Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations.

PubMed

Wu, Jingheng; Shen, Lin; Yang, Weitao

2017-10-28

Ab initio quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulation is a useful tool to calculate thermodynamic properties such as potential of mean force for chemical reactions but intensely time consuming. In this paper, we developed a new method using the internal force correction for low-level semiempirical QM/MM molecular dynamics samplings with a predefined reaction coordinate. As a correction term, the internal force was predicted with a machine learning scheme, which provides a sophisticated force field, and added to the atomic forces on the reaction coordinate related atoms at each integration step. We applied this method to two reactions in aqueous solution and reproduced potentials of mean force at the ab initio QM/MM level. The saving in computational cost is about 2 orders of magnitude. The present work reveals great potentials for machine learning in QM/MM simulations to study complex chemical processes.

Computer Simulations of Intrinsically Disordered Proteins

NASA Astrophysics Data System (ADS)

Chong, Song-Ho; Chatterjee, Prathit; Ham, Sihyun

2017-05-01

The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.

Three pillars for achieving quantum mechanical molecular dynamics simulations of huge systems: Divide-and-conquer, density-functional tight-binding, and massively parallel computation.

PubMed

Nishizawa, Hiroaki; Nishimura, Yoshifumi; Kobayashi, Masato; Irle, Stephan; Nakai, Hiromi

2016-08-05

The linear-scaling divide-and-conquer (DC) quantum chemical methodology is applied to the density-functional tight-binding (DFTB) theory to develop a massively parallel program that achieves on-the-fly molecular reaction dynamics simulations of huge systems from scratch. The functions to perform large scale geometry optimization and molecular dynamics with DC-DFTB potential energy surface are implemented to the program called DC-DFTB-K. A novel interpolation-based algorithm is developed for parallelizing the determination of the Fermi level in the DC method. The performance of the DC-DFTB-K program is assessed using a laboratory computer and the K computer. Numerical tests show the high efficiency of the DC-DFTB-K program, a single-point energy gradient calculation of a one-million-atom system is completed within 60 s using 7290 nodes of the K computer. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dielectric properties of organic solvents from non-polarizable molecular dynamics simulation with electronic continuum model and density functional theory.

PubMed

Lee, Sanghun; Park, Sung Soo

2011-11-03

Dielectric constants of electrolytic organic solvents are calculated employing nonpolarizable Molecular Dynamics simulation with Electronic Continuum (MDEC) model and Density Functional Theory. The molecular polarizabilities are obtained by the B3LYP/6-311++G(d,p) level of theory to estimate high-frequency refractive indices while the densities and dipole moment fluctuations are computed using nonpolarizable MD simulations. The dielectric constants reproduced from these procedures are evaluated to provide a reliable approach for estimating the experimental data. An additional feature, two representative solvents which have similar molecular weights but are different dielectric properties, i.e., ethyl methyl carbonate and propylene carbonate, are compared using MD simulations and the distinctly different dielectric behaviors are observed at short times as well as at long times.

Development of hardware accelerator for molecular dynamics simulations: a computation board that calculates nonbonded interactions in cooperation with fast multipole method.

PubMed

Amisaki, Takashi; Toyoda, Shinjiro; Miyagawa, Hiroh; Kitamura, Kunihiro

2003-04-15

Evaluation of long-range Coulombic interactions still represents a bottleneck in the molecular dynamics (MD) simulations of biological macromolecules. Despite the advent of sophisticated fast algorithms, such as the fast multipole method (FMM), accurate simulations still demand a great amount of computation time due to the accuracy/speed trade-off inherently involved in these algorithms. Unless higher order multipole expansions, which are extremely expensive to evaluate, are employed, a large amount of the execution time is still spent in directly calculating particle-particle interactions within the nearby region of each particle. To reduce this execution time for pair interactions, we developed a computation unit (board), called MD-Engine II, that calculates nonbonded pairwise interactions using a specially designed hardware. Four custom arithmetic-processors and a processor for memory manipulation ("particle processor") are mounted on the computation board. The arithmetic processors are responsible for calculation of the pair interactions. The particle processor plays a central role in realizing efficient cooperation with the FMM. The results of a series of 50-ps MD simulations of a protein-water system (50,764 atoms) indicated that a more stringent setting of accuracy in FMM computation, compared with those previously reported, was required for accurate simulations over long time periods. Such a level of accuracy was efficiently achieved using the cooperative calculations of the FMM and MD-Engine II. On an Alpha 21264 PC, the FMM computation at a moderate but tolerable level of accuracy was accelerated by a factor of 16.0 using three boards. At a high level of accuracy, the cooperative calculation achieved a 22.7-fold acceleration over the corresponding conventional FMM calculation. In the cooperative calculations of the FMM and MD-Engine II, it was possible to achieve more accurate computation at a comparable execution time by incorporating larger nearby regions. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 582-592, 2003

Computer simulation of surface and film processes

NASA Technical Reports Server (NTRS)

Tiller, W. A.; Halicioglu, M. T.

1984-01-01

All the investigations which were performed employed in one way or another a computer simulation technique based on atomistic level considerations. In general, three types of simulation methods were used for modeling systems with discrete particles that interact via well defined potential functions: molecular dynamics (a general method for solving the classical equations of motion of a model system); Monte Carlo (the use of Markov chain ensemble averaging technique to model equilibrium properties of a system); and molecular statics (provides properties of a system at T = 0 K). The effects of three-body forces on the vibrational frequencies of triatomic cluster were investigated. The multilayer relaxation phenomena for low index planes of an fcc crystal was analyzed also as a function of the three-body interactions. Various surface properties for Si and SiC system were calculated. Results obtained from static simulation calculations for slip formation were presented. The more elaborate molecular dynamics calculations on the propagation of cracks in two-dimensional systems were outlined.

Reproducing Quantum Probability Distributions at the Speed of Classical Dynamics: A New Approach for Developing Force-Field Functors.

PubMed

Sundar, Vikram; Gelbwaser-Klimovsky, David; Aspuru-Guzik, Alán

2018-04-05

Modeling nuclear quantum effects is required for accurate molecular dynamics (MD) simulations of molecules. The community has paid special attention to water and other biomolecules that show hydrogen bonding. Standard methods of modeling nuclear quantum effects like Ring Polymer Molecular Dynamics (RPMD) are computationally costlier than running classical trajectories. A force-field functor (FFF) is an alternative method that computes an effective force field that replicates quantum properties of the original force field. In this work, we propose an efficient method of computing FFF using the Wigner-Kirkwood expansion. As a test case, we calculate a range of thermodynamic properties of Neon, obtaining the same level of accuracy as RPMD, but with the shorter runtime of classical simulations. By modifying existing MD programs, the proposed method could be used in the future to increase the efficiency and accuracy of MD simulations involving water and proteins.

Evaporation kinetics of Mg2SiO4 crystals and melts from molecular dynamics simulations

NASA Technical Reports Server (NTRS)

Kubicki, J. D.; Stolper, E. M.

1993-01-01

Computer simulations based on the molecular dynamics (MD) technique were used to study the mechanisms and kinetics of free evaporation from crystalline and molten forsterite (i.e., Mg2SiO4) on an atomic level. The interatomic potential employed for these simulations reproduces the energetics of bonding in forsterite and in gas-phase MgO and SiO2 reasonably accurately. Results of the simulation include predicted evaporation rates, diffusion rates, and reaction mechanisms for Mg2SiO4(s or l) yields 2Mg(g) + 20(g) + SiO2(g).

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Fast Particle Methods for Multiscale Phenomena Simulations

NASA Technical Reports Server (NTRS)

Koumoutsakos, P.; Wray, A.; Shariff, K.; Pohorille, Andrew

2000-01-01

We are developing particle methods oriented at improving computational modeling capabilities of multiscale physical phenomena in : (i) high Reynolds number unsteady vortical flows, (ii) particle laden and interfacial flows, (iii)molecular dynamics studies of nanoscale droplets and studies of the structure, functions, and evolution of the earliest living cell. The unifying computational approach involves particle methods implemented in parallel computer architectures. The inherent adaptivity, robustness and efficiency of particle methods makes them a multidisciplinary computational tool capable of bridging the gap of micro-scale and continuum flow simulations. Using efficient tree data structures, multipole expansion algorithms, and improved particle-grid interpolation, particle methods allow for simulations using millions of computational elements, making possible the resolution of a wide range of length and time scales of these important physical phenomena.The current challenges in these simulations are in : [i] the proper formulation of particle methods in the molecular and continuous level for the discretization of the governing equations [ii] the resolution of the wide range of time and length scales governing the phenomena under investigation. [iii] the minimization of numerical artifacts that may interfere with the physics of the systems under consideration. [iv] the parallelization of processes such as tree traversal and grid-particle interpolations We are conducting simulations using vortex methods, molecular dynamics and smooth particle hydrodynamics, exploiting their unifying concepts such as : the solution of the N-body problem in parallel computers, highly accurate particle-particle and grid-particle interpolations, parallel FFT's and the formulation of processes such as diffusion in the context of particle methods. This approach enables us to transcend among seemingly unrelated areas of research.

Simulating Limb Formation in the U.S. EPA Virtual Embryo - Risk Assessment Project

EPA Science Inventory

The U.S. EPA’s Virtual Embryo project (v-Embryo™) is a computer model simulation of morphogenesis that integrates cell and molecular level data from mechanistic and in vitro assays with knowledge about normal development processes to assess in silico the effects of chemicals on d...

The Distributed Diagonal Force Decomposition Method for Parallelizing Molecular Dynamics Simulations

PubMed Central

Boršnik, Urban; Miller, Benjamin T.; Brooks, Bernard R.; Janežič, Dušanka

2011-01-01

Parallelization is an effective way to reduce the computational time needed for molecular dynamics simulations. We describe a new parallelization method, the distributed-diagonal force decomposition method, with which we extend and improve the existing force decomposition methods. Our new method requires less data communication during molecular dynamics simulations than replicated data and current force decomposition methods, increasing the parallel efficiency. It also dynamically load-balances the processors' computational load throughout the simulation. The method is readily implemented in existing molecular dynamics codes and it has been incorporated into the CHARMM program, allowing its immediate use in conjunction with the many molecular dynamics simulation techniques that are already present in the program. We also present the design of the Force Decomposition Machine, a cluster of personal computers and networks that is tailored to running molecular dynamics simulations using the distributed diagonal force decomposition method. The design is expandable and provides various degrees of fault resilience. This approach is easily adaptable to computers with Graphics Processing Units because it is independent of the processor type being used. PMID:21793007

Multiscale Reactive Molecular Dynamics

DTIC Science & Technology

2012-08-15

biology cannot be described without considering electronic and nuclear-level dynamics and their coupling to slower, cooperative motions of the system ...coupling to slower, cooperative motions of the system . These inherently multiscale problems require computationally efficient and accurate methods to...condensed phase systems with computational efficiency orders of magnitudes greater than currently possible with ab initio simulation methods, thus

High Performance Parallel Computational Nanotechnology

NASA Technical Reports Server (NTRS)

Saini, Subhash; Craw, James M. (Technical Monitor)

1995-01-01

At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.

Coarse-Grained Lattice Model Simulations of Sequence-Structure Fitness of a Ribosome-Inactivating Protein

DTIC Science & Technology

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

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Molecular simulations for energy, environmental and pharmaceutical applications of nanoporous materials: from zeolites, metal-organic frameworks to protein crystals.

PubMed

Jiang, Jianwen; Babarao, Ravichandar; Hu, Zhongqiao

2011-07-01

Nanoporous materials have widespread applications in chemical industry, but the pathway from laboratory synthesis and testing to practical utilization of nanoporous materials is substantially challenging and requires fundamental understanding from the bottom up. With ever-growing computational resources, molecular simulations have become an indispensable tool for material characterization, screening and design. This tutorial review summarizes the recent simulation studies in zeolites, metal-organic frameworks and protein crystals, and provides a molecular overview for energy, environmental and pharmaceutical applications of nanoporous materials with increasing degree of complexity in building blocks. It is demonstrated that molecular-level studies can bridge the gap between physical and engineering sciences, unravel microscopic insights that are otherwise experimentally inaccessible, and assist in the rational design of new materials. The review is concluded with major challenges in future simulation exploration of novel nanoporous materials for emerging applications.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

Static, rheological and mechanical properties of polymer nanocomposites studied by computer modeling and simulation.

PubMed

Liu, Jun; Zhang, Liqun; Cao, Dapeng; Wang, Wenchuan

2009-12-28

Polymer nanocomposites (PNCs) often exhibit excellent mechanical, thermal, electrical and optical properties, because they combine the performances of both polymers and inorganic or organic nanoparticles. Recently, computer modeling and simulation are playing an important role in exploring the reinforcement mechanism of the PNCs and even the design of functional PNCs. This report provides an overview of the progress made in past decades in the investigation of the static, rheological and mechanical properties of polymer nanocomposites studied by computer modeling and simulation. Emphases are placed on exploring the mechanisms at the molecular level for the dispersion of nanoparticles in nanocomposites, the effects of nanoparticles on chain conformation and glass transition temperature (T(g)), as well as viscoelastic and mechanical properties. Finally, some future challenges and opportunities in computer modeling and simulation of PNCs are addressed.

Evaluation of a grid based molecular dynamics approach for polypeptide simulations.

PubMed

Merelli, Ivan; Morra, Giulia; Milanesi, Luciano

2007-09-01

Molecular dynamics is very important for biomedical research because it makes possible simulation of the behavior of a biological macromolecule in silico. However, molecular dynamics is computationally rather expensive: the simulation of some nanoseconds of dynamics for a large macromolecule such as a protein takes very long time, due to the high number of operations that are needed for solving the Newton's equations in the case of a system of thousands of atoms. In order to obtain biologically significant data, it is desirable to use high-performance computation resources to perform these simulations. Recently, a distributed computing approach based on replacing a single long simulation with many independent short trajectories has been introduced, which in many cases provides valuable results. This study concerns the development of an infrastructure to run molecular dynamics simulations on a grid platform in a distributed way. The implemented software allows the parallel submission of different simulations that are singularly short but together bring important biological information. Moreover, each simulation is divided into a chain of jobs to avoid data loss in case of system failure and to contain the dimension of each data transfer from the grid. The results confirm that the distributed approach on grid computing is particularly suitable for molecular dynamics simulations thanks to the elevated scalability.

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks.

PubMed

Shen, Lin; Yang, Weitao

2018-03-13

Direct molecular dynamics (MD) simulation with ab initio quantum mechanical and molecular mechanical (QM/MM) methods is very powerful for studying the mechanism of chemical reactions in a complex environment but also very time-consuming. The computational cost of QM/MM calculations during MD simulations can be reduced significantly using semiempirical QM/MM methods with lower accuracy. To achieve higher accuracy at the ab initio QM/MM level, a correction on the existing semiempirical QM/MM model is an attractive idea. Recently, we reported a neural network (NN) method as QM/MM-NN to predict the potential energy difference between semiempirical and ab initio QM/MM approaches. The high-level results can be obtained using neural network based on semiempirical QM/MM MD simulations, but the lack of direct MD samplings at the ab initio QM/MM level is still a deficiency that limits the applications of QM/MM-NN. In the present paper, we developed a dynamic scheme of QM/MM-NN for direct MD simulations on the NN-predicted potential energy surface to approximate ab initio QM/MM MD. Since some configurations excluded from the database for NN training were encountered during simulations, which may cause some difficulties on MD samplings, an adaptive procedure inspired by the selection scheme reported by Behler [ Behler Int. J. Quantum Chem. 2015 , 115 , 1032 ; Behler Angew. Chem., Int. Ed. 2017 , 56 , 12828 ] was employed with some adaptions to update NN and carry out MD iteratively. We further applied the adaptive QM/MM-NN MD method to the free energy calculation and transition path optimization on chemical reactions in water. The results at the ab initio QM/MM level can be well reproduced using this method after 2-4 iteration cycles. The saving in computational cost is about 2 orders of magnitude. It demonstrates that the QM/MM-NN with direct MD simulations has great potentials not only for the calculation of thermodynamic properties but also for the characterization of reaction dynamics, which provides a useful tool to study chemical or biochemical systems in solution or enzymes.

Ab initio molecular simulations with numeric atom-centered orbitals

NASA Astrophysics Data System (ADS)

Blum, Volker; Gehrke, Ralf; Hanke, Felix; Havu, Paula; Havu, Ville; Ren, Xinguo; Reuter, Karsten; Scheffler, Matthias

2009-11-01

We describe a complete set of algorithms for ab initio molecular simulations based on numerically tabulated atom-centered orbitals (NAOs) to capture a wide range of molecular and materials properties from quantum-mechanical first principles. The full algorithmic framework described here is embodied in the Fritz Haber Institute "ab initio molecular simulations" (FHI-aims) computer program package. Its comprehensive description should be relevant to any other first-principles implementation based on NAOs. The focus here is on density-functional theory (DFT) in the local and semilocal (generalized gradient) approximations, but an extension to hybrid functionals, Hartree-Fock theory, and MP2/GW electron self-energies for total energies and excited states is possible within the same underlying algorithms. An all-electron/full-potential treatment that is both computationally efficient and accurate is achieved for periodic and cluster geometries on equal footing, including relaxation and ab initio molecular dynamics. We demonstrate the construction of transferable, hierarchical basis sets, allowing the calculation to range from qualitative tight-binding like accuracy to meV-level total energy convergence with the basis set. Since all basis functions are strictly localized, the otherwise computationally dominant grid-based operations scale as O(N) with system size N. Together with a scalar-relativistic treatment, the basis sets provide access to all elements from light to heavy. Both low-communication parallelization of all real-space grid based algorithms and a ScaLapack-based, customized handling of the linear algebra for all matrix operations are possible, guaranteeing efficient scaling (CPU time and memory) up to massively parallel computer systems with thousands of CPUs.

Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species with Application to DSMC Simulations

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2014-01-01

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for near-equilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion.

Chemical reactivity and spectroscopy explored from QM/MM molecular dynamics simulations using the LIO code

NASA Astrophysics Data System (ADS)

Marcolongo, Juan P.; Zeida, Ari; Semelak, Jonathan A.; Foglia, Nicolás O.; Morzan, Uriel N.; Estrin, Dario A.; González Lebrero, Mariano C.; Scherlis, Damián A.

2018-03-01

In this work we present the current advances in the development and the applications of LIO, a lab-made code designed for density functional theory calculations in graphical processing units (GPU), that can be coupled with different classical molecular dynamics engines. This code has been thoroughly optimized to perform efficient molecular dynamics simulations at the QM/MM DFT level, allowing for an exhaustive sampling of the configurational space. Selected examples are presented for the description of chemical reactivity in terms of free energy profiles, and also for the computation of optical properties, such as vibrational and electronic spectra in solvent and protein environments.

The Effect of Interactive, Three Dimensional, High Speed Simulations on High School Science Students' Conceptions of the Molecular Structure of Water.

ERIC Educational Resources Information Center

Hakerem, Gita; And Others

The Water and Molecular Networks (WAMNet) Project uses graduate student written Reduced Instruction Set Computing (RISC) computer simulations of the molecular structure of water to assist high school students learn about the nature of water. This study examined: (1) preconceptions concerning the molecular structure of water common among high…

Potential energy functions for atomic-level simulations of water and organic and biomolecular systems.

PubMed

Jorgensen, William L; Tirado-Rives, Julian

2005-05-10

An overview is provided on the development and status of potential energy functions that are used in atomic-level statistical mechanics and molecular dynamics simulations of water and of organic and biomolecular systems. Some topics that are considered are the form of force fields, their parameterization and performance, simulations of organic liquids, computation of free energies of hydration, universal extension for organic molecules, and choice of atomic charges. The discussion of water models covers some history, performance issues, and special topics such as nuclear quantum effects.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Du, Jincheng; Rimsza, Jessica

Computational simulations at the atomistic level play an increasing important role in understanding the structures, behaviors, and the structure-property relationships of glass and amorphous materials. In this paper, we reviewed atomistic simulation methods ranging from first principles calculations and ab initio molecular dynamics (AIMD), to classical molecular dynamics (MD) and meso-scale kinetic Monte Carlo (KMC) simulations and their applications to glass-water interactions and glass dissolutions. Particularly, the use of these simulation methods in understanding the reaction mechanisms of water with oxide glasses, water-glass interfaces, hydrated porous silica gels formation, the structure and properties of multicomponent glasses, and microstructure evolution aremore » reviewed. Here, the advantages and disadvantageous of these methods are discussed and the current challenges and future direction of atomistic simulations in glass dissolution are presented.« less

Molecular simulation workflows as parallel algorithms: the execution engine of Copernicus, a distributed high-performance computing platform.

PubMed

Pronk, Sander; Pouya, Iman; Lundborg, Magnus; Rotskoff, Grant; Wesén, Björn; Kasson, Peter M; Lindahl, Erik

2015-06-09

Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers-particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide more processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus.

MDGRAPE-4: a special-purpose computer system for molecular dynamics simulations.

PubMed

Ohmura, Itta; Morimoto, Gentaro; Ohno, Yousuke; Hasegawa, Aki; Taiji, Makoto

2014-08-06

We are developing the MDGRAPE-4, a special-purpose computer system for molecular dynamics (MD) simulations. MDGRAPE-4 is designed to achieve strong scalability for protein MD simulations through the integration of general-purpose cores, dedicated pipelines, memory banks and network interfaces (NIFs) to create a system on chip (SoC). Each SoC has 64 dedicated pipelines that are used for non-bonded force calculations and run at 0.8 GHz. Additionally, it has 65 Tensilica Xtensa LX cores with single-precision floating-point units that are used for other calculations and run at 0.6 GHz. At peak performance levels, each SoC can evaluate 51.2 G interactions per second. It also has 1.8 MB of embedded shared memory banks and six network units with a peak bandwidth of 7.2 GB s(-1) for the three-dimensional torus network. The system consists of 512 (8×8×8) SoCs in total, which are mounted on 64 node modules with eight SoCs. The optical transmitters/receivers are used for internode communication. The expected maximum power consumption is 50 kW. While MDGRAPE-4 software has still been improved, we plan to run MD simulations on MDGRAPE-4 in 2014. The MDGRAPE-4 system will enable long-time molecular dynamics simulations of small systems. It is also useful for multiscale molecular simulations where the particle simulation parts often become bottlenecks.

MDGRAPE-4: a special-purpose computer system for molecular dynamics simulations

PubMed Central

Ohmura, Itta; Morimoto, Gentaro; Ohno, Yousuke; Hasegawa, Aki; Taiji, Makoto

2014-01-01

We are developing the MDGRAPE-4, a special-purpose computer system for molecular dynamics (MD) simulations. MDGRAPE-4 is designed to achieve strong scalability for protein MD simulations through the integration of general-purpose cores, dedicated pipelines, memory banks and network interfaces (NIFs) to create a system on chip (SoC). Each SoC has 64 dedicated pipelines that are used for non-bonded force calculations and run at 0.8 GHz. Additionally, it has 65 Tensilica Xtensa LX cores with single-precision floating-point units that are used for other calculations and run at 0.6 GHz. At peak performance levels, each SoC can evaluate 51.2 G interactions per second. It also has 1.8 MB of embedded shared memory banks and six network units with a peak bandwidth of 7.2 GB s−1 for the three-dimensional torus network. The system consists of 512 (8×8×8) SoCs in total, which are mounted on 64 node modules with eight SoCs. The optical transmitters/receivers are used for internode communication. The expected maximum power consumption is 50 kW. While MDGRAPE-4 software has still been improved, we plan to run MD simulations on MDGRAPE-4 in 2014. The MDGRAPE-4 system will enable long-time molecular dynamics simulations of small systems. It is also useful for multiscale molecular simulations where the particle simulation parts often become bottlenecks. PMID:24982255

Evaluation of Kirkwood-Buff integrals via finite size scaling: a large scale molecular dynamics study

NASA Astrophysics Data System (ADS)

Dednam, W.; Botha, A. E.

2015-01-01

Solvation of bio-molecules in water is severely affected by the presence of co-solvent within the hydration shell of the solute structure. Furthermore, since solute molecules can range from small molecules, such as methane, to very large protein structures, it is imperative to understand the detailed structure-function relationship on the microscopic level. For example, it is useful know the conformational transitions that occur in protein structures. Although such an understanding can be obtained through large-scale molecular dynamic simulations, it is often the case that such simulations would require excessively large simulation times. In this context, Kirkwood-Buff theory, which connects the microscopic pair-wise molecular distributions to global thermodynamic properties, together with the recently developed technique, called finite size scaling, may provide a better method to reduce system sizes, and hence also the computational times. In this paper, we present molecular dynamics trial simulations of biologically relevant low-concentration solvents, solvated by aqueous co-solvent solutions. In particular we compare two different methods of calculating the relevant Kirkwood-Buff integrals. The first (traditional) method computes running integrals over the radial distribution functions, which must be obtained from large system-size NVT or NpT simulations. The second, newer method, employs finite size scaling to obtain the Kirkwood-Buff integrals directly by counting the particle number fluctuations in small, open sub-volumes embedded within a larger reservoir that can be well approximated by a much smaller simulation cell. In agreement with previous studies, which made a similar comparison for aqueous co-solvent solutions, without the additional solvent, we conclude that the finite size scaling method is also applicable to the present case, since it can produce computationally more efficient results which are equivalent to the more costly radial distribution function method.

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

PubMed Central

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-01-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services. PMID:27216779

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

NASA Astrophysics Data System (ADS)

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-05-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Avoiding Defect Nucleation during Equilibration in Molecular Dynamics Simulations with ReaxFF

DTIC Science & Technology

2015-04-01

respectively. All simulations are performed using the LAMMPS computer code.12 2 Fig. 1 a) Initial and b) final configurations of the molecular centers...Plimpton S. Fast parallel algorithms for short-range molecular dynamics. Comput J Phys. 1995;117:1–19. (Software available at http:// lammps .sandia.gov

Surface Modification Engineered Assembly of Novel Quantum Dot Architectures for Advanced Applications

DTIC Science & Technology

2008-02-09

Campbell, S. Ogata, and F. Shimojo, “ Multimillion atom simulations of nanosystems on parallel computers,” in Proceedings of the International...nanomesas: multimillion -atom molecular dynamics simulations on parallel computers,” J. Appl. Phys. 94, 6762 (2003). 21. P. Vashishta, R. K. Kalia...and A. Nakano, “ Multimillion atom molecular dynamics simulations of nanoparticles on parallel computers,” Journal of Nanoparticle Research 5, 119-135

Extension of the quantum-kinetic model to lunar and Mars return physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liechty, D. S.; Lewis, M. J.

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high-mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. A recently introduced molecular-level chemistry model, the quantum-kinetic, or Q-K, model that predicts reaction rates for gases in thermal equilibrium and non-equilibrium using only kinetic theory and fundamental molecular properties, is extended in the current work to include electronic energy level transitions and reactions involving charged particles. Like the Q-K procedures for neutral species chemical reactions, these new models are phenomenological procedures that aimmore » to reproduce the reaction/transition rates but do not necessarily capture the exact physics. These engineering models are necessarily efficient due to the requirement to compute billions of simulated collisions in direct simulation Monte Carlo (DSMC) simulations. The new models are shown to generally agree within the spread of reported transition and reaction rates from the literature for near equilibrium conditions.« less

Computational Nanotechnology of Molecular Materials, Electronics, and Actuators with Carbon Nanotubes and Fullerenes

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, Madhu; Cho, Kyeongjae; Biegel, Bryan (Technical Monitor)

2001-01-01

The role of computational nanotechnology in developing next generation of multifunctional materials, molecular scale electronic and computing devices, sensors, actuators, and machines is described through a brief review of enabling computational techniques and few recent examples derived from computer simulations of carbon nanotube based molecular nanotechnology.

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations.

PubMed

Sinko, William; de Oliveira, César Augusto F; Pierce, Levi C T; McCammon, J Andrew

2012-01-10

Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations.

Molecular Dynamics Simulations of Voltage-Gated Cation Channels: Insights on Voltage-Sensor Domain Function and Modulation

PubMed Central

Delemotte, Lucie; Klein, Michael L.; Tarek, Mounir

2012-01-01

Since their discovery in the 1950s, the structure and function of voltage-gated cation channels (VGCC) has been largely understood thanks to results stemming from electrophysiology, pharmacology, spectroscopy, and structural biology. Over the past decade, computational methods such as molecular dynamics (MD) simulations have also contributed, providing molecular level information that can be tested against experimental results, thereby allowing the validation of the models and protocols. Importantly, MD can shed light on elements of VGCC function that cannot be easily accessed through “classical” experiments. Here, we review the results of recent MD simulations addressing key questions that pertain to the function and modulation of the VGCC’s voltage-sensor domain (VSD) highlighting: (1) the movement of the S4-helix basic residues during channel activation, articulating how the electrical driving force acts upon them; (2) the nature of the VSD intermediate states on transitioning between open and closed states of the VGCC; and (3) the molecular level effects on the VSD arising from mutations of specific S4 positively charged residues involved in certain genetic diseases. PMID:22654756

Efficient and Flexible Computation of Many-Electron Wave Function Overlaps.

PubMed

Plasser, Felix; Ruckenbauer, Matthias; Mai, Sebastian; Oppel, Markus; Marquetand, Philipp; González, Leticia

2016-03-08

A new algorithm for the computation of the overlap between many-electron wave functions is described. This algorithm allows for the extensive use of recurring intermediates and thus provides high computational efficiency. Because of the general formalism employed, overlaps can be computed for varying wave function types, molecular orbitals, basis sets, and molecular geometries. This paves the way for efficiently computing nonadiabatic interaction terms for dynamics simulations. In addition, other application areas can be envisaged, such as the comparison of wave functions constructed at different levels of theory. Aside from explaining the algorithm and evaluating the performance, a detailed analysis of the numerical stability of wave function overlaps is carried out, and strategies for overcoming potential severe pitfalls due to displaced atoms and truncated wave functions are presented.

AceCloud: Molecular Dynamics Simulations in the Cloud.

PubMed

Harvey, M J; De Fabritiis, G

2015-05-26

We present AceCloud, an on-demand service for molecular dynamics simulations. AceCloud is designed to facilitate the secure execution of large ensembles of simulations on an external cloud computing service (currently Amazon Web Services). The AceCloud client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the cloud services. This gives the user the experience that all simulations are running on their local machine, minimizing the learning curve typically associated with the transition to using high performance computing services.

Crystal MD: The massively parallel molecular dynamics software for metal with BCC structure

NASA Astrophysics Data System (ADS)

Hu, Changjun; Bai, He; He, Xinfu; Zhang, Boyao; Nie, Ningming; Wang, Xianmeng; Ren, Yingwen

2017-02-01

Material irradiation effect is one of the most important keys to use nuclear power. However, the lack of high-throughput irradiation facility and knowledge of evolution process, lead to little understanding of the addressed issues. With the help of high-performance computing, we could make a further understanding of micro-level-material. In this paper, a new data structure is proposed for the massively parallel simulation of the evolution of metal materials under irradiation environment. Based on the proposed data structure, we developed the new molecular dynamics software named Crystal MD. The simulation with Crystal MD achieved over 90% parallel efficiency in test cases, and it takes more than 25% less memory on multi-core clusters than LAMMPS and IMD, which are two popular molecular dynamics simulation software. Using Crystal MD, a two trillion particles simulation has been performed on Tianhe-2 cluster.

Spectroscopic analysis and molecular docking of imidazole derivatives and investigation of its reactive properties by DFT and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Thomas, Renjith; Hossain, Mossaraf; Mary, Y. Sheena; Resmi, K. S.; Armaković, Stevan; Armaković, Sanja J.; Nanda, Ashis Kumar; Ranjan, Vivek Kumar; Vijayakumar, G.; Van Alsenoy, C.

2018-04-01

Solvent-free synthesis pathway for obtaining two imidazole derivatives (2-chloro-1-(4-methoxyphenyl)-4,5-dimethyl-1H-imidazole (CLMPDI) and 1-(4-bromophenyl)-2-chloro-4,5-dimethyl-1H-imidazole (BPCLDI) has been reported in this work, followed by detailed experimental and computational spectroscopic characterization and reactivity study. Spectroscopic methods encompassed IR, FT-Raman and NMR techniques, with the mutual comparison of experimentally and computationally obtained results at DFT/B3LYP level of theory. Reactivity study based on DFT calculations encompassed molecular orbitals analysis, followed by calculations of molecular electrostatic potential (MEP) and average local ionization energy (ALIE) values, Fukui functions and bond dissociation energies (BDE). Additionally, the stability of title molecules in water has been investigated via molecular dynamics (MD) simulations, while interactivity with aspulvinonedimethylallyl transferase protein has been evaluated by molecular docking procedure. CLMPDI compound showed antimicrobial activity against all four bacterial strain in both gram positive and gram negative bacteria while, BPCLDI showed only in gram positive bacteria, Staphylococcus Aureus (MTCC1144). The first order hyperpolarizability of CLMPDI and BPCLDI are 20.15 and 6.10 times that of the standard NLO material urea.

Computationally Efficient Multiscale Reactive Molecular Dynamics to Describe Amino Acid Deprotonation in Proteins

PubMed Central

2016-01-01

An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput.2014, 10, 2729−273725061442), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H+/Cl– antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins. PMID:26734942

Computationally Efficient Multiscale Reactive Molecular Dynamics to Describe Amino Acid Deprotonation in Proteins.

PubMed

Lee, Sangyun; Liang, Ruibin; Voth, Gregory A; Swanson, Jessica M J

2016-02-09

An important challenge in the simulation of biomolecular systems is a quantitative description of the protonation and deprotonation process of amino acid residues. Despite the seeming simplicity of adding or removing a positively charged hydrogen nucleus, simulating the actual protonation/deprotonation process is inherently difficult. It requires both the explicit treatment of the excess proton, including its charge defect delocalization and Grotthuss shuttling through inhomogeneous moieties (water and amino residues), and extensive sampling of coupled condensed phase motions. In a recent paper (J. Chem. Theory Comput. 2014, 10, 2729-2737), a multiscale approach was developed to map high-level quantum mechanics/molecular mechanics (QM/MM) data into a multiscale reactive molecular dynamics (MS-RMD) model in order to describe amino acid deprotonation in bulk water. In this article, we extend the fitting approach (called FitRMD) to create MS-RMD models for ionizable amino acids within proteins. The resulting models are shown to faithfully reproduce the free energy profiles of the reference QM/MM Hamiltonian for PT inside an example protein, the ClC-ec1 H(+)/Cl(-) antiporter. Moreover, we show that the resulting MS-RMD models are computationally efficient enough to then characterize more complex 2-dimensional free energy surfaces due to slow degrees of freedom such as water hydration of internal protein cavities that can be inherently coupled to the excess proton charge translocation. The FitRMD method is thus shown to be an effective way to map ab initio level accuracy into a much more computationally efficient reactive MD method in order to explicitly simulate and quantitatively describe amino acid protonation/deprotonation in proteins.

CO2 capture in amine solutions: modelling and simulations with non-empirical methods

NASA Astrophysics Data System (ADS)

Andreoni, Wanda; Pietrucci, Fabio

2016-12-01

Absorption in aqueous amine solutions is the most advanced technology for the capture of CO2, although suffering from drawbacks that do not allow exploitation on large scale. The search for optimum solvents has been pursued with empirical methods and has also motivated a number of computational approaches over the last decade. However, a deeper level of understanding of the relevant chemical reactions in solution is required so as to contribute to this effort. We present here a brief critical overview of the most recent applications of computer simulations using ab initio methods. Comparison of their outcome shows a strong dependence on the structural models employed to represent the molecular systems in solution and on the strategy used to simulate the reactions. In particular, the results of very recent ab initio molecular dynamics augmented with metadynamics are summarized, showing the crucial role of water, which has been so far strongly underestimated both in the calculations and in the interpretation of experimental data. Indications are given for advances in computational approaches that are necessary if meant to contribute to the rational design of new solvents.

A Computer Simulation Approach to Assessing Therapeutic Intervention Points for the Prevention of Cytokine-Induced Cartilage Breakdown

PubMed Central

Proctor, CJ; Macdonald, C; Milner, JM; Rowan, AD; Cawston, TE

2014-01-01

Objective To use a novel computational approach to examine the molecular pathways involved in cartilage breakdown and to use computer simulation to test possible interventions for reducing collagen release. Methods We constructed a computational model of the relevant molecular pathways using the Systems Biology Markup Language, a computer-readable format of a biochemical network. The model was constructed using our experimental data showing that interleukin-1 (IL-1) and oncostatin M (OSM) act synergistically to up-regulate collagenase protein levels and activity and initiate cartilage collagen breakdown. Simulations were performed using the COPASI software package. Results The model predicted that simulated inhibition of JNK or p38 MAPK, and overexpression of tissue inhibitor of metalloproteinases 3 (TIMP-3) led to a reduction in collagen release. Overexpression of TIMP-1 was much less effective than that of TIMP-3 and led to a delay, rather than a reduction, in collagen release. Simulated interventions of receptor antagonists and inhibition of JAK-1, the first kinase in the OSM pathway, were ineffective. So, importantly, the model predicts that it is more effective to intervene at targets that are downstream, such as the JNK pathway, rather than those that are close to the cytokine signal. In vitro experiments confirmed the effectiveness of JNK inhibition. Conclusion Our study shows the value of computer modeling as a tool for examining possible interventions by which to reduce cartilage collagen breakdown. The model predicts that interventions that either prevent transcription or inhibit the activity of collagenases are promising strategies and should be investigated further in an experimental setting. PMID:24757149

A Simple Method for Automated Equilibration Detection in Molecular Simulations.

PubMed

Chodera, John D

2016-04-12

Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure and demonstrate its utility on typical molecular simulation data.

A simple method for automated equilibration detection in molecular simulations

PubMed Central

Chodera, John D.

2016-01-01

Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest, in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure, and demonstrate its utility on typical molecular simulation data. PMID:26771390

FY10 Report on Multi-scale Simulation of Solvent Extraction Processes: Molecular-scale and Continuum-scale Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wardle, Kent E.; Frey, Kurt; Pereira, Candido

2014-02-02

This task is aimed at predictive modeling of solvent extraction processes in typical extraction equipment through multiple simulation methods at various scales of resolution. We have conducted detailed continuum fluid dynamics simulation on the process unit level as well as simulations of the molecular-level physical interactions which govern extraction chemistry. Through combination of information gained through simulations at each of these two tiers along with advanced techniques such as the Lattice Boltzmann Method (LBM) which can bridge these two scales, we can develop the tools to work towards predictive simulation for solvent extraction on the equipment scale (Figure 1). Themore » goal of such a tool-along with enabling optimized design and operation of extraction units-would be to allow prediction of stage extraction effrciency under specified conditions. Simulation efforts on each of the two scales will be described below. As the initial application of FELBM in the work performed during FYl0 has been on annular mixing it will be discussed in context of the continuum-scale. In the future, however, it is anticipated that the real value of FELBM will be in its use as a tool for sub-grid model development through highly refined DNS-like multiphase simulations facilitating exploration and development of droplet models including breakup and coalescence which will be needed for the large-scale simulations where droplet level physics cannot be resolved. In this area, it can have a significant advantage over traditional CFD methods as its high computational efficiency allows exploration of significantly greater physical detail especially as computational resources increase in the future.« less

Simulation of size-exclusion chromatography distribution coefficients of comb-shaped molecules in spherical pores comparison of simulation and experiment.

PubMed

Radke, Wolfgang

2004-03-05

Simulations of the distribution coefficients of linear polymers and regular combs with various spacings between the arms have been performed. The distribution coefficients were plotted as a function of the number of segments in order to compare the size exclusion chromatography (SEC)-elution behavior of combs relative to linear molecules. By comparing the simulated SEC-calibration curves it is possible to predict the elution behavior of comb-shaped polymers relative to linear ones. In order to compare the results obtained by computer simulations with experimental data, a variety of comb-shaped polymers varying in side chain length, spacing between the side chains and molecular weights of the backbone were analyzed by SEC with light-scattering detection. It was found that the computer simulations could predict the molecular weights of linear molecules having the same retention volume with an accuracy of about 10%, i.e. the error in the molecular weight obtained by calculating the molecular weight of the comb-polymer based on a calibration curve constructed using linear standards and the results of the computer simulations are of the same magnitude as the experimental error of absolute molecular weight determination.

Kinetic Theory and Simulation of Single-Channel Water Transport

NASA Astrophysics Data System (ADS)

Tajkhorshid, Emad; Zhu, Fangqiang; Schulten, Klaus

Water translocation between various compartments of a system is a fundamental process in biology of all living cells and in a wide variety of technological problems. The process is of interest in different fields of physiology, physical chemistry, and physics, and many scientists have tried to describe the process through physical models. Owing to advances in computer simulation of molecular processes at an atomic level, water transport has been studied in a variety of molecular systems ranging from biological water channels to artificial nanotubes. While simulations have successfully described various kinetic aspects of water transport, offering a simple, unified model to describe trans-channel translocation of water turned out to be a nontrivial task.

Exploring Biomolecular Recognition by Modeling and Simulation

NASA Astrophysics Data System (ADS)

Wade, Rebecca

2007-12-01

Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

MaMiCo: Software design for parallel molecular-continuum flow simulations

NASA Astrophysics Data System (ADS)

Neumann, Philipp; Flohr, Hanno; Arora, Rahul; Jarmatz, Piet; Tchipev, Nikola; Bungartz, Hans-Joachim

2016-03-01

The macro-micro-coupling tool (MaMiCo) was developed to ease the development of and modularize molecular-continuum simulations, retaining sequential and parallel performance. We demonstrate the functionality and performance of MaMiCo by coupling the spatially adaptive Lattice Boltzmann framework waLBerla with four molecular dynamics (MD) codes: the light-weight Lennard-Jones-based implementation SimpleMD, the node-level optimized software ls1 mardyn, and the community codes ESPResSo and LAMMPS. We detail interface implementations to connect each solver with MaMiCo. The coupling for each waLBerla-MD setup is validated in three-dimensional channel flow simulations which are solved by means of a state-based coupling method. We provide sequential and strong scaling measurements for the four molecular-continuum simulations. The overhead of MaMiCo is found to come at 10%-20% of the total (MD) runtime. The measurements further show that scalability of the hybrid simulations is reached on up to 500 Intel SandyBridge, and more than 1000 AMD Bulldozer compute cores.

Quantum Entanglement Molecular Absorption Spectrum Simulator

NASA Technical Reports Server (NTRS)

Nguyen, Quang-Viet; Kojima, Jun

2006-01-01

Quantum Entanglement Molecular Absorption Spectrum Simulator (QE-MASS) is a computer program for simulating two photon molecular-absorption spectroscopy using quantum-entangled photons. More specifically, QE-MASS simulates the molecular absorption of two quantum-entangled photons generated by the spontaneous parametric down-conversion (SPDC) of a fixed-frequency photon from a laser. The two-photon absorption process is modeled via a combination of rovibrational and electronic single-photon transitions, using a wave-function formalism. A two-photon absorption cross section as a function of the entanglement delay time between the two photons is computed, then subjected to a fast Fourier transform to produce an energy spectrum. The program then detects peaks in the Fourier spectrum and displays the energy levels of very short-lived intermediate quantum states (or virtual states) of the molecule. Such virtual states were only previously accessible using ultra-fast (femtosecond) laser systems. However, with the use of a single-frequency continuous wave laser to produce SPDC photons, and QEMASS program, these short-lived molecular states can now be studied using much simpler laser systems. QE-MASS can also show the dependence of the Fourier spectrum on the tuning range of the entanglement time of any externally introduced optical-path delay time. QE-MASS can be extended to any molecule for which an appropriate spectroscopic database is available. It is a means of performing an a priori parametric analysis of entangled photon spectroscopy for development and implementation of emerging quantum-spectroscopic sensing techniques. QE-MASS is currently implemented using the Mathcad software package.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

NASA Astrophysics Data System (ADS)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-11-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

Study of Nanocomposites of Amino Acids and Organic Polyethers by Means of Mass Spectrometry and Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Zobnina, V. G.; Kosevich, M. V.; Chagovets, V. V.; Boryak, O. A.

A problem of elucidation of structure of nanomaterials based on combination of proteins and polyether polymers is addressed on the monomeric level of single amino acids and oligomers of PEG-400 and OEG-5 polyethers. Efficiency of application of combined approach involving experimental electrospray mass spectrometry and computer modeling by molecular dynamics simulation is demonstrated. It is shown that oligomers of polyethers form stable complexes with amino acids valine, proline, histidine, glutamic, and aspartic acids. Molecular dynamics simulation has shown that stabilization of amino acid-polyether complexes is achieved due to winding of the polymeric chain around charged groups of amino acids. Structural motives revealed for complexes of single amino acids with polyethers can be realized in structures of protein-polyether nanoparticles currently designed for drug delivery.

Computationally Efficient Multiconfigurational Reactive Molecular Dynamics

PubMed Central

Yamashita, Takefumi; Peng, Yuxing; Knight, Chris; Voth, Gregory A.

2012-01-01

It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as “multistate”. These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations. PMID:25100924

Free Enthalpy Differences between α-, π-, and 310-Helices of an Atomic Level Fine-Grained Alanine Deca-Peptide Solvated in Supramolecular Coarse-Grained Water.

PubMed

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.

The Self-Assembly of Particles with Multipolar Interactions

DTIC Science & Technology

2004-01-01

the LATEX template in which this thesis has been written. I also thank Kevin Van Workum and Jack Douglas for contributing simulation work and some...of the computational expense of simulating such complex self-assembly systems at the molecular level and a desire to understand the self-assembly at...Dissertation directed by: Professor Wolfgang Losert Department of Physics In this thesis , we describe results from investigations of the self-assembly of

Molecular dynamics simulations and applications in computational toxicology and nanotoxicology.

PubMed

Selvaraj, Chandrabose; Sakkiah, Sugunadevi; Tong, Weida; Hong, Huixiao

2018-02-01

Nanotoxicology studies toxicity of nanomaterials and has been widely applied in biomedical researches to explore toxicity of various biological systems. Investigating biological systems through in vivo and in vitro methods is expensive and time taking. Therefore, computational toxicology, a multi-discipline field that utilizes computational power and algorithms to examine toxicology of biological systems, has gained attractions to scientists. Molecular dynamics (MD) simulations of biomolecules such as proteins and DNA are popular for understanding of interactions between biological systems and chemicals in computational toxicology. In this paper, we review MD simulation methods, protocol for running MD simulations and their applications in studies of toxicity and nanotechnology. We also briefly summarize some popular software tools for execution of MD simulations. Published by Elsevier Ltd.

