, 2017 1:51PM - 2:03PM |
F26.00010: Exploring the Space of Coarse-Grained Models Thomas Foley, M. Scott Shell, William Noid Using the exactly renormalizable Gaussian network model, we extend upon a previous study which explored the impact of resolution upon information and entropy in coarse-grained models. In this work, we exploit an intuitive decomposition of the coarse-grained Potential of Mean Force (PMF) under a given mapping into entropic and energetic terms. Focusing on the entropic term as a measure of information loss, we explore the space of all mappings using Monte Carlo simulations in order to characterize the structure and features of this space. Applying a statistical mechanical analysis to this system yields valuable insight into the "mapping problem" of coarse-grained modeling. [Preview Abstract] |
Tuesday, March 14, 2017 2:03PM - 2:15PM |
F26.00011: Predicting Viscosity of Complex Lubricant Molecules with Ester Functional Groups using Nonequilibrium Molecular Dynamics Simulations. M A Sabuj, Neeraj Rai The knowledge of transport properties (viscosity and diffusion) are important for a number of wide range of industrial applications. Although molecular simulations have made tremendous progress in the last decade in predicting thermodynamic and transport properties based only on molecular structure, predicting viscosities with good accuracy has remained a significant challenge. Here, we use nonequilibrium molecular dynamics simulation (NEMD) to predict shear viscosity of four different but structurally similar pentaerythritol ester (PE) molecules at five different temperatures and five different pressures using the TraPPE-UA force field. Our calculations shows that TraPPE force field can predict shear viscosity values within 10 $\backslash ${\%} of experimental measurements. Furthermore, PE molecules absorb moistures from atmosphere; therefore, the change of viscosity was calculated in the presence of 5, 10 and 25 mole $\backslash ${\%} of water. Structural analysis was provided to get molecular insights and relative order of viscosity. The free volume concept can predict the pressure dependence of viscosity very well, a quantitative and rigorous analysis of the pressure dependence of viscosity was provided in terms of the free volume of the liquid. [Preview Abstract] |
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