Molecular dynamics simulations in hybrid particle-continuum schemes: Pitfalls and caveats

NASA Astrophysics Data System (ADS)

Stalter, S.; Yelash, L.; Emamy, N.; Statt, A.; Hanke, M.; Lukáčová-Medvid'ová, M.; Virnau, P.

2018-03-01

Heterogeneous multiscale methods (HMM) combine molecular accuracy of particle-based simulations with the computational efficiency of continuum descriptions to model flow in soft matter liquids. In these schemes, molecular simulations typically pose a computational bottleneck, which we investigate in detail in this study. We find that it is preferable to simulate many small systems as opposed to a few large systems, and that a choice of a simple isokinetic thermostat is typically sufficient while thermostats such as Lowe-Andersen allow for simulations at elevated viscosity. We discuss suitable choices for time steps and finite-size effects which arise in the limit of very small simulation boxes. We also argue that if colloidal systems are considered as opposed to atomistic systems, the gap between microscopic and macroscopic simulations regarding time and length scales is significantly smaller. We propose a novel reduced-order technique for the coupling to the macroscopic solver, which allows us to approximate a non-linear stress-strain relation efficiently and thus further reduce computational effort of microscopic simulations.

Protocols for Molecular Dynamics Simulations of RNA Nanostructures.

PubMed

Kim, Taejin; Kasprzak, Wojciech K; Shapiro, Bruce A

2017-01-01

Molecular dynamics (MD) simulations have been used as one of the main research tools to study a wide range of biological systems and bridge the gap between X-ray crystallography or NMR structures and biological mechanism. In the field of RNA nanostructures, MD simulations have been used to fix steric clashes in computationally designed RNA nanostructures, characterize the dynamics, and investigate the interaction between RNA and other biomolecules such as delivery agents and membranes.In this chapter we present examples of computational protocols for molecular dynamics simulations in explicit and implicit solvent using the Amber Molecular Dynamics Package. We also show examples of post-simulation analysis steps and briefly mention selected tools beyond the Amber package. Limitations of the methods, tools, and protocols are also discussed. Most of the examples are illustrated for a small RNA duplex (helix), but the protocols are applicable to any nucleic acid structure, subject only to the computational speed and memory limitations of the hardware available to the user.

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

NASA Astrophysics Data System (ADS)

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-10-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.

Highly Efficient Computation of the Basal kon using Direct Simulation of Protein-Protein Association with Flexible Molecular Models.

PubMed

Saglam, Ali S; Chong, Lillian T

2016-01-14

An essential baseline for determining the extent to which electrostatic interactions enhance the kinetics of protein-protein association is the "basal" kon, which is the rate constant for association in the absence of electrostatic interactions. However, since such association events are beyond the milliseconds time scale, it has not been practical to compute the basal kon by directly simulating the association with flexible models. Here, we computed the basal kon for barnase and barstar, two of the most rapidly associating proteins, using highly efficient, flexible molecular simulations. These simulations involved (a) pseudoatomic protein models that reproduce the molecular shapes, electrostatic, and diffusion properties of all-atom models, and (b) application of the weighted ensemble path sampling strategy, which enhanced the efficiency of generating association events by >130-fold. We also examined the extent to which the computed basal kon is affected by inclusion of intermolecular hydrodynamic interactions in the simulations.

A high performance system for molecular dynamics simulation of biomolecules using a special-purpose computer.

PubMed

Komeiji, Y; Yokoyama, H; Uebayasi, M; Taiji, M; Fukushige, T; Sugimoto, D; Takata, R; Shimizu, A; Itsukashi, K

1996-01-01

GRAPE (GRavity PipE) processors are special purpose computers for simulation of classical particles. The performance of MD-GRAPE, one of the GRAPEs developed for molecular dynamics, was investigated. The effective speed of MD-GRAPE was equivalent to approximately 6 Gflops. The precision of MD-GRAPE was good judging from the acceptable fluctuation of the total energy. Then a software named PEACH (Program for Energetic Analysis of bioCHemical molecules) was developed for molecular dynamics of biomolecules in combination with MD-GRAPE. Molecular dynamics simulation was performed for several protein-solvent systems with different sizes. Simulation of the largest system investigated (27,000 atoms) took only 5 sec/step. Thus, the PEACH-GRAPE system is expected to be useful in accurate and reliable simulation of large biomolecules.

Extension of a Kinetic Approach to Chemical Reactions to Electronic Energy Levels and Reactions Involving Charged Species With Application to DSMC Simulations

NASA Technical Reports Server (NTRS)

Liechty, Derek S.

2013-01-01

The ability to compute rarefied, ionized hypersonic flows is becoming more important as missions such as Earth reentry, landing high mass payloads on Mars, and the exploration of the outer planets and their satellites are being considered. Recently introduced molecular-level chemistry models that predict equilibrium and nonequilibrium reaction rates using only kinetic theory and fundamental molecular properties are extended in the current work to include electronic energy level transitions and reactions involving charged particles. These extensions are shown to agree favorably with reported transition and reaction rates from the literature for nearequilibrium conditions. Also, the extensions are applied to the second flight of the Project FIRE flight experiment at 1634 seconds with a Knudsen number of 0.001 at an altitude of 76.4 km. In order to accomplish this, NASA's direct simulation Monte Carlo code DAC was rewritten to include the ability to simulate charge-neutral ionized flows, take advantage of the recently introduced chemistry model, and to include the extensions presented in this work. The 1634 second data point was chosen for comparisons to be made in order to include a CFD solution. The Knudsen number at this point in time is such that the DSMC simulations are still tractable and the CFD computations are at the edge of what is considered valid because, although near-transitional, the flow is still considered to be continuum. It is shown that the inclusion of electronic energy levels in the DSMC simulation is necessary for flows of this nature and is required for comparison to the CFD solution. The flow field solutions are also post-processed by the nonequilibrium radiation code HARA to compute the radiative portion of the heating and is then compared to the total heating measured in flight.

Structured water in polyelectrolyte dendrimers: Understanding small angle neutron scattering results through atomistic simulation

NASA Astrophysics Data System (ADS)

Wu, Bin; Kerkeni, Boutheïna; Egami, Takeshi; Do, Changwoo; Liu, Yun; Wang, Yongmei; Porcar, Lionel; Hong, Kunlun; Smith, Sean C.; Liu, Emily L.; Smith, Gregory S.; Chen, Wei-Ren

2012-04-01

Based on atomistic molecular dynamics (MD) simulations, the small angle neutron scattering (SANS) intensity behavior of a single generation-4 polyelectrolyte polyamidoamine starburst dendrimer is investigated at different levels of molecular protonation. The SANS form factor, P(Q), and Debye autocorrelation function, γ(r), are calculated from the equilibrium MD trajectory based on a mathematical approach proposed in this work. The consistency found in comparison against previously published experimental findings (W.-R. Chen, L. Porcar, Y. Liu, P. D. Butler, and L. J. Magid, Macromolecules 40, 5887 (2007)) leads to a link between the neutron scattering experiment and MD computation, and fresh perspectives. The simulations enable scattering calculations of not only the hydrocarbons but also the contribution from the scattering length density fluctuations caused by structured, confined water within the dendrimer. Based on our computational results, we explore the validity of using radius of gyration RG for microstructure characterization of a polyelectrolyte dendrimer from the scattering perspective.

Li-Doped Ionic Liquid Electrolytes: From Bulk Phase to Interfacial Behavior

NASA Technical Reports Server (NTRS)

Haskins, Justin B.; Lawson, John W.

2016-01-01

Ionic liquids have been proposed as candidate electrolytes for high-energy density, rechargeable batteries. We present an extensive computational analysis supported by experimental comparisons of the bulk and interfacial properties of a representative set of these electrolytes as a function of Li-salt doping. We begin by investigating the bulk electrolyte using quantum chemistry and ab initio molecular dynamics to elucidate the solvation structure of Li(+). MD simulations using the polarizable force field of Borodin and coworkers were then performed, from which we obtain an array of thermodynamic and transport properties. Excellent agreement is found with experiments for diffusion, ionic conductivity, and viscosity. Combining MD simulations with electronic structure computations, we computed the electrochemical window of the electrolytes across a range of Li(+)-doping levels and comment on the role of the liquid environment. Finally, we performed a suite of simulations of these Li-doped electrolytes at ideal electrified interfaces to evaluate the differential capacitance and the equilibrium Li(+) distribution in the double layer. The magnitude of differential capacitance is in good agreement with our experiments and exhibits the characteristic camel-shaped profile. In addition, the simulations reveal Li(+) to be highly localized to the second molecular layer of the double layer, which is supported by additional computations that find this layer to be a free energy minimum with respect to Li(+) translation.

Estimation of conformational entropy in protein-ligand interactions: a computational perspective.

PubMed

Polyansky, Anton A; Zubac, Ruben; Zagrovic, Bojan

2012-01-01

Conformational entropy is an important component of the change in free energy upon binding of a ligand to its target protein. As a consequence, development of computational techniques for reliable estimation of conformational entropies is currently receiving an increased level of attention in the context of computational drug design. Here, we review the most commonly used techniques for conformational entropy estimation from classical molecular dynamics simulations. Although by-and-large still not directly used in practical drug design, these techniques provide a golden standard for developing other, computationally less-demanding methods for such applications, in addition to furthering our understanding of protein-ligand interactions in general. In particular, we focus on the quasi-harmonic approximation and discuss different approaches that can be used to go beyond it, most notably, when it comes to treating anharmonic and/or correlated motions. In addition to reviewing basic theoretical formalisms, we provide a concrete set of steps required to successfully calculate conformational entropy from molecular dynamics simulations, as well as discuss a number of practical issues that may arise in such calculations.

Enhanced conformational sampling of carbohydrates by Hamiltonian replica-exchange simulation.

PubMed

Mishra, Sushil Kumar; Kara, Mahmut; Zacharias, Martin; Koca, Jaroslav

2014-01-01

Knowledge of the structure and conformational flexibility of carbohydrates in an aqueous solvent is important to improving our understanding of how carbohydrates function in biological systems. In this study, we extend a variant of the Hamiltonian replica-exchange molecular dynamics (MD) simulation to improve the conformational sampling of saccharides in an explicit solvent. During the simulations, a biasing potential along the glycosidic-dihedral linkage between the saccharide monomer units in an oligomer is applied at various levels along the replica runs to enable effective transitions between various conformations. One reference replica runs under the control of the original force field. The method was tested on disaccharide structures and further validated on biologically relevant blood group B, Lewis X and Lewis A trisaccharides. The biasing potential-based replica-exchange molecular dynamics (BP-REMD) method provided a significantly improved sampling of relevant conformational states compared with standard continuous MD simulations, with modest computational costs. Thus, the proposed BP-REMD approach adds a new dimension to existing carbohydrate conformational sampling approaches by enhancing conformational sampling in the presence of solvent molecules explicitly at relatively low computational cost.

A reduced basis method for molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Vincent-Finley, Rachel Elisabeth

In this dissertation, we develop a method for molecular simulation based on principal component analysis (PCA) of a molecular dynamics trajectory and least squares approximation of a potential energy function. Molecular dynamics (MD) simulation is a computational tool used to study molecular systems as they evolve through time. With respect to protein dynamics, local motions, such as bond stretching, occur within femtoseconds, while rigid body and large-scale motions, occur within a range of nanoseconds to seconds. To capture motion at all levels, time steps on the order of a femtosecond are employed when solving the equations of motion and simulations must continue long enough to capture the desired large-scale motion. To date, simulations of solvated proteins on the order of nanoseconds have been reported. It is typically the case that simulations of a few nanoseconds do not provide adequate information for the study of large-scale motions. Thus, the development of techniques that allow longer simulation times can advance the study of protein function and dynamics. In this dissertation we use principal component analysis (PCA) to identify the dominant characteristics of an MD trajectory and to represent the coordinates with respect to these characteristics. We augment PCA with an updating scheme based on a reduced representation of a molecule and consider equations of motion with respect to the reduced representation. We apply our method to butane and BPTI and compare the results to standard MD simulations of these molecules. Our results indicate that the molecular activity with respect to our simulation method is analogous to that observed in the standard MD simulation with simulations on the order of picoseconds.

Efficient Conformational Sampling in Explicit Solvent Using a Hybrid Replica Exchange Molecular Dynamics Method

DTIC Science & Technology

2011-12-01

REMD while reproducing the energy landscape of explicit solvent simulations . ’ INTRODUCTION Molecular dynamics (MD) simulations of proteins can pro...Mongan, J.; McCammon, J. A. Accelerated molecular dynamics : a promising and efficient simulation method for biomolecules. J. Chem. Phys. 2004, 120 (24...Chemical Theory and Computation ARTICLE (8) Abraham,M. J.; Gready, J. E. Ensuringmixing efficiency of replica- exchange molecular dynamics simulations . J

Physics Computing '92: Proceedings of the 4th International Conference

NASA Astrophysics Data System (ADS)

de Groot, Robert A.; Nadrchal, Jaroslav

1993-04-01

The Table of Contents for the book is as follows: * Preface * INVITED PAPERS * Ab Initio Theoretical Approaches to the Structural, Electronic and Vibrational Properties of Small Clusters and Fullerenes: The State of the Art * Neural Multigrid Methods for Gauge Theories and Other Disordered Systems * Multicanonical Monte Carlo Simulations * On the Use of the Symbolic Language Maple in Physics and Chemistry: Several Examples * Nonequilibrium Phase Transitions in Catalysis and Population Models * Computer Algebra, Symmetry Analysis and Integrability of Nonlinear Evolution Equations * The Path-Integral Quantum Simulation of Hydrogen in Metals * Digital Optical Computing: A New Approach of Systolic Arrays Based on Coherence Modulation of Light and Integrated Optics Technology * Molecular Dynamics Simulations of Granular Materials * Numerical Implementation of a K.A.M. Algorithm * Quasi-Monte Carlo, Quasi-Random Numbers and Quasi-Error Estimates * What Can We Learn from QMC Simulations * Physics of Fluctuating Membranes * Plato, Apollonius, and Klein: Playing with Spheres * Steady States in Nonequilibrium Lattice Systems * CONVODE: A REDUCE Package for Differential Equations * Chaos in Coupled Rotators * Symplectic Numerical Methods for Hamiltonian Problems * Computer Simulations of Surfactant Self Assembly * High-dimensional and Very Large Cellular Automata for Immunological Shape Space * A Review of the Lattice Boltzmann Method * Electronic Structure of Solids in the Self-interaction Corrected Local-spin-density Approximation * Dedicated Computers for Lattice Gauge Theory Simulations * Physics Education: A Survey of Problems and Possible Solutions * Parallel Computing and Electronic-Structure Theory * High Precision Simulation Techniques for Lattice Field Theory * CONTRIBUTED PAPERS * Case Study of Microscale Hydrodynamics Using Molecular Dynamics and Lattice Gas Methods * Computer Modelling of the Structural and Electronic Properties of the Supported Metal Catalysis * Ordered Particle Simulations for Serial and MIMD Parallel Computers * "NOLP" -- Program Package for Laser Plasma Nonlinear Optics * Algorithms to Solve Nonlinear Least Square Problems * Distribution of Hydrogen Atoms in Pd-H Computed by Molecular Dynamics * A Ray Tracing of Optical System for Protein Crystallography Beamline at Storage Ring-SIBERIA-2 * Vibrational Properties of a Pseudobinary Linear Chain with Correlated Substitutional Disorder * Application of the Software Package Mathematica in Generalized Master Equation Method * Linelist: An Interactive Program for Analysing Beam-foil Spectra * GROMACS: A Parallel Computer for Molecular Dynamics Simulations * GROMACS Method of Virial Calculation Using a Single Sum * The Interactive Program for the Solution of the Laplace Equation with the Elimination of Singularities for Boundary Functions * Random-Number Generators: Testing Procedures and Comparison of RNG Algorithms * Micro-TOPIC: A Tokamak Plasma Impurities Code * Rotational Molecular Scattering Calculations * Orthonormal Polynomial Method for Calibrating of Cryogenic Temperature Sensors * Frame-based System Representing Basis of Physics * The Role of Massively Data-parallel Computers in Large Scale Molecular Dynamics Simulations * Short-range Molecular Dynamics on a Network of Processors and Workstations * An Algorithm for Higher-order Perturbation Theory in Radiative Transfer Computations * Hydrostochastics: The Master Equation Formulation of Fluid Dynamics * HPP Lattice Gas on Transputers and Networked Workstations * Study on the Hysteresis Cycle Simulation Using Modeling with Different Functions on Intervals * Refined Pruning Techniques for Feed-forward Neural Networks * Random Walk Simulation of the Motion of Transient Charges in Photoconductors * The Optical Hysteresis in Hydrogenated Amorphous Silicon * Diffusion Monte Carlo Analysis of Modern Interatomic Potentials for He * A Parallel Strategy for Molecular Dynamics Simulations of Polar Liquids on Transputer Arrays * Distribution of Ions Reflected on Rough Surfaces * The Study of Step Density Distribution During Molecular Beam Epitaxy Growth: Monte Carlo Computer Simulation * Towards a Formal Approach to the Construction of Large-scale Scientific Applications Software * Correlated Random Walk and Discrete Modelling of Propagation through Inhomogeneous Media * Teaching Plasma Physics Simulation * A Theoretical Determination of the Au-Ni Phase Diagram * Boson and Fermion Kinetics in One-dimensional Lattices * Computational Physics Course on the Technical University * Symbolic Computations in Simulation Code Development and Femtosecond-pulse Laser-plasma Interaction Studies * Computer Algebra and Integrated Computing Systems in Education of Physical Sciences * Coordinated System of Programs for Undergraduate Physics Instruction * Program Package MIRIAM and Atomic Physics of Extreme Systems * High Energy Physics Simulation on the T_Node * The Chapman-Kolmogorov Equation as Representation of Huygens' Principle and the Monolithic Self-consistent Numerical Modelling of Lasers * Authoring System for Simulation Developments * Molecular Dynamics Study of Ion Charge Effects in the Structure of Ionic Crystals * A Computational Physics Introductory Course * Computer Calculation of Substrate Temperature Field in MBE System * Multimagnetical Simulation of the Ising Model in Two and Three Dimensions * Failure of the CTRW Treatment of the Quasicoherent Excitation Transfer * Implementation of a Parallel Conjugate Gradient Method for Simulation of Elastic Light Scattering * Algorithms for Study of Thin Film Growth * Algorithms and Programs for Physics Teaching in Romanian Technical Universities * Multicanonical Simulation of 1st order Transitions: Interface Tension of the 2D 7-State Potts Model * Two Numerical Methods for the Calculation of Periodic Orbits in Hamiltonian Systems * Chaotic Behavior in a Probabilistic Cellular Automata? * Wave Optics Computing by a Networked-based Vector Wave Automaton * Tensor Manipulation Package in REDUCE * Propagation of Electromagnetic Pulses in Stratified Media * The Simple Molecular Dynamics Model for the Study of Thermalization of the Hot Nucleon Gas * Electron Spin Polarization in PdCo Alloys Calculated by KKR-CPA-LSD Method * Simulation Studies of Microscopic Droplet Spreading * A Vectorizable Algorithm for the Multicolor Successive Overrelaxation Method * Tetragonality of the CuAu I Lattice and Its Relation to Electronic Specific Heat and Spin Susceptibility * Computer Simulation of the Formation of Metallic Aggregates Produced by Chemical Reactions in Aqueous Solution * Scaling in Growth Models with Diffusion: A Monte Carlo Study * The Nucleus as the Mesoscopic System * Neural Network Computation as Dynamic System Simulation * First-principles Theory of Surface Segregation in Binary Alloys * Data Smooth Approximation Algorithm for Estimating the Temperature Dependence of the Ice Nucleation Rate * Genetic Algorithms in Optical Design * Application of 2D-FFT in the Study of Molecular Exchange Processes by NMR * Advanced Mobility Model for Electron Transport in P-Si Inversion Layers * Computer Simulation for Film Surfaces and its Fractal Dimension * Parallel Computation Techniques and the Structure of Catalyst Surfaces * Educational SW to Teach Digital Electronics and the Corresponding Text Book * Primitive Trinomials (Mod 2) Whose Degree is a Mersenne Exponent * Stochastic Modelisation and Parallel Computing * Remarks on the Hybrid Monte Carlo Algorithm for the ∫4 Model * An Experimental Computer Assisted Workbench for Physics Teaching * A Fully Implicit Code to Model Tokamak Plasma Edge Transport * EXPFIT: An Interactive Program for Automatic Beam-foil Decay Curve Analysis * Mapping Technique for Solving General, 1-D Hamiltonian Systems * Freeway Traffic, Cellular Automata, and Some (Self-Organizing) Criticality * Photonuclear Yield Analysis by Dynamic Programming * Incremental Representation of the Simply Connected Planar Curves * Self-convergence in Monte Carlo Methods * Adaptive Mesh Technique for Shock Wave Propagation * Simulation of Supersonic Coronal Streams and Their Interaction with the Solar Wind * The Nature of Chaos in Two Systems of Ordinary Nonlinear Differential Equations * Considerations of a Window-shopper * Interpretation of Data Obtained by RTP 4-Channel Pulsed Radar Reflectometer Using a Multi Layer Perceptron * Statistics of Lattice Bosons for Finite Systems * Fractal Based Image Compression with Affine Transformations * Algorithmic Studies on Simulation Codes for Heavy-ion Reactions * An Energy-Wise Computer Simulation of DNA-Ion-Water Interactions Explains the Abnormal Structure of Poly[d(A)]:Poly[d(T)] * Computer Simulation Study of Kosterlitz-Thouless-Like Transitions * Problem-oriented Software Package GUN-EBT for Computer Simulation of Beam Formation and Transport in Technological Electron-Optical Systems * Parallelization of a Boundary Value Solver and its Application in Nonlinear Dynamics * The Symbolic Classification of Real Four-dimensional Lie Algebras * Short, Singular Pulses Generation by a Dye Laser at Two Wavelengths Simultaneously * Quantum Monte Carlo Simulations of the Apex-Oxygen-Model * Approximation Procedures for the Axial Symmetric Static Einstein-Maxwell-Higgs Theory * Crystallization on a Sphere: Parallel Simulation on a Transputer Network * FAMULUS: A Software Product (also) for Physics Education * MathCAD vs. FAMULUS -- A Brief Comparison * First-principles Dynamics Used to Study Dissociative Chemisorption * A Computer Controlled System for Crystal Growth from Melt * A Time Resolved Spectroscopic Method for Short Pulsed Particle Emission * Green's Function Computation in Radiative Transfer Theory * Random Search Optimization Technique for One-criteria and Multi-criteria Problems * Hartley Transform Applications to Thermal Drift Elimination in Scanning Tunneling Microscopy * Algorithms of Measuring, Processing and Interpretation of Experimental Data Obtained with Scanning Tunneling Microscope * Time-dependent Atom-surface Interactions * Local and Global Minima on Molecular Potential Energy Surfaces: An Example of N3 Radical * Computation of Bifurcation Surfaces * Symbolic Computations in Quantum Mechanics: Energies in Next-to-solvable Systems * A Tool for RTP Reactor and Lamp Field Design * Modelling of Particle Spectra for the Analysis of Solid State Surface * List of Participants

Multiscale computational models in physical systems biology of intracellular trafficking.

PubMed

Tourdot, Richard W; Bradley, Ryan P; Ramakrishnan, Natesan; Radhakrishnan, Ravi

2014-10-01

In intracellular trafficking, a definitive understanding of the interplay between protein binding and membrane morphology remains incomplete. The authors describe a computational approach by integrating coarse-grained molecular dynamics (CGMD) simulations with continuum Monte Carlo (CM) simulations of the membrane to study protein-membrane interactions and the ensuing membrane curvature. They relate the curvature field strength discerned from the molecular level to its effect at the cellular length-scale. They perform thermodynamic integration on the CM model to describe the free energy landscape of vesiculation in clathrin-mediated endocytosis. The method presented here delineates membrane morphologies and maps out the free energy changes associated with membrane remodeling due to varying coat sizes, coat curvature strengths, membrane bending rigidities, and tensions; furthermore several constraints on mechanisms underlying clathrin-mediated endocytosis have also been identified, Their CGMD simulations have revealed the importance of PIP2 for stable binding of proteins essential for curvature induction in the bilayer and have provided a molecular basis for the positive curvature induction by the epsin N-terminal homology (EIMTH) domain. Calculation of the free energy landscape for vesicle budding has identified the critical size and curvature strength of a clathrin coat required for nucleation and stabilisation of a mature vesicle.

Evaluation of synthetic linear motor-molecule actuation energetics

PubMed Central

Brough, Branden; Northrop, Brian H.; Schmidt, Jacob J.; Tseng, Hsian-Rong; Houk, Kendall N.; Stoddart, J. Fraser; Ho, Chih-Ming

2006-01-01

By applying atomic force microscope (AFM)-based force spectroscopy together with computational modeling in the form of molecular force-field simulations, we have determined quantitatively the actuation energetics of a synthetic motor-molecule. This multidisciplinary approach was performed on specifically designed, bistable, redox-controllable [2]rotaxanes to probe the steric and electrostatic interactions that dictate their mechanical switching at the single-molecule level. The fusion of experimental force spectroscopy and theoretical computational modeling has revealed that the repulsive electrostatic interaction, which is responsible for the molecular actuation, is as high as 65 kcal·mol−1, a result that is supported by ab initio calculations. PMID:16735470

Quantum ring-polymer contraction method: Including nuclear quantum effects at no additional computational cost in comparison to ab initio molecular dynamics

NASA Astrophysics Data System (ADS)

John, Christopher; Spura, Thomas; Habershon, Scott; Kühne, Thomas D.

2016-04-01

We present a simple and accurate computational method which facilitates ab initio path-integral molecular dynamics simulations, where the quantum-mechanical nature of the nuclei is explicitly taken into account, at essentially no additional computational cost in comparison to the corresponding calculation using classical nuclei. The predictive power of the proposed quantum ring-polymer contraction method is demonstrated by computing various static and dynamic properties of liquid water at ambient conditions using density functional theory. This development will enable routine inclusion of nuclear quantum effects in ab initio molecular dynamics simulations of condensed-phase systems.

Molecular-level simulations of turbulence and its decay

DOE PAGES

Gallis, M. A.; Bitter, N. P.; Koehler, T. P.; ...

2017-02-08

Here, we provide the first demonstration that molecular-level methods based on gas kinetic theory and molecular chaos can simulate turbulence and its decay. The direct simulation Monte Carlo (DSMC) method, a molecular-level technique for simulating gas flows that resolves phenomena from molecular to hydrodynamic (continuum) length scales, is applied to simulate the Taylor-Green vortex flow. The DSMC simulations reproduce the Kolmogorov –5/3 law and agree well with the turbulent kinetic energy and energy dissipation rate obtained from direct numerical simulation of the Navier-Stokes equations using a spectral method. This agreement provides strong evidence that molecular-level methods for gases can bemore » used to investigate turbulent flows quantitatively.« less

XaNSoNS: GPU-accelerated simulator of diffraction patterns of nanoparticles

NASA Astrophysics Data System (ADS)

Neverov, V. S.

XaNSoNS is an open source software with GPU support, which simulates X-ray and neutron 1D (or 2D) diffraction patterns and pair-distribution functions (PDF) for amorphous or crystalline nanoparticles (up to ∼107 atoms) of heterogeneous structural content. Among the multiple parameters of the structure the user may specify atomic displacements, site occupancies, molecular displacements and molecular rotations. The software uses general equations nonspecific to crystalline structures to calculate the scattering intensity. It supports four major standards of parallel computing: MPI, OpenMP, Nvidia CUDA and OpenCL, enabling it to run on various architectures, from CPU-based HPCs to consumer-level GPUs.

Computer Simulation of the Forces Acting on a Submerged Polystyrene Probe as it Approaches the Succinonitrile Melt-Solid Interface

NASA Technical Reports Server (NTRS)

Bune, Andris V.; Kaukler, William; Whitaker, Ann (Technical Monitor)

2001-01-01

A Modeling approach to simulate both mesoscale and microscopic forces acting in a typical AFM experiment is presented. A mesoscale level interaction between the cantilever tip and the sample surface is primarily described by the balance of attractive Van der Waals and repulsive forces. Ultimately, the goal is to measure the forces between a particle and the crystal-melt interface. Two modes of AFM operation are considered in this paper - a stationary and a "tapping" one. The continuous mechanics approach to model tip-surface interaction is presented. At microscopic levels, tip contamination and details of tip-surface interaction are modeled using a molecular dynamics approach for the case of polystyrene - succinonitrile contact. Integration of the mesoscale model with a molecular dynamic model is discussed.

Developing model asphalt systems using molecular simulation : final model.

DOT National Transportation Integrated Search

2009-09-01

Computer based molecular simulations have been used towards developing simple mixture compositions whose : physical properties resemble those of real asphalts. First, Monte Carlo simulations with the OPLS all-atom force : field were used to predict t...

A parametric study of surface roughness and bonding mechanisms of aluminum alloys with epoxies: a molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Timilsina, Rajendra; Termaath, Stephanie

The marine environment is highly aggressive towards most materials. However, aluminium-magnesium alloys (Al-Mg, specifically, 5xxx series) have exceptionally long service life in such aggressive marine environments. For instance, an Al-Mg alloy, AA5083, is extensively used in naval structures because of its good mechanical strength, formability, seawater corrosion resistance and weldability. However, bonding mechanisms of these alloys with epoxies in a rough surface environment are not fully understood yet. It requires a rigorous investigation at molecular or atomic levels. We performed a molecular dynamics simulation to study an adherend surface preparation and surface bonding mechanisms of Al-Mg alloy (AA5083) with different epoxies by developing several computer models. Various distributions of surface roughness are introduced in the models and performed molecular dynamics simulations. Formation of a beta phase (Al3Mg2) , microstructures, bonding energies at the interface, bonding strengths and durability are investigated. Office of Naval Research.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

DOE PAGES

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; ...

2017-11-27

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scalingmore » laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.« less

Assessment of Molecular Modeling & Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2002-01-03

This report reviews the development and applications of molecular and materials modeling in Europe and Japan in comparison to those in the United States. Topics covered include computational quantum chemistry, molecular simulations by molecular dynamics and Monte Carlo methods, mesoscale modeling of material domains, molecular-structure/macroscale property correlations like QSARs and QSPRs, and related information technologies like informatics and special-purpose molecular-modeling computers. The panel's findings include the following: The United States leads this field in many scientific areas. However, Canada has particular strengths in DFT methods and homogeneous catalysis; Europe in heterogeneous catalysis, mesoscale, and materials modeling; and Japan in materialsmore » modeling and special-purpose computing. Major government-industry initiatives are underway in Europe and Japan, notably in multi-scale materials modeling and in development of chemistry-capable ab-initio molecular dynamics codes.« less

A Series of Molecular Dynamics and Homology Modeling Computer Labs for an Undergraduate Molecular Modeling Course

ERIC Educational Resources Information Center

Elmore, Donald E.; Guayasamin, Ryann C.; Kieffer, Madeleine E.

2010-01-01

As computational modeling plays an increasingly central role in biochemical research, it is important to provide students with exposure to common modeling methods in their undergraduate curriculum. This article describes a series of computer labs designed to introduce undergraduate students to energy minimization, molecular dynamics simulations,…

Polymorphic phase transitions: Macroscopic theory and molecular simulation.

PubMed

Anwar, Jamshed; Zahn, Dirk

2017-08-01

Transformations in the solid state are of considerable interest, both for fundamental reasons and because they underpin important technological applications. The interest spans a wide spectrum of disciplines and application domains. For pharmaceuticals, a common issue is unexpected polymorphic transformation of the drug or excipient during processing or on storage, which can result in product failure. A more ambitious goal is that of exploiting the advantages of metastable polymorphs (e.g. higher solubility and dissolution rate) while ensuring their stability with respect to solid state transformation. To address these issues and to advance technology, there is an urgent need for significant insights that can only come from a detailed molecular level understanding of the involved processes. Whilst experimental approaches at best yield time- and space-averaged structural information, molecular simulation offers unprecedented, time-resolved molecular-level resolution of the processes taking place. This review aims to provide a comprehensive and critical account of state-of-the-art methods for modelling polymorph stability and transitions between solid phases. This is flanked by revisiting the associated macroscopic theoretical framework for phase transitions, including their classification, proposed molecular mechanisms, and kinetics. The simulation methods are presented in tutorial form, focusing on their application to phase transition phenomena. We describe molecular simulation studies for crystal structure prediction and polymorph screening, phase coexistence and phase diagrams, simulations of crystal-crystal transitions of various types (displacive/martensitic, reconstructive and diffusive), effects of defects, and phase stability and transitions at the nanoscale. Our selection of literature is intended to illustrate significant insights, concepts and understanding, as well as the current scope of using molecular simulations for understanding polymorphic transitions in an accessible way, rather than claiming completeness. With exciting prospects in both simulation methods development and enhancements in computer hardware, we are on the verge of accessing an unprecedented capability for designing and developing dosage forms and drug delivery systems in silico, including tackling challenges in polymorph control on a rational basis. Copyright © 2017 Elsevier B.V. All rights reserved.

myPresto/omegagene: a GPU-accelerated molecular dynamics simulator tailored for enhanced conformational sampling methods with a non-Ewald electrostatic scheme.

PubMed

Kasahara, Kota; Ma, Benson; Goto, Kota; Dasgupta, Bhaskar; Higo, Junichi; Fukuda, Ikuo; Mashimo, Tadaaki; Akiyama, Yutaka; Nakamura, Haruki

2016-01-01

Molecular dynamics (MD) is a promising computational approach to investigate dynamical behavior of molecular systems at the atomic level. Here, we present a new MD simulation engine named "myPresto/omegagene" that is tailored for enhanced conformational sampling methods with a non-Ewald electrostatic potential scheme. Our enhanced conformational sampling methods, e.g. , the virtual-system-coupled multi-canonical MD (V-McMD) method, replace a multi-process parallelized run with multiple independent runs to avoid inter-node communication overhead. In addition, adopting the non-Ewald-based zero-multipole summation method (ZMM) makes it possible to eliminate the Fourier space calculations altogether. The combination of these state-of-the-art techniques realizes efficient and accurate calculations of the conformational ensemble at an equilibrium state. By taking these advantages, myPresto/omegagene is specialized for the single process execution with Graphics Processing Unit (GPU). We performed benchmark simulations for the 20-mer peptide, Trp-cage, with explicit solvent. One of the most thermodynamically stable conformations generated by the V-McMD simulation is very similar to an experimentally solved native conformation. Furthermore, the computation speed is four-times faster than that of our previous simulation engine, myPresto/psygene-G. The new simulator, myPresto/omegagene, is freely available at the following URLs: http://www.protein.osaka-u.ac.jp/rcsfp/pi/omegagene/ and http://presto.protein.osaka-u.ac.jp/myPresto4/.

Cavity hydration dynamics in cytochrome c oxidase and functional implications

PubMed Central

Son, Chang Yun; Cui, Qiang

2017-01-01

Cytochrome c oxidase (CcO) is a transmembrane protein that uses the free energy of O2 reduction to generate the proton concentration gradient across the membrane. The regulation of competitive proton transfer pathways has been established to be essential to the vectorial transport efficiency of CcO, yet the underlying mechanism at the molecular level remains lacking. Recent studies have highlighted the potential importance of hydration-level change in an internal cavity that connects the proton entrance channel, the site of O2 reduction, and the putative proton exit route. In this work, we use atomistic molecular dynamics simulations to investigate the energetics and timescales associated with the volume fluctuation and hydration-level change in this central cavity. Extensive unrestrained molecular dynamics simulations (accumulatively ∼4 μs) and free energy computations for different chemical states of CcO support a model in which the volume and hydration level of the cavity are regulated by the protonation state of a propionate group of heme a3 and, to a lesser degree, the redox state of heme a and protonation state of Glu286. Markov-state model analysis of ∼2-μs trajectories suggests that hydration-level change occurs on the timescale of 100–200 ns before the proton-loading site is protonated. The computed energetic and kinetic features for the cavity wetting transition suggest that reversible hydration-level change of the cavity can indeed be a key factor that regulates the branching of proton transfer events and therefore contributes to the vectorial efficiency of proton transport. PMID:28973914

Visualizing functional motions of membrane transporters with molecular dynamics simulations.

PubMed

Shaikh, Saher A; Li, Jing; Enkavi, Giray; Wen, Po-Chao; Huang, Zhijian; Tajkhorshid, Emad

2013-01-29

Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins.

Visualizing Functional Motions of Membrane Transporters with Molecular Dynamics Simulations

PubMed Central

2013-01-01

Computational modeling and molecular simulation techniques have become an integral part of modern molecular research. Various areas of molecular sciences continue to benefit from, indeed rely on, the unparalleled spatial and temporal resolutions offered by these technologies, to provide a more complete picture of the molecular problems at hand. Because of the continuous development of more efficient algorithms harvesting ever-expanding computational resources, and the emergence of more advanced and novel theories and methodologies, the scope of computational studies has expanded significantly over the past decade, now including much larger molecular systems and far more complex molecular phenomena. Among the various computer modeling techniques, the application of molecular dynamics (MD) simulation and related techniques has particularly drawn attention in biomolecular research, because of the ability of the method to describe the dynamical nature of the molecular systems and thereby to provide a more realistic representation, which is often needed for understanding fundamental molecular properties. The method has proven to be remarkably successful in capturing molecular events and structural transitions highly relevant to the function and/or physicochemical properties of biomolecular systems. Herein, after a brief introduction to the method of MD, we use a number of membrane transport proteins studied in our laboratory as examples to showcase the scope and applicability of the method and its power in characterizing molecular motions of various magnitudes and time scales that are involved in the function of this important class of membrane proteins. PMID:23298176

Molecular Dynamics Analysis of Lysozyme Protein in Ethanol-Water Mixed Solvent Environment

NASA Astrophysics Data System (ADS)

Ochije, Henry Ikechukwu

Effect of protein-solvent interaction on the protein structure is widely studied using both experimental and computational techniques. Despite such extensive studies molecular level understanding of proteins and some simple solvents is still not fully understood. This work focuses on detailed molecular dynamics simulations to study of solvent effect on lysozyme protein, using water, alcohol and different concentrations of water-alcohol mixtures as solvents. The lysozyme protein structure in water, alcohol and alcohol-water mixture (0-12% alcohol) was studied using GROMACS molecular dynamics simulation code. Compared to water environment, the lysozome structure showed remarkable changes in solvents with increasing alcohol concentration. In particular, significant changes were observed in the protein secondary structure involving alpha helices. The influence of alcohol on the lysozyme protein was investigated by studying thermodynamic and structural properties. With increasing ethanol concentration we observed a systematic increase in total energy, enthalpy, root mean square deviation (RMSD), and radius of gyration. a polynomial interpolation approach. Using the resulting polynomial equation, we could determine above quantities for any intermediate alcohol percentage. In order to validate this approach, we selected an intermediate ethanol percentage and carried out full MD simulation. The results from MD simulation were in reasonably good agreement with that obtained using polynomial approach. Hence, the polynomial approach based method proposed here eliminates the need for computationally intensive full MD analysis for the concentrations within the range (0-12%) studied in this work.

Microscopic Structure and Solubility Predictions of Multifunctional Solids in Supercritical Carbon Dioxide: A Molecular Simulation Study.

PubMed

Noroozi, Javad; Paluch, Andrew S

2017-02-23

Molecular dynamics simulations were employed to both estimate the solubility of nonelectrolyte solids, such as acetanilide, acetaminophen, phenacetin, methylparaben, and lidocaine, in supercritical carbon dioxide and understand the underlying molecular-level driving forces. The solubility calculations involve the estimation of the solute's limiting activity coefficient, which may be computed using conventional staged free-energy calculations. For the case of lidocaine, wherein the infinite dilution approximation is not appropriate, we demonstrate how the activity coefficient at finite concentrations may be estimated without additional effort using the dilute solution approximation and how this may be used to further understand the solvation process. Combining with experimental pure-solid properties, namely, the normal melting point and enthalpy of fusion, solubilities were estimated. The results are in good quantitative agreement with available experimental data, suggesting that molecular simulations may be a powerful tool for understanding supercritical processes and the design of carbon dioxide-philic molecular systems. Structural analyses were performed to shed light on the microscopic details of the solvation of different functional groups by carbon dioxide and the observed solubility trends.

From in silica to in silico: retention thermodynamics at solid-liquid interfaces.

PubMed

El Hage, Krystel; Bemish, Raymond J; Meuwly, Markus

2018-06-28

The dynamics of solvated molecules at the solid/liquid interface is essential for a molecular-level understanding for the solution thermodynamics in reversed phase liquid chromatography (RPLC). The heterogeneous nature of the systems and the competing intermolecular interactions makes solute retention in RPLC a surprisingly challenging problem which benefits greatly from modelling at atomistic resolution. However, the quality of the underlying computational model needs to be sufficiently accurate to provide a realistic description of the energetics and dynamics of systems, especially for solution-phase simulations. Here, the retention thermodynamics and the retention mechanism of a range of benzene-derivatives in C18 stationary-phase chains in contact with water/methanol mixtures is studied using point charge (PC) and multipole (MTP) electrostatic models. The results demonstrate that free energy simulations with a faithful MTP representation of the computational model provide quantitative and molecular level insight into the thermodynamics of adsorption/desorption in chromatographic systems while a conventional PC representation fails in doing so. This provides a rational basis to develop more quantitative and validated models for the optimization of separation systems.

Inelastic neutron scattering of large molecular systems: The case of the original benzylic amide [2]catenane

NASA Astrophysics Data System (ADS)

Caciuffo, Roberto; Esposti, Alessandra Degli; Deleuze, Michael S.; Leigh, David A.; Murphy, Aden; Paci, Barbara; Parker, Stewart F.; Zerbetto, Francesco

1998-12-01

The inelastic neutron scattering (INS) spectrum of the original benzylic amide [2]catenane is recorded and simulated by a semiempirical quantum chemical procedure coupled with the most comprehensive approach available to date, the CLIMAX program. The successful simulation of the spectrum indicates that the modified neglect of differential overlap (MNDO) model can reproduce the intramolecular vibrations of a molecular system as large as a catenane (136 atoms). Because of the computational costs involved and some numerical instabilities, a less expensive approach is attempted which involves the molecular mechanics-based calculation of the INS response in terms of the most basic formulation for the scattering activity. The encouraging results obtained validate the less computationally intensive procedure and allow its extension to the calculation of the INS spectrum for a second, theoretical, co-conformer, which, although structurally and energetically reasonable, is not, in fact, found in the solid state. The second structure was produced by a Monte Carlo simulated annealing method run in the conformational space (a procedure that would have been prohibitively expensive at the semiempirical level) and is characterized by a higher degree of intramolecular hydrogen bonding than the x-ray structure. The two alternative structures yield different simulated spectra, only one of which, the authentic one, is compatible with the experimental data. Comparison of the two simulated and experimental spectra affords the identification of an inelastic neutron scattering spectral signature of the correct hydrogen bonding motif in the region slightly above 700 cm-1. The study illustrates that combinations of simulated INS data and experimental results can be successfully used to discriminate between different proposed structures or possible hydrogen bonding motifs in large functional molecular systems.

Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870

Melittin Aggregation in Aqueous Solutions: Insight from Molecular Dynamics Simulations.

PubMed

Liao, Chenyi; Esai Selvan, Myvizhi; Zhao, Jun; Slimovitch, Jonathan L; Schneebeli, Severin T; Shelley, Mee; Shelley, John C; Li, Jianing

2015-08-20

Melittin is a natural peptide that aggregates in aqueous solutions with paradigmatic monomer-to-tetramer and coil-to-helix transitions. Since little is known about the molecular mechanisms of melittin aggregation in solution, we simulated its self-aggregation process under various conditions. After confirming the stability of a melittin tetramer in solution, we observed—for the first time in atomistic detail—that four separated melittin monomers aggregate into a tetramer. Our simulated dependence of melittin aggregation on peptide concentration, temperature, and ionic strength is in good agreement with prior experiments. We propose that melittin mainly self-aggregates via a mechanism involving the sequential addition of monomers, which is supported by both qualitative and quantitative evidence obtained from unbiased and metadynamics simulations. Moreover, by combining computer simulations and a theory of the electrical double layer, we provide evidence to suggest why melittin aggregation in solution likely stops at the tetramer, rather than forming higher-order oligomers. Overall, our study not only explains prior experimental results at the molecular level but also provides quantitative mechanistic information that may guide the engineering of melittin for higher efficacy and safety.

Sampling Molecular Conformers in Solution with Quantum Mechanical Accuracy at a Nearly Molecular-Mechanics Cost.

PubMed

Rosa, Marta; Micciarelli, Marco; Laio, Alessandro; Baroni, Stefano

2016-09-13

We introduce a method to evaluate the relative populations of different conformers of molecular species in solution, aiming at quantum mechanical accuracy, while keeping the computational cost at a nearly molecular-mechanics level. This goal is achieved by combining long classical molecular-dynamics simulations to sample the free-energy landscape of the system, advanced clustering techniques to identify the most relevant conformers, and thermodynamic perturbation theory to correct the resulting populations, using quantum-mechanical energies from density functional theory. A quantitative criterion for assessing the accuracy thus achieved is proposed. The resulting methodology is demonstrated in the specific case of cyanin (cyanidin-3-glucoside) in water solution.

Computational investigation of the conformational profile of the four stereomers of Ac-L-Pro-c3Phe-NHMe (c3Phe= 2,3-methanophenylalanine).

PubMed

Rodriguez, Alejandro; Canto, Josep; Corcho, Francesc J; Perez, Juan J

2009-01-01

The present report regards a computational study aimed at assessing the conformational profile of the four stereoisomers of the peptide Ace-Pro-c3Phe-NMe, previously reported to exhibit beta-turn structures in dichloromethane with different type I/type II beta-turn profiles. Molecular systems were represented at the molecular mechanics level using the parm96 parameterization of the AMBER force field. Calculations were carried out in dichloromethane using an implicit solvent approach. Characterization of the conformational features of the peptide analogs was carried out using simulated annealing (SA), molecular dynamics (MD) and replica exchange molecular dynamics (REMD). Present results show that MD calculations do not provide a reasonable sampling after 300 ns. In contrast, both SA and REMD provide similar results and agree well with experimental observations. Copyright 2009 Wiley Periodicals, Inc.

Computer Simulation of Protein-Protein and Protein-Peptide Interactions

DTIC Science & Technology

1983-12-08

a full molecular dynamic z simulation is performed, with resulting dipolar re - laxation. However, this is prohibitive when a large . number of...1993 Dr. Mike Marron Program Manager Molecular Biology Office of Naval Research 800 N. Quincy Street Arlington, VA 22217 Dear Mike, Here is the...rztnbutior is unLi--ited. , 93-30630 98 12 � 12/08/93 01/0/92-;03/31/93: Final Report, Computer Simulation of Protein-Protein and Protein-Peptide

Simulation of the M13 life cycle I: Assembly of a genetically-structured deterministic chemical kinetic simulation.

PubMed

Smeal, Steven W; Schmitt, Margaret A; Pereira, Ronnie Rodrigues; Prasad, Ashok; Fisk, John D

2017-01-01

To expand the quantitative, systems level understanding and foster the expansion of the biotechnological applications of the filamentous bacteriophage M13, we have unified the accumulated quantitative information on M13 biology into a genetically-structured, experimentally-based computational simulation of the entire phage life cycle. The deterministic chemical kinetic simulation explicitly includes the molecular details of DNA replication, mRNA transcription, protein translation and particle assembly, as well as the competing protein-protein and protein-nucleic acid interactions that control the timing and extent of phage production. The simulation reproduces the holistic behavior of M13, closely matching experimentally reported values of the intracellular levels of phage species and the timing of events in the M13 life cycle. The computational model provides a quantitative description of phage biology, highlights gaps in the present understanding of M13, and offers a framework for exploring alternative mechanisms of regulation in the context of the complete M13 life cycle. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards the simulation of molecular collisions with a superconducting quantum computer

NASA Astrophysics Data System (ADS)

Geller, Michael

2013-05-01

I will discuss the prospects for the use of large-scale, error-corrected quantum computers to simulate complex quantum dynamics such as molecular collisions. This will likely require millions qubits. I will also discuss an alternative approach [M. R. Geller et al., arXiv:1210.5260] that is ideally suited for today's superconducting circuits, which uses the single-excitation subspace (SES) of a system of n tunably coupled qubits. The SES method allows many operations in the unitary group SU(n) to be implemented in a single step, bypassing the need for elementary gates, thereby making large computations possible without error correction. The method enables universal quantum simulation, including simulation of the time-dependent Schrodinger equation, and we argue that a 1000-qubit SES processor should be capable of achieving quantum speedup relative to a petaflop supercomputer. We speculate on the utility and practicality of such a simulator for atomic and molecular collision physics. Work supported by the US National Science Foundation CDI program.

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors.

PubMed

Glowacki, David R; O'Connor, Michael; Calabró, Gaetano; Price, James; Tew, Philip; Mitchell, Thomas; Hyde, Joseph; Tew, David P; Coughtrie, David J; McIntosh-Smith, Simon

2014-01-01

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude.

Teaching Molecular Biology with Microcomputers.

ERIC Educational Resources Information Center

Reiss, Rebecca; Jameson, David

1984-01-01

Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)

Computational Nanotechnology at NASA Ames Research Center, 1996

NASA Technical Reports Server (NTRS)

Globus, Al; Bailey, David; Langhoff, Steve; Pohorille, Andrew; Levit, Creon; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Some forms of nanotechnology appear to have enormous potential to improve aerospace and computer systems; computational nanotechnology, the design and simulation of programmable molecular machines, is crucial to progress. NASA Ames Research Center has begun a computational nanotechnology program including in-house work, external research grants, and grants of supercomputer time. Four goals have been established: (1) Simulate a hypothetical programmable molecular machine replicating itself and building other products. (2) Develop molecular manufacturing CAD (computer aided design) software and use it to design molecular manufacturing systems and products of aerospace interest, including computer components. (3) Characterize nanotechnologically accessible materials of aerospace interest. Such materials may have excellent strength and thermal properties. (4) Collaborate with experimentalists. Current in-house activities include: (1) Development of NanoDesign, software to design and simulate a nanotechnology based on functionalized fullerenes. Early work focuses on gears. (2) A design for high density atomically precise memory. (3) Design of nanotechnology systems based on biology. (4) Characterization of diamonoid mechanosynthetic pathways. (5) Studies of the laplacian of the electronic charge density to understand molecular structure and reactivity. (6) Studies of entropic effects during self-assembly. Characterization of properties of matter for clusters up to sizes exhibiting bulk properties. In addition, the NAS (NASA Advanced Supercomputing) supercomputer division sponsored a workshop on computational molecular nanotechnology on March 4-5, 1996 held at NASA Ames Research Center. Finally, collaborations with Bill Goddard at CalTech, Ralph Merkle at Xerox Parc, Don Brenner at NCSU (North Carolina State University), Tom McKendree at Hughes, and Todd Wipke at UCSC are underway.

NREL Receives Editors' Choice Awards for Supercomputer Research | News |

Science.gov Websites

function," Beckham said. "We followed up these molecular simulations with experimental work to Award. The awards recognize outstanding research in computational molecular science and engineering Mechanisms of Cellulose-Active Enzymes Using Molecular Simulation" at the AIChE 2014 Annual Meeting

Transient state kinetics tutorial using the kinetics simulation program, KINSIM.

PubMed Central

Wachsstock, D H; Pollard, T D

1994-01-01

This article provides an introduction to a computer tutorial on transient state kinetics. The tutorial uses our Macintosh version of the computer program, KINSIM, that calculates the time course of reactions. KINSIM is also available for other popular computers. This program allows even those investigators not mathematically inclined to evaluate the rate constants for the transitions between the intermediates in any reaction mechanism. These rate constants are one of the insights that are essential for understanding how biochemical processes work at the molecular level. The approach is applicable not only to enzyme reactions but also to any other type of process of interest to biophysicists, cell biologists, and molecular biologists in which concentrations change with time. In principle, the same methods could be used to characterize time-dependent, large-scale processes in ecology and evolution. Completion of the tutorial takes students 6-10 h. This investment is rewarded by a deep understanding of the principles of chemical kinetics and familiarity with the tools of kinetics simulation as an approach to solve everyday problems in the laboratory. PMID:7811941

Better, Cheaper, Faster Molecular Dynamics

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; DeVincenzi, Donald L. (Technical Monitor)

2001-01-01

Recent, revolutionary progress in genomics and structural, molecular and cellular biology has created new opportunities for molecular-level computer simulations of biological systems by providing vast amounts of data that require interpretation. These opportunities are further enhanced by the increasing availability of massively parallel computers. For many problems, the method of choice is classical molecular dynamics (iterative solving of Newton's equations of motion). It focuses on two main objectives. One is to calculate the relative stability of different states of the system. A typical problem that has' such an objective is computer-aided drug design. Another common objective is to describe evolution of the system towards a low energy (possibly the global minimum energy), "native" state. Perhaps the best example of such a problem is protein folding. Both types of problems share the same difficulty. Often, different states of the system are separated by high energy barriers, which implies that transitions between these states are rare events. This, in turn, can greatly impede exploration of phase space. In some instances this can lead to "quasi non-ergodicity", whereby a part of phase space is inaccessible on time scales of the simulation. To overcome this difficulty and to extend molecular dynamics to "biological" time scales (millisecond or longer) new physical formulations and new algorithmic developments are required. To be efficient they should account for natural limitations of multi-processor computer architecture. I will present work along these lines done in my group. In particular, I will focus on a new approach to calculating the free energies (stability) of different states and to overcoming "the curse of rare events". I will also discuss algorithmic improvements to multiple time step methods and to the treatment of slowly decaying, log-ranged, electrostatic effects.

Final report for the DOE Early Career Award #DE-SC0003912

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jayaraman, Arthi

This DoE supported early career project was aimed at developing computational models, theory and simulation methods that would be then be used to predict assembly and morphology in polymer nanocomposites. In particular, the focus was on composites in active layers of devices, containing conducting polymers that act as electron donors and nanoscale additives that act as electron acceptors. During the course this work, we developed the first of its kind molecular models to represent conducting polymers enabling simulations at the experimentally relevant length and time scales. By comparison with experimentally observed morphologies we validated these models. Furthermore, using these modelsmore » and molecular dynamics simulations on graphical processing units (GPUs) we predicted the molecular level design features in polymers and additive that lead to morphologies with optimal features for charge carrier behavior in solar cells. Additionally, we also predicted computationally new design rules for better dispersion of additives in polymers that have been confirmed through experiments. Achieving dispersion in polymer nanocomposites is valuable to achieve controlled macroscopic properties of the composite. The results obtained during the course of this DOE funded project enables optimal design of higher efficiency organic electronic and photovoltaic devices and improve every day life with engineering of these higher efficiency devices.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Animesh, E-mail: animesh@zedat.fu-berlin.de; Delle Site, Luigi, E-mail: dellesite@fu-berlin.de

Quantum effects due to the spatial delocalization of light atoms are treated in molecular simulation via the path integral technique. Among several methods, Path Integral (PI) Molecular Dynamics (MD) is nowadays a powerful tool to investigate properties induced by spatial delocalization of atoms; however, computationally this technique is very demanding. The above mentioned limitation implies the restriction of PIMD applications to relatively small systems and short time scales. One of the possible solutions to overcome size and time limitation is to introduce PIMD algorithms into the Adaptive Resolution Simulation Scheme (AdResS). AdResS requires a relatively small region treated at pathmore » integral level and embeds it into a large molecular reservoir consisting of generic spherical coarse grained molecules. It was previously shown that the realization of the idea above, at a simple level, produced reasonable results for toy systems or simple/test systems like liquid parahydrogen. Encouraged by previous results, in this paper, we show the simulation of liquid water at room conditions where AdResS, in its latest and more accurate Grand-Canonical-like version (GC-AdResS), is merged with two of the most relevant PIMD techniques available in the literature. The comparison of our results with those reported in the literature and/or with those obtained from full PIMD simulations shows a highly satisfactory agreement.« less

Teaching Ionic Solvation Structure with a Monte Carlo Liquid Simulation Program

ERIC Educational Resources Information Center

Serrano, Agostinho; Santos, Flavia M. T.; Greca, Ileana M.

2004-01-01

The use of molecular dynamics and Monte Carlo methods has provided efficient means to stimulate the behavior of molecular liquids and solutions. A Monte Carlo simulation program is used to compute the structure of liquid water and of water as a solvent to Na(super +), Cl(super -), and Ar on a personal computer to show that it is easily feasible to…

Prediction of solubility parameters and miscibility of pharmaceutical compounds by molecular dynamics simulations.

PubMed

Gupta, Jasmine; Nunes, Cletus; Vyas, Shyam; Jonnalagadda, Sriramakamal

2011-03-10

The objectives of this study were (i) to develop a computational model based on molecular dynamics technique to predict the miscibility of indomethacin in carriers (polyethylene oxide, glucose, and sucrose) and (ii) to experimentally verify the in silico predictions by characterizing the drug-carrier mixtures using thermoanalytical techniques. Molecular dynamics (MD) simulations were performed using the COMPASS force field, and the cohesive energy density and the solubility parameters were determined for the model compounds. The magnitude of difference in the solubility parameters of drug and carrier is indicative of their miscibility. The MD simulations predicted indomethacin to be miscible with polyethylene oxide and to be borderline miscible with sucrose and immiscible with glucose. The solubility parameter values obtained using the MD simulations values were in reasonable agreement with those calculated using group contribution methods. Differential scanning calorimetry showed melting point depression of polyethylene oxide with increasing levels of indomethacin accompanied by peak broadening, confirming miscibility. In contrast, thermal analysis of blends of indomethacin with sucrose and glucose verified general immiscibility. The findings demonstrate that molecular modeling is a powerful technique for determining the solubility parameters and predicting miscibility of pharmaceutical compounds. © 2011 American Chemical Society

Abstractions for DNA circuit design.

PubMed

Lakin, Matthew R; Youssef, Simon; Cardelli, Luca; Phillips, Andrew

2012-03-07

DNA strand displacement techniques have been used to implement a broad range of information processing devices, from logic gates, to chemical reaction networks, to architectures for universal computation. Strand displacement techniques enable computational devices to be implemented in DNA without the need for additional components, allowing computation to be programmed solely in terms of nucleotide sequences. A major challenge in the design of strand displacement devices has been to enable rapid analysis of high-level designs while also supporting detailed simulations that include known forms of interference. Another challenge has been to design devices capable of sustaining precise reaction kinetics over long periods, without relying on complex experimental equipment to continually replenish depleted species over time. In this paper, we present a programming language for designing DNA strand displacement devices, which supports progressively increasing levels of molecular detail. The language allows device designs to be programmed using a common syntax and then analysed at varying levels of detail, with or without interference, without needing to modify the program. This allows a trade-off to be made between the level of molecular detail and the computational cost of analysis. We use the language to design a buffered architecture for DNA devices, capable of maintaining precise reaction kinetics for a potentially unbounded period. We test the effectiveness of buffered gates to support long-running computation by designing a DNA strand displacement system capable of sustained oscillations.

Bio-inspired algorithms applied to molecular docking simulations.

PubMed

Heberlé, G; de Azevedo, W F

2011-01-01

Nature as a source of inspiration has been shown to have a great beneficial impact on the development of new computational methodologies. In this scenario, analyses of the interactions between a protein target and a ligand can be simulated by biologically inspired algorithms (BIAs). These algorithms mimic biological systems to create new paradigms for computation, such as neural networks, evolutionary computing, and swarm intelligence. This review provides a description of the main concepts behind BIAs applied to molecular docking simulations. Special attention is devoted to evolutionary algorithms, guided-directed evolutionary algorithms, and Lamarckian genetic algorithms. Recent applications of these methodologies to protein targets identified in the Mycobacterium tuberculosis genome are described.

DFTBaby: A software package for non-adiabatic molecular dynamics simulations based on long-range corrected tight-binding TD-DFT(B)

NASA Astrophysics Data System (ADS)

Humeniuk, Alexander; Mitrić, Roland

2017-12-01

A software package, called DFTBaby, is published, which provides the electronic structure needed for running non-adiabatic molecular dynamics simulations at the level of tight-binding DFT. A long-range correction is incorporated to avoid spurious charge transfer states. Excited state energies, their analytic gradients and scalar non-adiabatic couplings are computed using tight-binding TD-DFT. These quantities are fed into a molecular dynamics code, which integrates Newton's equations of motion for the nuclei together with the electronic Schrödinger equation. Non-adiabatic effects are included by surface hopping. As an example, the program is applied to the optimization of excited states and non-adiabatic dynamics of polyfluorene. The python and Fortran source code is available at http://www.dftbaby.chemie.uni-wuerzburg.de.

Molecular Docking, Molecular Dynamics Simulations, Computational Screening to Design Quorum Sensing Inhibitors Targeting LuxP of Vibrio harveyi and Its Biological Evaluation.

PubMed

Rajamanikandan, Sundaraj; Jeyakanthan, Jeyaraman; Srinivasan, Pappu

2017-01-01

Quorum sensing (QS) plays an important role in the biofilm formation, production of virulence factors and stress responses in Vibrio harveyi. Therefore, interrupting QS is a possible approach to modulate bacterial behavior. In the present study, three docking protocols, such as Rigid Receptor Docking (RRD), Induced Fit Docking (IFD), and Quantum Polarized Ligand Docking (QPLD) were used to elucidate the binding mode of boronic acid derivatives into the binding pocket of LuxP protein in V. harveyi. Among the three docking protocols, IFD accurately predicted the correct binding mode of the studied inhibitors. Molecular dynamics (MD) simulations of the protein-ligand complexes indicates that the inter-molecular hydrogen bonds formed between the protein and ligand complex remains stable during the simulation time. Pharmacophore and shape-based virtual screening were performed to find selective and potent compounds from ChemBridge database. Five hit compounds were selected and subjected to IFD and MD simulations to validate the binding mode. In addition, enrichment calculation was performed to discriminate and separate active compounds from the inactive compounds. Based on the computational studies, the potent Bicyclo [2.2.1] hept-5-ene-2,3-dicarboxylic acid-2,6-dimethylpyridine 1-oxide (ChemBridge_5144368) was selected for in vitro assays. The compound exhibited dose dependent inhibition in bioluminescence and also inhibits biofilm formation in V. harveyi to the level of 64.25 %. The result from the study suggests that ChemBridge_5144368 could serve as an anti-quorum sensing molecule for V. harveyi.

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

PubMed Central

Ando, Tadashi; Chow, Edmond; Saad, Yousef; Skolnick, Jeffrey

2012-01-01

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing Brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the Brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N2) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the “block” version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10 000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale Brownian dynamics simulations with hydrodynamic interactions. PMID:22897254

Utilizing fast multipole expansions for efficient and accurate quantum-classical molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Schwörer, Magnus; Lorenzen, Konstantin; Mathias, Gerald; Tavan, Paul

2015-03-01

Recently, a novel approach to hybrid quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations has been suggested [Schwörer et al., J. Chem. Phys. 138, 244103 (2013)]. Here, the forces acting on the atoms are calculated by grid-based density functional theory (DFT) for a solute molecule and by a polarizable molecular mechanics (PMM) force field for a large solvent environment composed of several 103-105 molecules as negative gradients of a DFT/PMM hybrid Hamiltonian. The electrostatic interactions are efficiently described by a hierarchical fast multipole method (FMM). Adopting recent progress of this FMM technique [Lorenzen et al., J. Chem. Theory Comput. 10, 3244 (2014)], which particularly entails a strictly linear scaling of the computational effort with the system size, and adapting this revised FMM approach to the computation of the interactions between the DFT and PMM fragments of a simulation system, here, we show how one can further enhance the efficiency and accuracy of such DFT/PMM-MD simulations. The resulting gain of total performance, as measured for alanine dipeptide (DFT) embedded in water (PMM) by the product of the gains in efficiency and accuracy, amounts to about one order of magnitude. We also demonstrate that the jointly parallelized implementation of the DFT and PMM-MD parts of the computation enables the efficient use of high-performance computing systems. The associated software is available online.

Computer Modeling of the Earliest Cellular Structures and Functions

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl

2000-01-01

In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perkins, Stephen J.; Wright, David W.; Zhang, Hailiang

2016-10-14

The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-artmore » molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in whichGenAppprovides the deployment infrastructure for running applications on both standard and high-performance computing hardware, andSASSIEprovides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data.GenAppproduces the accessible web-based front end termedSASSIE-web, andGenAppandSASSIEalso make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic `bottlebrush' polymers.« less

Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS).

PubMed

Perkins, Stephen J; Wright, David W; Zhang, Hailiang; Brookes, Emre H; Chen, Jianhan; Irving, Thomas C; Krueger, Susan; Barlow, David J; Edler, Karen J; Scott, David J; Terrill, Nicholas J; King, Stephen M; Butler, Paul D; Curtis, Joseph E

2016-12-01

The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web , and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic 'bottlebrush' polymers.

Penetration of Gold Nanoparticles through Human Skin: Unraveling Its Mechanisms at the Molecular Scale.

PubMed

Gupta, Rakesh; Rai, Beena

2016-07-28

Recent experimental studies suggest that nanosized gold nanoparticles (AuNPs) are able to penetrate into the deeper layer (epidermis and dermis) of rat and human skin. However, the mechanisms by which these AuNPs penetrate and disrupt the skin's lipid matrix are not well understood. In this study, we have used computer simulations to explore the translocation and the permeation of AuNPs through the model skin lipid membrane using both unconstrained and constrained coarse-grained molecular dynamics simulations. Each AuNP (1-6 nm) disrupted the bilayer packing and entered the interior of the bilayer rapidly (within 100 ns). It created a hydrophobic vacancy in the bilayer, which was mostly filled by skin constituents. Bigger AuNPs induced changes in the bilayer structure, and undulations were observed in the bilayer. The bilayer exhibited self-healing properties; it retained its original form once the simulation was run further after the removal of the AuNPs. Constrained simulation results showed that there was a trade-off between the kinetics and thermodynamics of AuNP permeation at a molecular scale. The combined effect of both resulted in a high permeation of small-sized AuNPs. The molecular-level information obtained through our simulations offers a very convenient method to design novel drug delivery systems and effective cosmetics.

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids.

PubMed

Aradi, Bálint; Niklasson, Anders M N; Frauenheim, Thomas

2015-07-14

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born-Oppenheimer molecular dynamics. For systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can be applied to a broad range of problems in materials science, chemistry, and biology.

Simulating the Physical World

NASA Astrophysics Data System (ADS)

Berendsen, Herman J. C.

2004-06-01

The simulation of physical systems requires a simplified, hierarchical approach which models each level from the atomistic to the macroscopic scale. From quantum mechanics to fluid dynamics, this book systematically treats the broad scope of computer modeling and simulations, describing the fundamental theory behind each level of approximation. Berendsen evaluates each stage in relation to its applications giving the reader insight into the possibilities and limitations of the models. Practical guidance for applications and sample programs in Python are provided. With a strong emphasis on molecular models in chemistry and biochemistry, this book will be suitable for advanced undergraduate and graduate courses on molecular modeling and simulation within physics, biophysics, physical chemistry and materials science. It will also be a useful reference to all those working in the field. Additional resources for this title including solutions for instructors and programs are available online at www.cambridge.org/9780521835275. The first book to cover the wide range of modeling and simulations, from atomistic to the macroscopic scale, in a systematic fashion Providing a wealth of background material, it does not assume advanced knowledge and is eminently suitable for course use Contains practical examples and sample programs in Python

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

PubMed Central

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

2016-01-01

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

PubMed

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

2016-06-13

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Nanopyroxene Grafting with β-Cyclodextrin Monomer for Wastewater Applications.

PubMed

Nafie, Ghada; Vitale, Gerardo; Carbognani Ortega, Lante; Nassar, Nashaat N

2017-12-06

Emerging nanoparticle technology provides opportunities for environmentally friendly wastewater treatment applications, including those in the large liquid tailings containments in the Alberta oil sands. In this study, we synthesize β-cyclodextrin grafted nanopyroxenes to offer an ecofriendly platform for the selective removal of organic compounds typically present in these types of applications. We carry out computational modeling at the micro level through molecular mechanics and molecular dynamics simulations and laboratory experiments at the macro level to understand the interactions between the synthesized nanomaterials and two-model naphthenic acid molecules (cyclopentanecarboxylic and trans-4-pentylcyclohexanecarboxylic acids) typically existing in tailing ponds. The proof-of-concept computational modeling and experiments demonstrate that monomer grafted nanopyroxene  or nano-AE of the sodium iron-silicate aegirine are found to be promising candidates for the removal of polar organic compounds from wastewater, among other applications. These nano-AE offer new possibilities for treating tailing ponds generated by the oil sands industry.

Enhanced sampling techniques in molecular dynamics simulations of biological systems.

PubMed

Bernardi, Rafael C; Melo, Marcelo C R; Schulten, Klaus

2015-05-01

Molecular dynamics has emerged as an important research methodology covering systems to the level of millions of atoms. However, insufficient sampling often limits its application. The limitation is due to rough energy landscapes, with many local minima separated by high-energy barriers, which govern the biomolecular motion. In the past few decades methods have been developed that address the sampling problem, such as replica-exchange molecular dynamics, metadynamics and simulated annealing. Here we present an overview over theses sampling methods in an attempt to shed light on which should be selected depending on the type of system property studied. Enhanced sampling methods have been employed for a broad range of biological systems and the choice of a suitable method is connected to biological and physical characteristics of the system, in particular system size. While metadynamics and replica-exchange molecular dynamics are the most adopted sampling methods to study biomolecular dynamics, simulated annealing is well suited to characterize very flexible systems. The use of annealing methods for a long time was restricted to simulation of small proteins; however, a variant of the method, generalized simulated annealing, can be employed at a relatively low computational cost to large macromolecular complexes. Molecular dynamics trajectories frequently do not reach all relevant conformational substates, for example those connected with biological function, a problem that can be addressed by employing enhanced sampling algorithms. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Insights from molecular dynamics simulations for computational protein design.

PubMed

Childers, Matthew Carter; Daggett, Valerie

2017-02-01

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Insights from molecular dynamics simulations for computational protein design

PubMed Central

Childers, Matthew Carter; Daggett, Valerie

2017-01-01

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures. PMID:28239489

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic 'two component system' protein network.

PubMed

Di Paola, Vieri; Marijuán, Pedro C; Lahoz-Beltra, Rafael

2004-01-01

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

PubMed

Grindon, Christina; Harris, Sarah; Evans, Tom; Novik, Keir; Coveney, Peter; Laughton, Charles

2004-07-15

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Mixing coarse-grained and fine-grained water in molecular dynamics simulations of a single system.

PubMed

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.

Molecular dynamics simulations through GPU video games technologies

PubMed Central

Loukatou, Styliani; Papageorgiou, Louis; Fakourelis, Paraskevas; Filntisi, Arianna; Polychronidou, Eleftheria; Bassis, Ioannis; Megalooikonomou, Vasileios; Makałowski, Wojciech; Vlachakis, Dimitrios; Kossida, Sophia

2016-01-01

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations. PMID:27525251

Towards data warehousing and mining of protein unfolding simulation data.

PubMed

Berrar, Daniel; Stahl, Frederic; Silva, Candida; Rodrigues, J Rui; Brito, Rui M M; Dubitzky, Werner

2005-10-01

The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Development of a Computational Assay for the Estrogen Receptor

DTIC Science & Technology

2006-07-01

University Ashley Deline, Senior Thesis in chemistry, " Molecular Dynamic Simulations of a Glycoform and its Constituent Parts Related to Rheumatoid Arthritis...involves running a long molecular dynamics (MD) simulation of the uncoupled receptor in order to sample the protein’s unique conformations. The second...Receptor binding domain. * Performed several long molecular dynamics simulations (800 ps - 3 ns) on the ligand-ER system using ligands with known

Atomistic Simulation and Electronic Structure of Lithium Doped Ionic Liquids: Structure, Transport, and Electrochemical Stability

NASA Technical Reports Server (NTRS)

Haskins, Justin B.; Bauschlicher, Charles W.; Lawson, John W.

2015-01-01

Zero-temperature density functional theory (DFT), density functional theory molecular dynamics (DFT-MD), and classical molecular dynamics using polarizable force fields (PFF-MD) are employed to evaluate the influence of Lithium ion on the structure, transport, and electrochemical stability of three potential ionic liquid electrolytes: N--methyl-N-butylpyrrolidinium bis(trifluoromethanesulfonyl)imide ([pyr14][TFSI]), N--methyl-N-propylpyrrolidinium bis(fluorosulfonyl)imide ([pyr13][FSI]), and 1-ethyl-3--methylimidazolium boron tetrafluoride ([EMIM][BF4]). We characterize the Lithium ion solvation shell through zero-temperature DFT simulations of [Li(Anion)sub n](exp n-1) -clusters, DFT-MD simulations of isolated lithium ions in small ionic liquid systems, and PFF-MD simulations with high Li-doping levels in large ionic liquid systems. At low levels of Li-salt doping, highly stable solvation shells having 2-3 anions are seen in both [pyr14][TFSI] and [pyr13][FSI], while solvation shells with 4 anions dominate in [EMIM][BF sub 4]. At higher levels of doping, we find the formation of complex Li-network structures that increase the frequency of 4 anion-coordinated solvation shells. A comparison of computational and experimental Raman spectra for a wide range of [Li(Anion) sub n](exp n -1) - clusters shows that our proposed structures are consistent with experiment. We estimate the ion diffusion coefficients and quantify both size and simulation time effects. We find estimates of lithium ion diffusion are a reasonable order of magnitude and can be corrected for simulation time effects. Simulation size, on the other hand, is also important, with diffusion coefficients from long PFF-MD simulations of small cells having 20-40% error compared to large-cell values. Finally, we compute the electrochemical window using differences in electronic energy levels of both isolated cation/anion pairs and small ionic liquid systems with Li-salt doping. The single pair and liquid-phase systems provide similar estimates of electrochemical window, while Li-doping in the liquid-phase systems results in electrochemical windows little changed from the neat systems. Pure and hybrid functionals systematically provide an upper and lower bound, respectively, to the experimental electrochemical window for the systems studied here.

Detection of boron nitride radicals by emission spectroscopy in a laser-induced plasma

NASA Astrophysics Data System (ADS)

Dutouquet, C.; Acquaviva, S.; Hermann, J.

2001-06-01

Several vibrational bands of boron nitride radicals have been observed in a plasma produced by pulsed-laser ablation of a boron nitride target in low-pressure nitrogen or argon atmospheres. Using time- and space-resolved emission spectroscopic measurements with a high dynamic range, the most abundant isotopic species B 11N have been detected. The emission bands in the spectral range from 340 to 380 nm belong to the Δυ =-1, 0, +1 sequences of the triplet system (transition A 3Π-X 3Π). For positive identification, the molecular emission bands have been compared with synthetic spectra obtained by computer simulations. Furthermore, B 10N emission bands have been reproduced by computer simulation using molecular constants which have been deduced from the B 11N constants. Nevertheless, the presence of the lower abundant isotopic radical B 10N was not proved due the noise level which masked the low emission intensity of the B 10N band heads.

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

DOE PAGES

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

2017-06-01

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

Molecular simulation of separation of CO{sub 2} from flue gases in Cu-BTC metal-organic framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Q.Y.; Xue, C.Y.; Zhong, C.L.

2007-11-15

In this work, a computational study was performed on the adsorption separation of CO{sub 2} from flue gases (mixtures of CO{sub 2}/N{sub 2}/O{sub 2}) in Cu-BTC metal-organic framework (MOF) to investigate the applicability of MOFs to this important industrial system. The computational results showed that Cu-BTC is a promising material for separation of CO{sub 2} from flue gases, and the macroscopic separation behaviors of the MOF were elucidated at a molecular level to give insight into the underlying mechanisms. The present work not only provided useful information for understanding the separation characteristics of MOFs, but also showed their potential applicationsmore » in chemical industry.« less

Asymmetric Epoxidation: A Twinned Laboratory and Molecular Modeling Experiment for Upper-Level Organic Chemistry Students

ERIC Educational Resources Information Center

Hii, King Kuok; Rzepa, Henry S.; Smith, Edward H.

2015-01-01

The coupling of a student experiment involving the preparation and use of a catalyst for the asymmetric epoxidation of an alkene with computational simulations of various properties of the resulting epoxide is set out in the form of a software toolbox from which students select appropriate components. At the core of these are the computational…

Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes.

PubMed

Drusbosky, Leylah M; Cogle, Christopher R

2017-10-01

This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results. As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early results showing high accuracy in predicting treatment response to standard of care drugs. Furthermore, the computational MDS models serve as clinically relevant MDS cell lines for pre-clinical assays of investigational agents. MDS is an ideal disease for computational modeling and digital drug simulations. Current research is focused on establishing the prediction value of computational modeling. Future research will test the clinical advantage of computer-informed therapy in MDS.

A Review of Enhanced Sampling Approaches for Accelerated Molecular Dynamics

NASA Astrophysics Data System (ADS)

Tiwary, Pratyush; van de Walle, Axel

Molecular dynamics (MD) simulations have become a tool of immense use and popularity for simulating a variety of systems. With the advent of massively parallel computer resources, one now routinely sees applications of MD to systems as large as hundreds of thousands to even several million atoms, which is almost the size of most nanomaterials. However, it is not yet possible to reach laboratory timescales of milliseconds and beyond with MD simulations. Due to the essentially sequential nature of time, parallel computers have been of limited use in solving this so-called timescale problem. Instead, over the years a large range of statistical mechanics based enhanced sampling approaches have been proposed for accelerating molecular dynamics, and accessing timescales that are well beyond the reach of the fastest computers. In this review we provide an overview of these approaches, including the underlying theory, typical applications, and publicly available software resources to implement them.

A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

PubMed

Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

2007-06-01

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Extending rule-based methods to model molecular geometry and 3D model resolution.

PubMed

Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

2016-08-01

Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models quantify the variation in aggregate size that results from differences in molecular geometry and from model resolution.

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

Relative complexation energies for Li(+) ion in solution: molecular level solvation versus polarizable continuum model study.

PubMed

Eilmes, Andrzej; Kubisiak, Piotr

2010-01-21

Relative complexation energies for the lithium cation in acetonitrile and diethyl ether have been studied. Quantum-chemical calculations explicitly describing the solvation of Li(+) have been performed based on structures obtained from molecular dynamics simulations. The effect of an increasing number of solvent molecules beyond the first solvation shell has been found to consist in reduction of the differences in complexation energies for different coordination numbers. Explicit-solvation data have served as a benchmark to the results of polarizable continuum model (PCM) calculations. It has been demonstrated that the PCM approach can yield relative complexation energies comparable to the predictions based on molecular-level solvation, but at significantly lower computational cost. The best agreement between the explicit-solvation and the PCM results has been obtained when the van der Waals surface was adopted to build the molecular cavity.

Thermalized Drude Oscillators with the LAMMPS Molecular Dynamics Simulator.

PubMed

Dequidt, Alain; Devémy, Julien; Pádua, Agílio A H

2016-01-25

LAMMPS is a very customizable molecular dynamics simulation software, which can be used to simulate a large diversity of systems. We introduce a new package for simulation of polarizable systems with LAMMPS using thermalized Drude oscillators. The implemented functionalities are described and are illustrated by examples. The implementation was validated by comparing simulation results with published data and using a reference software. Computational performance is also analyzed.

Understanding glass formation and ion transport in polymeric ionic liquids using computer simulations

NASA Astrophysics Data System (ADS)

Patra, Tarak; Yang, Junhong; Cheng, Yiz; Simmons, David

Polymeric ionic liquids (PILs) are very promising materials to enable more environmentally stable high density energy storage devices. Realization of PILs providing high environmental and mechanical stability while maximizing ion conductivity would be accelerated by an improved molecular level understanding of their structure and dynamics. Extensive evidence suggests that both mechanical properties and ion conductivity in anhydrous PILs are intimately related to the PIL's glass formation behavior. This represents a major challenge to the rational design of these materials, given that the basic nature of glass formation and its connection to molecular properties remains a substantial open question in polymer and condensed matter physics. Here we describe coarse-grained and atomistic molecular dynamics simulations probing the relationship between PIL architecture and interactions, glass formation behavior, and ion transport characteristics. These studies provide guidance towards the design of PILs with improved stability and ion conductivity for future energy applications.

Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

PubMed Central

Patmanidis, Ilias

2018-01-01

In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation. PMID:29688238

Molecular dynamics simulations of collision-induced absorption: Implementation in LAMMPS

NASA Astrophysics Data System (ADS)

Fakhardji, W.; Gustafsson, M.

2017-02-01

We pursue simulations of collision-induced absorption in a mixture of argon and xenon gas at room temperature by means of classical molecular dynamics. The established theoretical approach (Hartmann et al. 2011 J. Chem. Phys. 134 094316) is implemented with the molecular dynamics package LAMMPS. The bound state features in the absorption spectrum are well reproduced with the molecular dynamics simulation in comparison with a laboratory measurement. The magnitude of the computed absorption, however, is underestimated in a large part of the spectrum. We suggest some aspects of the simulation that could be improved.

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Extended Lagrangian Density Functional Tight-Binding Molecular Dynamics for Molecules and Solids

DOE PAGES

Aradi, Bálint; Niklasson, Anders M. N.; Frauenheim, Thomas

2015-06-26

A computationally fast quantum mechanical molecular dynamics scheme using an extended Lagrangian density functional tight-binding formulation has been developed and implemented in the DFTB+ electronic structure program package for simulations of solids and molecular systems. The scheme combines the computational speed of self-consistent density functional tight-binding theory with the efficiency and long-term accuracy of extended Lagrangian Born–Oppenheimer molecular dynamics. Furthermore, for systems without self-consistent charge instabilities, only a single diagonalization or construction of the single-particle density matrix is required in each time step. The molecular dynamics simulation scheme can also be applied to a broad range of problems in materialsmore » science, chemistry, and biology.« less

Communication: A method to compute the transport coefficient of pure fluids diffusing through planar interfaces from equilibrium molecular dynamics simulations.

PubMed

Vermorel, Romain; Oulebsir, Fouad; Galliero, Guillaume

2017-09-14

The computation of diffusion coefficients in molecular systems ranks among the most useful applications of equilibrium molecular dynamics simulations. However, when dealing with the problem of fluid diffusion through vanishingly thin interfaces, classical techniques are not applicable. This is because the volume of space in which molecules diffuse is ill-defined. In such conditions, non-equilibrium techniques allow for the computation of transport coefficients per unit interface width, but their weak point lies in their inability to isolate the contribution of the different physical mechanisms prone to impact the flux of permeating molecules. In this work, we propose a simple and accurate method to compute the diffusional transport coefficient of a pure fluid through a planar interface from equilibrium molecular dynamics simulations, in the form of a diffusion coefficient per unit interface width. In order to demonstrate its validity and accuracy, we apply our method to the case study of a dilute gas diffusing through a smoothly repulsive single-layer porous solid. We believe this complementary technique can benefit to the interpretation of the results obtained on single-layer membranes by means of complex non-equilibrium methods.

Constraint methods that accelerate free-energy simulations of biomolecules.

PubMed

Perez, Alberto; MacCallum, Justin L; Coutsias, Evangelos A; Dill, Ken A

2015-12-28

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

Site Identification by Ligand Competitive Saturation (SILCS) simulations for fragment-based drug design.

PubMed

Faller, Christina E; Raman, E Prabhu; MacKerell, Alexander D; Guvench, Olgun

2015-01-01

Fragment-based drug design (FBDD) involves screening low molecular weight molecules ("fragments") that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind nonoverlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy.The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is "soaked" in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called "FragMaps" can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine "Grid Free Energies (GFEs)," which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities.

Investigating the Effectiveness of Computer Simulations for Chemistry Learning

ERIC Educational Resources Information Center

Plass, Jan L.; Milne, Catherine; Homer, Bruce D.; Schwartz, Ruth N.; Hayward, Elizabeth O.; Jordan, Trace; Verkuilen, Jay; Ng, Florrie; Wang, Yan; Barrientos, Juan

2012-01-01

Are well-designed computer simulations an effective tool to support student understanding of complex concepts in chemistry when integrated into high school science classrooms? We investigated scaling up the use of a sequence of simulations of kinetic molecular theory and associated topics of diffusion, gas laws, and phase change, which we designed…

Towards Highly Scalable Ab Initio Molecular Dynamics (AIMD) Simulations on the Intel Knights Landing Manycore Processor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacquelin, Mathias; De Jong, Wibe A.; Bylaska, Eric J.

2017-07-03

The Ab Initio Molecular Dynamics (AIMD) method allows scientists to treat the dynamics of molecular and condensed phase systems while retaining a first-principles-based description of their interactions. This extremely important method has tremendous computational requirements, because the electronic Schr¨odinger equation, approximated using Kohn-Sham Density Functional Theory (DFT), is solved at every time step. With the advent of manycore architectures, application developers have a significant amount of processing power within each compute node that can only be exploited through massive parallelism. A compute intensive application such as AIMD forms a good candidate to leverage this processing power. In this paper, wemore » focus on adding thread level parallelism to the plane wave DFT methodology implemented in NWChem. Through a careful optimization of tall-skinny matrix products, which are at the heart of the Lagrange multiplier and nonlocal pseudopotential kernels, as well as 3D FFTs, our OpenMP implementation delivers excellent strong scaling on the latest Intel Knights Landing (KNL) processor. We assess the efficiency of our Lagrange multiplier kernels by building a Roofline model of the platform, and verify that our implementation is close to the roofline for various problem sizes. Finally, we present strong scaling results on the complete AIMD simulation for a 64 water molecules test case, that scales up to all 68 cores of the Knights Landing processor.« less

SimGen: A General Simulation Method for Large Systems.

PubMed

Taylor, William R

2017-02-03

SimGen is a stand-alone computer program that reads a script of commands to represent complex macromolecules, including proteins and nucleic acids, in a structural hierarchy that can then be viewed using an integral graphical viewer or animated through a high-level application programming interface in C++. Structural levels in the hierarchy range from α-carbon or phosphate backbones through secondary structure to domains, molecules, and multimers with each level represented in an identical data structure that can be manipulated using the application programming interface. Unlike most coarse-grained simulation approaches, the higher-level objects represented in SimGen can be soft, allowing the lower-level objects that they contain to interact directly. The default motion simulated by SimGen is a Brownian-like diffusion that can be set to occur across all levels of representation in the hierarchy. Links can also be defined between objects, which, when combined with large high-level random movements, result in an effective search strategy for constraint satisfaction, including structure prediction from predicted pairwise distances. The implementation of SimGen makes use of the hierarchic data structure to avoid unnecessary calculation, especially for collision detection, allowing it to be simultaneously run and viewed on a laptop computer while simulating large systems of over 20,000 objects. It has been used previously to model complex molecular interactions including the motion of a myosin-V dimer "walking" on an actin fibre, RNA stem-loop packing, and the simulation of cell motion and aggregation. Several extensions to this original functionality are described. Copyright © 2016 The Francis Crick Institute. Published by Elsevier Ltd.. All rights reserved.

nMoldyn: a program package for a neutron scattering oriented analysis of molecular dynamics simulations.

PubMed

Róg, T; Murzyn, K; Hinsen, K; Kneller, G R

2003-04-15

We present a new implementation of the program nMoldyn, which has been developed for the computation and decomposition of neutron scattering intensities from Molecular Dynamics trajectories (Comp. Phys. Commun 1995, 91, 191-214). The new implementation extends the functionality of the original version, provides a much more convenient user interface (both graphical/interactive and batch), and can be used as a tool set for implementing new analysis modules. This was made possible by the use of a high-level language, Python, and of modern object-oriented programming techniques. The quantities that can be calculated by nMoldyn are the mean-square displacement, the velocity autocorrelation function as well as its Fourier transform (the density of states) and its memory function, the angular velocity autocorrelation function and its Fourier transform, the reorientational correlation function, and several functions specific to neutron scattering: the coherent and incoherent intermediate scattering functions with their Fourier transforms, the memory function of the coherent scattering function, and the elastic incoherent structure factor. The possibility to compute memory function is a new and powerful feature that allows to relate simulation results to theoretical studies. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 657-667, 2003

Development of massive multilevel molecular dynamics simulation program, Platypus (PLATform for dYnamic Protein Unified Simulation), for the elucidation of protein functions.

PubMed

Takano, Yu; Nakata, Kazuto; Yonezawa, Yasushige; Nakamura, Haruki

2016-05-05

A massively parallel program for quantum mechanical-molecular mechanical (QM/MM) molecular dynamics simulation, called Platypus (PLATform for dYnamic Protein Unified Simulation), was developed to elucidate protein functions. The speedup and the parallelization ratio of Platypus in the QM and QM/MM calculations were assessed for a bacteriochlorophyll dimer in the photosynthetic reaction center (DIMER) on the K computer, a massively parallel computer achieving 10 PetaFLOPs with 705,024 cores. Platypus exhibited the increase in speedup up to 20,000 core processors at the HF/cc-pVDZ and B3LYP/cc-pVDZ, and up to 10,000 core processors by the CASCI(16,16)/6-31G** calculations. We also performed excited QM/MM-MD simulations on the chromophore of Sirius (SIRIUS) in water. Sirius is a pH-insensitive and photo-stable ultramarine fluorescent protein. Platypus accelerated on-the-fly excited-state QM/MM-MD simulations for SIRIUS in water, using over 4000 core processors. In addition, it also succeeded in 50-ps (200,000-step) on-the-fly excited-state QM/MM-MD simulations for the SIRIUS in water. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

The Computer Simulation of Liquids by Molecular Dynamics.

ERIC Educational Resources Information Center

Smith, W.

1987-01-01

Proposes a mathematical computer model for the behavior of liquids using the classical dynamic principles of Sir Isaac Newton and the molecular dynamics method invented by other scientists. Concludes that other applications will be successful using supercomputers to go beyond simple Newtonian physics. (CW)

Efficient electron open boundaries for simulating electrochemical cells

NASA Astrophysics Data System (ADS)

Zauchner, Mario G.; Horsfield, Andrew P.; Todorov, Tchavdar N.

2018-01-01

Nonequilibrium electrochemistry raises new challenges for atomistic simulation: we need to perform molecular dynamics for the nuclear degrees of freedom with an explicit description of the electrons, which in turn must be free to enter and leave the computational cell. Here we present a limiting form for electron open boundaries that we expect to apply when the magnitude of the electric current is determined by the drift and diffusion of ions in a solution and which is sufficiently computationally efficient to be used with molecular dynamics. We present tight-binding simulations of a parallel-plate capacitor with nothing, a dimer, or an atomic wire situated in the space between the plates. These simulations demonstrate that this scheme can be used to perform molecular dynamics simulations when there is an applied bias between two metal plates with, at most, weak electronic coupling between them. This simple system captures some of the essential features of an electrochemical cell, suggesting this approach might be suitable for simulations of electrochemical cells out of equilibrium.

Lanthanide and transition metal complexes of bioactive coumarins: molecular modeling and spectroscopic studies.

PubMed

Georgieva, I; Mihaylov, Tz; Trendafilova, N

2014-06-01

The present paper summarizes theoretical and spectroscopic investigations on a series of active coumarins and their lanthanide and transition metal complexes with application in medicine and pharmacy. Molecular modeling as well as IR, Raman, NMR and electronic spectral simulations at different levels of theory were performed to obtain important molecular descriptors: total energy, formation energy, binding energy, stability, conformations, structural parameters, electron density distribution, molecular electrostatic potential, Fukui functions, atomic charges, and reactive indexes. The computations are performed both in gas phase and in solution with consideration of the solvent effect on the molecular structural and energetic parameters. The investigations have shown that the advanced computational methods are reliable for prediction of the metal-coumarin binding mode, electron density distribution, thermodynamic properties as well as the strength and nature of the metal-coumarin interaction (not experimentally accessible) and correctly interpret the experimental spectroscopic data. Known results from biological tests for cytotoxic, antimicrobial, anti-fungal, spasmolytic and anti-HIV activities on the studied metal complexes are reported and discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Hamiltonian adaptive resolution molecular dynamics simulation of infrared dielectric functions of liquids

NASA Astrophysics Data System (ADS)

Wang, C. C.; Tan, J. Y.; Liu, L. H.

2018-05-01

Hamiltonian adaptive resolution scheme (H-AdResS), which allows to simulate materials by treating different domains of the system at different levels of resolution, is a recently proposed atomistic/coarse-grained multiscale model. In this work, a scheme to calculate the dielectric functions of liquids on account of H-AdResS is presented. In the proposed H-AdResS dielectric-function calculation scheme (DielectFunctCalS), the corrected molecular dipole moments are calculated by multiplying molecular dipole moment by the weighting fraction of the molecular mapping point. As the widths of all-atom and hybrid regions show different degrees of influence on the dielectric functions, a prefactor is multiplied to eliminate the effects of all-atom and hybrid region widths. Since one goal of using the H-AdResS method is to reduce computational costs, widths of the all-atom region and the hybrid region can be reduced considering that the coarse-grained simulation is much more timesaving compared to atomistic simulation. Liquid water and ethanol are taken as test cases to validate the DielectFunctCalS. The H-AdResS DielectFunctCalS results are in good agreement with all-atom molecular dynamics simulations. The accuracy of the H-AdResS results, together with all-atom molecular dynamics results, depends heavily on the choice of the force field and force field parameters. The H-AdResS DielectFunctCalS allows us to calculate the dielectric functions of macromolecule systems with high efficiency and makes the dielectric function calculations of large biomolecular systems possible.

A Review of Computational Methods in Materials Science: Examples from Shock-Wave and Polymer Physics

PubMed Central

Steinhauser, Martin O.; Hiermaier, Stefan

2009-01-01

This review discusses several computational methods used on different length and time scales for the simulation of material behavior. First, the importance of physical modeling and its relation to computer simulation on multiscales is discussed. Then, computational methods used on different scales are shortly reviewed, before we focus on the molecular dynamics (MD) method. Here we survey in a tutorial-like fashion some key issues including several MD optimization techniques. Thereafter, computational examples for the capabilities of numerical simulations in materials research are discussed. We focus on recent results of shock wave simulations of a solid which are based on two different modeling approaches and we discuss their respective assets and drawbacks with a view to their application on multiscales. Then, the prospects of computer simulations on the molecular length scale using coarse-grained MD methods are covered by means of examples pertaining to complex topological polymer structures including star-polymers, biomacromolecules such as polyelectrolytes and polymers with intrinsic stiffness. This review ends by highlighting new emerging interdisciplinary applications of computational methods in the field of medical engineering where the application of concepts of polymer physics and of shock waves to biological systems holds a lot of promise for improving medical applications such as extracorporeal shock wave lithotripsy or tumor treatment. PMID:20054467

Algorithms of GPU-enabled reactive force field (ReaxFF) molecular dynamics.

PubMed

Zheng, Mo; Li, Xiaoxia; Guo, Li

2013-04-01

Reactive force field (ReaxFF), a recent and novel bond order potential, allows for reactive molecular dynamics (ReaxFF MD) simulations for modeling larger and more complex molecular systems involving chemical reactions when compared with computation intensive quantum mechanical methods. However, ReaxFF MD can be approximately 10-50 times slower than classical MD due to its explicit modeling of bond forming and breaking, the dynamic charge equilibration at each time-step, and its one order smaller time-step than the classical MD, all of which pose significant computational challenges in simulation capability to reach spatio-temporal scales of nanometers and nanoseconds. The very recent advances of graphics processing unit (GPU) provide not only highly favorable performance for GPU enabled MD programs compared with CPU implementations but also an opportunity to manage with the computing power and memory demanding nature imposed on computer hardware by ReaxFF MD. In this paper, we present the algorithms of GMD-Reax, the first GPU enabled ReaxFF MD program with significantly improved performance surpassing CPU implementations on desktop workstations. The performance of GMD-Reax has been benchmarked on a PC equipped with a NVIDIA C2050 GPU for coal pyrolysis simulation systems with atoms ranging from 1378 to 27,283. GMD-Reax achieved speedups as high as 12 times faster than Duin et al.'s FORTRAN codes in Lammps on 8 CPU cores and 6 times faster than the Lammps' C codes based on PuReMD in terms of the simulation time per time-step averaged over 100 steps. GMD-Reax could be used as a new and efficient computational tool for exploiting very complex molecular reactions via ReaxFF MD simulation on desktop workstations. Copyright © 2013 Elsevier Inc. All rights reserved.

A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES).

PubMed

Campos, Marcelino; Llorens, Carlos; Sempere, José M; Futami, Ricardo; Rodriguez, Irene; Carrasco, Purificación; Capilla, Rafael; Latorre, Amparo; Coque, Teresa M; Moya, Andres; Baquero, Fernando

2015-08-05

Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem. In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis. The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http://gydb.org/ares.

Free-energy simulations reveal molecular mechanism for functional switch of a DNA helicase

PubMed Central

Ma, Wen; Whitley, Kevin D; Schulten, Klaus

2018-01-01

Helicases play key roles in genome maintenance, yet it remains elusive how these enzymes change conformations and how transitions between different conformational states regulate nucleic acid reshaping. Here, we developed a computational technique combining structural bioinformatics approaches and atomic-level free-energy simulations to characterize how the Escherichia coli DNA repair enzyme UvrD changes its conformation at the fork junction to switch its function from unwinding to rezipping DNA. The lowest free-energy path shows that UvrD opens the interface between two domains, allowing the bound ssDNA to escape. The simulation results predict a key metastable 'tilted' state during ssDNA strand switching. By simulating FRET distributions with fluorophores attached to UvrD, we show that the new state is supported quantitatively by single-molecule measurements. The present study deciphers key elements for the 'hyper-helicase' behavior of a mutant and provides an effective framework to characterize directly structure-function relationships in molecular machines. PMID:29664402

Free-energy simulations reveal molecular mechanism for functional switch of a DNA helicase.

PubMed

Ma, Wen; Whitley, Kevin D; Chemla, Yann R; Luthey-Schulten, Zaida; Schulten, Klaus

2018-04-17

Helicases play key roles in genome maintenance, yet it remains elusive how these enzymes change conformations and how transitions between different conformational states regulate nucleic acid reshaping. Here, we developed a computational technique combining structural bioinformatics approaches and atomic-level free-energy simulations to characterize how the Escherichia coli DNA repair enzyme UvrD changes its conformation at the fork junction to switch its function from unwinding to rezipping DNA. The lowest free-energy path shows that UvrD opens the interface between two domains, allowing the bound ssDNA to escape. The simulation results predict a key metastable 'tilted' state during ssDNA strand switching. By simulating FRET distributions with fluorophores attached to UvrD, we show that the new state is supported quantitatively by single-molecule measurements. The present study deciphers key elements for the 'hyper-helicase' behavior of a mutant and provides an effective framework to characterize directly structure-function relationships in molecular machines. © 2018, Ma et al.

Quantum mechanical force fields for condensed phase molecular simulations

NASA Astrophysics Data System (ADS)

Giese, Timothy J.; York, Darrin M.

2017-09-01

Molecular simulations are powerful tools for providing atomic-level details into complex chemical and physical processes that occur in the condensed phase. For strongly interacting systems where quantum many-body effects are known to play an important role, density-functional methods are often used to provide the model with the potential energy used to drive dynamics. These methods, however, suffer from two major drawbacks. First, they are often too computationally intensive to practically apply to large systems over long time scales, limiting their scope of application. Second, there remain challenges for these models to obtain the necessary level of accuracy for weak non-bonded interactions to obtain quantitative accuracy for a wide range of condensed phase properties. Quantum mechanical force fields (QMFFs) provide a potential solution to both of these limitations. In this review, we address recent advances in the development of QMFFs for condensed phase simulations. In particular, we examine the development of QMFF models using both approximate and ab initio density-functional models, the treatment of short-ranged non-bonded and long-ranged electrostatic interactions, and stability issues in molecular dynamics calculations. Example calculations are provided for crystalline systems, liquid water, and ionic liquids. We conclude with a perspective for emerging challenges and future research directions.

Radiation damage of biomolecules (RADAM) database development: current status

NASA Astrophysics Data System (ADS)

Denifl, S.; Garcia, G.; Huber, B. A.; Marinković, B. P.; Mason, N.; Postler, J.; Rabus, H.; Rixon, G.; Solov'yov, A. V.; Suraud, E.; Yakubovich, A. V.

2013-06-01

Ion beam therapy offers the possibility of excellent dose localization for treatment of malignant tumours, minimizing radiation damage in normal tissue, while maximizing cell killing within the tumour. However, as the underlying dependent physical, chemical and biological processes are too complex to treat them on a purely analytical level, most of our current and future understanding will rely on computer simulations, based on mathematical equations, algorithms and last, but not least, on the available atomic and molecular data. The viability of the simulated output and the success of any computer simulation will be determined by these data, which are treated as the input variables in each computer simulation performed. The radiation research community lacks a complete database for the cross sections of all the different processes involved in ion beam induced damage: ionization and excitation cross sections for ions with liquid water and biological molecules, all the possible electron - medium interactions, dielectric response data, electron attachment to biomolecules etc. In this paper we discuss current progress in the creation of such a database, outline the roadmap of the project and review plans for the exploitation of such a database in future simulations.

Molecular Dynamics Simulation of WSK-3, a Computationally Designed, Water-Soluble Variant of the Integral Membrane Protein KcsA

PubMed Central

Bronson, Jonathan; Lee, One-Sun; Saven, Jeffery G.

2006-01-01

Poor solubility and low expression levels often make membrane proteins difficult to study. An alternative to the use of detergents to solubilize these aggregation-prone proteins is the partial redesign of the sequence so as to confer water solubility. Recently, computationally assisted membrane protein solubilization (CAMPS) has been reported, where exposed hydrophobic residues on a protein's surface are computationally redesigned. Herein, the structure and fluctuations of a designed, water-soluble variant of KcsA (WSK-3) were studied using molecular dynamics simulations. The root mean square deviation of the protein from its starting structure, where the backbone coordinates are those of KcsA, was 1.8 Å. The structure of salt bridges involved in structural specificity and solubility were examined. The preferred configuration of ions and water in the selectivity filter of WSK-3 was consistent with the reported preferences for KcsA. The structure of the selectivity filter was maintained, which is consistent with WSK-3 having an affinity for agitoxin2 comparable to that of wild-type KcsA. In contrast to KcsA, the central cavity's side chains were observed to reorient, allowing water diffusion through the side of the cavity wall. These simulations provide an atomistic analysis of the CAMPS strategy and its implications for further investigations of membrane proteins. PMID:16299086

Hyperfine excitation of CH in collisions with atomic and molecular hydrogen

NASA Astrophysics Data System (ADS)

Dagdigian, Paul J.

2018-04-01

We investigate here the excitation of methylidene (CH) induced by collisions with atomic and molecular hydrogen (H and H2). The hyperfine-resolved rate coefficients were obtained from close coupling nuclear-spin-free scattering calculations. The calculations are based upon recent, high-accuracy calculations of the CH(X2Π)-H(2S) and CH(X2Π)-H2 potential energy surfaces. Cross-sections and rate coefficients for collisions with atomic H, para-H2, and ortho-H2 were computed for all transitions between the 32 hyperfine levels for CH(X2Π) involving the n ≤ 4 rotational levels for temperatures between 10 and 300 K. These rate coefficients should significantly aid in the interpretation of astronomical observations of CH spectra. As a first application, the excitation of CH is simulated for conditions in typical molecular clouds.

Explicit polarization (X-Pol) potential using ab initio molecular orbital theory and density functional theory.

PubMed

Song, Lingchun; Han, Jaebeom; Lin, Yen-lin; Xie, Wangshen; Gao, Jiali

2009-10-29

The explicit polarization (X-Pol) method has been examined using ab initio molecular orbital theory and density functional theory. The X-Pol potential was designed to provide a novel theoretical framework for developing next-generation force fields for biomolecular simulations. Importantly, the X-Pol potential is a general method, which can be employed with any level of electronic structure theory. The present study illustrates the implementation of the X-Pol method using ab initio Hartree-Fock theory and hybrid density functional theory. The computational results are illustrated by considering a set of bimolecular complexes of small organic molecules and ions with water. The computed interaction energies and hydrogen bond geometries are in good accord with CCSD(T) calculations and B3LYP/aug-cc-pVDZ optimizations.

Quantum Fragment Based ab Initio Molecular Dynamics for Proteins.

PubMed

Liu, Jinfeng; Zhu, Tong; Wang, Xianwei; He, Xiao; Zhang, John Z H

2015-12-08

Developing ab initio molecular dynamics (AIMD) methods for practical application in protein dynamics is of significant interest. Due to the large size of biomolecules, applying standard quantum chemical methods to compute energies for dynamic simulation is computationally prohibitive. In this work, a fragment based ab initio molecular dynamics approach is presented for practical application in protein dynamics study. In this approach, the energy and forces of the protein are calculated by a recently developed electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. For simulation in explicit solvent, mechanical embedding is introduced to treat protein interaction with explicit water molecules. This AIMD approach has been applied to MD simulations of a small benchmark protein Trpcage (with 20 residues and 304 atoms) in both the gas phase and in solution. Comparison to the simulation result using the AMBER force field shows that the AIMD gives a more stable protein structure in the simulation, indicating that quantum chemical energy is more reliable. Importantly, the present fragment-based AIMD simulation captures quantum effects including electrostatic polarization and charge transfer that are missing in standard classical MD simulations. The current approach is linear-scaling, trivially parallel, and applicable to performing the AIMD simulation of proteins with a large size.

Interactions of Organics within Hydrated Selective Layer of Reverse Osmosis Desalination Membrane: A Combined Experimental and Computational Study.

PubMed

Ghoufi, Aziz; Dražević, Emil; Szymczyk, Anthony

2017-03-07

In this work we have examined a computational approach in predicting the interactions between uncharged organic solutes and polyamide membranes. We used three model organic molecules with identical molecular weights (100.1 g/mol), 4-aminopiperidine, 3,3-dimethyl-2-butanone (pinacolone) and methylisobutyl ketone for which we obtained experimental data on partitioning, diffusion and separation on a typical seawater reverse osmosis (RO) membrane. The interaction energy between the solutes and the membrane phase (fully aromatic polyamide) was computed from molecular dynamics (MD) simulations and the resulting sequence was found to correlate well with the experimental rejections and sorption data. Sorption of the different organic solutes within the membrane skin layer determined from attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) nicely agreed with interaction energies computed from molecular simulations. Qualitative information about solute diffusivity inside the membrane was also extracted from MD simulations while ATR-FTIR experiments indicated strongly hindered diffusion with diffusion coefficients in the membrane about 10 -15 m 2 /s. The computational approach presented here could be a first step toward predicting rejections trends of, for example, hormones and pharmaceuticals by RO dense membranes.

FTIR, FT-Raman, UV-Visible spectra and quantum chemical calculations of allantoin molecule and its hydrogen bonded dimers.

PubMed

Alam, Mohammad Jane; Ahmad, Shabbir

2015-02-05

FTIR, FT-Raman and electronic spectra of allantoin molecule are recorded and investigated using DFT and MP2 methods with 6-311++G(d,p) basis set. The molecular structure, anharmonic vibrational spectra, natural atomic charges, non-linear optical properties, etc. have been computed for the ground state of allantoin. The anharmonic vibrational frequencies are calculated using PT2 algorithm (Barone method) as well as VSCF and CC-VSCF methods. These methods yield results that are in remarkable agreement with the experiment. The coupling strengths between pairs of modes are also calculated using coupling integral based on 2MR-QFF approximation. The simulations on allantoin dimers have been also performed at B3LYP/6-311++G(d,p) level of theory to investigate the effect of the intermolecular interactions on the molecular structure and vibrational frequencies of the monomer. Vibrational assignments are made with the great accuracy using PED calculations and animated modes. The combination and overtone bands have been also identified in the FTIR spectrum with the help of anharmonic computations. The electronic spectra are simulated in gas and solution at TD-B3LYP/6-311++G(d,p) level of theory. The important global quantities such as electro-negativity, electronic chemical potential, electrophilicity index, chemical hardness and softness based on HOMO, LUMO energy eigenvalues are also computed. NBO analysis has been performed for monomer and dimers of allantoin at B3LYP/6-311++G(d,p) level of theory. Copyright © 2014 Elsevier B.V. All rights reserved.

Coarse-Grained Models Reveal Functional Dynamics – II. Molecular Dynamics Simulation at the Coarse-Grained Level – Theories and Biological Applications

PubMed Central

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

On the origin of the electrostatic potential difference at a liquid-vacuum interface.

PubMed

Harder, Edward; Roux, Benoît

2008-12-21

The microscopic origin of the interface potential calculated from computer simulations is elucidated by considering a simple model of molecules near an interface. The model posits that molecules are isotropically oriented and their charge density is Gaussian distributed. Molecules that have a charge density that is more negative toward their interior tend to give rise to a negative interface potential relative to the gaseous phase, while charge densities more positive toward their interior give rise to a positive interface potential. The interface potential for the model is compared to the interface potential computed from molecular dynamics simulations of the nonpolar vacuum-methane system and the polar vacuum-water interface system. The computed vacuum-methane interface potential from a molecular dynamics simulation (-220 mV) is captured with quantitative precision by the model. For the vacuum-water interface system, the model predicts a potential of -400 mV compared to -510 mV, calculated from a molecular dynamics simulation. The physical implications of this isotropic contribution to the interface potential is examined using the example of ion solvation in liquid methane.

Enhanced Molecular Dynamics Methods Applied to Drug Design Projects.

PubMed

Ziada, Sonia; Braka, Abdennour; Diharce, Julien; Aci-Sèche, Samia; Bonnet, Pascal

2018-01-01

Nobel Laureate Richard P. Feynman stated: "[…] everything that living things do can be understood in terms of jiggling and wiggling of atoms […]." The importance of computer simulations of macromolecules, which use classical mechanics principles to describe atom behavior, is widely acknowledged and nowadays, they are applied in many fields such as material sciences and drug discovery. With the increase of computing power, molecular dynamics simulations can be applied to understand biological mechanisms at realistic timescales. In this chapter, we share our computational experience providing a global view of two of the widely used enhanced molecular dynamics methods to study protein structure and dynamics through the description of their characteristics, limits and we provide some examples of their applications in drug design. We also discuss the appropriate choice of software and hardware. In a detailed practical procedure, we describe how to set up, run, and analyze two main molecular dynamics methods, the umbrella sampling (US) and the accelerated molecular dynamics (aMD) methods.

Computer simulation studies of the growth of strained layers by molecular-beam epitaxy

NASA Astrophysics Data System (ADS)

Faux, D. A.; Gaynor, G.; Carson, C. L.; Hall, C. K.; Bernholc, J.

1990-08-01

Two new types of discrete-space Monte Carlo computer simulation are presented for the modeling of the early stages of strained-layer growth by molecular-beam epitaxy. The simulations are more economical on computer resources than continuous-space Monte Carlo or molecular dynamics. Each model is applied to the study of growth onto a substrate in two dimensions with use of Lennard-Jones interatomic potentials. Up to seven layers are deposited for a variety of lattice mismatches, temperatures, and growth rates. Both simulations give similar results. At small lattice mismatches (<~4%) the growth is in registry with the substrate, while at high mismatches (>~6%) the growth is incommensurate with the substrate. At intermediate mismatches, a transition from registered to incommensurate growth is observed which commences at the top of the crystal and propagates down to the first layer. Faster growth rates are seen to inhibit this transition. The growth mode is van der Merwe (layer-by-layer) at 2% lattice mismatch, but at larger mismatches Volmer-Weber (island) growth is preferred. The Monte Carlo simulations are assessed in the light of these results and the ease at which they can be extended to three dimensions and to more sophisticated potentials is discussed.

Equation-free multiscale computation: algorithms and applications.

PubMed

Kevrekidis, Ioannis G; Samaey, Giovanni

2009-01-01

In traditional physicochemical modeling, one derives evolution equations at the (macroscopic, coarse) scale of interest; these are used to perform a variety of tasks (simulation, bifurcation analysis, optimization) using an arsenal of analytical and numerical techniques. For many complex systems, however, although one observes evolution at a macroscopic scale of interest, accurate models are only given at a more detailed (fine-scale, microscopic) level of description (e.g., lattice Boltzmann, kinetic Monte Carlo, molecular dynamics). Here, we review a framework for computer-aided multiscale analysis, which enables macroscopic computational tasks (over extended spatiotemporal scales) using only appropriately initialized microscopic simulation on short time and length scales. The methodology bypasses the derivation of macroscopic evolution equations when these equations conceptually exist but are not available in closed form-hence the term equation-free. We selectively discuss basic algorithms and underlying principles and illustrate the approach through representative applications. We also discuss potential difficulties and outline areas for future research.

Multi-Scale Computational Enzymology: Enhancing Our Understanding of Enzymatic Catalysis

PubMed Central

Gherib, Rami; Dokainish, Hisham M.; Gauld, James W.

2014-01-01

Elucidating the origin of enzymatic catalysis stands as one the great challenges of contemporary biochemistry and biophysics. The recent emergence of computational enzymology has enhanced our atomistic-level description of biocatalysis as well the kinetic and thermodynamic properties of their mechanisms. There exists a diversity of computational methods allowing the investigation of specific enzymatic properties. Small or large density functional theory models allow the comparison of a plethora of mechanistic reactive species and divergent catalytic pathways. Molecular docking can model different substrate conformations embedded within enzyme active sites and determine those with optimal binding affinities. Molecular dynamics simulations provide insights into the dynamics and roles of active site components as well as the interactions between substrate and enzymes. Hybrid quantum mechanical/molecular mechanical (QM/MM) can model reactions in active sites while considering steric and electrostatic contributions provided by the surrounding environment. Using previous studies done within our group, on OvoA, EgtB, ThrRS, LuxS and MsrA enzymatic systems, we will review how these methods can be used either independently or cooperatively to get insights into enzymatic catalysis. PMID:24384841

Ensemble Sampling vs. Time Sampling in Molecular Dynamics Simulations of Thermal Conductivity

DOE PAGES

Gordiz, Kiarash; Singh, David J.; Henry, Asegun

2015-01-29

In this report we compare time sampling and ensemble averaging as two different methods available for phase space sampling. For the comparison, we calculate thermal conductivities of solid argon and silicon structures, using equilibrium molecular dynamics. We introduce two different schemes for the ensemble averaging approach, and show that both can reduce the total simulation time as compared to time averaging. It is also found that velocity rescaling is an efficient mechanism for phase space exploration. Although our methodology is tested using classical molecular dynamics, the ensemble generation approaches may find their greatest utility in computationally expensive simulations such asmore » first principles molecular dynamics. For such simulations, where each time step is costly, time sampling can require long simulation times because each time step must be evaluated sequentially and therefore phase space averaging is achieved through sequential operations. On the other hand, with ensemble averaging, phase space sampling can be achieved through parallel operations, since each ensemble is independent. For this reason, particularly when using massively parallel architectures, ensemble sampling can result in much shorter simulation times and exhibits similar overall computational effort.« less

Computer Simulation of the Elastic Properties of Titanium Alloys for Medical Applications

NASA Astrophysics Data System (ADS)

Estevez, Elsa Paz; Burganova, R. M.; Lysogorskii, Yu. V.

2016-09-01

Results of a computer simulation of the elastic properties of α+β- and β-titanium alloys, used for medical purposes, within the framework of the molecular-dynamics method are presented. It is shown that β-titanium alloys are best suited for the use as bone implants because of their small moduli of elasticity. The advisability of the use of the molecular-dynamics method for the study of the elastic properties of titanium alloys, serving as bone implants, is demonstrated.

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein.

PubMed

Xu, Mingyuan; Zhu, Tong; Zhang, John Z H

2018-01-01

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA) 9 -NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

Using Multistate Reweighting to Rapidly and Efficiently Explore Molecular Simulation Parameters Space for Nonbonded Interactions.

PubMed

Paliwal, Himanshu; Shirts, Michael R

2013-11-12

Multistate reweighting methods such as the multistate Bennett acceptance ratio (MBAR) can predict free energies and expectation values of thermodynamic observables at poorly sampled or unsampled thermodynamic states using simulations performed at only a few sampled states combined with single point energy reevaluations of these samples at the unsampled states. In this study, we demonstrate the power of this general reweighting formalism by exploring the effect of simulation parameters controlling Coulomb and Lennard-Jones cutoffs on free energy calculations and other observables. Using multistate reweighting, we can quickly identify, with very high sensitivity, the computationally least expensive nonbonded parameters required to obtain a specified accuracy in observables compared to the answer obtained using an expensive "gold standard" set of parameters. We specifically examine free energy estimates of three molecular transformations in a benchmark molecular set as well as the enthalpy of vaporization of TIP3P. The results demonstrates the power of this multistate reweighting approach for measuring changes in free energy differences or other estimators with respect to simulation or model parameters with very high precision and/or very low computational effort. The results also help to identify which simulation parameters affect free energy calculations and provide guidance to determine which simulation parameters are both appropriate and computationally efficient in general.

A computational study to identify the key residues of peroxisome proliferator-activated receptor gamma in the interactions with its antagonists.

PubMed

Sharifi, Tayebeh; Ghayeb, Yousef

2018-05-01

Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors, PPARα, PPARβ, and PPARγ, which mediate the effects of lipidic ligands at the transcriptional level. Among these, the PPARγ has been known to regulate adipocyte differentiation, fatty acid storage and glucose metabolism, and is a target of antidiabetic drugs. In this work, the interactions between PPARγ and its six known antagonists were investigated using computational methods such as molecular docking, molecular dynamics (MD) simulations, and the hybrid quantum mechanics/molecular mechanics (QM/MM). The binding energies evaluated by molecular docking varied between -22.59 and -35.15 kJ mol - 1 . In addition, MD simulations were performed to investigate the binding modes and PPARγ conformational changes upon binding of antagonists. Analysis of the root-mean-square fluctuations (RMSF) of backbone atoms shows that H3 of PPARγ has a higher mobility in the absence of antagonists and moderate conformational changes were observed. The interaction energies between antagonists and each PPARγ residue involved in the interactions were studied by QM/MM calculations. These calculations reveal that antagonists with different structures show different interaction energies with the same residue of PPARγ. Therefore, it can be concluded that the key residues vary depending on the structure of the ligand, which binds to PPARγ.

Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

NASA Astrophysics Data System (ADS)

Bolhuis, Peter

Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

PubMed Central

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic. PMID:26177039

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.

PubMed

Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro

2015-01-01

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Comprehensive Experimental and Computational Spectroscopic Study of Hexacyanoferrate Complexes in Water: From Infrared to X-ray Wavelengths.

PubMed

Ross, Matthew; Andersen, Amity; Fox, Zachary W; Zhang, Yu; Hong, Kiryong; Lee, Jae-Hyuk; Cordones, Amy; March, Anne Marie; Doumy, Gilles; Southworth, Stephen H; Marcus, Matthew A; Schoenlein, Robert W; Mukamel, Shaul; Govind, Niranjan; Khalil, Munira

2018-05-17

We present a joint experimental and computational study of the hexacyanoferrate aqueous complexes at equilibrium in the 250 meV to 7.15 keV regime. The experiments and the computations include the vibrational spectroscopy of the cyanide ligands, the valence electronic absorption spectra, and Fe 1s core hole spectra using element-specific-resonant X-ray absorption and emission techniques. Density functional theory-based quantum mechanics/molecular mechanics molecular dynamics simulations are performed to generate explicit solute-solvent configurations, which serve as inputs for the spectroscopy calculations of the experiments spanning the IR to X-ray wavelengths. The spectroscopy simulations are performed at the same level of theory across this large energy window, which allows for a systematic comparison of the effects of explicit solute-solvent interactions in the vibrational, valence electronic, and core-level spectra of hexacyanoferrate complexes in water. Although the spectroscopy of hexacyanoferrate complexes in solution has been the subject of several studies, most of the previous works have focused on a narrow energy window and have not accounted for explicit solute-solvent interactions in their spectroscopy simulations. In this work, we focus our analysis on identifying how the local solvation environment around the hexacyanoferrate complexes influences the intensity and line shape of specific spectroscopic features in the UV/vis, X-ray absorption, and valence-to-core X-ray emission spectra. The identification of these features and their relationship to solute-solvent interactions is important because hexacyanoferrate complexes serve as model systems for understanding the photochemistry and photophysics of a large class of Fe(II) and Fe(III) complexes in solution.

Parsing partial molar volumes of small molecules: a molecular dynamics study.

PubMed

Patel, Nisha; Dubins, David N; Pomès, Régis; Chalikian, Tigran V

2011-04-28

We used molecular dynamics (MD) simulations in conjunction with the Kirkwood-Buff theory to compute the partial molar volumes for a number of small solutes of various chemical natures. We repeated our computations using modified pair potentials, first, in the absence of the Coulombic term and, second, in the absence of the Coulombic and the attractive Lennard-Jones terms. Comparison of our results with experimental data and the volumetric results of Monte Carlo simulation with hard sphere potentials and scaled particle theory-based computations led us to conclude that, for small solutes, the partial molar volume computed with the Lennard-Jones potential in the absence of the Coulombic term nearly coincides with the cavity volume. On the other hand, MD simulations carried out with the pair interaction potentials containing only the repulsive Lennard-Jones term produce unrealistically large partial molar volumes of solutes that are close to their excluded volumes. Our simulation results are in good agreement with the reported schemes for parsing partial molar volume data on small solutes. In particular, our determined interaction volumes() and the thickness of the thermal volume for individual compounds are in good agreement with empirical estimates. This work is the first computational study that supports and lends credence to the practical algorithms of parsing partial molar volume data that are currently in use for molecular interpretations of volumetric data.

Structure and dynamics of human vimentin intermediate filament dimer and tetramer in explicit and implicit solvent models.

PubMed

Qin, Zhao; Buehler, Markus J

2011-01-01

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, 9). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non-alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms.

Full Quantum Dynamics Simulation of a Realistic Molecular System Using the Adaptive Time-Dependent Density Matrix Renormalization Group Method.

PubMed

Yao, Yao; Sun, Ke-Wei; Luo, Zhen; Ma, Haibo

2018-01-18

The accurate theoretical interpretation of ultrafast time-resolved spectroscopy experiments relies on full quantum dynamics simulations for the investigated system, which is nevertheless computationally prohibitive for realistic molecular systems with a large number of electronic and/or vibrational degrees of freedom. In this work, we propose a unitary transformation approach for realistic vibronic Hamiltonians, which can be coped with using the adaptive time-dependent density matrix renormalization group (t-DMRG) method to efficiently evolve the nonadiabatic dynamics of a large molecular system. We demonstrate the accuracy and efficiency of this approach with an example of simulating the exciton dissociation process within an oligothiophene/fullerene heterojunction, indicating that t-DMRG can be a promising method for full quantum dynamics simulation in large chemical systems. Moreover, it is also shown that the proper vibronic features in the ultrafast electronic process can be obtained by simulating the two-dimensional (2D) electronic spectrum by virtue of the high computational efficiency of the t-DMRG method.

How to identify dislocations in molecular dynamics simulations?

NASA Astrophysics Data System (ADS)

Li, Duo; Wang, FengChao; Yang, ZhenYu; Zhao, YaPu

2014-12-01

Dislocations are of great importance in revealing the underlying mechanisms of deformed solid crystals. With the development of computational facilities and technologies, the observations of dislocations at atomic level through numerical simulations are permitted. Molecular dynamics (MD) simulation suggests itself as a powerful tool for understanding and visualizing the creation of dislocations as well as the evolution of crystal defects. However, the numerical results from the large-scale MD simulations are not very illuminating by themselves and there exist various techniques for analyzing dislocations and the deformed crystal structures. Thus, it is a big challenge for the beginners in this community to choose a proper method to start their investigations. In this review, we summarized and discussed up to twelve existing structure characterization methods in MD simulations of deformed crystal solids. A comprehensive comparison was made between the advantages and disadvantages of these typical techniques. We also examined some of the recent advances in the dynamics of dislocations related to the hydraulic fracturing. It was found that the dislocation emission has a significant effect on the propagation and bifurcation of the crack tip in the hydraulic fracturing.

Incremental update of electrostatic interactions in adaptively restrained particle simulations.

PubMed

Edorh, Semeho Prince A; Redon, Stéphane

2018-04-06

The computation of long-range potentials is one of the demanding tasks in Molecular Dynamics. During the last decades, an inventive panoply of methods was developed to reduce the CPU time of this task. In this work, we propose a fast method dedicated to the computation of the electrostatic potential in adaptively restrained systems. We exploit the fact that, in such systems, only some particles are allowed to move at each timestep. We developed an incremental algorithm derived from a multigrid-based alternative to traditional Fourier-based methods. Our algorithm was implemented inside LAMMPS, a popular molecular dynamics simulation package. We evaluated the method on different systems. We showed that the new algorithm's computational complexity scales with the number of active particles in the simulated system, and is able to outperform the well-established Particle Particle Particle Mesh (P3M) for adaptively restrained simulations. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules

PubMed Central

2014-01-01

Background Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme. Results We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength. Conclusions An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials. PMID:25045516

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

Converging ligand-binding free energies obtained with free-energy perturbations at the quantum mechanical level.

PubMed

Olsson, Martin A; Söderhjelm, Pär; Ryde, Ulf

2016-06-30

In this article, the convergence of quantum mechanical (QM) free-energy simulations based on molecular dynamics simulations at the molecular mechanics (MM) level has been investigated. We have estimated relative free energies for the binding of nine cyclic carboxylate ligands to the octa-acid deep-cavity host, including the host, the ligand, and all water molecules within 4.5 Å of the ligand in the QM calculations (158-224 atoms). We use single-step exponential averaging (ssEA) and the non-Boltzmann Bennett acceptance ratio (NBB) methods to estimate QM/MM free energy with the semi-empirical PM6-DH2X method, both based on interaction energies. We show that ssEA with cumulant expansion gives a better convergence and uses half as many QM calculations as NBB, although the two methods give consistent results. With 720,000 QM calculations per transformation, QM/MM free-energy estimates with a precision of 1 kJ/mol can be obtained for all eight relative energies with ssEA, showing that this approach can be used to calculate converged QM/MM binding free energies for realistic systems and large QM partitions. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Integration of Molecular Dynamics Based Predictions into the Optimization of De Novo Protein Designs: Limitations and Benefits.

PubMed

Carvalho, Henrique F; Barbosa, Arménio J M; Roque, Ana C A; Iranzo, Olga; Branco, Ricardo J F

2017-01-01

Recent advances in de novo protein design have gained considerable insight from the intrinsic dynamics of proteins, based on the integration of molecular dynamics simulations protocols on the state-of-the-art de novo protein design protocols used nowadays. With this protocol we illustrate how to set up and run a molecular dynamics simulation followed by a functional protein dynamics analysis. New users will be introduced to some useful open-source computational tools, including the GROMACS molecular dynamics simulation software package and ProDy for protein structural dynamics analysis.

Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains

NASA Technical Reports Server (NTRS)

Glaessgen, E. H.; Saether, E.; Yamakov, V.

2008-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.

Thermodynamic and transport properties of nitrogen fluid: Molecular theory and computer simulations

NASA Astrophysics Data System (ADS)

Eskandari Nasrabad, A.; Laghaei, R.

2018-04-01

Computer simulations and various theories are applied to compute the thermodynamic and transport properties of nitrogen fluid. To model the nitrogen interaction, an existing potential in the literature is modified to obtain a close agreement between the simulation results and experimental data for the orthobaric densities. We use the Generic van der Waals theory to calculate the mean free volume and apply the results within the modified Cohen-Turnbull relation to obtain the self-diffusion coefficient. Compared to experimental data, excellent results are obtained via computer simulations for the orthobaric densities, the vapor pressure, the equation of state, and the shear viscosity. We analyze the results of the theory and computer simulations for the various thermophysical properties.

Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

NASA Astrophysics Data System (ADS)

Endah Saraswati, Teguh; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

2017-01-01

Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH3). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory.

CARES/LIFE Software Commercialization

NASA Technical Reports Server (NTRS)

1995-01-01

The NASA Lewis Research Center has entered into a letter agreement with BIOSYM Technologies Inc. (now merged with Molecular Simulations Inc. (MSI)). Under this agreement, NASA will provide a developmental copy of the CARES/LIFE computer program to BIOSYM for evaluation. This computer code predicts the time-dependent reliability of a thermomechanically loaded component. BIOSYM will become familiar with CARES/LIFE, provide results of computations useful in validating the code, evaluate it for potential commercialization, and submit suggestions for improvements or extensions to the code or its documentation. If BIOSYM/Molecular Simulations reaches a favorable evaluation of CARES/LIFE, NASA will enter into negotiations for a cooperative agreement with BIOSYM/Molecular Simulations to further develop the code--adding features such as a user-friendly interface and other improvements. This agreement would give BIOSYM intellectual property rights in the modified codes, which they could protect and then commercialize. NASA would provide BIOSYM with the NASA-developed source codes and would agree to cooperate with BIOSYM in further developing the code. In return, NASA would receive certain use rights in the modified CARES/LIFE program. Presently BIOSYM Technologies Inc. has been involved with integration issues concerning its merger with Molecular Simulations Inc., since both companies used to compete in the computational chemistry market, and to some degree, in the materials market. Consequently, evaluation of the CARES/LIFE software is on hold for a month or two while the merger is finalized. Their interest in CARES continues, however, and they expect to get back to the evaluation by early November 1995.

Site Identification by Ligand Competitive Saturation (SILCS) Simulations for Fragment-Based Drug Design

PubMed Central

Faller, Christina E.; Raman, E. Prabhu; MacKerell, Alexander D.; Guvench, Olgun

2015-01-01

Fragment-based drug design (FBDD) involves screening low molecular weight molecules (“fragments”) that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind non-overlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy. The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is “soaked” in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called “FragMaps” can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine “Grid Free Energies (GFEs),” which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities. PMID:25709034

Investigations of glass structure using fluorescence line narrowing and moleuclar dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, M.J.; Brawer, S.A.

1982-07-02

The local structure at individual ion sites in simple and multicomponent glasses is simulated using methods of molecular dynamics. Computer simulations of fluoroberyllate glasses predict a range of ion separations and coordination numbers that increases with increasing complexity of the glass composition. This occurs at both glass forming and glass modifying cation sites. Laser-induced fluorescence line-narrowing techniques provide a unique probe of the local environments of selected subsets of ions and are used to measure site to site variations in the electronic energy levels and transition probabilities of rare earth ions. These and additional results from EXAFS, neutron and x-raymore » diffraction, and NMR experiments are compared with simulated glass structures.« less

Molecular Dynamics Simulations of Nucleic Acids. From Tetranucleotides to the Ribosome.

PubMed

Šponer, Jiří; Banáš, Pavel; Jurečka, Petr; Zgarbová, Marie; Kührová, Petra; Havrila, Marek; Krepl, Miroslav; Stadlbauer, Petr; Otyepka, Michal

2014-05-15

We present a brief overview of explicit solvent molecular dynamics (MD) simulations of nucleic acids. We explain physical chemistry limitations of the simulations, namely, the molecular mechanics (MM) force field (FF) approximation and limited time scale. Further, we discuss relations and differences between simulations and experiments, compare standard and enhanced sampling simulations, discuss the role of starting structures, comment on different versions of nucleic acid FFs, and relate MM computations with contemporary quantum chemistry. Despite its limitations, we show that MD is a powerful technique for studying the structural dynamics of nucleic acids with a fast growing potential that substantially complements experimental results and aids their interpretation.

Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

PubMed

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.

Early Experiences Porting the NAMD and VMD Molecular Simulation and Analysis Software to GPU-Accelerated OpenPOWER Platforms

PubMed Central

Stone, John E.; Hynninen, Antti-Pekka; Phillips, James C.; Schulten, Klaus

2017-01-01

All-atom molecular dynamics simulations of biomolecules provide a powerful tool for exploring the structure and dynamics of large protein complexes within realistic cellular environments. Unfortunately, such simulations are extremely demanding in terms of their computational requirements, and they present many challenges in terms of preparation, simulation methodology, and analysis and visualization of results. We describe our early experiences porting the popular molecular dynamics simulation program NAMD and the simulation preparation, analysis, and visualization tool VMD to GPU-accelerated OpenPOWER hardware platforms. We report our experiences with compiler-provided autovectorization and compare with hand-coded vector intrinsics for the POWER8 CPU. We explore the performance benefits obtained from unique POWER8 architectural features such as 8-way SMT and its value for particular molecular modeling tasks. Finally, we evaluate the performance of several GPU-accelerated molecular modeling kernels and relate them to other hardware platforms. PMID:29202130

Hyperfine excitation of C2H in collisions with ortho- and para-H2

NASA Astrophysics Data System (ADS)

Dagdigian, Paul J.

2018-06-01

Accurate estimation of the abundance of the ethynyl (C2H) radical requires accurate radiative and collisional rate coefficients. Hyperfine-resolved rate coefficients for (de-)excitation of C2H in collisions with ortho- and para-H2 are presented in this work. These rate coefficients were computed in time-independent close-coupling quantum scattering calculations that employed a potential energy surface recently computed at the coupled-clusters level of theory that describes the interaction of C2H with H2. Rate coefficients for temperatures from 10 to 300 K were computed for all transitions among the first 40 hyperfine energy levels of C2H in collisions with ortho- and para-H2. These rate coefficients were employed in simple radiative transfer calculations to simulate the excitation of C2H in typical molecular clouds.

Non-Adiabatic Molecular Dynamics Methods for Materials Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Furche, Filipp; Parker, Shane M.; Muuronen, Mikko J.

2017-04-04

The flow of radiative energy in light-driven materials such as photosensitizer dyes or photocatalysts is governed by non-adiabatic transitions between electronic states and cannot be described within the Born-Oppenheimer approximation commonly used in electronic structure theory. The non-adiabatic molecular dynamics (NAMD) methods based on Tully surface hopping and time-dependent density functional theory developed in this project have greatly extended the range of molecular materials that can be tackled by NAMD simulations. New algorithms to compute molecular excited state and response properties efficiently were developed. Fundamental limitations of common non-linear response methods were discovered and characterized. Methods for accurate computations ofmore » vibronic spectra of materials such as black absorbers were developed and applied. It was shown that open-shell TDDFT methods capture bond breaking in NAMD simulations, a longstanding challenge for single-reference molecular dynamics simulations. The methods developed in this project were applied to study the photodissociation of acetaldehyde and revealed that non-adiabatic effects are experimentally observable in fragment kinetic energy distributions. Finally, the project enabled the first detailed NAMD simulations of photocatalytic water oxidation by titania nanoclusters, uncovering the mechanism of this fundamentally important reaction for fuel generation and storage.« less

A multilevel-skin neighbor list algorithm for molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Zhao, Mingcan; Hou, Chaofeng; Ge, Wei

2018-01-01

Searching of the interaction pairs and organization of the interaction processes are important steps in molecular dynamics (MD) algorithms and are critical to the overall efficiency of the simulation. Neighbor lists are widely used for these steps, where thicker skin can reduce the frequency of list updating but is discounted by more computation in distance check for the particle pairs. In this paper, we propose a new neighbor-list-based algorithm with a precisely designed multilevel skin which can reduce unnecessary computation on inter-particle distances. The performance advantages over traditional methods are then analyzed against the main simulation parameters on Intel CPUs and MICs (many integrated cores), and are clearly demonstrated. The algorithm can be generalized for various discrete simulations using neighbor lists.

Implementation of the force decomposition machine for molecular dynamics simulations.

PubMed

Borštnik, Urban; Miller, Benjamin T; Brooks, Bernard R; Janežič, Dušanka

2012-09-01

We present the design and implementation of the force decomposition machine (FDM), a cluster of personal computers (PCs) that is tailored to running molecular dynamics (MD) simulations using the distributed diagonal force decomposition (DDFD) parallelization method. The cluster interconnect architecture is optimized for the communication pattern of the DDFD method. Our implementation of the FDM relies on standard commodity components even for networking. Although the cluster is meant for DDFD MD simulations, it remains general enough for other parallel computations. An analysis of several MD simulation runs on both the FDM and a standard PC cluster demonstrates that the FDM's interconnect architecture provides a greater performance compared to a more general cluster interconnect. Copyright © 2012 Elsevier Inc. All rights reserved.

wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

PubMed Central

De Paris, Renata; Frantz, Fábio A.; Norberto de Souza, Osmar; Ruiz, Duncan D. A.

2013-01-01

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. PMID:23691504

Dissociation and Internal Excitation of Molecular Nitrogen Due to N + N2 Collisions Using Direct Molecular Simulation

NASA Technical Reports Server (NTRS)

Grover, Maninder S.; Schwartzentruber, Thomas E.; Jaffe, Richard L.

2017-01-01

In this work we present a molecular level study of N2+N collisions, focusing on excitation of internal energy modes and non-equilibrium dissociation. The computation technique used here is the direct molecular simulation (DMS) method and the molecular interactions have been modeled using an ab-initio potential energy surface (PES) developed at NASA's Ames Research Center. We carried out vibrational excitation calculations between 5000K and 30000K and found that the characteristic vibrational excitation time for the N + N2 process was an order of magnitude lower than that predicted by the Millikan and White correlation. It is observed that during vibrational excitation the high energy tail of the vibrational energy distribution gets over populated first and the lower energy levels get populated as the system evolves. It is found that the non-equilibrium dissociation rate coefficients for the N + N2 process are larger than those for the N2 + N2 process. This is attributed to the non-equilibrium vibrational energy distributions for the N + N2 process being less depleted than that for the N2 +N2 process. For an isothermal simulation we find that the probability of dissociation goes as 1/T(sub tr) for molecules with internal energy (epsilon(sub int)) less than approximately 9.9eV, while for molecules with epsilon (sub int) greater than 9.9eV the dissociation probability was weakly dependent on translational temperature of the system. We compared non-equilibrium dissociation rate coefficients and characteristic vibrational excitation times obtained by using the ab-initio PES developed at NASA's Ames Research Center to those obtained by using an ab-initio PES developed at the University of Minnesota. Good agreement was found between the macroscopic properties and molecular level description of the system obtained by using the two PESs.

Characterizing rare-event property distributions via replicate molecular dynamics simulations of proteins.

PubMed

Krishnan, Ranjani; Walton, Emily B; Van Vliet, Krystyn J

2009-11-01

As computational resources increase, molecular dynamics simulations of biomolecules are becoming an increasingly informative complement to experimental studies. In particular, it has now become feasible to use multiple initial molecular configurations to generate an ensemble of replicate production-run simulations that allows for more complete characterization of rare events such as ligand-receptor unbinding. However, there are currently no explicit guidelines for selecting an ensemble of initial configurations for replicate simulations. Here, we use clustering analysis and steered molecular dynamics simulations to demonstrate that the configurational changes accessible in molecular dynamics simulations of biomolecules do not necessarily correlate with observed rare-event properties. This informs selection of a representative set of initial configurations. We also employ statistical analysis to identify the minimum number of replicate simulations required to sufficiently sample a given biomolecular property distribution. Together, these results suggest a general procedure for generating an ensemble of replicate simulations that will maximize accurate characterization of rare-event property distributions in biomolecules.

Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models

NASA Astrophysics Data System (ADS)

Zang, Tianwu

Predicting the 3-dimentional structure of protein has been a major interest in the modern computational biology. While lots of successful methods can generate models with 3˜5A root-mean-square deviation (RMSD) from the solution, the progress of refining these models is quite slow. It is therefore urgently needed to develop effective methods to bring low-quality models to higher-accuracy ranges (e.g., less than 2 A RMSD). In this thesis, I present several novel computational methods to address the high-accuracy refinement problem. First, an enhanced sampling method, named parallel continuous simulated tempering (PCST), is developed to accelerate the molecular dynamics (MD) simulation. Second, two energy biasing methods, Structure-Based Model (SBM) and Ensemble-Based Model (EBM), are introduced to perform targeted sampling around important conformations. Third, a three-step method is developed to blindly select high-quality models along the MD simulation. These methods work together to make significant refinement of low-quality models without any knowledge of the solution. The effectiveness of these methods is examined in different applications. Using the PCST-SBM method, models with higher global distance test scores (GDT_TS) are generated and selected in the MD simulation of 18 targets from the refinement category of the 10th Critical Assessment of Structure Prediction (CASP10). In addition, in the refinement test of two CASP10 targets using the PCST-EBM method, it is indicated that EBM may bring the initial model to even higher-quality levels. Furthermore, a multi-round refinement protocol of PCST-SBM improves the model quality of a protein to the level that is sufficient high for the molecular replacement in X-ray crystallography. Our results justify the crucial position of enhanced sampling in the protein structure prediction and demonstrate that a considerable improvement of low-accuracy structures is still achievable with current force fields.

First principle chemical kinetics in zeolites: the methanol-to-olefin process as a case study.

PubMed

Van Speybroeck, Veronique; De Wispelaere, Kristof; Van der Mynsbrugge, Jeroen; Vandichel, Matthias; Hemelsoet, Karen; Waroquier, Michel

2014-11-07

To optimally design next generation catalysts a thorough understanding of the chemical phenomena at the molecular scale is a prerequisite. Apart from qualitative knowledge on the reaction mechanism, it is also essential to be able to predict accurate rate constants. Molecular modeling has become a ubiquitous tool within the field of heterogeneous catalysis. Herein, we review current computational procedures to determine chemical kinetics from first principles, thus by using no experimental input and by modeling the catalyst and reacting species at the molecular level. Therefore, we use the methanol-to-olefin (MTO) process as a case study to illustrate the various theoretical concepts. This process is a showcase example where rational design of the catalyst was for a long time performed on the basis of trial and error, due to insufficient knowledge of the mechanism. For theoreticians the MTO process is particularly challenging as the catalyst has an inherent supramolecular nature, for which not only the Brønsted acidic site is important but also organic species, trapped in the zeolite pores, must be essentially present during active catalyst operation. All these aspects give rise to specific challenges for theoretical modeling. It is shown that present computational techniques have matured to a level where accurate enthalpy barriers and rate constants can be predicted for reactions occurring at a single active site. The comparison with experimental data such as apparent kinetic data for well-defined elementary reactions has become feasible as current computational techniques also allow predicting adsorption enthalpies with reasonable accuracy. Real catalysts are truly heterogeneous in a space- and time-like manner. Future theory developments should focus on extending our view towards phenomena occurring at longer length and time scales and integrating information from various scales towards a unified understanding of the catalyst. Within this respect molecular dynamics methods complemented with additional techniques to simulate rare events are now gradually making their entrance within zeolite catalysis. Recent applications have already given a flavor of the benefit of such techniques to simulate chemical reactions in complex molecular environments.

Molecular dynamics simulations of the dielectric properties of fructose aqueous solutions

NASA Astrophysics Data System (ADS)

Sonoda, Milton T.; Elola, M. Dolores; Skaf, Munir S.

2016-10-01

The static dielectric permittivity and dielectric relaxation properties of fructose aqueous solutions of different concentrations ranging from 1.0 to 4.0 mol l-1 are investigated by means of molecular dynamics simulations. The contributions from intra- and interspecies molecular correlations were computed individually for both the static and frequency-dependent dielectric properties, and the results were compared with the available experimental data. Simulation results in the time- and frequency-domains were analyzed and indicate that the presence of fructose has little effect on the position of the fast, high-frequency (>500 cm-1) components of the dielectric response spectrum. The low-frequency (<0.1 cm-1) components, however, are markedly influenced by sugar concentration. Our analysis indicates that fructose-fructose and fructose-water interactions strongly affect the rotational-diffusion regime of molecular motions in the solutions. Increasing fructose concentration not only enhances sugar-sugar and sugar-water low frequency contributions to the dielectric loss spectrum but also slows down the reorientational dynamics of water molecules. These results are consistent with previous computer simulations carried out for other disaccharide aqueous solutions.

Temperature specification in atomistic molecular dynamics and its impact on simulation efficacy

NASA Astrophysics Data System (ADS)

Ocaya, R. O.; Terblans, J. J.

2017-10-01

Temperature is a vital thermodynamical function for physical systems. Knowledge of system temperature permits assessment of system ergodicity, entropy, system state and stability. Rapid theoretical and computational developments in the fields of condensed matter physics, chemistry, material science, molecular biology, nanotechnology and others necessitate clarity in the temperature specification. Temperature-based materials simulations, both standalone and distributed computing, are projected to grow in prominence over diverse research fields. In this article we discuss the apparent variability of temperature modeling formalisms used currently in atomistic molecular dynamics simulations, with respect to system energetics,dynamics and structural evolution. Commercial simulation programs, which by nature are heuristic, do not openly discuss this fundamental question. We address temperature specification in the context of atomistic molecular dynamics. We define a thermostat at 400K relative to a heat bath at 300K firstly using a modified ab-initio Newtonian method, and secondly using a Monte-Carlo method. The thermostatic vacancy formation and cohesion energies, equilibrium lattice constant for FCC copper is then calculated. Finally we compare and contrast the results.

Heterogeneity in homogeneous nucleation from billion-atom molecular dynamics simulation of solidification of pure metal.

PubMed

Shibuta, Yasushi; Sakane, Shinji; Miyoshi, Eisuke; Okita, Shin; Takaki, Tomohiro; Ohno, Munekazu

2017-04-05

Can completely homogeneous nucleation occur? Large scale molecular dynamics simulations performed on a graphics-processing-unit rich supercomputer can shed light on this long-standing issue. Here, a billion-atom molecular dynamics simulation of homogeneous nucleation from an undercooled iron melt reveals that some satellite-like small grains surrounding previously formed large grains exist in the middle of the nucleation process, which are not distributed uniformly. At the same time, grains with a twin boundary are formed by heterogeneous nucleation from the surface of the previously formed grains. The local heterogeneity in the distribution of grains is caused by the local accumulation of the icosahedral structure in the undercooled melt near the previously formed grains. This insight is mainly attributable to the multi-graphics processing unit parallel computation combined with the rapid progress in high-performance computational environments.Nucleation is a fundamental physical process, however it is a long-standing issue whether completely homogeneous nucleation can occur. Here the authors reveal, via a billion-atom molecular dynamics simulation, that local heterogeneity exists during homogeneous nucleation in an undercooled iron melt.

Effect of Computer Simulations at the Particulate and Macroscopic Levels on Students' Understanding of the Particulate Nature of Matter

ERIC Educational Resources Information Center

Tang, Hui; Abraham, Michael R.

2016-01-01

Computer-based simulations can help students visualize chemical representations and understand chemistry concepts, but simulations at different levels of representation may vary in effectiveness on student learning. This study investigated the influence of computer activities that simulate chemical reactions at different levels of representation…

Exploring transmembrane transport through alpha-hemolysin with grid-steered molecular dynamics.

PubMed

Wells, David B; Abramkina, Volha; Aksimentiev, Aleksei

2007-09-28

The transport of biomolecules across cell boundaries is central to cellular function. While structures of many membrane channels are known, the permeation mechanism is known only for a select few. Molecular dynamics (MD) is a computational method that can provide an accurate description of permeation events at the atomic level, which is required for understanding the transport mechanism. However, due to the relatively short time scales accessible to this method, it is of limited utility. Here, we present a method for all-atom simulation of electric field-driven transport of large solutes through membrane channels, which in tens of nanoseconds can provide a realistic account of a permeation event that would require a millisecond simulation using conventional MD. In this method, the average distribution of the electrostatic potential in a membrane channel under a transmembrane bias of interest is determined first from an all-atom MD simulation. This electrostatic potential, defined on a grid, is subsequently applied to a charged solute to steer its permeation through the membrane channel. We apply this method to investigate permeation of DNA strands, DNA hairpins, and alpha-helical peptides through alpha-hemolysin. To test the accuracy of the method, we computed the relative permeation rates of DNA strands having different sequences and global orientations. The results of the G-SMD simulations were found to be in good agreement in experiment.

In silico modelling of drug–polymer interactions for pharmaceutical formulations

PubMed Central

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

Modeling molecular mechanisms in the axon

NASA Astrophysics Data System (ADS)

de Rooij, R.; Miller, K. E.; Kuhl, E.

2017-03-01

Axons are living systems that display highly dynamic changes in stiffness, viscosity, and internal stress. However, the mechanistic origin of these phenomenological properties remains elusive. Here we establish a computational mechanics model that interprets cellular-level characteristics as emergent properties from molecular-level events. We create an axon model of discrete microtubules, which are connected to neighboring microtubules via discrete crosslinking mechanisms that obey a set of simple rules. We explore two types of mechanisms: passive and active crosslinking. Our passive and active simulations suggest that the stiffness and viscosity of the axon increase linearly with the crosslink density, and that both are highly sensitive to the crosslink detachment and reattachment times. Our model explains how active crosslinking with dynein motors generates internal stresses and actively drives axon elongation. We anticipate that our model will allow us to probe a wide variety of molecular phenomena—both in isolation and in interaction—to explore emergent cellular-level features under physiological and pathological conditions.

Development of the Next Generation of Biogeochemistry Simulations Using EMSL's NWChem Molecular Modeling Software

NASA Astrophysics Data System (ADS)

Bylaska, E. J.; Kowalski, K.; Apra, E.; Govind, N.; Valiev, M.

2017-12-01

Methods of directly simulating the behavior of complex strongly interacting atomic systems (molecular dynamics, Monte Carlo) have provided important insight into the behavior of nanoparticles, biogeochemical systems, mineral/fluid systems, nanoparticles, actinide systems and geofluids. The limitation of these methods to even wider applications is the difficulty of developing accurate potential interactions in these systems at the molecular level that capture their complex chemistry. The well-developed tools of quantum chemistry and physics have been shown to approach the accuracy required. However, despite the continuous effort being put into improving their accuracy and efficiency, these tools will be of little value to condensed matter problems without continued improvements in techniques to traverse and sample the high-dimensional phase space needed to span the ˜10^12 time scale differences between molecular simulation and chemical events. In recent years, we have made considerable progress in developing electronic structure and AIMD methods tailored to treat biochemical and geochemical problems, including very efficient implementations of many-body methods, fast exact exchange methods, electron-transfer methods, excited state methods, QM/MM, and new parallel algorithms that scale to +100,000 cores. The poster will focus on the fundamentals of these methods and the realities in terms of system size, computational requirements and simulation times that are required for their application to complex biogeochemical systems.

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.

Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations.

PubMed

Knapp, Bernhard; Demharter, Samuel; Esmaielbeiki, Reyhaneh; Deane, Charlotte M

2015-11-01

The interaction between T-cell receptors (TCRs) and major histocompatibility complex (MHC)-bound epitopes is one of the most important processes in the adaptive human immune response. Several hypotheses on TCR triggering have been proposed. Many of them involve structural and dynamical adjustments in the TCR/peptide/MHC interface. Molecular Dynamics (MD) simulations are a computational technique that is used to investigate structural dynamics at atomic resolution. Such simulations are used to improve understanding of signalling on a structural level. Here we review how MD simulations of the TCR/peptide/MHC complex have given insight into immune system reactions not achievable with current experimental methods. Firstly, we summarize methods of TCR/peptide/MHC complex modelling and TCR/peptide/MHC MD trajectory analysis methods. Then we classify recently published simulations into categories and give an overview of approaches and results. We show that current studies do not come to the same conclusions about TCR/peptide/MHC interactions. This discrepancy might be caused by too small sample sizes or intrinsic differences between each interaction process. As computational power increases future studies will be able to and should have larger sample sizes, longer runtimes and additional parts of the immunological synapse included. © The Author 2015. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.

NASA Astrophysics Data System (ADS)

Elliott, William Dewey

1995-01-01

A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over several simulation timesteps. One MD application described here highlights the utility of including long range contributions to Lennard-Jones potential in constant pressure simulations. Another application shows the time dependence of long range forces in a multiple time step MD simulation.

Substructured multibody molecular dynamics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grest, Gary Stephen; Stevens, Mark Jackson; Plimpton, Steven James

2006-11-01

We have enhanced our parallel molecular dynamics (MD) simulation software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator, lammps.sandia.gov) to include many new features for accelerated simulation including articulated rigid body dynamics via coupling to the Rensselaer Polytechnic Institute code POEMS (Parallelizable Open-source Efficient Multibody Software). We use new features of the LAMMPS software package to investigate rhodopsin photoisomerization, and water model surface tension and capillary waves at the vapor-liquid interface. Finally, we motivate the recipes of MD for practitioners and researchers in numerical analysis and computational mechanics.

How does ytterbium chloride interact with DMPC bilayers? A computational and experimental study.

PubMed

Gonzalez, Miguel A; Barriga, Hanna M G; Richens, Joanna L; Law, Robert V; O'Shea, Paul; Bresme, Fernando

2017-03-29

Lanthanide salts have been studied for many years, primarily in Nuclear Magnetic Resonance (NMR) experiments of mixed lipid-protein systems and more recently to study lipid flip-flop in model membrane systems. It is well recognised that lanthanide salts can influence the behaviour of both lipid and protein systems, however a full molecular level description of lipid-lanthanide interactions is still outstanding. Here we present a study of lanthanide-bilayer interactions, using molecular dynamics computer simulations, fluorescence electrostatic potential experiments and nuclear magnetic resonance. Computer simulations reveal the microscopic structure of DMPC lipid bilayers in the presence of Yb 3+ , and a surprising ability of the membranes to adsorb significant concentrations of Yb 3+ without disrupting the overall membrane structure. At concentrations commonly used in NMR experiments, Yb 3+ ions bind strongly to 5 lipids, inducing a small decrease of the area per lipid and a slight increase of the ordering of the aliphatic chains and the bilayer thickness. The area compressibility modulus increases by a factor of two, with respect to the free-salt case, showing that Yb 3+ ions make the bilayer more rigid. These modifications of the bilayer properties should be taken into account in the interpretation of NMR experiments.

Computer Simulations and Theoretical Studies of Complex Systems: from complex fluids to frustrated magnets

NASA Astrophysics Data System (ADS)

Choi, Eunsong

Computer simulations are an integral part of research in modern condensed matter physics; they serve as a direct bridge between theory and experiment by systemactically applying a microscopic model to a collection of particles that effectively imitate a macroscopic system. In this thesis, we study two very differnt condensed systems, namely complex fluids and frustrated magnets, primarily by simulating classical dynamics of each system. In the first part of the thesis, we focus on ionic liquids (ILs) and polymers--the two complementary classes of materials that can be combined to provide various unique properties. The properties of polymers/ILs systems, such as conductivity, viscosity, and miscibility, can be fine tuned by choosing an appropriate combination of cations, anions, and polymers. However, designing a system that meets a specific need requires a concrete understanding of physics and chemistry that dictates a complex interplay between polymers and ionic liquids. In this regard, molecular dynamics (MD) simulation is an efficient tool that provides a molecular level picture of such complex systems. We study the behavior of Poly (ethylene oxide) (PEO) and the imidazolium based ionic liquids, using MD simulations and statistical mechanics. We also discuss our efforts to develop reliable and efficient classical force-fields for PEO and the ionic liquids. The second part is devoted to studies on geometrically frustrated magnets. In particular, a microscopic model, which gives rise to an incommensurate spiral magnetic ordering observed in a pyrochlore antiferromagnet is investigated. The validation of the model is made via a comparison of the spin-wave spectra with the neutron scattering data. Since the standard Holstein-Primakoff method is difficult to employ in such a complex ground state structure with a large unit cell, we carry out classical spin dynamics simulations to compute spin-wave spectra directly from the Fourier transform of spin trajectories. We conclude the study by showing an excellent agreement between the simulation and the experiment.

Unveiling the Atomic-Level Determinants of Acylase-Ligand Complexes: An Experimental and Computational Study.

PubMed

Mollica, Luca; Conti, Gianluca; Pollegioni, Loredano; Cavalli, Andrea; Rosini, Elena

2015-10-26

The industrial production of higher-generation semisynthetic cephalosporins starts from 7-aminocephalosporanic acid (7-ACA), which is obtained by deacylation of the naturally occurring antibiotic cephalosporin C (CephC). The enzymatic process in which CephC is directly converted into 7-ACA by a cephalosporin C acylase has attracted industrial interest because of the prospects of simplifying the process and reducing costs. We recently enhanced the catalytic efficiency on CephC of a glutaryl acylase from Pseudomonas N176 (named VAC) by a protein engineering approach and solved the crystal structures of wild-type VAC and the H57βS-H70βS VAC double variant. In the present work, experimental measurements on several CephC derivatives and six VAC variants were carried out, and the binding of ligands into the VAC active site was investigated at an atomistic level by means of molecular docking and molecular dynamics simulations and analyzed on the basis of the molecular geometry of encounter complex formation and protein-ligand potential of mean force profiles. The observed significant correlation between the experimental data and estimated binding energies highlights the predictive power of our computational method to identify the ligand binding mode. The present experimental-computational study is well-suited both to provide deep insight into the reaction mechanism of cephalosporin C acylase and to improve the efficiency of the corresponding industrial process.

Clustering molecular dynamics trajectories for optimizing docking experiments.

PubMed

De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Removing systematic errors in interionic potentials of mean force computed in molecular simulations using reaction-field-based electrostatics

PubMed Central

Baumketner, Andrij

2009-01-01

The performance of reaction-field methods to treat electrostatic interactions is tested in simulations of ions solvated in water. The potential of mean force between sodium chloride pair of ions and between side chains of lysine and aspartate are computed using umbrella sampling and molecular dynamics simulations. It is found that in comparison with lattice sum calculations, the charge-group-based approaches to reaction-field treatments produce a large error in the association energy of the ions that exhibits strong systematic dependence on the size of the simulation box. The atom-based implementation of the reaction field is seen to (i) improve the overall quality of the potential of mean force and (ii) remove the dependence on the size of the simulation box. It is suggested that the atom-based truncation be used in reaction-field simulations of mixed media. PMID:19292522

Final report for Conference Support Grant "From Computational Biophysics to Systems Biology - CBSB12"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansmann, Ulrich H.E.

2012-07-02

This report summarizes the outcome of the international workshop From Computational Biophysics to Systems Biology (CBSB12) which was held June 3-5, 2012, at the University of Tennessee Conference Center in Knoxville, TN, and supported by DOE through the Conference Support Grant 120174. The purpose of CBSB12 was to provide a forum for the interaction between a data-mining interested systems biology community and a simulation and first-principle oriented computational biophysics/biochemistry community. CBSB12 was the sixth in a series of workshops of the same name organized in recent years, and the second that has been held in the USA. As in previousmore » years, it gave researchers from physics, biology, and computer science an opportunity to acquaint each other with current trends in computational biophysics and systems biology, to explore venues of cooperation, and to establish together a detailed understanding of cells at a molecular level. The conference grant of $10,000 was used to cover registration fees and provide travel fellowships to selected students and postdoctoral scientists. By educating graduate students and providing a forum for young scientists to perform research into the working of cells at a molecular level, the workshop adds to DOE's mission of paving the way to exploit the abilities of living systems to capture, store and utilize energy.« less

Ab initio molecular dynamics with nuclear quantum effects at classical cost: Ring polymer contraction for density functional theory.

PubMed

Marsalek, Ondrej; Markland, Thomas E

2016-02-07

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to accurately describe systems containing light nuclei. However, path integral simulations have traditionally required a computational cost around two orders of magnitude greater than treating the nuclei classically, making them prohibitively costly for most applications. Here we show that the cost of path integral simulations can be dramatically reduced by extending our ring polymer contraction approach to ab initio molecular dynamics simulations. By using density functional tight binding as a reference system, we show that our ring polymer contraction scheme gives rapid and systematic convergence to the full path integral density functional theory result. We demonstrate the efficiency of this approach in ab initio simulations of liquid water and the reactive protonated and deprotonated water dimer systems. We find that the vast majority of the nuclear quantum effects are accurately captured using contraction to just the ring polymer centroid, which requires the same number of density functional theory calculations as a classical simulation. Combined with a multiple time step scheme using the same reference system, which allows the time step to be increased, this approach is as fast as a typical classical ab initio molecular dynamics simulation and 35× faster than a full path integral calculation, while still exactly including the quantum sampling of nuclei. This development thus offers a route to routinely include nuclear quantum effects in ab initio molecular dynamics simulations at negligible computational cost.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.

Logic circuits based on molecular spider systems.

PubMed

Mo, Dandan; Lakin, Matthew R; Stefanovic, Darko

2016-08-01

Spatial locality brings the advantages of computation speed-up and sequence reuse to molecular computing. In particular, molecular walkers that undergo localized reactions are of interest for implementing logic computations at the nanoscale. We use molecular spider walkers to implement logic circuits. We develop an extended multi-spider model with a dynamic environment wherein signal transmission is triggered via localized reactions, and use this model to implement three basic gates (AND, OR, NOT) and a cascading mechanism. We develop an algorithm to automatically generate the layout of the circuit. We use a kinetic Monte Carlo algorithm to simulate circuit computations, and we analyze circuit complexity: our design scales linearly with formula size and has a logarithmic time complexity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Efficient compression of molecular dynamics trajectory files.

PubMed

Marais, Patrick; Kenwood, Julian; Smith, Keegan Carruthers; Kuttel, Michelle M; Gain, James

2012-10-15

We investigate whether specific properties of molecular dynamics trajectory files can be exploited to achieve effective file compression. We explore two classes of lossy, quantized compression scheme: "interframe" predictors, which exploit temporal coherence between successive frames in a simulation, and more complex "intraframe" schemes, which compress each frame independently. Our interframe predictors are fast, memory-efficient and well suited to on-the-fly compression of massive simulation data sets, and significantly outperform the benchmark BZip2 application. Our schemes are configurable: atomic positional accuracy can be sacrificed to achieve greater compression. For high fidelity compression, our linear interframe predictor gives the best results at very little computational cost: at moderate levels of approximation (12-bit quantization, maximum error ≈ 10(-2) Å), we can compress a 1-2 fs trajectory file to 5-8% of its original size. For 200 fs time steps-typically used in fine grained water diffusion experiments-we can compress files to ~25% of their input size, still substantially better than BZip2. While compression performance degrades with high levels of quantization, the simulation error is typically much greater than the associated approximation error in such cases. Copyright © 2012 Wiley Periodicals, Inc.

Turbocharged molecular discovery of OLED emitters: from high-throughput quantum simulation to highly efficient TADF devices

NASA Astrophysics Data System (ADS)

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Ha, Dong-Gwang; Einzinger, Markus; Wu, Tony; Baldo, Marc A.; Aspuru-Guzik, Alán.

2016-09-01

Discovering new OLED emitters requires many experiments to synthesize candidates and test performance in devices. Large scale computer simulation can greatly speed this search process but the problem remains challenging enough that brute force application of massive computing power is not enough to successfully identify novel structures. We report a successful High Throughput Virtual Screening study that leveraged a range of methods to optimize the search process. The generation of candidate structures was constrained to contain combinatorial explosion. Simulations were tuned to the specific problem and calibrated with experimental results. Experimentalists and theorists actively collaborated such that experimental feedback was regularly utilized to update and shape the computational search. Supervised machine learning methods prioritized candidate structures prior to quantum chemistry simulation to prevent wasting compute on likely poor performers. With this combination of techniques, each multiplying the strength of the search, this effort managed to navigate an area of molecular space and identify hundreds of promising OLED candidate structures. An experimentally validated selection of this set shows emitters with external quantum efficiencies as high as 22%.

Predictive role of computer simulation in assessing signaling pathways of crizotinib-treated A549 lung cancer cells.

PubMed

Xia, Pu; Mou, Fei-Fei; Wang, Li-Wei

2012-01-01

Non-small-cell lung cancer (NSCLC) is a leading cause of cancer deaths worldwide. Crizotinib has been approved by the U.S. Food and Drug Administration for the treatment of patients with advanced NSCLC. However, understanding of mechanisms of action is still limited. In our studies, we confirmed crizotinib-induced apoptosis in A549 lung cancer cells. In order to assess mechanisms, small molecular docking technology was used as a preliminary simulation of signaling pathways. Interesting, our results of experiments were consistent with the results of computer simulation. This indicates that small molecular docking technology should find wide use for its reliability and convenience.

Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations.

PubMed

Ható, Zoltán; Valiskó, Mónika; Kristóf, Tamás; Gillespie, Dirk; Boda, Dezsö

2017-07-21

In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore at two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs. output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at the details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the z-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

Impact of anisotropy on the structure and dynamics of ionic liquids: A computational study of 1-butyl-3-methyl-imidazolium trifluoroacetate

NASA Astrophysics Data System (ADS)

Schröder, C.; Rudas, T.; Neumayr, G.; Gansterer, W.; Steinhauser, O.

2007-07-01

The complex ionic network of 1-butyl-3-methyl-imidazolium trifluoroacetate was simulated by means of the molecular dynamics methods over a time period of 100ns. The influence of the anisotropy of the shape and charge distribution of both the cations and the anions on the local (molecular) and global (collective) structure and dynamics is analyzed. The distance-dependent g coefficients of the orientational probability function g(r,Ω) were found to be an excellent way to interpret local structure. Thereby, the combination and interrelation of individual g coefficients elucidate the mutual orientation. Dynamics at the molecular level is characterized by the time correlation function of the center-of-mass corrected molecular dipole moment μcm. Upon uniting the set of molecular dipoles to a single collective rotational dipole moment, MD, dynamics on a global level is studied. Decomposing into subsets of cations and anions respective self terms as well as the prominent cross term can be extracted. This decomposition also enables a detailed peak assignment in dielectric spectra.

Impact of anisotropy on the structure and dynamics of ionic liquids: a computational study of 1-butyl-3-methyl-imidazolium trifluoroacetate.

PubMed

Schröder, C; Rudas, T; Neumayr, G; Gansterer, W; Steinhauser, O

2007-07-28

The complex ionic network of 1-butyl-3-methyl-imidazolium trifluoroacetate was simulated by means of the molecular dynamics methods over a time period of 100 ns. The influence of the anisotropy of the shape and charge distribution of both the cations and the anions on the local (molecular) and global (collective) structure and dynamics is analyzed. The distance-dependent g coefficients of the orientational probability function g(r,Omega) were found to be an excellent way to interpret local structure. Thereby, the combination and interrelation of individual g coefficients elucidate the mutual orientation. Dynamics at the molecular level is characterized by the time correlation function of the center-of-mass corrected molecular dipole moment mucm. Upon uniting the set of molecular dipoles to a single collective rotational dipole moment, MD, dynamics on a global level is studied. Decomposing into subsets of cations and anions respective self terms as well as the prominent cross term can be extracted. This decomposition also enables a detailed peak assignment in dielectric spectra.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

27ps DFT Molecular Dynamics Simulation of a-maltose: A Reduced Basis Set Study.

USDA-ARS?s Scientific Manuscript database

DFT molecular dynamics simulations are time intensive when carried out on carbohydrates such as alpha-maltose, requiring up to three or more weeks on a fast 16-processor computer to obtain just 5ps of constant energy dynamics. In a recent publication [1] forces for dynamics were generated from B3LY...

An Educational Software for Simulating the Sample Size of Molecular Marker Experiments

ERIC Educational Resources Information Center

Helms, T. C.; Doetkott, C.

2007-01-01

We developed educational software to show graduate students how to plan molecular marker experiments. These computer simulations give the students feedback on the precision of their experiments. The objective of the software was to show students using a hands-on approach how: (1) environmental variation influences the range of the estimates of the…

GPU-Accelerated Molecular Modeling Coming Of Age

PubMed Central

Stone, John E.; Hardy, David J.; Ufimtsev, Ivan S.

2010-01-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. PMID:20675161

GPU-accelerated molecular modeling coming of age.

PubMed

Stone, John E; Hardy, David J; Ufimtsev, Ivan S; Schulten, Klaus

2010-09-01

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks. (c) 2010 Elsevier Inc. All rights reserved.

Solid-liquid phase coexistence of alkali nitrates from molecular dynamics simulations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jayaraman, Saivenkataraman

2010-03-01

Alkali nitrate eutectic mixtures are finding application as industrial heat transfer fluids in concentrated solar power generation systems. An important property for such applications is the melting point, or phase coexistence temperature. We have computed melting points for lithium, sodium and potassium nitrate from molecular dynamics simulations using a recently developed method, which uses thermodynamic integration to compute the free energy difference between the solid and liquid phases. The computed melting point for NaNO3 was within 15K of its experimental value, while for LiNO3 and KNO3, the computed melting points were within 100K of the experimental values [4]. We aremore » currently extending the approach to calculate melting temperatures for binary mixtures of lithium and sodium nitrate.« less

Computer Series, 29: Bits and Pieces, 10.

ERIC Educational Resources Information Center

Moore, John W., Ed.

1982-01-01

Describes computer programs (available from authors) including molecular input to computer, programs for quantum chemistry, library orientation to technical literature, plotting potentiometric titration data, simulating oscilloscope curves, organic qualitative analysis with dynamic graphics, extended Huckel calculations, and calculator programs…

First-principles simulations of heat transport

NASA Astrophysics Data System (ADS)

Puligheddu, Marcello; Gygi, Francois; Galli, Giulia

2017-11-01

Advances in understanding heat transport in solids were recently reported by both experiment and theory. However an efficient and predictive quantum simulation framework to investigate thermal properties of solids, with the same complexity as classical simulations, has not yet been developed. Here we present a method to compute the thermal conductivity of solids by performing ab initio molecular dynamics at close to equilibrium conditions, which only requires calculations of first-principles trajectories and atomic forces, thus avoiding direct computation of heat currents and energy densities. In addition the method requires much shorter sequential simulation times than ordinary molecular dynamics techniques, making it applicable within density functional theory. We discuss results for a representative oxide, MgO, at different temperatures and for ordered and nanostructured morphologies, showing the performance of the method in different conditions.

A collaborative visual analytics suite for protein folding research.

PubMed

Harvey, William; Park, In-Hee; Rübel, Oliver; Pascucci, Valerio; Bremer, Peer-Timo; Li, Chenglong; Wang, Yusu

2014-09-01

Molecular dynamics (MD) simulation is a crucial tool for understanding principles behind important biochemical processes such as protein folding and molecular interaction. With the rapidly increasing power of modern computers, large-scale MD simulation experiments can be performed regularly, generating huge amounts of MD data. An important question is how to analyze and interpret such massive and complex data. One of the (many) challenges involved in analyzing MD simulation data computationally is the high-dimensionality of such data. Given a massive collection of molecular conformations, researchers typically need to rely on their expertise and prior domain knowledge in order to retrieve certain conformations of interest. It is not easy to make and test hypotheses as the data set as a whole is somewhat "invisible" due to its high dimensionality. In other words, it is hard to directly access and examine individual conformations from a sea of molecular structures, and to further explore the entire data set. There is also no easy and convenient way to obtain a global view of the data or its various modalities of biochemical information. To this end, we present an interactive, collaborative visual analytics tool for exploring massive, high-dimensional molecular dynamics simulation data sets. The most important utility of our tool is to provide a platform where researchers can easily and effectively navigate through the otherwise "invisible" simulation data sets, exploring and examining molecular conformations both as a whole and at individual levels. The visualization is based on the concept of a topological landscape, which is a 2D terrain metaphor preserving certain topological and geometric properties of the high dimensional protein energy landscape. In addition to facilitating easy exploration of conformations, this 2D terrain metaphor also provides a platform where researchers can visualize and analyze various properties (such as contact density) overlayed on the top of the 2D terrain. Finally, the software provides a collaborative environment where multiple researchers can assemble observations and biochemical events into storyboards and share them in real time over the Internet via a client-server architecture. The software is written in Scala and runs on the cross-platform Java Virtual Machine. Binaries and source code are available at http://www.aylasoftware.org and have been released under the GNU General Public License. Copyright © 2014 Elsevier Inc. All rights reserved.

A fast recursive algorithm for molecular dynamics simulation

NASA Technical Reports Server (NTRS)

Jain, A.; Vaidehi, N.; Rodriguez, G.

1993-01-01

The present recursive algorithm for solving molecular systems' dynamical equations of motion employs internal variable models that reduce such simulations' computation time by an order of magnitude, relative to Cartesian models. Extensive use is made of spatial operator methods recently developed for analysis and simulation of the dynamics of multibody systems. A factor-of-450 speedup over the conventional O(N-cubed) algorithm is demonstrated for the case of a polypeptide molecule with 400 residues.

Molecular dynamics simulations of methane hydrate decomposition.

PubMed

Myshakin, Evgeniy M; Jiang, Hao; Warzinski, Robert P; Jordan, Kenneth D

2009-03-12

Molecular dynamics simulations have been carried out to study decomposition of methane hydrate at different cage occupancies. The decomposition rate is found to depend sensitively on the hydration number. The rate of the destruction of the cages displays Arrhenius behavior, consistent with an activated mechanism. During the simulations, reversible formation of partial water cages around methane molecules in the liquid was observed at the interface at temperatures above the computed hydrate decomposition temperature.

Simulated quantum computation of molecular energies.

PubMed

Aspuru-Guzik, Alán; Dutoi, Anthony D; Love, Peter J; Head-Gordon, Martin

2005-09-09

The calculation time for the energy of atoms and molecules scales exponentially with system size on a classical computer but polynomially using quantum algorithms. We demonstrate that such algorithms can be applied to problems of chemical interest using modest numbers of quantum bits. Calculations of the water and lithium hydride molecular ground-state energies have been carried out on a quantum computer simulator using a recursive phase-estimation algorithm. The recursive algorithm reduces the number of quantum bits required for the readout register from about 20 to 4. Mappings of the molecular wave function to the quantum bits are described. An adiabatic method for the preparation of a good approximate ground-state wave function is described and demonstrated for a stretched hydrogen molecule. The number of quantum bits required scales linearly with the number of basis functions, and the number of gates required grows polynomially with the number of quantum bits.

ms2: A molecular simulation tool for thermodynamic properties

NASA Astrophysics Data System (ADS)

Deublein, Stephan; Eckl, Bernhard; Stoll, Jürgen; Lishchuk, Sergey V.; Guevara-Carrion, Gabriela; Glass, Colin W.; Merker, Thorsten; Bernreuther, Martin; Hasse, Hans; Vrabec, Jadran

2011-11-01

This work presents the molecular simulation program ms2 that is designed for the calculation of thermodynamic properties of bulk fluids in equilibrium consisting of small electro-neutral molecules. ms2 features the two main molecular simulation techniques, molecular dynamics (MD) and Monte-Carlo. It supports the calculation of vapor-liquid equilibria of pure fluids and multi-component mixtures described by rigid molecular models on the basis of the grand equilibrium method. Furthermore, it is capable of sampling various classical ensembles and yields numerous thermodynamic properties. To evaluate the chemical potential, Widom's test molecule method and gradual insertion are implemented. Transport properties are determined by equilibrium MD simulations following the Green-Kubo formalism. ms2 is designed to meet the requirements of academia and industry, particularly achieving short response times and straightforward handling. It is written in Fortran90 and optimized for a fast execution on a broad range of computer architectures, spanning from single processor PCs over PC-clusters and vector computers to high-end parallel machines. The standard Message Passing Interface (MPI) is used for parallelization and ms2 is therefore easily portable to different computing platforms. Feature tools facilitate the interaction with the code and the interpretation of input and output files. The accuracy and reliability of ms2 has been shown for a large variety of fluids in preceding work. Program summaryProgram title:ms2 Catalogue identifier: AEJF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Special Licence supplied by the authors No. of lines in distributed program, including test data, etc.: 82 794 No. of bytes in distributed program, including test data, etc.: 793 705 Distribution format: tar.gz Programming language: Fortran90 Computer: The simulation tool ms2 is usable on a wide variety of platforms, from single processor machines over PC-clusters and vector computers to vector-parallel architectures. (Tested with Fortran compilers: gfortran, Intel, PathScale, Portland Group and Sun Studio.) Operating system: Unix/Linux, Windows Has the code been vectorized or parallelized?: Yes. Message Passing Interface (MPI) protocol Scalability. Excellent scalability up to 16 processors for molecular dynamics and >512 processors for Monte-Carlo simulations. RAM:ms2 runs on single processors with 512 MB RAM. The memory demand rises with increasing number of processors used per node and increasing number of molecules. Classification: 7.7, 7.9, 12 External routines: Message Passing Interface (MPI) Nature of problem: Calculation of application oriented thermodynamic properties for rigid electro-neutral molecules: vapor-liquid equilibria, thermal and caloric data as well as transport properties of pure fluids and multi-component mixtures. Solution method: Molecular dynamics, Monte-Carlo, various classical ensembles, grand equilibrium method, Green-Kubo formalism. Restrictions: No. The system size is user-defined. Typical problems addressed by ms2 can be solved by simulating systems containing typically 2000 molecules or less. Unusual features: Feature tools are available for creating input files, analyzing simulation results and visualizing molecular trajectories. Additional comments: Sample makefiles for multiple operation platforms are provided. Documentation is provided with the installation package and is available at http://www.ms-2.de. Running time: The running time of ms2 depends on the problem set, the system size and the number of processes used in the simulation. Running four processes on a "Nehalem" processor, simulations calculating VLE data take between two and twelve hours, calculating transport properties between six and 24 hours.

Molecular-level Simulations of Shock Generation and Propagation in Polyurea

DTIC Science & Technology

2011-01-26

homepage: www.e lsev ier .com/ locate /msea Molecular-level simulations of shock generation and propagation in polyurea M. Grujicica,∗, B. Pandurangana... Polyurea Shock-wave generation and propagation Molecular-level calculations a b s t r a c t A non-equilibrium molecular dynamics method is employed in order...to study various phenomena accompanying the generation and propagation of shock waves in polyurea (a micro-phase segregated elastomer). Several

Oxygen transport properties estimation by DSMC-CT simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruno, Domenico; Frezzotti, Aldo; Ghiroldi, Gian Pietro

Coupling DSMC simulations with classical trajectories calculations is emerging as a powerful tool to improve predictive capabilities of computational rarefied gas dynamics. The considerable increase of computational effort outlined in the early application of the method (Koura,1997) can be compensated by running simulations on massively parallel computers. In particular, GPU acceleration has been found quite effective in reducing computing time (Ferrigni,2012; Norman et al.,2013) of DSMC-CT simulations. The aim of the present work is to study rarefied Oxygen flows by modeling binary collisions through an accurate potential energy surface, obtained by molecular beams scattering (Aquilanti, et al.,1999). The accuracy ofmore » the method is assessed by calculating molecular Oxygen shear viscosity and heat conductivity following three different DSMC-CT simulation methods. In the first one, transport properties are obtained from DSMC-CT simulations of spontaneous fluctuation of an equilibrium state (Bruno et al, Phys. Fluids, 23, 093104, 2011). In the second method, the collision trajectory calculation is incorporated in a Monte Carlo integration procedure to evaluate the Taxman’s expressions for the transport properties of polyatomic gases (Taxman,1959). In the third, non-equilibrium zero and one-dimensional rarefied gas dynamic simulations are adopted and the transport properties are computed from the non-equilibrium fluxes of momentum and energy. The three methods provide close values of the transport properties, their estimated statistical error not exceeding 3%. The experimental values are slightly underestimated, the percentage deviation being, again, few percent.« less

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

NASA Astrophysics Data System (ADS)

Negre, Christian

2017-06-01

A new framework for extended Lagrangian first-principles molecular dynamics simulations is presented, which overcomes shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while maintaining important advantages of the unified extended Lagrangian formulation of density functional theory pioneered by Car and Parrinello three decades ago. The new framework allows, for the first time, energy conserving, linear-scaling Born-Oppenheimer molecular dynamics simulations, which is necessary to study larger and more realistic systems over longer simulation times than previously possible. Expensive, self-consinstent-field optimizations are avoided and normal integration time steps of regular, direct Born-Oppenheimer molecular dynamics can be used. Linear scaling electronic structure theory is presented using a graph-based approach that is ideal for parallel calculations on hybrid computer platforms. For the first time, quantum based Born-Oppenheimer molecular dynamics simulation is becoming a practically feasible approach in simulations of +100,000 atoms-representing a competitive alternative to classical polarizable force field methods. In collaboration with: Anders Niklasson, Los Alamos National Laboratory.

Building better water models using the shape of the charge distribution of a water molecule

NASA Astrophysics Data System (ADS)

Dharmawardhana, Chamila Chathuranga; Ichiye, Toshiko

2017-11-01

The unique properties of liquid water apparently arise from more than just the tetrahedral bond angle between the nuclei of a water molecule since simple three-site models of water are poor at mimicking these properties in computer simulations. Four- and five-site models add partial charges on dummy sites and are better at modeling these properties, which suggests that the shape of charge distribution is important. Since a multipole expansion of the electrostatic potential describes a charge distribution in an orthogonal basis set that is exact in the limit of infinite order, multipoles may be an even better way to model the charge distribution. In particular, molecular multipoles up to the octupole centered on the oxygen appear to describe the electrostatic potential from electronic structure calculations better than four- and five-site models, and molecular multipole models give better agreement with the temperature and pressure dependence of many liquid state properties of water while retaining the computational efficiency of three-site models. Here, the influence of the shape of the molecular charge distribution on liquid state properties is examined by correlating multipoles of non-polarizable water models with their liquid state properties in computer simulations. This will aid in the development of accurate water models for classical simulations as well as in determining the accuracy needed in quantum mechanical/molecular mechanical studies and ab initio molecular dynamics simulations of water. More fundamentally, this will lead to a greater understanding of how the charge distribution of a water molecule leads to the unique properties of liquid water. In particular, these studies indicate that p-orbital charge out of the molecular plane is important.

On the hydration of subnanometric antifouling organosilane adlayers: a molecular dynamics simulation.

PubMed

Sheikh, Sonia; Blaszykowski, Christophe; Nolan, Robert; Thompson, Damien; Thompson, Michael

2015-01-01

The connection between antifouling and surface hydration is a fascinating but daunting question to answer. Herein, we use molecular dynamics (MD) computer simulations to gain further insight into the role of surface functionalities in the molecular-level structuration of water (surface kosmotropicity)--within and atop subnanometric organosilane adlayers that were shown in previous experimental work to display varied antifouling behavior. Our simulations support the hypothesized intimate link between surface hydration and antifouling, in particular the importance of both internal and interfacial hydrophilicity and kosmotropicity. The antifouling mechanism is also discussed in terms of surface dehydration energy and water dynamicity (lability and mobility), notably the crucial requirement for clustered water molecules to remain tightly bound for extensive periods of time--i.e. exhibit slow exchange dynamics. A substrate effect on surface hydration, which would also participate in endowing antifouling adlayers with hydrogel-like characteristics, is also proposed. In contrast, the role of adlayer flexibility, if any, is assigned a secondary role in these ultrathin structures made of short building blocks. The conclusions from this work are well in line with those previously drawn in the literature. Copyright © 2014 Elsevier Inc. All rights reserved.

Computer Simulations of Small Molecules in Membranes: Insights from Computer Simulations into the Interactions of Small Molecules with Lipid Bilayers

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; New, Michael H.; Schweighofer, Karl; Wilson, Michael A.; DeVincenzi, Donald L. (Technical Monitor)

2000-01-01

Two of Ernest Overton's lasting contributions to biology are the Meyer-Overton relationship between the potency of an anesthetic and its solubility in oil, and the Overton rule which relates the permeability of a membrane to the oil-water partition coefficient of the permeating molecule. A growing body of experimental evidence, however, cannot be reconciled with these theories. In particular, the molecular nature of membranes, unknown to Overton, needs to be included in any description of these phenomena. Computer simulations are ideally suited for providing atomic-level information about the behavior of small molecules in membranes. The authors discuss simulation studies relevant to Overton's ideas. Through simulations it was found that anesthetics tend to concentrate at interfaces and their anesthetic potency correlates better with solubility at the water-membrane interface than with solubility in oil. Simulation studies of membrane permeation revealed the anisotropic nature of the membranes, as evidenced, for example, by the highly nonuniform distribution of free volume in the bilayer. This, in turn, influences the diffusion rates of solutes, which increase with the depth in the membrane. Small solutes tend to move by hopping between voids in the bilayer, and this hopping motion may be responsible for the deviation from the Overton rule of the permeation rates of these molecules.

Geochemical Reaction Mechanism Discovery from Molecular Simulation

DOE PAGES

Stack, Andrew G.; Kent, Paul R. C.

2014-11-10

Methods to explore reactions using computer simulation are becoming increasingly quantitative, versatile, and robust. In this review, a rationale for how molecular simulation can help build better geochemical kinetics models is first given. We summarize some common methods that geochemists use to simulate reaction mechanisms, specifically classical molecular dynamics and quantum chemical methods and discuss their strengths and weaknesses. Useful tools such as umbrella sampling and metadynamics that enable one to explore reactions are discussed. Several case studies wherein geochemists have used these tools to understand reaction mechanisms are presented, including water exchange and sorption on aqueous species and mineralmore » surfaces, surface charging, crystal growth and dissolution, and electron transfer. The impact that molecular simulation has had on our understanding of geochemical reactivity are highlighted in each case. In the future, it is anticipated that molecular simulation of geochemical reaction mechanisms will become more commonplace as a tool to validate and interpret experimental data, and provide a check on the plausibility of geochemical kinetic models.« less

Computational Materials Research

NASA Technical Reports Server (NTRS)

Hinkley, Jeffrey A. (Editor); Gates, Thomas S. (Editor)

1996-01-01

Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.

Simulation of aerosol flow interaction with a solid body on molecular level

NASA Astrophysics Data System (ADS)

Amelyushkin, Ivan A.; Stasenko, Albert L.

2018-05-01

Physico-mathematical models and numerical algorithm of two-phase flow interaction with a solid body are developed. Results of droplet motion and its impingement upon a rough surface in real gas boundary layer simulation on the molecular level obtained via molecular dynamics technique are presented.

Optimization and benchmarking of a perturbative Metropolis Monte Carlo quantum mechanics/molecular mechanics program

NASA Astrophysics Data System (ADS)

Feldt, Jonas; Miranda, Sebastião; Pratas, Frederico; Roma, Nuno; Tomás, Pedro; Mata, Ricardo A.

2017-12-01

In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.

Optimization and benchmarking of a perturbative Metropolis Monte Carlo quantum mechanics/molecular mechanics program.

PubMed

Feldt, Jonas; Miranda, Sebastião; Pratas, Frederico; Roma, Nuno; Tomás, Pedro; Mata, Ricardo A

2017-12-28

In this work, we present an optimized perturbative quantum mechanics/molecular mechanics (QM/MM) method for use in Metropolis Monte Carlo simulations. The model adopted is particularly tailored for the simulation of molecular systems in solution but can be readily extended to other applications, such as catalysis in enzymatic environments. The electrostatic coupling between the QM and MM systems is simplified by applying perturbation theory to estimate the energy changes caused by a movement in the MM system. This approximation, together with the effective use of GPU acceleration, leads to a negligible added computational cost for the sampling of the environment. Benchmark calculations are carried out to evaluate the impact of the approximations applied and the overall computational performance.

The Use of Multiscale Molecular Simulations in Understanding a Relationship between the Structure and Function of Biological Systems of the Brain: The Application to Monoamine Oxidase Enzymes

PubMed Central

Vianello, Robert; Domene, Carmen; Mavri, Janez

2016-01-01

HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic activities and their inhibition. As an illustrative example, the later will focus on the monoamine oxidase family of enzymes, which catalyze the degradation of amine neurotransmitters in various parts of the brain, the imbalance of which is associated with the development and progression of a range of neurodegenerative disorders. Inhibitors that act mainly on MAO A are used in the treatment of depression, due to their ability to raise serotonin concentrations, while MAO B inhibitors decrease dopamine degradation and improve motor control in patients with Parkinson disease. Our results give strong support that both MAO isoforms, A and B, operate through the hydride transfer mechanism. Relevance of MAO catalyzed reactions and MAO inhibition in the context of neurodegeneration will be discussed. PMID:27471444

Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads.

PubMed

Stone, John E; Hallock, Michael J; Phillips, James C; Peterson, Joseph R; Luthey-Schulten, Zaida; Schulten, Klaus

2016-05-01

Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers.

Molecular Dynamics, Monte Carlo Simulations, and Langevin Dynamics: A Computational Review

PubMed Central

Paquet, Eric; Viktor, Herna L.

2015-01-01

Macromolecular structures, such as neuraminidases, hemagglutinins, and monoclonal antibodies, are not rigid entities. Rather, they are characterised by their flexibility, which is the result of the interaction and collective motion of their constituent atoms. This conformational diversity has a significant impact on their physicochemical and biological properties. Among these are their structural stability, the transport of ions through the M2 channel, drug resistance, macromolecular docking, binding energy, and rational epitope design. To assess these properties and to calculate the associated thermodynamical observables, the conformational space must be efficiently sampled and the dynamic of the constituent atoms must be simulated. This paper presents algorithms and techniques that address the abovementioned issues. To this end, a computational review of molecular dynamics, Monte Carlo simulations, Langevin dynamics, and free energy calculation is presented. The exposition is made from first principles to promote a better understanding of the potentialities, limitations, applications, and interrelations of these computational methods. PMID:25785262

An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses

NASA Technical Reports Server (NTRS)

Saether, E.; Glaessgen, E.H.; Yamakov, V.

2008-01-01

The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

A New Concurrent Multiscale Methodology for Coupling Molecular Dynamics and Finite Element Analyses

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin; Saether, Erik; Glaessgen, Edward H/.

2008-01-01

The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

A Computational Model Predicting Disruption of Blood Vessel Development

PubMed Central

Kleinstreuer, Nicole; Dix, David; Rountree, Michael; Baker, Nancy; Sipes, Nisha; Reif, David; Spencer, Richard; Knudsen, Thomas

2013-01-01

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology. PMID:23592958

Rapid communication: Computational simulation and analysis of a candidate for the design of a novel silk-based biopolymer.

PubMed

Golas, Ewa I; Czaplewski, Cezary

2014-09-01

This work theoretically investigates the mechanical properties of a novel silk-derived biopolymer as polymerized in silico from sericin and elastin-like monomers. Molecular Dynamics simulations and Steered Molecular Dynamics were the principal computational methods used, the latter of which applies an external force onto the system and thereby enables an observation of its response to stress. The models explored herein are single-molecule approximations, and primarily serve as tools in a rational design process for the preliminary assessment of properties in a new material candidate. © 2014 Wiley Periodicals, Inc.

eScience for molecular-scale simulations and the eMinerals project.

PubMed

Salje, E K H; Artacho, E; Austen, K F; Bruin, R P; Calleja, M; Chappell, H F; Chiang, G-T; Dove, M T; Frame, I; Goodwin, A L; Kleese van Dam, K; Marmier, A; Parker, S C; Pruneda, J M; Todorov, I T; Trachenko, K; Tyer, R P; Walker, A M; White, T O H

2009-03-13

We review the work carried out within the eMinerals project to develop eScience solutions that facilitate a new generation of molecular-scale simulation work. Technological developments include integration of compute and data systems, developing of collaborative frameworks and new researcher-friendly tools for grid job submission, XML data representation, information delivery, metadata harvesting and metadata management. A number of diverse science applications will illustrate how these tools are being used for large parameter-sweep studies, an emerging type of study for which the integration of computing, data and collaboration is essential.

Direct simulation of high-vorticity gas flows

NASA Technical Reports Server (NTRS)

Bird, G. A.

1987-01-01

The computational limitations associated with the molecular dynamics (MD) method and the direct simulation Monte Carlo (DSMC) method are reviewed in the context of the computation of dilute gas flows with high vorticity. It is concluded that the MD method is generally limited to the dense gas case in which the molecular diameter is one-tenth or more of the mean free path. It is shown that the cell size in DSMC calculations should be small in comparison with the mean free path, and that this may be facilitated by a new subcell procedure for the selection of collision partners.

Computer simulations of local anesthetic mechanisms: Quantum chemical investigation of procaine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Jeremy C; Bondar, A.N.; Suhai, Sandor

2007-02-01

A description at the atomic level of detail of the interaction between local anesthetics, lipid membranes and membrane proteins, is essential for understanding the mechanism of local anesthesia. The importance of performing computer simulations to decipher the mechanism of local anesthesia is discussed here in the context of the current status of understanding of the local anesthetics action. As a first step towards accurate simulations of the interaction between local anesthetics, proteins, lipid and water molecules, here we use quantum mechanical methods to assess the charge distribution and structural properties of procaine in the presence and in the absence ofmore » water molecules. The calculations indicate that, in the absence of hydrogen-bonding water molecules, protonated procaine strongly prefers a compact structure enabled by intramolecular hydrogen bonding. In the presence of water molecules the torsional energy pro?le of procaine is modified, and hydrogen bonding to water molecules is favored relative to intra-molecular hydrogen bonding.« less

Molecular simulation aspects of amyloid peptides at membrane interface.

PubMed

Liu, Yonglan; Ren, Baiping; Zhang, Yanxian; Sun, Yan; Chang, Yung; Liang, Guizhao; Xu, Lijian; Zheng, Jie

2018-02-06

The interactions of amyloid peptides with cell membranes play an important role in maintaining the integrity and functionality of cell membrane. A thorough molecular-level understanding of the structure, dynamics, and interactions between amyloid peptides and cell membranes is critical to amyloid aggregation and toxicity mechanisms for the bench-to-bedside applications. Here we review the most recent computational studies of amyloid peptides at model cell membranes. Different mechanisms of action of amyloid peptides on/in cell membranes, targeted by different computational techniques at different lengthscales and timescales, are rationally discussed. Finally, we have proposed some new insights into the remaining challenges and perspectives for future studies to improve our understanding of the activity of amyloid peptides associated with protein-misfolding diseases. This article is part of a Special Issue entitled: Protein Aggregation and Misfolding at the Cell Membrane Interface edited by Ayyalusamy Ramamoorthy. Copyright © 2018 Elsevier B.V. All rights reserved.

Computer simulation of the linear and nonlinear optical susceptibilities of p-nitroaniline in cyclohexane, 1,4-dioxane, and tetrahydrofuran in quadrupolar approximation. II. Local field effects and optical susceptibilitities.

PubMed

Reis, H; Papadopoulos, M G; Grzybowski, A

2006-09-21

This is the second part of a study to elucidate the local field effects on the nonlinear optical properties of p-nitroaniline (pNA) in three solvents of different multipolar character, that is, cyclohexane (CH), 1,4-dioxane (DI), and tetrahydrofuran (THF), employing a discrete description of the solutions. By the use of liquid structure information from molecular dynamics simulations and molecular properties computed by high-level ab initio methods, the local field and local field gradients on p-nitroaniline and the solvent molecules are computed in quadrupolar approximation. To validate the simulations and the induction model, static and dynamic (non)linear properties of the pure solvents are also computed. With the exception of the static dielectric constant of pure THF, a good agreement between computed and experimental refractive indices, dielectric constants, and third harmonic generation signals is obtained for the solvents. For the solutions, it is found that multipole moments up to two orders higher than quadrupole have a negligible influence on the local fields on pNA, if a simple distribution model is employed for the electric properties of pNA. Quadrupole effects are found to be nonnegligible in all three solvents but are especially pronounced in the 1,4-dioxane solvent, in which the local fields are similar to those in THF, although the dielectric constant of DI is 2.2 and that of the simulated THF is 5.4. The electric-field-induced second harmonic generation (EFISH) signal and the hyper-Rayleigh scattering signal of pNA in the solutions computed with the local field are in good to fair agreement with available experimental results. This confirms the effect of the "dioxane anomaly" also on nonlinear optical properties. Predictions based on an ellipsoidal Onsager model as applied by experimentalists are in very good agreement with the discrete model predictions. This is in contrast to a recent discrete reaction field calculation of pNA in 1,4-dioxane, which found that the predicted first hyperpolarizability of pNA deviated strongly from the predictions obtained using Onsager-Lorentz local field factors.

Molecular Dynamics Simulations of Supramolecular Anticancer Nanotubes.

PubMed

Kang, Myungshim; Chakraborty, Kaushik; Loverde, Sharon M

2018-06-25

We report here on long-time all-atomistic molecular dynamics simulations of functional supramolecular nanotubes composed by the self-assembly of peptide-drug amphiphiles (DAs). These DAs have been shown to possess an inherently high drug loading of the hydrophobic anticancer drug camptothecin. We probe the self-assembly mechanism from random with ∼0.4 μs molecular dynamics simulations. Furthermore, we also computationally characterize the interfacial structure, directionality of π-π stacking, and water dynamics within several peptide-drug nanotubes with diameters consistent with the reported experimental nanotube diameter. Insight gained should inform the future design of these novel anticancer drug delivery systems.

Dielectric relaxation of ethylene carbonate and propylene carbonate from molecular dynamics simulations

DOE PAGES

Chaudhari, Mangesh I.; You, Xinli; Pratt, Lawrence R.; ...

2015-11-24

Ethylene carbonate (EC) and propylene carbonate (PC) are widely used solvents in lithium (Li)-ion batteries and supercapacitors. Ion dissolution and diffusion in those media are correlated with solvent dielectric responses. Here, we use all-atom molecular dynamics simulations of the pure solvents to calculate dielectric constants and relaxation times, and molecular mobilities. The computed results are compared with limited available experiments to assist more exhaustive studies of these important characteristics. As a result, the observed agreement is encouraging and provides guidance for further validation of force-field simulation models for EC and PC solvents.

Integrated Multiscale Modeling of Molecular Computing Devices. Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tim Schulze

2012-11-01

The general theme of this research has been to expand the capabilities of a simulation technique, Kinetic Monte Carlo (KMC) and apply it to study self-assembled nano-structures on epitaxial thin films. KMC simulates thin film growth and evolution by replacing the detailed dynamics of the system's evolution, which might otherwise be studied using molecular dynamics, with an appropriate stochastic process.

Deorbitalization strategies for meta-generalized-gradient-approximation exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Mejia-Rodriguez, Daniel; Trickey, S. B.

2017-11-01

We explore the simplification of widely used meta-generalized-gradient approximation (mGGA) exchange-correlation functionals to the Laplacian level of refinement by use of approximate kinetic-energy density functionals (KEDFs). Such deorbitalization is motivated by the prospect of reducing computational cost while recovering a strictly Kohn-Sham local potential framework (rather than the usual generalized Kohn-Sham treatment of mGGAs). A KEDF that has been rather successful in solid simulations proves to be inadequate for deorbitalization, but we produce other forms which, with parametrization to Kohn-Sham results (not experimental data) on a small training set, yield rather good results on standard molecular test sets when used to deorbitalize the meta-GGA made very simple, Tao-Perdew-Staroverov-Scuseria, and strongly constrained and appropriately normed functionals. We also study the difference between high-fidelity and best-performing deorbitalizations and discuss possible implications for use in ab initio molecular dynamics simulations of complicated condensed phase systems.

Effect of mutation at the interface of Trp-repressor dimeric protein: a steered molecular dynamics simulation.

PubMed

Miño, German; Baez, Mauricio; Gutierrez, Gonzalo

2013-09-01

The strength of key interfacial contacts that stabilize protein-protein interactions have been studied by computer simulation. Experimentally, changes in the interface are evaluated by generating specific mutations at one or more points of the protein structure. Here, such an evaluation is performed by means of steered molecular dynamics and use of a dimeric model of tryptophan repressor and in-silico mutants as a test case. Analysis of four particular cases shows that, in principle, it is possible to distinguish between wild-type and mutant forms by examination of the total energy and force-extension profiles. In particular, detailed atomic level structural analysis indicates that specific mutations at the interface of the dimeric model (positions 19 and 39) alter interactions that appear in the wild-type form of tryptophan repressor, reducing the energy and force required to separate both subunits.

Machine Learning Estimates of Natural Product Conformational Energies

PubMed Central

Rupp, Matthias; Bauer, Matthias R.; Wilcken, Rainer; Lange, Andreas; Reutlinger, Michael; Boeckler, Frank M.; Schneider, Gisbert

2014-01-01

Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor of vacuolar-type ATPase, from the myxobacterium Archangium gephyra as an example. Our model estimates energies of new conformations by exploiting information from previous calculations via Gaussian process regression. Predictive variance is used to assess whether a conformation is in the interpolation region, allowing a controlled trade-off between prediction accuracy and computational speed-up. For energies of relaxed conformations at the density functional level of theory (implicit solvent, DFT/BLYP-disp3/def2-TZVP), mean absolute errors of less than 1 kcal/mol were achieved. The study demonstrates that predictive machine learning models can be developed for structurally complex, pharmaceutically relevant compounds, potentially enabling considerable speed-ups in simulations of larger molecular structures. PMID:24453952

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Looking at the Disordered Proteins through the Computational Microscope.

PubMed

Das, Payel; Matysiak, Silvina; Mittal, Jeetain

2018-05-23

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure-function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

Looking at the Disordered Proteins through the Computational Microscope

PubMed Central

2018-01-01

Intrinsically disordered proteins (IDPs) have attracted wide interest over the past decade due to their surprising prevalence in the proteome and versatile roles in cell physiology and pathology. A large selection of IDPs has been identified as potential targets for therapeutic intervention. Characterizing the structure–function relationship of disordered proteins is therefore an essential but daunting task, as these proteins can adapt transient structure, necessitating a new paradigm for connecting structural disorder to function. Molecular simulation has emerged as a natural complement to experiments for atomic-level characterizations and mechanistic investigations of this intriguing class of proteins. The diverse range of length and time scales involved in IDP function requires performing simulations at multiple levels of resolution. In this Outlook, we focus on summarizing available simulation methods, along with a few interesting example applications. We also provide an outlook on how these simulation methods can be further improved in order to provide a more accurate description of IDP structure, binding, and assembly.

Quantum chemistry simulation on quantum computers: theories and experiments.

PubMed

Lu, Dawei; Xu, Boruo; Xu, Nanyang; Li, Zhaokai; Chen, Hongwei; Peng, Xinhua; Xu, Ruixue; Du, Jiangfeng

2012-07-14

It has been claimed that quantum computers can mimic quantum systems efficiently in the polynomial scale. Traditionally, those simulations are carried out numerically on classical computers, which are inevitably confronted with the exponential growth of required resources, with the increasing size of quantum systems. Quantum computers avoid this problem, and thus provide a possible solution for large quantum systems. In this paper, we first discuss the ideas of quantum simulation, the background of quantum simulators, their categories, and the development in both theories and experiments. We then present a brief introduction to quantum chemistry evaluated via classical computers followed by typical procedures of quantum simulation towards quantum chemistry. Reviewed are not only theoretical proposals but also proof-of-principle experimental implementations, via a small quantum computer, which include the evaluation of the static molecular eigenenergy and the simulation of chemical reaction dynamics. Although the experimental development is still behind the theory, we give prospects and suggestions for future experiments. We anticipate that in the near future quantum simulation will become a powerful tool for quantum chemistry over classical computations.

Computer simulation and experimental study of the polysaccharide-polysaccharide interaction in the bacteria Azospirillum brasilense Sp245

NASA Astrophysics Data System (ADS)

Arefeva, Oksana A.; Kuznetsov, Pavel E.; Tolmachev, Sergey A.; Kupadze, Machammad S.; Khlebtsov, Boris N.; Rogacheva, Svetlana M.

2003-09-01

We have studied the conformational properties and molecular dynamics of polysaccharides by using molecular modeling methods. Theoretical and experimental results of polysaccharide-polysaccharide interactions are described.

A domain specific language for performance portable molecular dynamics algorithms

NASA Astrophysics Data System (ADS)

Saunders, William Robert; Grant, James; Müller, Eike Hermann

2018-03-01

Developers of Molecular Dynamics (MD) codes face significant challenges when adapting existing simulation packages to new hardware. In a continuously diversifying hardware landscape it becomes increasingly difficult for scientists to be experts both in their own domain (physics/chemistry/biology) and specialists in the low level parallelisation and optimisation of their codes. To address this challenge, we describe a "Separation of Concerns" approach for the development of parallel and optimised MD codes: the science specialist writes code at a high abstraction level in a domain specific language (DSL), which is then translated into efficient computer code by a scientific programmer. In a related context, an abstraction for the solution of partial differential equations with grid based methods has recently been implemented in the (Py)OP2 library. Inspired by this approach, we develop a Python code generation system for molecular dynamics simulations on different parallel architectures, including massively parallel distributed memory systems and GPUs. We demonstrate the efficiency of the auto-generated code by studying its performance and scalability on different hardware and compare it to other state-of-the-art simulation packages. With growing data volumes the extraction of physically meaningful information from the simulation becomes increasingly challenging and requires equally efficient implementations. A particular advantage of our approach is the easy expression of such analysis algorithms. We consider two popular methods for deducing the crystalline structure of a material from the local environment of each atom, show how they can be expressed in our abstraction and implement them in the code generation framework.

Ab initio molecular dynamics with nuclear quantum effects at classical cost: Ring polymer contraction for density functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marsalek, Ondrej; Markland, Thomas E., E-mail: tmarkland@stanford.edu

Path integral molecular dynamics simulations, combined with an ab initio evaluation of interactions using electronic structure theory, incorporate the quantum mechanical nature of both the electrons and nuclei, which are essential to accurately describe systems containing light nuclei. However, path integral simulations have traditionally required a computational cost around two orders of magnitude greater than treating the nuclei classically, making them prohibitively costly for most applications. Here we show that the cost of path integral simulations can be dramatically reduced by extending our ring polymer contraction approach to ab initio molecular dynamics simulations. By using density functional tight binding asmore » a reference system, we show that our ring polymer contraction scheme gives rapid and systematic convergence to the full path integral density functional theory result. We demonstrate the efficiency of this approach in ab initio simulations of liquid water and the reactive protonated and deprotonated water dimer systems. We find that the vast majority of the nuclear quantum effects are accurately captured using contraction to just the ring polymer centroid, which requires the same number of density functional theory calculations as a classical simulation. Combined with a multiple time step scheme using the same reference system, which allows the time step to be increased, this approach is as fast as a typical classical ab initio molecular dynamics simulation and 35× faster than a full path integral calculation, while still exactly including the quantum sampling of nuclei. This development thus offers a route to routinely include nuclear quantum effects in ab initio molecular dynamics simulations at negligible computational cost.« less

Generalized image charge solvation model for electrostatic interactions in molecular dynamics simulations of aqueous solutions

PubMed Central

Deng, Shaozhong; Xue, Changfeng; Baumketner, Andriy; Jacobs, Donald; Cai, Wei

2013-01-01

This paper extends the image charge solvation model (ICSM) [J. Chem. Phys. 131, 154103 (2009)], a hybrid explicit/implicit method to treat electrostatic interactions in computer simulations of biomolecules formulated for spherical cavities, to prolate spheroidal and triaxial ellipsoidal cavities, designed to better accommodate non-spherical solutes in molecular dynamics (MD) simulations. In addition to the utilization of a general truncated octahedron as the MD simulation box, central to the proposed extension is an image approximation method to compute the reaction field for a point charge placed inside such a non-spherical cavity by using a single image charge located outside the cavity. The resulting generalized image charge solvation model (GICSM) is tested in simulations of liquid water, and the results are analyzed in comparison with those obtained from the ICSM simulations as a reference. We find that, for improved computational efficiency due to smaller simulation cells and consequently a less number of explicit solvent molecules, the generalized model can still faithfully reproduce known static and dynamic properties of liquid water at least for systems considered in the present paper, indicating its great potential to become an accurate but more efficient alternative to the ICSM when bio-macromolecules of irregular shapes are to be simulated. PMID:23913979

A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods

NASA Technical Reports Server (NTRS)

Saether, E.; Yamakov, V.; Glaessgen, E.

2007-01-01

Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.

Conformational landscapes of membrane proteins delineated by enhanced sampling molecular dynamics simulations.

PubMed

Harpole, Tyler J; Delemotte, Lucie

2018-04-01

The expansion of computational power, better parameterization of force fields, and the development of novel algorithms to enhance the sampling of the free energy landscapes of proteins have allowed molecular dynamics (MD) simulations to become an indispensable tool to understand the function of biomolecules. The temporal and spatial resolution of MD simulations allows for the study of a vast number of processes of interest. Here, we review the computational efforts to uncover the conformational free energy landscapes of a subset of membrane proteins: ion channels, transporters and G-protein coupled receptors. We focus on the various enhanced sampling techniques used to study these questions, how the conclusions come together to build a coherent picture, and the relationship between simulation outcomes and experimental observables. Copyright © 2017 Elsevier B.V. All rights reserved.

Lightweight computational steering of very large scale molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beazley, D.M.; Lomdahl, P.S.

1996-09-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less

Aspects of numerical and representational methods related to the finite-difference simulation of advective and dispersive transport of freshwater in a thin brackish aquifer

USGS Publications Warehouse

Merritt, M.L.

1993-01-01

The simulation of the transport of injected freshwater in a thin brackish aquifer, overlain and underlain by confining layers containing more saline water, is shown to be influenced by the choice of the finite-difference approximation method, the algorithm for representing vertical advective and dispersive fluxes, and the values assigned to parametric coefficients that specify the degree of vertical dispersion and molecular diffusion that occurs. Computed potable water recovery efficiencies will differ depending upon the choice of algorithm and approximation method, as will dispersion coefficients estimated based on the calibration of simulations to match measured data. A comparison of centered and backward finite-difference approximation methods shows that substantially different transition zones between injected and native waters are depicted by the different methods, and computed recovery efficiencies vary greatly. Standard and experimental algorithms and a variety of values for molecular diffusivity, transverse dispersivity, and vertical scaling factor were compared in simulations of freshwater storage in a thin brackish aquifer. Computed recovery efficiencies vary considerably, and appreciable differences are observed in the distribution of injected freshwater in the various cases tested. The results demonstrate both a qualitatively different description of transport using the experimental algorithms and the interrelated influences of molecular diffusion and transverse dispersion on simulated recovery efficiency. When simulating natural aquifer flow in cross-section, flushing of the aquifer occurred for all tested coefficient choices using both standard and experimental algorithms. ?? 1993.

The Bravyi-Kitaev transformation for quantum computation of electronic structure

NASA Astrophysics Data System (ADS)

Seeley, Jacob T.; Richard, Martin J.; Love, Peter J.

2012-12-01

Quantum simulation is an important application of future quantum computers with applications in quantum chemistry, condensed matter, and beyond. Quantum simulation of fermionic systems presents a specific challenge. The Jordan-Wigner transformation allows for representation of a fermionic operator by O(n) qubit operations. Here, we develop an alternative method of simulating fermions with qubits, first proposed by Bravyi and Kitaev [Ann. Phys. 298, 210 (2002), 10.1006/aphy.2002.6254; e-print arXiv:quant-ph/0003137v2], that reduces the simulation cost to O(log n) qubit operations for one fermionic operation. We apply this new Bravyi-Kitaev transformation to the task of simulating quantum chemical Hamiltonians, and give a detailed example for the simplest possible case of molecular hydrogen in a minimal basis. We show that the quantum circuit for simulating a single Trotter time step of the Bravyi-Kitaev derived Hamiltonian for H2 requires fewer gate applications than the equivalent circuit derived from the Jordan-Wigner transformation. Since the scaling of the Bravyi-Kitaev method is asymptotically better than the Jordan-Wigner method, this result for molecular hydrogen in a minimal basis demonstrates the superior efficiency of the Bravyi-Kitaev method for all quantum computations of electronic structure.

Density-Functional Theory with Dispersion-Correcting Potentials for Methane: Bridging the Efficiency and Accuracy Gap between High-Level Wave Function and Classical Molecular Mechanics Methods.

PubMed

Torres, Edmanuel; DiLabio, Gino A

2013-08-13

Large clusters of noncovalently bonded molecules can only be efficiently modeled by classical mechanics simulations. One prominent challenge associated with this approach is obtaining force-field parameters that accurately describe noncovalent interactions. High-level correlated wave function methods, such as CCSD(T), are capable of correctly predicting noncovalent interactions, and are widely used to produce reference data. However, high-level correlated methods are generally too computationally costly to generate the critical reference data required for good force-field parameter development. In this work we present an approach to generate Lennard-Jones force-field parameters to accurately account for noncovalent interactions. We propose the use of a computational step that is intermediate to CCSD(T) and classical molecular mechanics, that can bridge the accuracy and computational efficiency gap between them, and demonstrate the efficacy of our approach with methane clusters. On the basis of CCSD(T)-level binding energy data for a small set of methane clusters, we develop methane-specific, atom-centered, dispersion-correcting potentials (DCPs) for use with the PBE0 density-functional and 6-31+G(d,p) basis sets. We then use the PBE0-DCP approach to compute a detailed map of the interaction forces associated with the removal of a single methane molecule from a cluster of eight methane molecules and use this map to optimize the Lennard-Jones parameters for methane. The quality of the binding energies obtained by the Lennard-Jones parameters we obtained is assessed on a set of methane clusters containing from 2 to 40 molecules. Our Lennard-Jones parameters, used in combination with the intramolecular parameters of the CHARMM force field, are found to closely reproduce the results of our dispersion-corrected density-functional calculations. The approach outlined can be used to develop Lennard-Jones parameters for any kind of molecular system.

Comparative simulation study of chemical synthesis of functional DADNE material.

PubMed

Liu, Min Hsien; Liu, Chuan Wen

2017-01-01

Amorphous molecular simulation to model the reaction species in the synthesis of chemically inert and energetic 1,1-diamino-2,2-dinitroethene (DADNE) explosive material was performed in this work. Nitromethane was selected as the starting reactant to undergo halogenation, nitration, deprotonation, intermolecular condensation, and dehydration to produce the target DADNE product. The Materials Studio (MS) forcite program allowed fast energy calculations and reliable geometric optimization of all aqueous molecular reaction systems (0.1-0.5 M) at 283 K and 298 K. The MS forcite-computed and Gaussian polarizable continuum model (PCM)-computed results were analyzed and compared in order to explore feasible reaction pathways under suitable conditions for the synthesis of DADNE. Through theoretical simulation, the findings revealed that synthesis was possible, and a total energy barrier of 449.6 kJ mol -1 needed to be overcome in order to carry out the reaction according to MS calculation of the energy barriers at each stage at 283 K, as shown by the reaction profiles. Local analysis of intermolecular interaction, together with calculation of the stabilization energy of each reaction system, provided information that can be used as a reference regarding molecular integrated stability. Graphical Abstract Materials Studio software has been suggested for the computation and simulation of DADNE synthesis.

Radiative Heat Transfer and Turbulence-Radiation Interactions in a Heavy-Duty Diesel Engine

NASA Astrophysics Data System (ADS)

Paul, C.; Sircar, A.; Ferreyro, S.; Imren, A.; Haworth, D. C.; Roy, S.; Ge, W.; Modest, M. F.

2016-11-01

Radiation in piston engines has received relatively little attention to date. Recently, it is being revisited in light of current trends towards higher operating pressures and higher levels of exhaust-gas recirculation, both of which enhance molecular gas radiation. Advanced high-efficiency engines also are expected to function closer to the limits of stable operation, where even small perturbations to the energy balance can have a large influence on system behavior. Here several different spectral radiation property models and radiative transfer equation (RTE) solvers have been implemented in an OpenFOAM-based engine CFD code, and simulations have been performed for a heavy-duty diesel engine. Differences in computed temperature fields, NO and soot levels, and wall heat transfer rates are shown for different combinations of spectral models and RTE solvers. The relative importance of molecular gas radiation versus soot radiation is examined. And the influence of turbulence-radiation interactions is determined by comparing results obtained using local mean values of composition and temperature to compute radiative emission and absorption with those obtained using a particle-based transported probability density function method. DOE, NSF.

Radiative Heat Transfer modelling in a Heavy-Duty Diesel Engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Chandan; Sircar, Arpan; Ferreyro-Fernandez, Sebastian

Detailed radiation modelling in piston engines has received relatively little attention to date. Recently, it is being revisited in light of current trends towards higher operating pressures and higher levels of exhaust-gas recirculation, both of which enhance molecular gas radiation. Advanced high-efficiency engines also are expected to function closer to the limits of stable operation, where even small perturbations to the energy balance can have a large influence on system behavior. Here several different spectral radiation property models and radiative transfer equation (RTE) solvers have been implemented in an OpenFOAM-based engine CFD code, and simulations have been performed for amore » heavy-duty diesel engine. Differences in computed temperature fields, NO and soot levels, and wall heat transfer rates are shown for different combinations of spectral models and RTE solvers. The relative importance of molecular gas radiation versus soot radiation is examined. And the influence of turbulence-radiation interactions is determined by comparing results obtained using local mean values of composition and temperature to compute radiative emission and absorption with those obtained using a particle-based transported probability density function method.« less

Protonation States in molecular dynamics simulations of peptide folding and binding.

PubMed

Ben-Shimon, Avraham; Shalev, Deborah E; Niv, Masha Y

2013-01-01

Peptides are important signaling modules, acting both as individual hormones and as parts of larger molecules, mediating their protein-protein interactions. Many peptidic and peptidomimetic drugs have reached the marketplace and opportunities for peptide-based drug discovery are on the rise. pH-dependent behavior of peptides is well documented in the context of misfolding diseases and peptide translocation. Changes in the protonation states of peptide residues often have a crucial effect on a peptide's structure, dynamics and function, which may be exploited for biotechnological applications. The current review surveys the increasing levels of sophistication in the treatment of protonation states in computational studies involving peptides. Specifically we describe I) the common practice of assigning a single protonation state and using it throughout the dynamic simulation, II) approaches that consider multiple protonation states and compare computed observables to experimental ones, III) constant pH molecular dynamics methods that couple changes in protonation states with conformational dynamics "on the fly". Applications of conformational dynamics treatment of peptides in the context of binding, folding and interactions with the membrane are presented, illustrating the growing body of work in this field and highlighting the importance of careful handling of protonation states of peptidic residues.

Density functional theory calculation of refractive indices of liquid-forming silicon oil compounds

NASA Astrophysics Data System (ADS)

Lee, Sanghun; Park, Sung Soo; Hagelberg, Frank

2012-02-01

A combination of quantum chemical calculation and molecular dynamics simulation is applied to compute refractive indices of liquid-forming silicon oils. The densities of these species are obtained from molecular dynamics simulations based on the NPT ensemble while the molecular polarizabilities are evaluated by density functional theory. This procedure is shown to yield results well compatible with available experimental data, suggesting that it represents a robust and economic route for determining the refractive indices of liquid-forming organic complexes containing silicon.

Multinuclear NMR of CaSiO(3) glass: simulation from first-principles.

PubMed

Pedone, Alfonso; Charpentier, Thibault; Menziani, Maria Cristina

2010-06-21

An integrated computational method which couples classical molecular dynamics simulations with density functional theory calculations is used to simulate the solid-state NMR spectra of amorphous CaSiO(3). Two CaSiO(3) glass models are obtained by shell-model molecular dynamics simulations, successively relaxed at the GGA-PBE level of theory. The calculation of the NMR parameters (chemical shielding and quadrupolar parameters), which are then used to simulate solid-state 1D and 2D-NMR spectra of silicon-29, oxygen-17 and calcium-43, is achieved by the gauge including projector augmented-wave (GIPAW) and the projector augmented-wave (PAW) methods. It is shown that the limitations due to the finite size of the MD models can be overcome using a Kernel Estimation Density (KDE) approach to simulate the spectra since it better accounts for the disorder effects on the NMR parameter distribution. KDE allows reconstructing a smoothed NMR parameter distribution from the MD/GIPAW data. Simulated NMR spectra calculated with the present approach are found to be in excellent agreement with the experimental data. This further validates the CaSiO(3) structural model obtained by MD simulations allowing the inference of relationships between structural data and NMR response. The methods used to simulate 1D and 2D-NMR spectra from MD GIPAW data have been integrated in a package (called fpNMR) freely available on request.

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

PubMed Central

De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.

2015-01-01

Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944

Electron Nuclear Dynamics Simulations of Proton Cancer Therapy Reactions: Water Radiolysis and Proton- and Electron-Induced DNA Damage in Computational Prototypes.

PubMed

Teixeira, Erico S; Uppulury, Karthik; Privett, Austin J; Stopera, Christopher; McLaurin, Patrick M; Morales, Jorge A

2018-05-06

Proton cancer therapy (PCT) utilizes high-energy proton projectiles to obliterate cancerous tumors with low damage to healthy tissues and without the side effects of X-ray therapy. The healing action of the protons results from their damage on cancerous cell DNA. Despite established clinical use, the chemical mechanisms of PCT reactions at the molecular level remain elusive. This situation prevents a rational design of PCT that can maximize its therapeutic power and minimize its side effects. The incomplete characterization of PCT reactions is partially due to the health risks associated with experimental/clinical techniques applied to human subjects. To overcome this situation, we are conducting time-dependent and non-adiabatic computer simulations of PCT reactions with the electron nuclear dynamics (END) method. Herein, we present a review of our previous and new END research on three fundamental types of PCT reactions: water radiolysis reactions, proton-induced DNA damage and electron-induced DNA damage. These studies are performed on the computational prototypes: proton + H₂O clusters, proton + DNA/RNA bases and + cytosine nucleotide, and electron + cytosine nucleotide + H₂O. These simulations provide chemical mechanisms and dynamical properties of the selected PCT reactions in comparison with available experimental and alternative computational results.

A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery.

PubMed

Morgnanesi, Dante; Heinrichs, Eric J; Mele, Anthony R; Wilkinson, Sean; Zhou, Suzanne; Kulp, John L

2015-11-01

Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B." Copyright © 2015 Elsevier B.V. All rights reserved.

| NREL

Science.gov Websites

of NREL's Computational Science Center, where he uses electronic structure calculations and other introductory chemistry and physical chemistry. Research Interests Electronic structure and dynamics in the quantum/classical molecular dynamics simulation|Coupling of molecular electronic structure to

Computational Study of the Bulk Properties of a Novel Molecule: alpha-Tocopherol-Ascorbic Acid Surfactant

NASA Astrophysics Data System (ADS)

Stirling, Shannon; Kim, Hye-Young

Alpha-tocopherol-ascorbic acid surfactant (EC) is a novel amphiphilic molecule of antioxidant properties, which has a hydrophobic vitamin E and a hydrophilic vitamin C chemically linked. We have developed atomistic force fields (g54a7) for a protonated (neutral) EC molecule. Our goal is to carry out molecular dynamics (MD) simulations of protonated EC molecules using the newly developed force fields and study the molecular properties. First we ran energy minimization (EM) with one molecule in a vacuum to obtain the low energy molecular configuration with emtol =10. We then used Packmol to insert 125 EC molecules in a 3nm cube. We then performed MD simulations of the bulk system composed of 125 EC molecules, from which we measured the bulk density and the evaporation energy of the molecular system. Gromacs2016 is used for the EM and MD simulation studies. We will present the results of the ongoing research. National Institute Of General Medical Sciences of the National Institutes of Health under Award Number P20GM103424 (Kim). Computational resources were provided by the Louisiana Optical Network Initiative.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

ERIC Educational Resources Information Center

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

iBIOMES Lite: Summarizing Biomolecular Simulation Data in Limited Settings

PubMed Central

2015-01-01

As the amount of data generated by biomolecular simulations dramatically increases, new tools need to be developed to help manage this data at the individual investigator or small research group level. In this paper, we introduce iBIOMES Lite, a lightweight tool for biomolecular simulation data indexing and summarization. The main goal of iBIOMES Lite is to provide a simple interface to summarize computational experiments in a setting where the user might have limited privileges and limited access to IT resources. A command-line interface allows the user to summarize, publish, and search local simulation data sets. Published data sets are accessible via static hypertext markup language (HTML) pages that summarize the simulation protocols and also display data analysis graphically. The publication process is customized via extensible markup language (XML) descriptors while the HTML summary template is customized through extensible stylesheet language (XSL). iBIOMES Lite was tested on different platforms and at several national computing centers using various data sets generated through classical and quantum molecular dynamics, quantum chemistry, and QM/MM. The associated parsers currently support AMBER, GROMACS, Gaussian, and NWChem data set publication. The code is available at https://github.com/jcvthibault/ibiomes. PMID:24830957

Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate.

PubMed

Resat, H; Mezei, M

1996-09-01

The grand canonical ensemble Monte Carlo molecular simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical ensemble simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed molecular simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand ensemble simulations can be far more advantageous than the comparable canonical ensemble simulations.

Molecular dynamics simulations of biological membranes and membrane proteins using enhanced conformational sampling algorithms☆

PubMed Central

Mori, Takaharu; Miyashita, Naoyuki; Im, Wonpil; Feig, Michael; Sugita, Yuji

2016-01-01

This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins. Guest Editors: J.C. Gumbart and Sergei Noskov. PMID:26766517

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

The H2 + + He proton transfer reaction: quantum reactive differential cross sections to be linked with future velocity mapping experiments

NASA Astrophysics Data System (ADS)

Hernández Vera, Mario; Wester, Roland; Gianturco, Francesco Antonio

2018-01-01

We construct the velocity map images of the proton transfer reaction between helium and molecular hydrogen ion {{{H}}}2+. We perform simulations of imaging experiments at one representative total collision energy taking into account the inherent aberrations of the velocity mapping in order to explore the feasibility of direct comparisons between theory and future experiments planned in our laboratory. The asymptotic angular distributions of the fragments in a 3D velocity space is determined from the quantum state-to-state differential reactive cross sections and reaction probabilities which are computed by using the time-independent coupled channel hyperspherical coordinate method. The calculations employ an earlier ab initio potential energy surface computed at the FCI/cc-pVQZ level of theory. The present simulations indicate that the planned experiments would be selective enough to differentiate between product distributions resulting from different initial internal states of the reactants.

Conformational Heterogeneity of Bax Helix 9 Dimer for Apoptotic Pore Formation

NASA Astrophysics Data System (ADS)

Liao, Chenyi; Zhang, Zhi; Kale, Justin; Andrews, David W.; Lin, Jialing; Li, Jianing

2016-07-01

Helix α9 of Bax protein can dimerize in the mitochondrial outer membrane (MOM) and lead to apoptotic pores. However, it remains unclear how different conformations of the dimer contribute to the pore formation on the molecular level. Thus we have investigated various conformational states of the α9 dimer in a MOM model — using computer simulations supplemented with site-specific mutagenesis and crosslinking of the α9 helices. Our data not only confirmed the critical membrane environment for the α9 stability and dimerization, but also revealed the distinct lipid-binding preference of the dimer in different conformational states. In our proposed pathway, a crucial iso-parallel dimer that mediates the conformational transition was discovered computationally and validated experimentally. The corroborating evidence from simulations and experiments suggests that, helix α9 assists Bax activation via the dimer heterogeneity and interactions with specific MOM lipids, which eventually facilitate proteolipidic pore formation in apoptosis regulation.

Simulation tools for particle-based reaction-diffusion dynamics in continuous space

PubMed Central

2014-01-01

Particle-based reaction-diffusion algorithms facilitate the modeling of the diffusional motion of individual molecules and the reactions between them in cellular environments. A physically realistic model, depending on the system at hand and the questions asked, would require different levels of modeling detail such as particle diffusion, geometrical confinement, particle volume exclusion or particle-particle interaction potentials. Higher levels of detail usually correspond to increased number of parameters and higher computational cost. Certain systems however, require these investments to be modeled adequately. Here we present a review on the current field of particle-based reaction-diffusion software packages operating on continuous space. Four nested levels of modeling detail are identified that capture incrementing amount of detail. Their applicability to different biological questions is discussed, arching from straight diffusion simulations to sophisticated and expensive models that bridge towards coarse grained molecular dynamics. PMID:25737778

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elber, Ron

Atomically detailed computer simulations of complex molecular events attracted the imagination of many researchers in the field as providing comprehensive information on chemical, biological, and physical processes. However, one of the greatest limitations of these simulations is of time scales. The physical time scales accessible to straightforward simulations are too short to address many interesting and important molecular events. In the last decade significant advances were made in different directions (theory, software, and hardware) that significantly expand the capabilities and accuracies of these techniques. This perspective describes and critically examines some of these advances.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application.

PubMed

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics' equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques.

Multiscale models and stochastic simulation methods for computing rare but key binding events in cell biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guerrier, C.; Holcman, D., E-mail: david.holcman@ens.fr; Mathematical Institute, Oxford OX2 6GG, Newton Institute

The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationallymore » greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.« less

Wetting Hysteresis at the Molecular Scale

NASA Technical Reports Server (NTRS)

Jin, Wei; Koplik, Joel; Banavar, Jayanth R.

1996-01-01

The motion of a fluid-fluid-solid contact line on a rough surface is well known to display hysteresis in the contact angle vs. velocity relationship. In order to understand the phenomenon at a fundamental microscopic level, we have conducted molecular dynamics computer simulations of a Wilhelmy plate experiment in which a solid surface is dipped into a liquid bath, and the force-velocity characteristics are measured. We directly observe a systematic variation of force and contact angle with velocity, which is single-valued for the case of an atomically smooth solid surface. In the microscopically rough case, however, we find (as intuitively expected) an open hysteresis loop. Further characterization of the interface dynamics is in progress.

Synthesis and conformational analysis by 1H NMR and restrained molecular dynamics simulations of the cyclic decapeptide [Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly

NASA Astrophysics Data System (ADS)

Buono, Ronald A.; Kucharczyk, Nathalie; Neuenschwander, Magrit; Kemmink, Johan; Hwang, Lih-Yueh; Fauchère, Jean-Luc; Venanzi, Carol A.

1996-06-01

The design of enzyme mimics with therapeutic and industrial applications has interested both experimental and computational chemists for several decades. Recent advances in the computational methodology of restrained molecular dynamics, used in conjunction with data obtained from two-dimensional 1H NMR spectroscopy, make it a promising method to study peptide and protein structure and function. Several issues, however, need to be addressed in order to assess the validity of this method for its explanatory and predictive value. Among the issues addressed in this study are: the accuracy and generizability of the GROMOS peptide molecular mechanics force field; the effect of inclusion of solvent on the simulations; and the effect of different types of restraining algorithms on the computational results. The decapeptide Ser-Tyr-Ser-Met-Glu-His-Phe-Arg-Trp-Gly, which corresponds to the sequence of ACTH1-10, has been synthesized, cyclized, and studied by two-dimensional 1H NMR spectroscopy. Restrained molecular dynamics (RMD) and time-averaged restrained molecular dynamics (TARMD) simulations were carried out on four different distance-geometry starting structures in order to determine and contrast the behavior of cyclic ACTH1-10 in vacuum and in solution. For the RMD simulations, the structures did not fit the NOE data well, even at high values of the restraining potential. The TARMD simulation method, however, was able to give structures that fit the NOE data at high values of the restraining potential. In both cases, inclusion of explicit solvent molecules in the simulation had little effect on the quality of the fit, although it was found to dampen the motion of the cyclic peptide. For both simulation techniques, the number and size of the NOE violations increased as the restraining potential approached zero. This is due, presumably, to inadequacies in the force field. Additional TARMD vacuum-phase simulations, run with a larger memory length or with a larger sampling size (16 additional distance-geometry structures), yielded no significantly different results. The computed data were then analyzed to help explain the sparse NOE data and poor chymotryptic activity of the cyclic peptide. Cyclic ACTH1-10, which contains the functional moieties of the catalytic triad of chymotrypsin, was evaluated as a potential mimic of chymotrypsin by measurement of the rate of hydrolysis of esters of L-and d-phenylalanine. The poor rate of hydrolysis is attributed to the flexibility of the decapeptide, the motion of the side chains, which result in the absence of long-range NOEs, the small size of the macrocycle relative to that of the substrate, and the inappropriate orientation of the Gly, His, and Ser residues. The results demonstrate the utility of this method in computer-aided molecular design of cyclic peptides and suggest structural modifications for future work based on a larger and more rigid peptide framework.

Structure simulation with calculated NMR parameters - integrating COSMOS into the CCPN framework.

PubMed

Schneider, Olaf; Fogh, Rasmus H; Sternberg, Ulrich; Klenin, Konstantin; Kondov, Ivan

2012-01-01

The Collaborative Computing Project for NMR (CCPN) has build a software framework consisting of the CCPN data model (with APIs) for NMR related data, the CcpNmr Analysis program and additional tools like CcpNmr FormatConverter. The open architecture allows for the integration of external software to extend the abilities of the CCPN framework with additional calculation methods. Recently, we have carried out the first steps for integrating our software Computer Simulation of Molecular Structures (COSMOS) into the CCPN framework. The COSMOS-NMR force field unites quantum chemical routines for the calculation of molecular properties with a molecular mechanics force field yielding the relative molecular energies. COSMOS-NMR allows introducing NMR parameters as constraints into molecular mechanics calculations. The resulting infrastructure will be made available for the NMR community. As a first application we have tested the evaluation of calculated protein structures using COSMOS-derived 13C Cα and Cβ chemical shifts. In this paper we give an overview of the methodology and a roadmap for future developments and applications.

Ab initio molecular dynamics simulation of LiBr association in water

NASA Astrophysics Data System (ADS)

Izvekov, Sergei; Philpott, Michael R.

2000-12-01

A computationally economical scheme which unifies the density functional description of an ionic solute and the classical description of a solvent was developed. The density functional part of the scheme comprises Car-Parrinello and related formalisms. The substantial saving in the computer time is achieved by performing the ab initio molecular dynamics of the solute electronic structure in a relatively small basis set constructed from lowest energy Kohn-Sham orbitals calculated for a single anion in vacuum, instead of using plane wave basis. The methodology permits simulation of an ionic solution for longer time scales while keeping accuracy in the prediction of the solute electronic structure. As an example the association of the Li+-Br- ion-pair system in water is studied. The results of the combined molecular dynamics simulation are compared with that obtained from the classical simulation with ion-ion interaction described by the pair potential of Born-Huggins-Mayer type. The comparison reveals an important role played by the polarization of the Br- ion in the dynamics of ion pair association.

Molecular understanding of mutagenicity using potential energy methods. Progress report, July 1, 1992--September 30, 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Broyde, S.; Shapiro, R.

1993-09-01

Our objective has been to elucidate on a molecular level, at atomic resolution, the structures of DNAs modified by highly mutagenic aromatic amines and hydrocarbons. The underlying hypothesis is that DNA replicates with reduced fidelity when its normal right-handed B-structure is altered, and one result is a higher mutation rate. This change in structure may occur normally at a low incidence but it may be enhanced greatly after covalent modification by a mutagenic substance. The methods that we use to elucidate structures are computational, but we keep in close contact with experimental developments, and we incorporate data from NMR studiesmore » in our calculations when they are available. X-ray and low resolution spectroscopic studies have not succeeded in producing atomic resolution views of mutagen and carcinogen-oligonucleotide adducts. Even the high resolution NMR method cannot alone yield molecular views, though it does so in combination with our computations. The specific methods that we employ are minimized potential energy calculations using the torsion angle space molecular mechanics program DUPLEX to yield static views. Molecular dynamics simulations of static structures with solvent and salt can be carried out with the program AMBER; this yields mobile views in a medium that mimics aspects of the natural aqueous environment of the cell.« less

AHPCRC (Army High Performance Computing Research Center) Bulletin. Volume 2, Issue 2, 2011

DTIC Science & Technology

2011-01-01

fixed (i.e., no flapping). The simulation was performed at sea level conditions with a pressure of 101 kPa and a density of 1.23 kg/m3. The air speed...Hardening Behavior in Au Nanopillar Microplasticity . IJMCE 5 (3&4) 287–294. (2007) 5. S. J. Plimpton. Fast Parallel Algorithms for Short- Range Molecular...such as crude oil underwa- ter. Scattering is also used for sea floor mapping. For example, communications companies laying underwa- ter fiber optic

Molecular Basis of Ligand Dissociation from G Protein-Coupled Receptors and Predicting Residence Time.

PubMed

Guo, Dong; IJzerman, Adriaan P

2018-01-01

G protein-coupled receptors (GPCRs) are integral membrane proteins and represent the largest class of drug targets. During the past decades progress in structural biology has enabled the crystallographic elucidation of the architecture of these important macromolecules. It also provided atomic-level visualization of ligand-receptor interactions, dramatically boosting the impact of structure-based approaches in drug discovery. However, knowledge obtained through crystallography is limited to static structural information. Less information is available showing how a ligand associates with or dissociates from a given receptor, whose importance is in fact increasingly recognized by the drug research community. Owing to recent advances in computer power and algorithms, molecular dynamics stimulations have become feasible that help in analyzing the kinetics of the ligand binding process. Here, we review what is currently known about the dynamics of GPCRs in the context of ligand association and dissociation, as determined through both crystallography and computer simulations. We particularly focus on the molecular basis of ligand dissociation from GPCRs and provide case studies that predict ligand dissociation pathways and residence time.

Dynameomics: design of a computational lab workflow and scientific data repository for protein simulations.

PubMed

Simms, Andrew M; Toofanny, Rudesh D; Kehl, Catherine; Benson, Noah C; Daggett, Valerie

2008-06-01

Dynameomics is a project to investigate and catalog the native-state dynamics and thermal unfolding pathways of representatives of all protein folds using solvated molecular dynamics simulations, as described in the preceding paper. Here we introduce the design of the molecular dynamics data warehouse, a scalable, reliable repository that houses simulation data that vastly simplifies management and access. In the succeeding paper, we describe the development of a complementary multidimensional database. A single protein unfolding or native-state simulation can take weeks to months to complete, and produces gigabytes of coordinate and analysis data. Mining information from over 3000 completed simulations is complicated and time-consuming. Even the simplest queries involve writing intricate programs that must be built from low-level file system access primitives and include significant logic to correctly locate and parse data of interest. As a result, programs to answer questions that require data from hundreds of simulations are very difficult to write. Thus, organization and access to simulation data have been major obstacles to the discovery of new knowledge in the Dynameomics project. This repository is used internally and is the foundation of the Dynameomics portal site http://www.dynameomics.org. By organizing simulation data into a scalable, manageable and accessible form, we can begin to address substantial questions that move us closer to solving biomedical and bioengineering problems.

Molecular Dynamics: New Frontier in Personalized Medicine.

PubMed

Sneha, P; Doss, C George Priya

2016-01-01

The field of drug discovery has witnessed infinite development over the last decade with the demand for discovery of novel efficient lead compounds. Although the development of novel compounds in this field has seen large failure, a breakthrough in this area might be the establishment of personalized medicine. The trend of personalized medicine has shown stupendous growth being a hot topic after the successful completion of Human Genome Project and 1000 genomes pilot project. Genomic variant such as SNPs play a vital role with respect to inter individual's disease susceptibility and drug response. Hence, identification of such genetic variants has to be performed before administration of a drug. This process requires high-end techniques to understand the complexity of the molecules which might bring an insight to understand the compounds at their molecular level. To sustenance this, field of bioinformatics plays a crucial role in revealing the molecular mechanism of the mutation and thereby designing a drug for an individual in fast and affordable manner. High-end computational methods, such as molecular dynamics (MD) simulation has proved to be a constitutive approach to detecting the minor changes associated with an SNP for better understanding of the structural and functional relationship. The parameters used in molecular dynamic simulation elucidate different properties of a macromolecule, such as protein stability and flexibility. MD along with docking analysis can reveal the synergetic effect of an SNP in protein-ligand interaction and provides a foundation for designing a particular drug molecule for an individual. This compelling application of computational power and the advent of other technologies have paved a promising way toward personalized medicine. In this in-depth review, we tried to highlight the different wings of MD toward personalized medicine. © 2016 Elsevier Inc. All rights reserved.

Exploring GPCR-Lipid Interactions by Molecular Dynamics Simulations: Excitements, Challenges, and the Way Forward.

PubMed

Sengupta, Durba; Prasanna, Xavier; Mohole, Madhura; Chattopadhyay, Amitabha

2018-06-07

Gprotein-coupled receptors (GPCRs) are seven transmembrane receptors that mediate a large number of cellular responses and are important drug targets. One of the current challenges in GPCR biology is to analyze the molecular signatures of receptor-lipid interactions and their subsequent effects on GPCR structure, organization, and function. Molecular dynamics simulation studies have been successful in predicting molecular determinants of receptor-lipid interactions. In particular, predicted cholesterol interaction sites appear to correspond well with experimentally determined binding sites and estimated time scales of association. In spite of several success stories, the methodologies in molecular dynamics simulations are still emerging. In this Feature Article, we provide a comprehensive overview of coarse-grain and atomistic molecular dynamics simulations of GPCR-lipid interaction in the context of experimental observations. In addition, we discuss the effect of secondary and tertiary structural constraints in coarse-grain simulations in the context of functional dynamics and structural plasticity of GPCRs. We envision that this comprehensive overview will help resolve differences in computational studies and provide a way forward.

Independent saturation of three TrpRS subsites generates a partially assembled state similar to those observed in molecular simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laowanapiban, Poramaet; Kapustina, Maryna; Vonrhein, Clemens

2009-03-05

Two new crystal structures of Bacillus stearothermophilus tryptophanyl-tRNA synthetase (TrpRS) afford evidence that a closed interdomain hinge angle requires a covalent bond between AMP and an occupant of either pyrophosphate or tryptophan subsite. They also are within experimental error of a cluster of structures observed in a nonequilibrium molecular dynamics simulation showing partial active-site assembly. Further, the highest energy structure in a minimum action pathway computed by using elastic network models for Open and Pretransition state (PreTS) conformations for the fully liganded TrpRS monomer is intermediate between that simulated structure and a partially disassembled structure from a nonequilibrium molecular dynamicsmore » trajectory for the unliganded PreTS. These mutual consistencies provide unexpected validation of inferences drawn from molecular simulations.« less

Molecular simulation studies on chemical reactivity of methylcyclopentadiene.

PubMed

Wang, Qingsheng; Zhang, Yingchun; Rogers, William J; Mannan, M Sam

2009-06-15

Molecular simulations are important to predict thermodynamic values for reactive chemicals especially when sufficient experimental data are not available. Methylcyclopentadiene (MCP) is an example of a highly reactive and hazardous compound in the chemical process industry. In this work, chemical reactivity of 2-methylcyclopentadiene, including isomerization, dimerization, and oxidation reactions, is investigated in detail by theoretical computational chemistry methods and empirical thermodynamic-energy correlation. On the basis of molecular simulations, an average value of -15.2 kcal/mol for overall heat of dimerization and -45.6 kcal/mol for overall heat of oxidation were obtained in gaseous phase at 298 K and 1 atm. These molecular simulation studies can provide guidance for the design of safer chemical processes, safer handling of MCP, and also provide useful information for an investigation of the T2 Laboratories explosion on December 19, 2007, in Florida.

An autonomous molecular computer for logical control of gene expression.

PubMed

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2004-05-27

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.

Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads

PubMed Central

Stone, John E.; Hallock, Michael J.; Phillips, James C.; Peterson, Joseph R.; Luthey-Schulten, Zaida; Schulten, Klaus

2016-01-01

Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers. PMID:27516922

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

High temperature phonon dispersion in graphene using classical molecular dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anees, P., E-mail: anees@igcar.gov.in; Panigrahi, B. K.; Valsakumar, M. C., E-mail: anees@igcar.gov.in

2014-04-24

Phonon dispersion and phonon density of states of graphene are calculated using classical molecular dynamics simulations. In this method, the dynamical matrix is constructed based on linear response theory by computing the displacement of atoms during the simulations. The computed phonon dispersions show excellent agreement with experiments. The simulations are done in both NVT and NPT ensembles at 300 K and found that the LO/TO modes are getting hardened at the Γ point. The NPT ensemble simulations capture the anharmonicity of the crystal accurately and the hardening of LO/TO modes is more pronounced. We also found that at 300 Kmore » the C-C bond length reduces below the equilibrium value and the ZA bending mode frequency becomes imaginary close to Γ along K-Γ direction, which indicates instability of the flat 2D graphene sheets.« less

Development and application of a particle-particle particle-mesh Ewald method for dispersion interactions.

PubMed

Isele-Holder, Rolf E; Mitchell, Wayne; Ismail, Ahmed E

2012-11-07

For inhomogeneous systems with interfaces, the inclusion of long-range dispersion interactions is necessary to achieve consistency between molecular simulation calculations and experimental results. For accurate and efficient incorporation of these contributions, we have implemented a particle-particle particle-mesh Ewald solver for dispersion (r(-6)) interactions into the LAMMPS molecular dynamics package. We demonstrate that the solver's O(N log N) scaling behavior allows its application to large-scale simulations. We carefully determine a set of parameters for the solver that provides accurate results and efficient computation. We perform a series of simulations with Lennard-Jones particles, SPC/E water, and hexane to show that with our choice of parameters the dependence of physical results on the chosen cutoff radius is removed. Physical results and computation time of these simulations are compared to results obtained using either a plain cutoff or a traditional Ewald sum for dispersion.

Quantum probability ranking principle for ligand-based virtual screening.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening

NASA Astrophysics Data System (ADS)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study

DOE PAGES

Song, Lingshuang; Yang, Lin; Meng, Jie; ...

2016-12-29

Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less

Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental–Computational Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Lingshuang; Yang, Lin; Meng, Jie

Here, we present a joint experimental-computational study to quantitatively describe the thermodynamics of hydrophobic leucine amino acids in aqueous solution. X-ray scattering data were acquired at a series of solute and salt concentrations to effectively measure inter-leucine interactions, indicating that a major scattering peak is observed consistently at q = 0.83 Å -1. Atomistic molecular dynamics simulations were then performed and compared with the scattering data, achieving high consistency at both small and wider scattering angles (q = 0$-$1.5 Å -1). This experimental-computational consistence enables a first glimpse of the leucineleucine interacting landscape, where two leucine molecules are aligned mostlymore » in a parallel fashion, as opposed to anti-parallel, but also allows us to derive effective leucine-leucine interactions in solution. Collectively, this combined approach of employing experimental scattering and molecular simulation enables a quantitative characterization on effective inter-molecular interactions of hydrophobic amino acids, critical for protein function and dynamics such as protein folding.« less

Polymerization and Structure of Bio-Based Plastics: A Computer Simulation

NASA Astrophysics Data System (ADS)

Khot, Shrikant N.; Wool, Richard P.

2001-03-01

We recently examined several hundred chemical pathways to convert chemically functionalized plant oil triglycerides, monoglycerides and reactive diluents into high performance plastics with a broad range of properties (US Patent No. 6,121,398). The resulting polymers had linear, branched, light- and highly-crosslinked chain architectures and could be used as pressure sensitive adhesives, elastomers and high performance rigid thermoset composite resins. To optimize the molecular design and minimize the number of chemical trials in this system with excess degrees of freedom, we developed a computer simulation of the free radical polymerization process. The triglyceride structure, degree of chemical substitution, mole fractions, fatty acid distribution function, and reaction kinetic parameters were used as initial inputs on a 3d lattice simulation. The evolution of the network fractal structure was computed and used to measure crosslink density, dangling ends, degree of reaction and defects in the lattice. The molecular connectivity was used to determine strength via a vector percolation model of fracture. The simulation permitted the optimal design of new bio-based materials with respect to monomer selection, cure reaction conditions and desired properties. Supported by the National Science Foundation

Stochastic hybrid systems for studying biochemical processes.

PubMed

Singh, Abhyudai; Hespanha, João P

2010-11-13

Many protein and mRNA species occur at low molecular counts within cells, and hence are subject to large stochastic fluctuations in copy numbers over time. Development of computationally tractable frameworks for modelling stochastic fluctuations in population counts is essential to understand how noise at the cellular level affects biological function and phenotype. We show that stochastic hybrid systems (SHSs) provide a convenient framework for modelling the time evolution of population counts of different chemical species involved in a set of biochemical reactions. We illustrate recently developed techniques that allow fast computations of the statistical moments of the population count, without having to run computationally expensive Monte Carlo simulations of the biochemical reactions. Finally, we review different examples from the literature that illustrate the benefits of using SHSs for modelling biochemical processes.

Sucrose in Aqueous Solution Revisited: 2. Adaptively Biased Molecular Dynamics Simulations and Computational Analysis of NMR Relaxation

PubMed Central

Xia, Junchao; Case, David A.

2012-01-01

We report 100 ns molecular dynamics simulations, at various temperatures, of sucrose in water (with concentrations of sucrose ranging from 0.02 to 4 M), and in a 7:3 water-DMSO mixture. Convergence of the resulting conformational ensembles was checked using adaptive-biased simulations along the glycosidic φ and ψ torsion angles. NMR relaxation parameters, including longitudinal (R1) and transverse (R2) relaxation rates, nuclear Overhauser enhancements (NOE), and generalized order parameter (S2) were computed from the resulting time-correlation functions. The amplitude and time scales of molecular motions change with temperature and concentration in ways that track closely with experimental results, and are consistent with a model in which sucrose conformational fluctuations are limited (with 80–90% of the conformations having φ – ψ values within 20° of an average conformation), but with some important differences in conformation between pure water and DMSO-water mixtures. PMID:22058066

Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

DOE PAGES

Sornborger, Andrew Tyler; Stancil, Phillip; Geller, Michael R.

2018-03-22

Here, one of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputedmore » potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born–Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3–8 channels and circuit depths < 1000.« less

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations

PubMed Central

2016-01-01

The nucleation of crystals in liquids is one of nature’s most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insights into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that, in the past few decades, have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state-of-the-art computational methods by reviewing simulations of such processes as ice nucleation and the crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insights into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that, as a result, the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that, by improving (i) existing interatomic potentials and (ii) currently available enhanced sampling methods, the community can move toward accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments. PMID:27228560

Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sornborger, Andrew Tyler; Stancil, Phillip; Geller, Michael R.

Here, one of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputedmore » potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born–Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3–8 channels and circuit depths < 1000.« less

Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

NASA Astrophysics Data System (ADS)

Sornborger, Andrew T.; Stancil, Phillip; Geller, Michael R.

2018-05-01

One of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputed potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born-Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈ 10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3-8 channels and circuit depths < 1000.

Crystal Nucleation in Liquids: Open Questions and Future Challenges in Molecular Dynamics Simulations.

PubMed

Sosso, Gabriele C; Chen, Ji; Cox, Stephen J; Fitzner, Martin; Pedevilla, Philipp; Zen, Andrea; Michaelides, Angelos

2016-06-22

The nucleation of crystals in liquids is one of nature's most ubiquitous phenomena, playing an important role in areas such as climate change and the production of drugs. As the early stages of nucleation involve exceedingly small time and length scales, atomistic computer simulations can provide unique insights into the microscopic aspects of crystallization. In this review, we take stock of the numerous molecular dynamics simulations that, in the past few decades, have unraveled crucial aspects of crystal nucleation in liquids. We put into context the theoretical framework of classical nucleation theory and the state-of-the-art computational methods by reviewing simulations of such processes as ice nucleation and the crystallization of molecules in solutions. We shall see that molecular dynamics simulations have provided key insights into diverse nucleation scenarios, ranging from colloidal particles to natural gas hydrates, and that, as a result, the general applicability of classical nucleation theory has been repeatedly called into question. We have attempted to identify the most pressing open questions in the field. We believe that, by improving (i) existing interatomic potentials and (ii) currently available enhanced sampling methods, the community can move toward accurate investigations of realistic systems of practical interest, thus bringing simulations a step closer to experiments.

Key issues in the computational simulation of GPCR function: representation of loop domains

NASA Astrophysics Data System (ADS)

Mehler, E. L.; Periole, X.; Hassan, S. A.; Weinstein, H.

2002-11-01

Some key concerns raised by molecular modeling and computational simulation of functional mechanisms for membrane proteins are discussed and illustrated for members of the family of G protein coupled receptors (GPCRs). Of particular importance are issues related to the modeling and computational treatment of loop regions. These are demonstrated here with results from different levels of computational simulations applied to the structures of rhodopsin and a model of the 5-HT2A serotonin receptor, 5-HT2AR. First, comparative Molecular Dynamics (MD) simulations are reported for rhodopsin in vacuum and embedded in an explicit representation of the membrane and water environment. It is shown that in spite of a partial accounting of solvent screening effects by neutralization of charged side chains, vacuum MD simulations can lead to severe distortions of the loop structures. The primary source of the distortion appears to be formation of artifactual H-bonds, as has been repeatedly observed in vacuum simulations. To address such shortcomings, a recently proposed approach that has been developed for calculating the structure of segments that connect elements of secondary structure with known coordinates, is applied to 5-HT2AR to obtain an initial representation of the loops connecting the transmembrane (TM) helices. The approach consists of a simulated annealing combined with biased scaled collective variables Monte Carlo technique, and is applied to loops connecting the TM segments on both the extra-cellular and the cytoplasmic sides of the receptor. Although this initial calculation treats the loops as independent structural entities, the final structure exhibits a number of interloop interactions that may have functional significance. Finally, it is shown here that in the case where a given loop from two different GPCRs (here rhodopsin and 5-HT2AR) has approximately the same length and some degree of sequence identity, the fold adopted by the loops can be similar. Thus, in such special cases homology modeling might be used to obtain initial structures of these loops. Notably, however, all other loops in these two receptors appear to be very different in sequence and structure, so that their conformations can be found reliably only by ab initio, energy based methods and not by homology modeling.

Vibrational, spectroscopic, molecular docking and density functional theory studies on N-(5-aminopyridin-2-yl)acetamide

NASA Astrophysics Data System (ADS)

Asath, R. Mohamed; Rekha, T. N.; Premkumar, S.; Mathavan, T.; Benial, A. Milton Franklin

2016-12-01

Conformational analysis was carried out for N-(5-aminopyridin-2-yl)acetamide (APA) molecule. The most stable, optimized structure was predicted by the density functional theory calculations using the B3LYP functional with cc-pVQZ basis set. The optimized structural parameters and vibrational frequencies were calculated. The experimental and theoretical vibrational frequencies were assigned and compared. Ultraviolet-visible spectrum was simulated and validated experimentally. The molecular electrostatic potential surface was simulated. Frontier molecular orbitals and related molecular properties were computed, which reveals that the higher molecular reactivity and stability of the APA molecule and further density of states spectrum was simulated. The natural bond orbital analysis was also performed to confirm the bioactivity of the APA molecule. Antidiabetic activity was studied based on the molecular docking analysis and the APA molecule was identified that it can act as a good inhibitor against diabetic nephropathy.

Asynchronous Replica Exchange Software for Grid and Heterogeneous Computing.

PubMed

Gallicchio, Emilio; Xia, Junchao; Flynn, William F; Zhang, Baofeng; Samlalsingh, Sade; Mentes, Ahmet; Levy, Ronald M

2015-11-01

Parallel replica exchange sampling is an extended ensemble technique often used to accelerate the exploration of the conformational ensemble of atomistic molecular simulations of chemical systems. Inter-process communication and coordination requirements have historically discouraged the deployment of replica exchange on distributed and heterogeneous resources. Here we describe the architecture of a software (named ASyncRE) for performing asynchronous replica exchange molecular simulations on volunteered computing grids and heterogeneous high performance clusters. The asynchronous replica exchange algorithm on which the software is based avoids centralized synchronization steps and the need for direct communication between remote processes. It allows molecular dynamics threads to progress at different rates and enables parameter exchanges among arbitrary sets of replicas independently from other replicas. ASyncRE is written in Python following a modular design conducive to extensions to various replica exchange schemes and molecular dynamics engines. Applications of the software for the modeling of association equilibria of supramolecular and macromolecular complexes on BOINC campus computational grids and on the CPU/MIC heterogeneous hardware of the XSEDE Stampede supercomputer are illustrated. They show the ability of ASyncRE to utilize large grids of desktop computers running the Windows, MacOS, and/or Linux operating systems as well as collections of high performance heterogeneous hardware devices.

Effect of Material Ion Exchanges on the Mechanical Stiffness Properties and Shear Deformation of Hydrated Cement Material Chemistry Structure C-S-H Jennit - A Computational Modeling Study

DTIC Science & Technology

2014-01-01

Study Material properties and performance are governed by material molecular chemistry structures and molecular level interactions. Methods to...understand relationships between the material properties and performance and their correlation to the molecular level chemistry and morphology, and thus...find ways of manipulating and adjusting matters at the atomistic level in order to improve material performance are required. A computational material

VMS-ROT: A New Module of the Virtual Multifrequency Spectrometer for Simulation, Interpretation, and Fitting of Rotational Spectra

PubMed Central

2017-01-01

The Virtual Multifrequency Spectrometer (VMS) is a tool that aims at integrating a wide range of computational and experimental spectroscopic techniques with the final goal of disclosing the static and dynamic physical–chemical properties “hidden” in molecular spectra. VMS is composed of two parts, namely, VMS-Comp, which provides access to the latest developments in the field of computational spectroscopy, and VMS-Draw, which provides a powerful graphical user interface (GUI) for an intuitive interpretation of theoretical outcomes and a direct comparison to experiment. In the present work, we introduce VMS-ROT, a new module of VMS that has been specifically designed to deal with rotational spectroscopy. This module offers an integrated environment for the analysis of rotational spectra: from the assignment of spectral transitions to the refinement of spectroscopic parameters and the simulation of the spectrum. While bridging theoretical and experimental rotational spectroscopy, VMS-ROT is strongly integrated with quantum-chemical calculations, and it is composed of four independent, yet interacting units: (1) the computational engine for the calculation of the spectroscopic parameters that are employed as a starting point for guiding experiments and for the spectral interpretation, (2) the fitting-prediction engine for the refinement of the molecular parameters on the basis of the assigned transitions and the prediction of the rotational spectrum of the target molecule, (3) the GUI module that offers a powerful set of tools for a vis-à-vis comparison between experimental and simulated spectra, and (4) the new assignment tool for the assignment of experimental transitions in terms of quantum numbers upon comparison with the simulated ones. The implementation and the main features of VMS-ROT are presented, and the software is validated by means of selected test cases ranging from isolated molecules of different sizes to molecular complexes. VMS-ROT therefore offers an integrated environment for the analysis of the rotational spectra, with the innovative perspective of an intimate connection to quantum-chemical calculations that can be exploited at different levels of refinement, as an invaluable support and complement for experimental studies. PMID:28742339

Computational design and multiscale modeling of a nanoactuator using DNA actuation.

PubMed

Hamdi, Mustapha

2009-12-02

Developments in the field of nanobiodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier.

Empirical simulations of materials

NASA Astrophysics Data System (ADS)

Jogireddy, Vasantha

2011-12-01

Molecular dynamics is a specialized discipline of molecular modelling and computer techniques. In this work, first we presented simulation results from a study carried out on silicon nanowires. In the second part of the work, we presented an electrostatic screened coulomb potential developed for studying metal alloys and metal oxides. In particular, we have studied aluminum-copper alloys, aluminum oxides and copper oxides. Parameter optimization for the potential is done using multiobjective optimization algorithms.

A Fast Algorithm for Massively Parallel, Long-Term, Simulation of Complex Molecular Dynamics Systems

NASA Technical Reports Server (NTRS)

Jaramillo-Botero, Andres; Goddard, William A, III; Fijany, Amir

1997-01-01

The advances in theory and computing technology over the last decade have led to enormous progress in applying atomistic molecular dynamics (MD) methods to the characterization, prediction, and design of chemical, biological, and material systems,.

Experiment-scale molecular simulation study of liquid crystal thin films

NASA Astrophysics Data System (ADS)

Nguyen, Trung Dac; Carrillo, Jan-Michael Y.; Matheson, Michael A.; Brown, W. Michael

2014-03-01

Supercomputers have now reached a performance level adequate for studying thin films with molecular detail at the relevant scales. By exploiting the power of GPU accelerators on Titan, we have been able to perform simulations of characteristic liquid crystal films that provide remarkable qualitative agreement with experimental images. We have demonstrated that key features of spinodal instability can only be observed with sufficiently large system sizes, which were not accessible with previous simulation studies. Our study emphasizes the capability and significance of petascale simulations in providing molecular-level insights in thin film systems as well as other interfacial phenomena.

Informing Mechanistic Toxicology with Computational Molecular Models

EPA Science Inventory

Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo effo...

Accelerated Molecular Dynamics Simulations with the AMOEBA Polarizable Force Field on Graphics Processing Units

PubMed Central

2013-01-01

The accelerated molecular dynamics (aMD) method has recently been shown to enhance the sampling of biomolecules in molecular dynamics (MD) simulations, often by several orders of magnitude. Here, we describe an implementation of the aMD method for the OpenMM application layer that takes full advantage of graphics processing units (GPUs) computing. The aMD method is shown to work in combination with the AMOEBA polarizable force field (AMOEBA-aMD), allowing the simulation of long time-scale events with a polarizable force field. Benchmarks are provided to show that the AMOEBA-aMD method is efficiently implemented and produces accurate results in its standard parametrization. For the BPTI protein, we demonstrate that the protein structure described with AMOEBA remains stable even on the extended time scales accessed at high levels of accelerations. For the DNA repair metalloenzyme endonuclease IV, we show that the use of the AMOEBA force field is a significant improvement over fixed charged models for describing the enzyme active-site. The new AMOEBA-aMD method is publicly available (http://wiki.simtk.org/openmm/VirtualRepository) and promises to be interesting for studying complex systems that can benefit from both the use of a polarizable force field and enhanced sampling. PMID:24634618

Ligand diffusion in proteins via enhanced sampling in molecular dynamics.

PubMed

Rydzewski, J; Nowak, W

2017-12-01

Computational simulations in biophysics describe the dynamics and functions of biological macromolecules at the atomic level. Among motions particularly important for life are the transport processes in heterogeneous media. The process of ligand diffusion inside proteins is an example of a complex rare event that can be modeled using molecular dynamics simulations. The study of physical interactions between a ligand and its biological target is of paramount importance for the design of novel drugs and enzymes. Unfortunately, the process of ligand diffusion is difficult to study experimentally. The need for identifying the ligand egress pathways and understanding how ligands migrate through protein tunnels has spurred the development of several methodological approaches to this problem. The complex topology of protein channels and the transient nature of the ligand passage pose difficulties in the modeling of the ligand entry/escape pathways by canonical molecular dynamics simulations. In this review, we report a methodology involving a reconstruction of the ligand diffusion reaction coordinates and the free-energy profiles along these reaction coordinates using enhanced sampling of conformational space. We illustrate the above methods on several ligand-protein systems, including cytochromes and G-protein-coupled receptors. The methods are general and may be adopted to other transport processes in living matter. Copyright © 2017 Elsevier B.V. All rights reserved.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling

PubMed Central

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

PubMed

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Kinetic barriers in the isomerization of substituted ureas: implications for computer-aided drug design.

PubMed

Loeffler, Johannes R; Ehmki, Emanuel S R; Fuchs, Julian E; Liedl, Klaus R

2016-05-01

Urea derivatives are ubiquitously found in many chemical disciplines. N,N'-substituted ureas may show different conformational preferences depending on their substitution pattern. The high energetic barrier for isomerization of the cis and trans state poses additional challenges on computational simulation techniques aiming at a reproduction of the biological properties of urea derivatives. Herein, we investigate energetics of urea conformations and their interconversion using a broad spectrum of methodologies ranging from data mining, via quantum chemistry to molecular dynamics simulation and free energy calculations. We find that the inversion of urea conformations is inherently slow and beyond the time scale of typical simulation protocols. Therefore, extra care needs to be taken by computational chemists to work with appropriate model systems. We find that both knowledge-driven approaches as well as physics-based methods may guide molecular modelers towards accurate starting structures for expensive calculations to ensure that conformations of urea derivatives are modeled as adequately as possible.

Importance of Vibronic Effects in the UV-Vis Spectrum of the 7,7,8,8-Tetracyanoquinodimethane Anion.

PubMed

Tapavicza, Enrico; Furche, Filipp; Sundholm, Dage

2016-10-11

We present a computational method for simulating vibronic absorption spectra in the ultraviolet-visible (UV-vis) range and apply it to the 7,7,8,8-tetracyanoquinodimethane anion (TCNQ - ), which has been used as a ligand in black absorbers. Gaussian broadening of vertical electronic excitation energies of TCNQ - from linear-response time-dependent density functional theory produces only one band, which is qualitatively incorrect. Thus, the harmonic vibrational modes of the two lowest doublet states were computed, and the vibronic UV-vis spectrum was simulated using the displaced harmonic oscillator approximation, the frequency-shifted harmonic oscillator approximation, and the full Duschinsky formalism. An efficient real-time generating function method was implemented to avoid the exponential complexity of conventional Franck-Condon approaches to vibronic spectra. The obtained UV-vis spectra for TCNQ - agree well with experiment; the Duschinsky rotation is found to have only a minor effect on the spectrum. Born-Oppenheimer molecular dynamics simulations combined with calculations of the electronic excitation energies for a large number of molecular structures were also used for simulating the UV-vis spectrum. The Born-Oppenheimer molecular dynamics simulations yield a broadening of the energetically lowest peak in the absorption spectrum, but additional vibrational bands present in the experimental and simulated quantum harmonic oscillator spectra are not observed in the molecular dynamics simulations. Our results underline the importance of vibronic effects for the UV-vis spectrum of TCNQ - , and they establish an efficient method for obtaining vibronic spectra using a combination of linear-response time-dependent density functional theory and a real-time generating function approach.

Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics.

PubMed

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.

Grand canonical ensemble Monte Carlo simulation of the dCpG/proflavine crystal hydrate.

PubMed Central

Resat, H; Mezei, M

1996-01-01

The grand canonical ensemble Monte Carlo molecular simulation method is used to investigate hydration patterns in the crystal hydrate structure of the dCpG/proflavine intercalated complex. The objective of this study is to show by example that the recently advocated grand canonical ensemble simulation is a computationally efficient method for determining the positions of the hydrating water molecules in protein and nucleic acid structures. A detailed molecular simulation convergence analysis and an analogous comparison of the theoretical results with experiments clearly show that the grand ensemble simulations can be far more advantageous than the comparable canonical ensemble simulations. Images FIGURE 5 FIGURE 7 PMID:8873992

Uncovering molecular processes in crystal nucleation and growth by using molecular simulation.

PubMed

Anwar, Jamshed; Zahn, Dirk

2011-02-25

Exploring nucleation processes by molecular simulation provides a mechanistic understanding at the atomic level and also enables kinetic and thermodynamic quantities to be estimated. However, whilst the potential for modeling crystal nucleation and growth processes is immense, there are specific technical challenges to modeling. In general, rare events, such as nucleation cannot be simulated using a direct "brute force" molecular dynamics approach. The limited time and length scales that are accessible by conventional molecular dynamics simulations have inspired a number of advances to tackle problems that were considered outside the scope of molecular simulation. While general insights and features could be explored from efficient generic models, new methods paved the way to realistic crystal nucleation scenarios. The association of single ions in solvent environments, the mechanisms of motif formation, ripening reactions, and the self-organization of nanocrystals can now be investigated at the molecular level. The analysis of interactions with growth-controlling additives gives a new understanding of functionalized nanocrystals and the precipitation of composite materials. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Science | Argonne National Laboratory

Science.gov Websites

Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at Argonne Work with Scientific Publications Researchers Postdocs Exascale Computing Institute for Molecular Engineering at understand, predict, and ultimately control matter and energy at the electronic, atomic, and molecular levels

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP; Soares, Thereza A.

2007-12-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Data Intensive Analysis of Biomolecular Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straatsma, TP

2008-03-01

The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less

Quantum Monte Carlo for large chemical systems: implementing efficient strategies for petascale platforms and beyond.

PubMed

Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

2013-04-30

Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC=Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible. Copyright © 2013 Wiley Periodicals, Inc.

Structural dynamics of possible late-stage intermediates in folding of quadruplex DNA studied by molecular simulations

PubMed Central

Stadlbauer, Petr; Krepl, Miroslav; Cheatham, Thomas E.; Koča, Jaroslav; Šponer, Jiří

2013-01-01

Explicit solvent molecular dynamics simulations have been used to complement preceding experimental and computational studies of folding of guanine quadruplexes (G-DNA). We initiate early stages of unfolding of several G-DNAs by simulating them under no-salt conditions and then try to fold them back using standard excess salt simulations. There is a significant difference between G-DNAs with all-anti parallel stranded stems and those with stems containing mixtures of syn and anti guanosines. The most natural rearrangement for all-anti stems is a vertical mutual slippage of the strands. This leads to stems with reduced numbers of tetrads during unfolding and a reduction of strand slippage during refolding. The presence of syn nucleotides prevents mutual strand slippage; therefore, the antiparallel and hybrid quadruplexes initiate unfolding via separation of the individual strands. The simulations confirm the capability of G-DNA molecules to adopt numerous stable locally and globally misfolded structures. The key point for a proper individual folding attempt appears to be correct prior distribution of syn and anti nucleotides in all four G-strands. The results suggest that at the level of individual molecules, G-DNA folding is an extremely multi-pathway process that is slowed by numerous misfolding arrangements stabilized on highly variable timescales. PMID:23700306

Accuracy of buffered-force QM/MM simulations of silica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peguiron, Anke; Moras, Gianpietro; Colombi Ciacchi, Lucio

2015-02-14

We report comparisons between energy-based quantum mechanics/molecular mechanics (QM/MM) and buffered force-based QM/MM simulations in silica. Local quantities—such as density of states, charges, forces, and geometries—calculated with both QM/MM approaches are compared to the results of full QM simulations. We find the length scale over which forces computed using a finite QM region converge to reference values obtained in full quantum-mechanical calculations is ∼10 Å rather than the ∼5 Å previously reported for covalent materials such as silicon. Electrostatic embedding of the QM region in the surrounding classical point charges gives only a minor contribution to the force convergence. Whilemore » the energy-based approach provides accurate results in geometry optimizations of point defects, we find that the removal of large force errors at the QM/MM boundary provided by the buffered force-based scheme is necessary for accurate constrained geometry optimizations where Si–O bonds are elongated and for finite-temperature molecular dynamics simulations of crack propagation. Moreover, the buffered approach allows for more flexibility, since special-purpose QM/MM coupling terms that link QM and MM atoms are not required and the region that is treated at the QM level can be adaptively redefined during the course of a dynamical simulation.« less

Solvation of fluoro-acetonitrile in water by 2D-IR spectroscopy: A combined experimental-computational study

NASA Astrophysics Data System (ADS)

Cazade, Pierre-André; Tran, Halina; Bereau, Tristan; Das, Akshaya K.; Kläsi, Felix; Hamm, Peter; Meuwly, Markus

2015-06-01

The solvent dynamics around fluorinated acetonitrile is characterized by 2-dimensional infrared spectroscopy and atomistic simulations. The lineshape of the linear infrared spectrum is better captured by semiempirical (density functional tight binding) mixed quantum mechanical/molecular mechanics simulations, whereas force field simulations with multipolar interactions yield lineshapes that are significantly too narrow. For the solvent dynamics, a relatively slow time scale of 2 ps is found from the experiments and supported by the mixed quantum mechanical/molecular mechanics simulations. With multipolar force fields fitted to the available thermodynamical data, the time scale is considerably faster—on the 0.5 ps time scale. The simulations provide evidence for a well established CF-HOH hydrogen bond (population of 25%) which is found from the radial distribution function g(r) from both, force field and quantum mechanics/molecular mechanics simulations.

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

PubMed Central

2010-01-01

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics. PMID:21067546

The Structure and Properties of Silica Glass Nanostructures using Novel Computational Systems

NASA Astrophysics Data System (ADS)

Doblack, Benjamin N.

The structure and properties of silica glass nanostructures are examined using computational methods in this work. Standard synthesis methods of silica and its associated material properties are first discussed in brief. A review of prior experiments on this amorphous material is also presented. Background and methodology for the simulation of mechanical tests on amorphous bulk silica and nanostructures are later presented. A new computational system for the accurate and fast simulation of silica glass is also presented, using an appropriate interatomic potential for this material within the open-source molecular dynamics computer program LAMMPS. This alternative computational method uses modern graphics processors, Nvidia CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model select materials, this enhancement allows the addition of accelerated molecular dynamics simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal of this project is to investigate the structure and size dependent mechanical properties of silica glass nanohelical structures under tensile MD conditions using the innovative computational system. Specifically, silica nanoribbons and nanosprings are evaluated which revealed unique size dependent elastic moduli when compared to the bulk material. For the nanoribbons, the tensile behavior differed widely between the models simulated, with distinct characteristic extended elastic regions. In the case of the nanosprings simulated, more clear trends are observed. In particular, larger nanospring wire cross-sectional radii (r) lead to larger Young's moduli, while larger helical diameters (2R) resulted in smaller Young's moduli. Structural transformations and theoretical models are also analyzed to identify possible factors which might affect the mechanical response of silica nanostructures under tension. The work presented outlines an innovative simulation methodology, and discusses how results can be validated against prior experimental and simulation findings. The ultimate goal is to develop new computational methods for the study of nanostructures which will make the field of materials science more accessible, cost effective and efficient.

Molecular dynamics simulations of substitutional diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xiaowang; Jones, Reese E.; Gruber, Jacob

2016-12-18

In atomistic simulations, diffusion energy barriers are usually calculated for each atomic jump path using a nudged elastic band method. Practical materials often involve thousands of distinct atomic jump paths that are not known a priori. Hence, it is often preferred to determine an overall diffusion energy barrier and an overall pre-exponential factor from the Arrhenius equation constructed through molecular dynamics simulations of mean square displacement of the diffusion species at different temperatures. This approach has been well established for interstitial diffusion, but not for substitutional diffusion at the same confidence. Using In 0.1 Ga 0.9 N as an example,more » we have identified conditions where molecular dynamics simulations can be used to calculate highly converged Arrhenius plots for substitutional alloys. As a result, this may enable many complex diffusion problems to be easily and reliably studied in the future using molecular dynamics, provided that moderate computing resources are available.« less

Adaptively restrained molecular dynamics in LAMMPS

NASA Astrophysics Data System (ADS)

Kant Singh, Krishna; Redon, Stephane

2017-07-01

Adaptively restrained molecular dynamics (ARMD) is a recently introduced particles simulation method that switches positional degrees of freedom on and off during simulation in order to speed up calculations. In the NVE ensemble, ARMD allows users to trade between precision and speed while, in the NVT ensemble, it makes it possible to compute statistical averages faster. Despite the conceptual simplicity of the approach, however, integrating it in existing molecular dynamics packages is non-trivial, in particular since implemented potentials should a priori be rewritten to take advantage of frozen particles and achieve a speed-up. In this paper, we present novel algorithms for integrating ARMD in LAMMPS, a popular multi-purpose molecular simulation package. In particular, we demonstrate how to enable ARMD in LAMMPS without having to re-implement all available force fields. The proposed algorithms are assessed on four different benchmarks, and show how they allow us to speed up simulations up to one order of magnitude.

MaMiCo: Transient multi-instance molecular-continuum flow simulation on supercomputers

NASA Astrophysics Data System (ADS)

Neumann, Philipp; Bian, Xin

2017-11-01

We present extensions of the macro-micro-coupling tool MaMiCo, which was designed to couple continuum fluid dynamics solvers with discrete particle dynamics. To enable local extraction of smooth flow field quantities especially on rather short time scales, sampling over an ensemble of molecular dynamics simulations is introduced. We provide details on these extensions including the transient coupling algorithm, open boundary forcing, and multi-instance sampling. Furthermore, we validate the coupling in Couette flow using different particle simulation software packages and particle models, i.e. molecular dynamics and dissipative particle dynamics. Finally, we demonstrate the parallel scalability of the molecular-continuum simulations by using up to 65 536 compute cores of the supercomputer Shaheen II located at KAUST. Program Files doi:http://dx.doi.org/10.17632/w7rgdrhb85.1 Licensing provisions: BSD 3-clause Programming language: C, C++ External routines/libraries: For compiling: SCons, MPI (optional) Subprograms used: ESPResSo, LAMMPS, ls1 mardyn, waLBerla For installation procedures of the MaMiCo interfaces, see the README files in the respective code directories located in coupling/interface/impl. Journal reference of previous version: P. Neumann, H. Flohr, R. Arora, P. Jarmatz, N. Tchipev, H.-J. Bungartz. MaMiCo: Software design for parallel molecular-continuum flow simulations, Computer Physics Communications 200: 324-335, 2016 Does the new version supersede the previous version?: Yes. The functionality of the previous version is completely retained in the new version. Nature of problem: Coupled molecular-continuum simulation for multi-resolution fluid dynamics: parts of the domain are resolved by molecular dynamics or another particle-based solver whereas large parts are covered by a mesh-based CFD solver, e.g. a lattice Boltzmann automaton. Solution method: We couple existing MD and CFD solvers via MaMiCo (macro-micro coupling tool). Data exchange and coupling algorithmics are abstracted and incorporated in MaMiCo. Once an algorithm is set up in MaMiCo, it can be used and extended, even if other solvers are used (as soon as the respective interfaces are implemented/available). Reasons for the new version: We have incorporated a new algorithm to simulate transient molecular-continuum systems and to automatically sample data over multiple MD runs that can be executed simultaneously (on, e.g., a compute cluster). MaMiCo has further been extended by an interface to incorporate boundary forcing to account for open molecular dynamics boundaries. Besides support for coupling with various MD and CFD frameworks, the new version contains a test case that allows to run molecular-continuum Couette flow simulations out-of-the-box. No external tools or simulation codes are required anymore. However, the user is free to switch from the included MD simulation package to LAMMPS. For details on how to run the transient Couette problem, see the file README in the folder coupling/tests, Remark on MaMiCo V1.1. Summary of revisions: Open boundary forcing; Multi-instance MD sampling; support for transient molecular-continuum systems Restrictions: Currently, only single-centered systems are supported. For access to the LAMMPS-based implementation of DPD boundary forcing, please contact Xin Bian, xin.bian@tum.de. Additional comments: Please see file license_mamico.txt for further details regarding distribution and advertising of this software.

Atomistic Simulation of Interfaces in Materials of Solid State Ionics

NASA Astrophysics Data System (ADS)

Ivanov-Schitz, A. K.; Mazo, G. N.

2018-01-01

The possibilities of describing correctly interfaces of different types in solids within a computer experiment using molecular statics simulation, molecular dynamics simulation, and quantum chemical calculations are discussed. Heterophase boundaries of various types, including grain boundaries and solid electrolyte‒solid electrolyte and ionic conductor‒electrode material interfaces, are considered. Specific microstructural features and mechanisms of the ion transport in real heterophase structures (cationic conductor‒metal anode and anionic conductor‒cathode) existing in solid state ionics devices (such as solid-state batteries and fuel cells) are discussed.

Complex molecular assemblies at hand via interactive simulations.

PubMed

Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc

2009-11-30

Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.

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.

An autonomous molecular computer for logical control of gene expression

PubMed Central

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2013-01-01

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1–7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8–15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for ‘logical’ control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12–17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18–22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug. PMID:15116117

Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

PubMed Central

Crawford, Alasdair O.; Hamerton, Ian; Cavalli, Gabriel; Howlin, Brendan J.

2012-01-01

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties. PMID:22970230

Coulomb interactions in charged fluids.

PubMed

Vernizzi, Graziano; Guerrero-García, Guillermo Iván; de la Cruz, Monica Olvera

2011-07-01

The use of Ewald summation schemes for calculating long-range Coulomb interactions, originally applied to ionic crystalline solids, is a very common practice in molecular simulations of charged fluids at present. Such a choice imposes an artificial periodicity which is generally absent in the liquid state. In this paper we propose a simple analytical O(N(2)) method which is based on Gauss's law for computing exactly the Coulomb interaction between charged particles in a simulation box, when it is averaged over all possible orientations of a surrounding infinite lattice. This method mitigates the periodicity typical of crystalline systems and it is suitable for numerical studies of ionic liquids, charged molecular fluids, and colloidal systems with Monte Carlo and molecular dynamics simulations.

Molecular Gibbs Surface Excess and CO2-Hydrate Density Determine the Strong Temperature- and Pressure-Dependent Supercritical CO2-Brine Interfacial Tension.

PubMed

Ji, Jiayuan; Zhao, Lingling; Tao, Lu; Lin, Shangchao

2017-06-29

In CO 2 geological storage, the interfacial tension (IFT) between supercritical CO 2 and brine is critical for the storage capacitance design to prevent CO 2 leakage. IFT relies not only on the interfacial molecule properties but also on the environmental conditions at different storage sites. In this paper, supercritical CO 2 -NaCl solution systems are modeled at 343-373 K and 6-35 MPa under the salinity of 1.89 mol/L using molecular dynamics simulations. After computing and comparing the molecular density profile across the interface, the atomic radial distribution function, the molecular orientation distribution, the molecular Gibbs surface excess (derived from the molecular density profile), and the CO 2 -hydrate number density under the above environmental conditions, we confirm that only the molecular Gibbs surface excess of CO 2 molecules and the CO 2 -hydrate number density correlate strongly with the temperature- and pressure-dependent IFTs. We also compute the populations of two distinct CO 2 -hydrate structures (T-type and H-type) and attribute the observed dependence of IFTs to the dominance of the more stable, surfactant-like T-type CO 2 -hydrates at the interface. On the basis of these new molecular mechanisms behind IFT variations, this study could guide the rational design of suitable injecting environmental pressure and temperature conditions. We believe that the above two molecular-level metrics (Gibbs surface excess and hydrate number density) are of great fundamental importance for understanding the supercritical CO 2 -water interface and engineering applications in geological CO 2 storage.

Molecular dynamics simulations of biological membranes and membrane proteins using enhanced conformational sampling algorithms.

PubMed

Mori, Takaharu; Miyashita, Naoyuki; Im, Wonpil; Feig, Michael; Sugita, Yuji

2016-07-01

This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Atomdroid: a computational chemistry tool for mobile platforms.

PubMed

Feldt, Jonas; Mata, Ricardo A; Dieterich, Johannes M

2012-04-23

We present the implementation of a new molecular mechanics program designed for use in mobile platforms, the first specifically built for these devices. The software is designed to run on Android operating systems and is compatible with several modern tablet-PCs and smartphones available in the market. It includes molecular viewer/builder capabilities with integrated routines for geometry optimizations and Monte Carlo simulations. These functionalities allow it to work as a stand-alone tool. We discuss some particular development aspects, as well as the overall feasibility of using computational chemistry software packages in mobile platforms. Benchmark calculations show that through efficient implementation techniques even hand-held devices can be used to simulate midsized systems using force fields.

Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials.

PubMed

Skelton, Jonathan M; Loke, Desmond; Lee, Taehoon; Elliott, Stephen R

2015-07-08

We present an in silico study of the neuromorphic-computing behavior of the prototypical phase-change material, Ge2Sb2Te5, using ab initio molecular-dynamics simulations. Stepwise changes in structural order in response to temperature pulses of varying length and duration are observed, and a good reproduction of the spike-timing-dependent plasticity observed in nanoelectronic synapses is demonstrated. Short above-melting pulses lead to instantaneous loss of structural and chemical order, followed by delayed partial recovery upon structural relaxation. We also investigate the link between structural order and electrical and optical properties. These results pave the way toward a first-principles understanding of phase-change physics beyond binary switching.

Optimization of the molecular dynamics method for simulations of DNA and ion transport through biological nanopores.

PubMed

Wells, David B; Bhattacharya, Swati; Carr, Rogan; Maffeo, Christopher; Ho, Anthony; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Molecular dynamics (MD) simulations have become a standard method for the rational design and interpretation of experimental studies of DNA translocation through nanopores. The MD method, however, offers a multitude of algorithms, parameters, and other protocol choices that can affect the accuracy of the resulting data as well as computational efficiency. In this chapter, we examine the most popular choices offered by the MD method, seeking an optimal set of parameters that enable the most computationally efficient and accurate simulations of DNA and ion transport through biological nanopores. In particular, we examine the influence of short-range cutoff, integration timestep and force field parameters on the temperature and concentration dependence of bulk ion conductivity, ion pairing, ion solvation energy, DNA structure, DNA-ion interactions, and the ionic current through a nanopore.

Educational aspects of molecular simulation

NASA Astrophysics Data System (ADS)

Allen, Michael P.

This article addresses some aspects of teaching simulation methods to undergraduates and graduate students. Simulation is increasingly a cross-disciplinary activity, which means that the students who need to learn about simulation methods may have widely differing backgrounds. Also, they may have a wide range of views on what constitutes an interesting application of simulation methods. Almost always, a successful simulation course includes an element of practical, hands-on activity: a balance always needs to be struck between treating the simulation software as a 'black box', and becoming bogged down in programming issues. With notebook computers becoming widely available, students often wish to take away the programs to run themselves, and access to raw computer power is not the limiting factor that it once was; on the other hand, the software should be portable and, if possible, free. Examples will be drawn from the author's experience in three different contexts. (1) An annual simulation summer school for graduate students, run by the UK CCP5 organization, in which practical sessions are combined with an intensive programme of lectures describing the methodology. (2) A molecular modelling module, given as part of a doctoral training centre in the Life Sciences at Warwick, for students who might not have a first degree in the physical sciences. (3) An undergraduate module in Physics at Warwick, also taken by students from other disciplines, teaching high performance computing, visualization, and scripting in the context of a physical application such as Monte Carlo simulation.

PyRETIS: A well-done, medium-sized python library for rare events.

PubMed

Lervik, Anders; Riccardi, Enrico; van Erp, Titus S

2017-10-30

Transition path sampling techniques are becoming common approaches in the study of rare events at the molecular scale. More efficient methods, such as transition interface sampling (TIS) and replica exchange transition interface sampling (RETIS), allow the investigation of rare events, for example, chemical reactions and structural/morphological transitions, in a reasonable computational time. Here, we present PyRETIS, a Python library for performing TIS and RETIS simulations. PyRETIS directs molecular dynamics (MD) simulations in order to sample rare events with unbiased dynamics. PyRETIS is designed to be easily interfaced with any molecular simulation package and in the present release, it has been interfaced with GROMACS and CP2K, for classical and ab initio MD simulations, respectively. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Nucleic acids: theory and computer simulation, Y2K.

PubMed

Beveridge, D L; McConnell, K J

2000-04-01

Molecular dynamics simulations on DNA and RNA that include solvent are now being performed under realistic environmental conditions of water activity and salt. Improvements to force-fields and treatments of long-range interactions have significantly increased the reliability of simulations. New studies of sequence effects, axis bending, solvation and conformational transitions have appeared.

Parallel Simulation of Unsteady Turbulent Flames

NASA Technical Reports Server (NTRS)

Menon, Suresh

1996-01-01

Time-accurate simulation of turbulent flames in high Reynolds number flows is a challenging task since both fluid dynamics and combustion must be modeled accurately. To numerically simulate this phenomenon, very large computer resources (both time and memory) are required. Although current vector supercomputers are capable of providing adequate resources for simulations of this nature, the high cost and their limited availability, makes practical use of such machines less than satisfactory. At the same time, the explicit time integration algorithms used in unsteady flow simulations often possess a very high degree of parallelism, making them very amenable to efficient implementation on large-scale parallel computers. Under these circumstances, distributed memory parallel computers offer an excellent near-term solution for greatly increased computational speed and memory, at a cost that may render the unsteady simulations of the type discussed above more feasible and affordable.This paper discusses the study of unsteady turbulent flames using a simulation algorithm that is capable of retaining high parallel efficiency on distributed memory parallel architectures. Numerical studies are carried out using large-eddy simulation (LES). In LES, the scales larger than the grid are computed using a time- and space-accurate scheme, while the unresolved small scales are modeled using eddy viscosity based subgrid models. This is acceptable for the moment/energy closure since the small scales primarily provide a dissipative mechanism for the energy transferred from the large scales. However, for combustion to occur, the species must first undergo mixing at the small scales and then come into molecular contact. Therefore, global models cannot be used. Recently, a new model for turbulent combustion was developed, in which the combustion is modeled, within the subgrid (small-scales) using a methodology that simulates the mixing and the molecular transport and the chemical kinetics within each LES grid cell. Finite-rate kinetics can be included without any closure and this approach actually provides a means to predict the turbulent rates and the turbulent flame speed. The subgrid combustion model requires resolution of the local time scales associated with small-scale mixing, molecular diffusion and chemical kinetics and, therefore, within each grid cell, a significant amount of computations must be carried out before the large-scale (LES resolved) effects are incorporated. Therefore, this approach is uniquely suited for parallel processing and has been implemented on various systems such as: Intel Paragon, IBM SP-2, Cray T3D and SGI Power Challenge (PC) using the system independent Message Passing Interface (MPI) compiler. In this paper, timing data on these machines is reported along with some characteristic results.

Quantum Molecular Dynamics Simulations of Nanotube Tip Assisted Reactions

NASA Technical Reports Server (NTRS)

Menon, Madhu

1998-01-01

In this report we detail the development and application of an efficient quantum molecular dynamics computational algorithm and its application to the nanotube-tip assisted reactions on silicon and diamond surfaces. The calculations shed interesting insights into the microscopic picture of tip surface interactions.

Investigation for Molecular Attraction Impact Between Contacting Surfaces in Micro-Gears

NASA Astrophysics Data System (ADS)

Yang, Ping; Li, Xialong; Zhao, Yanfang; Yang, Haiying; Wang, Shuting; Yang, Jianming

2013-10-01

The aim of this research work is to provide a systematic method to perform molecular attraction impact between contacting surfaces in micro-gear train. This method is established by integrating involute profile analysis and molecular dynamics simulation. A mathematical computation of micro-gear involute is presented based on geometrical properties, Taylor expression and Hamaker assumption. In the meantime, Morse potential function and the cut-off radius are introduced with a molecular dynamics simulation. So a hybrid computational method for the Van Der Waals force between the contacting faces in micro-gear train is developed. An example is illustrated to show the performance of this method. The results show that the change of Van Der Waals force in micro-gear train has a nonlinear characteristic with parameters change such as the modulus of the gear and the tooth number of gear etc. The procedure implies a potential feasibility that we can control the Van Der Waals force by adjusting the manufacturing parameters for gear train design.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

PubMed

Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai

2009-03-14

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.; Knepley, Matthew G.; Anitescu, Mihai

2009-03-01

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Modeling charge transport in organic photovoltaic materials.

PubMed

Nelson, Jenny; Kwiatkowski, Joe J; Kirkpatrick, James; Frost, Jarvist M

2009-11-17

The performance of an organic photovoltaic cell depends critically on the mobility of charge carriers within the constituent molecular semiconductor materials. However, a complex combination of phenomena that span a range of length and time scales control charge transport in disordered organic semiconductors. As a result, it is difficult to rationalize charge transport properties in terms of material parameters. Until now, efforts to improve charge mobilities in molecular semiconductors have proceeded largely by trial and error rather than through systematic design. However, recent developments have enabled the first predictive simulation studies of charge transport in disordered organic semiconductors. This Account describes a set of computational methods, specifically molecular modeling methods, to simulate molecular packing, quantum chemical calculations of charge transfer rates, and Monte Carlo simulations of charge transport. Using case studies, we show how this combination of methods can reproduce experimental mobilities with few or no fitting parameters. Although currently applied to material systems of high symmetry or well-defined structure, further developments of this approach could address more complex systems such anisotropic or multicomponent solids and conjugated polymers. Even with an approximate treatment of packing disorder, these computational methods simulate experimental mobilities within an order of magnitude at high electric fields. We can both reproduce the relative values of electron and hole mobility in a conjugated small molecule and rationalize those values based on the symmetry of frontier orbitals. Using fully atomistic molecular dynamics simulations of molecular packing, we can quantitatively replicate vertical charge transport along stacks of discotic liquid crystals which vary only in the structure of their side chains. We can reproduce the trends in mobility with molecular weight for self-organizing polymers using a cheap, coarse-grained structural simulation method. Finally, we quantitatively reproduce the field-effect mobility in disordered C60 films. On the basis of these results, we conclude that all of the necessary building blocks are in place for the predictive simulation of charge transport in macromolecular electronic materials and that such methods can be used as a tool toward the future rational design of functional organic electronic materials.

Computational studies of adsorption in metal organic frameworks and interaction of nanoparticles in condensed phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Annapureddy, HVR; Motkuri, RK; Nguyen, PTM

In this review, we describe recent efforts to systematically study nano-structured metal organic frameworks (MOFs), also known as metal organic heat carriers, with particular emphasis on their application in heating and cooling processes. We used both molecular dynamics and grand canonical Monte Carlo simulation techniques to gain a molecular-level understanding of the adsorption mechanism of gases in these porous materials. We investigated the uptake of various gases such as refrigerants R12 and R143a. We also evaluated the effects of temperature and pressure on the uptake mechanism. Our computed results compared reasonably well with available measurements from experiments, thus validating ourmore » potential models and approaches. In addition, we investigated the structural, diffusive and adsorption properties of different hydrocarbons in Ni-2(dhtp). Finally, to elucidate the mechanism of nanoparticle dispersion in condensed phases, we studied the interactions among nanoparticles in various liquids, such as n-hexane, water and methanol.« less

Rationalizing the permeation of polar antibiotics into Gram-negative bacteria.

PubMed

Scorciapino, Mariano Andrea; Acosta-Gutierrez, Silvia; Benkerrou, Dehbia; D'Agostino, Tommaso; Malloci, Giuliano; Samanta, Susruta; Bodrenko, Igor; Ceccarelli, Matteo

2017-03-22

The increasing level of antibiotic resistance in Gram-negative bacteria, together with the lack of new potential drug scaffolds in the pipeline, make the problem of infectious diseases a global challenge for modern medicine. The main reason that Gram-negative bacteria are particularly challenging is the presence of an outer cell-protecting membrane, which is not present in Gram-positive species. Such an asymmetric bilayer is a highly effective barrier for polar molecules. Several protein systems are expressed in the outer membrane to control the internal concentration of both nutrients and noxious species, in particular: (i) water-filled channels that modulate the permeation of polar molecules and ions according to concentration gradients, and (ii) efflux pumps to actively expel toxic compounds. Thus, besides expressing specific enzymes for drugs degradation, Gram-negative bacteria can also resist by modulating the influx and efflux of antibiotics, keeping the internal concentration low. However, there are no direct and robust experimental methods capable of measuring the permeability of small molecules, thus severely limiting our knowledge of the molecular mechanisms that ultimately control the permeation of antibiotics through the outer membrane. This is the innovation gap to be filled for Gram-negative bacteria. This review is focused on the permeation of small molecules through porins, considered the main path for the entry of polar antibiotics into Gram-negative bacteria. A fundamental understanding of how these proteins are able to filter small molecules is a prerequisite to design/optimize antibacterials with improved permeation. The level of sophistication of modern molecular modeling algorithms and the advances in new computer hardware has made the simulation of such complex processes possible at the molecular level. In this work we aim to share our experience and perspectives in the context of a multidisciplinary extended collaboration within the IMI-Translocation consortium. The synergistic combination of structural data, in vitro assays and computer simulations has proven to give new insights towards the identification and description of physico-chemical properties modulating permeation. Once similar general rules are identified, we believe that the use of virtual screening techniques will be very helpful in searching for new molecular scaffolds with enhanced permeation, and that molecular modeling will be of fundamental assistance to the optimization stage.

Rationalizing the permeation of polar antibiotics into Gram-negative bacteria

NASA Astrophysics Data System (ADS)

Scorciapino, Mariano Andrea; Acosta-Gutierrez, Silvia; Benkerrou, Dehbia; D'Agostino, Tommaso; Malloci, Giuliano; Samanta, Susruta; Bodrenko, Igor; Ceccarelli, Matteo

2017-03-01

The increasing level of antibiotic resistance in Gram-negative bacteria, together with the lack of new potential drug scaffolds in the pipeline, make the problem of infectious diseases a global challenge for modern medicine. The main reason that Gram-negative bacteria are particularly challenging is the presence of an outer cell-protecting membrane, which is not present in Gram-positive species. Such an asymmetric bilayer is a highly effective barrier for polar molecules. Several protein systems are expressed in the outer membrane to control the internal concentration of both nutrients and noxious species, in particular: (i) water-filled channels that modulate the permeation of polar molecules and ions according to concentration gradients, and (ii) efflux pumps to actively expel toxic compounds. Thus, besides expressing specific enzymes for drugs degradation, Gram-negative bacteria can also resist by modulating the influx and efflux of antibiotics, keeping the internal concentration low. However, there are no direct and robust experimental methods capable of measuring the permeability of small molecules, thus severely limiting our knowledge of the molecular mechanisms that ultimately control the permeation of antibiotics through the outer membrane. This is the innovation gap to be filled for Gram-negative bacteria. This review is focused on the permeation of small molecules through porins, considered the main path for the entry of polar antibiotics into Gram-negative bacteria. A fundamental understanding of how these proteins are able to filter small molecules is a prerequisite to design/optimize antibacterials with improved permeation. The level of sophistication of modern molecular modeling algorithms and the advances in new computer hardware has made the simulation of such complex processes possible at the molecular level. In this work we aim to share our experience and perspectives in the context of a multidisciplinary extended collaboration within the IMI-Translocation consortium. The synergistic combination of structural data, in vitro assays and computer simulations has proven to give new insights towards the identification and description of physico-chemical properties modulating permeation. Once similar general rules are identified, we believe that the use of virtual screening techniques will be very helpful in searching for new molecular scaffolds with enhanced permeation, and that molecular modeling will be of fundamental assistance to the optimization stage.

Recent advances in QM/MM free energy calculations using reference potentials.

PubMed

Duarte, Fernanda; Amrein, Beat A; Blaha-Nelson, David; Kamerlin, Shina C L

2015-05-01

Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Synthesis, characterization and computational study of the newly synthetized sulfonamide molecule

NASA Astrophysics Data System (ADS)

Murthy, P. Krishna; Suneetha, V.; Armaković, Stevan; Armaković, Sanja J.; Suchetan, P. A.; Giri, L.; Rao, R. Sreenivasa

2018-02-01

A new compound N-(2,5-dimethyl-4-nitrophenyl)-4-methylbenzenesulfonamide (NDMPMBS) has been derived from 2,5-dimethyl-4-nitroaniline and 4-methylbenzene-1-sulfonyl chloride. Structure was characterized by SCXRD studies and spectroscopic tools. Compound crystallized in the monoclinic crystal system with P21/c space group a = 10.0549, b = 18.967, c = 8.3087, β = 103.18 and Z = 4. Type and nature of intermolecular interaction in crystal state investigated by 3D-Hirshfeld surface and 2D-finger print plots revealed that title compound stabilized by several interactions. The structural and electronic properties of title compound have been calculated at DFT/B3LYP/6-311G++(d,p) level of theory. Computationally obtained spectral data was compared with experimental results, showing excellent mutual agreement. Assignment of each vibrational wave number was done on the basis of potential energy distribution (PED). Investigation of local reactivity descriptors encompassed visualization of molecular electrostatic potential (MEP) and average local ionization energy (ALIE) surfaces, visualization of Fukui functions, natural bond order (NBO) analysis, bond dissociation energies for hydrogen abstraction (H-BDE) and radial distribution functions (RDF) after molecular dynamics (MD) simulations. MD simulations were also used in order to investigate interaction of NDMPMBS molecule with 1WKR and 3ETT proteins protein.

Functionalized lipids and surfactants for specific applications.

PubMed

Kepczynski, Mariusz; Róg, Tomasz

2016-10-01

Synthetic lipids and surfactants that do not exist in biological systems have been used for the last few decades in both basic and applied science. The most notable applications for synthetic lipids and surfactants are drug delivery, gene transfection, as reporting molecules, and as support for structural lipid biology. In this review, we describe the potential of the synergistic combination of computational and experimental methodologies to study the behavior of synthetic lipids and surfactants embedded in lipid membranes and liposomes. We focused on select cases in which molecular dynamics simulations were used to complement experimental studies aiming to understand the structure and properties of new compounds at the atomistic level. We also describe cases in which molecular dynamics simulations were used to design new synthetic lipids and surfactants, as well as emerging fields for the application of these compounds. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling Radiative Heat Transfer and Turbulence-Radiation Interactions in Engines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Chandan; Sircar, Arpan; Ferreyro-Fernandez, Sebastian

Detailed radiation modelling in piston engines has received relatively little attention to date. Recently, it is being revisited in light of current trends towards higher operating pressures and higher levels of exhaust-gas recirculation, both of which enhance molecular gas radiation. Advanced high-efficiency engines also are expected to function closer to the limits of stable operation, where even small perturbations to the energy balance can have a large influence on system behavior. Here several different spectral radiation property models and radiative transfer equation (RTE) solvers have been implemented in an OpenFOAM-based engine CFD code, and simulations have been performed for amore » full-load (peak pressure ~200 bar) heavy-duty diesel engine. Differences in computed temperature fields, NO and soot levels, and wall heat transfer rates are shown for different combinations of spectral models and RTE solvers. The relative importance of molecular gas radiation versus soot radiation is examined. And the influence of turbulence-radiation interactions is determined by comparing results obtained using local mean values of composition and temperature to compute radiative emission and absorption with those obtained using a particle-based transported probability density function method.« less

Equilibration and analysis of first-principles molecular dynamics simulations of water

NASA Astrophysics Data System (ADS)

Dawson, William; Gygi, François

2018-03-01

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. We assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. A comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

Equilibration and analysis of first-principles molecular dynamics simulations of water.

PubMed

Dawson, William; Gygi, François

2018-03-28

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. We assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. A comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

Finite-Size Effects of Binary Mutual Diffusion Coefficients from Molecular Dynamics

PubMed Central

2018-01-01

Molecular dynamics simulations were performed for the prediction of the finite-size effects of Maxwell-Stefan diffusion coefficients of molecular mixtures and a wide variety of binary Lennard–Jones systems. A strong dependency of computed diffusivities on the system size was observed. Computed diffusivities were found to increase with the number of molecules. We propose a correction for the extrapolation of Maxwell–Stefan diffusion coefficients to the thermodynamic limit, based on the study by Yeh and Hummer (J. Phys. Chem. B, 2004, 108, 15873−15879). The proposed correction is a function of the viscosity of the system, the size of the simulation box, and the thermodynamic factor, which is a measure for the nonideality of the mixture. Verification is carried out for more than 200 distinct binary Lennard–Jones systems, as well as 9 binary systems of methanol, water, ethanol, acetone, methylamine, and carbon tetrachloride. Significant deviations between finite-size Maxwell–Stefan diffusivities and the corresponding diffusivities at the thermodynamic limit were found for mixtures close to demixing. In these cases, the finite-size correction can be even larger than the simulated (finite-size) Maxwell–Stefan diffusivity. Our results show that considering these finite-size effects is crucial and that the suggested correction allows for reliable computations. PMID:29664633

Parametric models to compute tryptophan fluorescence wavelengths from classical protein simulations.

PubMed

Lopez, Alvaro J; Martínez, Leandro

2018-02-26

Fluorescence spectroscopy is an important method to study protein conformational dynamics and solvation structures. Tryptophan (Trp) residues are the most important and practical intrinsic probes for protein fluorescence due to the variability of their fluorescence wavelengths: Trp residues emit in wavelengths ranging from 308 to 360 nm depending on the local molecular environment. Fluorescence involves electronic transitions, thus its computational modeling is a challenging task. We show that it is possible to predict the wavelength of emission of a Trp residue from classical molecular dynamics simulations by computing the solvent-accessible surface area or the electrostatic interaction between the indole group and the rest of the system. Linear parametric models are obtained to predict the maximum emission wavelengths with standard errors of the order 5 nm. In a set of 19 proteins with emission wavelengths ranging from 308 to 352 nm, the best model predicts the maximum wavelength of emission with a standard error of 4.89 nm and a quadratic Pearson correlation coefficient of 0.81. These models can be used for the interpretation of fluorescence spectra of proteins with multiple Trp residues, or for which local Trp environmental variability exists and can be probed by classical molecular dynamics simulations. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Review of the fundamental theories behind small angle X-ray scattering, molecular dynamics simulations, and relevant integrated application

PubMed Central

Boldon, Lauren; Laliberte, Fallon; Liu, Li

2015-01-01

In this paper, the fundamental concepts and equations necessary for performing small angle X-ray scattering (SAXS) experiments, molecular dynamics (MD) simulations, and MD-SAXS analyses were reviewed. Furthermore, several key biological and non-biological applications for SAXS, MD, and MD-SAXS are presented in this review; however, this article does not cover all possible applications. SAXS is an experimental technique used for the analysis of a wide variety of biological and non-biological structures. SAXS utilizes spherical averaging to produce one- or two-dimensional intensity profiles, from which structural data may be extracted. MD simulation is a computer simulation technique that is used to model complex biological and non-biological systems at the atomic level. MD simulations apply classical Newtonian mechanics’ equations of motion to perform force calculations and to predict the theoretical physical properties of the system. This review presents several applications that highlight the ability of both SAXS and MD to study protein folding and function in addition to non-biological applications, such as the study of mechanical, electrical, and structural properties of non-biological nanoparticles. Lastly, the potential benefits of combining SAXS and MD simulations for the study of both biological and non-biological systems are demonstrated through the presentation of several examples that combine the two techniques. PMID:25721341

An Investigation of Molecular Docking and Molecular Dynamic Simulation on Imidazopyridines as B-Raf Kinase Inhibitors.

PubMed

Xie, Huiding; Li, Yupeng; Yu, Fang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-11-16

In the recent cancer treatment, B-Raf kinase is one of key targets. Nowadays, a group of imidazopyridines as B-Raf kinase inhibitors have been reported. In order to investigate the interaction between this group of inhibitors and B-Raf kinase, molecular docking, molecular dynamic (MD) simulation and binding free energy (ΔGbind) calculation were performed in this work. Molecular docking was carried out to identify the key residues in the binding site, and MD simulations were performed to determine the detail binding mode. The results obtained from MD simulation reveal that the binding site is stable during the MD simulations, and some hydrogen bonds (H-bonds) in MD simulations are different from H-bonds in the docking mode. Based on the obtained MD trajectories, ΔGbind was computed by using Molecular Mechanics Generalized Born Surface Area (MM-GBSA), and the obtained energies are consistent with the activities. An energetic analysis reveals that both electrostatic and van der Waals contributions are important to ΔGbind, and the unfavorable polar solvation contribution results in the instability of the inhibitor with the lowest activity. These results are expected to understand the binding between B-Raf and imidazopyridines and provide some useful information to design potential B-Raf inhibitors.

Accelerated molecular dynamics: A promising and efficient simulation method for biomolecules

NASA Astrophysics Data System (ADS)

Hamelberg, Donald; Mongan, John; McCammon, J. Andrew

2004-06-01

Many interesting dynamic properties of biological molecules cannot be simulated directly using molecular dynamics because of nanosecond time scale limitations. These systems are trapped in potential energy minima with high free energy barriers for large numbers of computational steps. The dynamic evolution of many molecular systems occurs through a series of rare events as the system moves from one potential energy basin to another. Therefore, we have proposed a robust bias potential function that can be used in an efficient accelerated molecular dynamics approach to simulate the transition of high energy barriers without any advance knowledge of the location of either the potential energy wells or saddle points. In this method, the potential energy landscape is altered by adding a bias potential to the true potential such that the escape rates from potential wells are enhanced, which accelerates and extends the time scale in molecular dynamics simulations. Our definition of the bias potential echoes the underlying shape of the potential energy landscape on the modified surface, thus allowing for the potential energy minima to be well defined, and hence properly sampled during the simulation. We have shown that our approach, which can be extended to biomolecules, samples the conformational space more efficiently than normal molecular dynamics simulations, and converges to the correct canonical distribution.

Computational studies of adsorption in metal organic frameworks and interaction of nanoparticles in condensed phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Annapureddy, Harsha V.; Motkuri, Radha K.; Nguyen, Phuong T.

In this review, we describe recent efforts in which computer simulations were used to systematically study nano-structured metal organic frameworks, with particular emphasis on their application in heating and cooling processes. These materials also are known as metal organic heat carriers. We used both molecular dynamics and Grand Canonical Monte Carlo simulation techniques to gain a molecular-level understanding of the adsorption mechanism of gases in these porous materials. We investigated the uptake of various gases such as refrigerants R12 and R143a and also the elemental gases Xe and Rn by the metal organic framework (i.e., Ni2(dhtp)). We also evaluated themore » effects of temperature and pressure on the uptake mechanism. Our computed results compared reasonably well with available experimental measurements, thus validating our potential models and approaches. In addition, we also investigated the structural, diffusive, and adsorption properties of different hydrocarbons in Ni2(dhtp). To elucidate the mechanism of nanoparticle dispersion in condensed phases, we also studied the interactions among nanoparticles in various liquids, such as n-hexane, water and methanol. This work was performed at Pacific Northwest National Laboratory (PNNL) and was supported by the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences, U.S. Department of Energy (DOE). PNNL is operated by Battelle for the DOE. The authors also gratefully acknowledge support received from the National Energy Technology Laboratory of DOE's Office of Fossil Energy.« less

Modification of S-Adenosyl-l-Homocysteine as Inhibitor of Nonstructural Protein 5 Methyltransferase Dengue Virus Through Molecular Docking and Molecular Dynamics Simulation

PubMed Central

Tambunan, Usman Sumo Friend; Nasution, Mochammad Arfin Fardiansyah; Azhima, Fauziah; Parikesit, Arli Aditya; Toepak, Erwin Prasetya; Idrus, Syarifuddin; Kerami, Djati

2017-01-01

Dengue fever is still a major threat worldwide, approximately threatening two-fifths of the world’s population in tropical and subtropical countries. Nonstructural protein 5 (NS5) methyltransferase enzyme plays a vital role in the process of messenger RNA capping of dengue by transferring methyl groups from S-adenosyl-l-methionine to N7 atom of the guanine bases of RNA and the RNA ribose group of 2′OH, resulting in S-adenosyl-l-homocysteine (SAH). The modification of SAH compound was screened using molecular docking and molecular dynamics simulation, along with computational ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) test. The 2 simulations were performed using Molecular Operating Environment (MOE) 2008.10 software, whereas the ADME-Tox test was performed using various software. The modification of SAH compound was done using several functional groups that possess different polarities and properties, resulting in 3460 ligands to be docked. After conducting docking simulation, we earned 3 best ligands (SAH-M331, SAH-M2696, and SAH-M1356) based on ΔGbinding and molecular interactions, which show better results than the standard ligands. Moreover, the results of molecular dynamics simulation show that the best ligands are still able to maintain the active site residue interaction with the binding site until the end of the simulation. After a series of molecular docking and molecular dynamics simulation were performed, we concluded that SAH-M1356 ligand is the most potential SAH-based compound to inhibit NS5 methyltransferase enzyme for treating dengue fever. PMID:28469408

Exhaustively sampling peptide adsorption with metadynamics.

PubMed

Deighan, Michael; Pfaendtner, Jim

2013-06-25

Simulating the adsorption of a peptide or protein and obtaining quantitative estimates of thermodynamic observables remains challenging for many reasons. One reason is the dearth of molecular scale experimental data available for validating such computational models. We also lack simulation methodologies that effectively address the dual challenges of simulating protein adsorption: overcoming strong surface binding and sampling conformational changes. Unbiased classical simulations do not address either of these challenges. Previous attempts that apply enhanced sampling generally focus on only one of the two issues, leaving the other to chance or brute force computing. To improve our ability to accurately resolve adsorbed protein orientation and conformational states, we have applied the Parallel Tempering Metadynamics in the Well-Tempered Ensemble (PTMetaD-WTE) method to several explicitly solvated protein/surface systems. We simulated the adsorption behavior of two peptides, LKα14 and LKβ15, onto two self-assembled monolayer (SAM) surfaces with carboxyl and methyl terminal functionalities. PTMetaD-WTE proved effective at achieving rapid convergence of the simulations, whose results elucidated different aspects of peptide adsorption including: binding free energies, side chain orientations, and preferred conformations. We investigated how specific molecular features of the surface/protein interface change the shape of the multidimensional peptide binding free energy landscape. Additionally, we compared our enhanced sampling technique with umbrella sampling and also evaluated three commonly used molecular dynamics force fields.

A meta-analysis of outcomes from the use of computer-simulated experiments in science education

NASA Astrophysics Data System (ADS)

Lejeune, John Van

The purpose of this study was to synthesize the findings from existing research on the effects of computer simulated experiments on students in science education. Results from 40 reports were integrated by the process of meta-analysis to examine the effect of computer-simulated experiments and interactive videodisc simulations on student achievement and attitudes. Findings indicated significant positive differences in both low-level and high-level achievement of students who use computer-simulated experiments and interactive videodisc simulations as compared to students who used more traditional learning activities. No significant differences in retention, student attitudes toward the subject, or toward the educational method were found. Based on the findings of this study, computer-simulated experiments and interactive videodisc simulations should be used to enhance students' learning in science, especially in cases where the use of traditional laboratory activities are expensive, dangerous, or impractical.

Molecular mechanics and dynamics characterization of an in silico mutated protein: a stand-alone lab module or support activity for in vivo and in vitro analyses of targeted proteins.

PubMed

Chiang, Harry; Robinson, Lucy C; Brame, Cynthia J; Messina, Troy C

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems. Computer simulations of molecular events can now be accomplished quickly and with standard computer technology. Also, simulation software is freely available for most computing platforms, and online support for the novice user is ample. We have therefore created a molecular dynamics laboratory module to enhance undergraduate student understanding of molecular events underlying organismal phenotype. This module builds on a previously described project in which students use site-directed mutagenesis to investigate functions of conserved sequence features in members of a eukaryotic protein kinase family. In this report, we detail the laboratory activities of a MD module that provide a complement to phenotypic outcomes by providing a hypothesis-driven and quantifiable measure of predicted structural changes caused by targeted mutations. We also present examples of analyses students may perform. These laboratory activities can be integrated with genetics or biochemistry experiments as described, but could also be used independently in any course that would benefit from a quantitative approach to protein structure-function relationships. Copyright © 2013 Wiley Periodicals, Inc.

Modifying Poisson equation for near-solute dielectric polarization and solvation free energy

NASA Astrophysics Data System (ADS)

Yang, Pei-Kun

2016-06-01

The dielectric polarization P is important for calculating the stability of protein conformation and the binding affinity of protein-protein/ligand interactions and for exploring the nonthermal effect of an external electric field on biomolecules. P was decomposed into the product of the electric dipole moment per molecule p; bulk solvent density Nbulk; and relative solvent molecular density g. For a molecular solute, 4πr2p(r) oscillates with the distance r to the solute, and g(r) has a large peak in the near-solute region, as observed in molecular dynamics (MD) simulations. Herein, the Poisson equation was modified for computing p based on the modified Gauss's law of Maxwell's equations, and the potential of the mean force was used for computing g. For one or two charged atoms in a water cluster, the solvation free energies of the solutes obtained by these equations were similar to those obtained from MD simulations.

Protein Dynamics from NMR and Computer Simulation

NASA Astrophysics Data System (ADS)

Wu, Qiong; Kravchenko, Olga; Kemple, Marvin; Likic, Vladimir; Klimtchuk, Elena; Prendergast, Franklyn

2002-03-01

Proteins exhibit internal motions from the millisecond to sub-nanosecond time scale. The challenge is to relate these internal motions to biological function. A strategy to address this aim is to apply a combination of several techniques including high-resolution NMR, computer simulation of molecular dynamics (MD), molecular graphics, and finally molecular biology, the latter to generate appropriate samples. Two difficulties that arise are: (1) the time scale which is most directly biologically relevant (ms to μs) is not readily accessible by these techniques and (2) the techniques focus on local and not collective motions. We will outline methods using ^13C-NMR to help alleviate the second problem, as applied to intestinal fatty acid binding protein, a relatively small intracellular protein believed to be involved in fatty acid transport and metabolism. This work is supported in part by PHS Grant GM34847 (FGP) and by a fellowship from the American Heart Association (QW).

Energy conserving, linear scaling Born-Oppenheimer molecular dynamics.

PubMed

Cawkwell, M J; Niklasson, Anders M N

2012-10-07

Born-Oppenheimer molecular dynamics simulations with long-term conservation of the total energy and a computational cost that scales linearly with system size have been obtained simultaneously. Linear scaling with a low pre-factor is achieved using density matrix purification with sparse matrix algebra and a numerical threshold on matrix elements. The extended Lagrangian Born-Oppenheimer molecular dynamics formalism [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] yields microcanonical trajectories with the approximate forces obtained from the linear scaling method that exhibit no systematic drift over hundreds of picoseconds and which are indistinguishable from trajectories computed using exact forces.

Determination of partial molar volumes from free energy perturbation theory†

PubMed Central

Vilseck, Jonah Z.; Tirado-Rives, Julian

2016-01-01

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood–Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm3 mol−1. The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute–solvent interactions. PMID:25589343

Determination of partial molar volumes from free energy perturbation theory.

PubMed

Vilseck, Jonah Z; Tirado-Rives, Julian; Jorgensen, William L

2015-04-07

Partial molar volume is an important thermodynamic property that gives insights into molecular size and intermolecular interactions in solution. Theoretical frameworks for determining the partial molar volume (V°) of a solvated molecule generally apply Scaled Particle Theory or Kirkwood-Buff theory. With the current abilities to perform long molecular dynamics and Monte Carlo simulations, more direct methods are gaining popularity, such as computing V° directly as the difference in computed volume from two simulations, one with a solute present and another without. Thermodynamically, V° can also be determined as the pressure derivative of the free energy of solvation in the limit of infinite dilution. Both approaches are considered herein with the use of free energy perturbation (FEP) calculations to compute the necessary free energies of solvation at elevated pressures. Absolute and relative partial molar volumes are computed for benzene and benzene derivatives using the OPLS-AA force field. The mean unsigned error for all molecules is 2.8 cm(3) mol(-1). The present methodology should find use in many contexts such as the development and testing of force fields for use in computer simulations of organic and biomolecular systems, as a complement to related experimental studies, and to develop a deeper understanding of solute-solvent interactions.

Study on photon transport problem based on the platform of molecular optical simulation environment.

PubMed

Peng, Kuan; Gao, Xinbo; Liang, Jimin; Qu, Xiaochao; Ren, Nunu; Chen, Xueli; Ma, Bin; Tian, Jie

2010-01-01

As an important molecular imaging modality, optical imaging has attracted increasing attention in the recent years. Since the physical experiment is usually complicated and expensive, research methods based on simulation platforms have obtained extensive attention. We developed a simulation platform named Molecular Optical Simulation Environment (MOSE) to simulate photon transport in both biological tissues and free space for optical imaging based on noncontact measurement. In this platform, Monte Carlo (MC) method and the hybrid radiosity-radiance theorem are used to simulate photon transport in biological tissues and free space, respectively, so both contact and noncontact measurement modes of optical imaging can be simulated properly. In addition, a parallelization strategy for MC method is employed to improve the computational efficiency. In this paper, we study the photon transport problems in both biological tissues and free space using MOSE. The results are compared with Tracepro, simplified spherical harmonics method (SP(n)), and physical measurement to verify the performance of our study method on both accuracy and efficiency.

Study on Photon Transport Problem Based on the Platform of Molecular Optical Simulation Environment

PubMed Central

Peng, Kuan; Gao, Xinbo; Liang, Jimin; Qu, Xiaochao; Ren, Nunu; Chen, Xueli; Ma, Bin; Tian, Jie

2010-01-01

As an important molecular imaging modality, optical imaging has attracted increasing attention in the recent years. Since the physical experiment is usually complicated and expensive, research methods based on simulation platforms have obtained extensive attention. We developed a simulation platform named Molecular Optical Simulation Environment (MOSE) to simulate photon transport in both biological tissues and free space for optical imaging based on noncontact measurement. In this platform, Monte Carlo (MC) method and the hybrid radiosity-radiance theorem are used to simulate photon transport in biological tissues and free space, respectively, so both contact and noncontact measurement modes of optical imaging can be simulated properly. In addition, a parallelization strategy for MC method is employed to improve the computational efficiency. In this paper, we study the photon transport problems in both biological tissues and free space using MOSE. The results are compared with Tracepro, simplified spherical harmonics method (S P n), and physical measurement to verify the performance of our study method on both accuracy and efficiency. PMID:20445737

Molecular Level Understanding of the Factors Affecting the Stability of Dimethoxy Benzene Catholyte Candidates from First-Principles Investigations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Assary, Rajeev S.; Zhang, Lu; Huang, Jinhua

First-principles simulations are performed to gain molecular level insights into the factors affecting the stability of seven 1,4-dimethoxybenzene (DMB) derivatives. These molecules are potential catholyte candidates for nonaqueous redox flow battery systems. Computations are performed to predict oxidation potentials in various dielectric mediums, intrinsic-reorganization energies, and structural changes of these representative catholyte molecules during the redox process. In order to understand the stability of the DMB-based radical cations, the thermodynamic feasibility of the following reactions is computed using density functional theory: (a) deprotonation, (b) dimerization, (c) hydrolysis, and (d) demethylation. The computations indicate that radical cations of the 2,3-dimethyl andmore » 2,5-dimethyl derivatives are the most stable among the DMB derivatives considered in this study. In the presence of solvents with high-proton solvating ability (water, DMSO, acetonitrile), degradation of cation radical occurring via deprotonation is the most likely mechanism. In the presence of solvents such as propylene carbonate (PC), demethylation was found to be the most likely reaction that causes degradation of radical cations. From the computed enthalpy of activation (Delta H-double dagger) for a demethylation reaction in PC, the 2,5-dimethyl DMB cation radical would exhibit better kinetic stability in comparison to the other candidates. Finally, this investigation suggests that computational studies of structural properties such as redox potentials, reorganization energies, and the computed reaction energetics (deprotonation and demethylation) of charged species can be used to predict the relative stability of a large set of molecules required for the discovery of novel redox active materials for flow battery applications« less

Molecular Level Understanding of the Factors Affecting the Stability of Dimethoxy Benzene Catholyte Candidates from First-Principles Investigations

DOE PAGES

Assary, Rajeev S.; Zhang, Lu; Huang, Jinhua; ...

2016-06-14

First-principles simulations are performed to gain molecular level insights into the factors affecting the stability of seven 1,4-dimethoxybenzene (DMB) derivatives. These molecules are potential catholyte candidates for nonaqueous redox flow battery systems. Computations are performed to predict oxidation potentials in various dielectric mediums, intrinsic-reorganization energies, and structural changes of these representative catholyte molecules during the redox process. In order to understand the stability of the DMB-based radical cations, the thermodynamic feasibility of the following reactions is computed using density functional theory: (a) deprotonation, (b) dimerization, (c) hydrolysis, and (d) demethylation. The computations indicate that radical cations of the 2,3-dimethyl andmore » 2,5-dimethyl derivatives are the most stable among the DMB derivatives considered in this study. In the presence of solvents with high-proton solvating ability (water, DMSO, acetonitrile), degradation of cation radical occurring via deprotonation is the most likely mechanism. In the presence of solvents such as propylene carbonate (PC), demethylation was found to be the most likely reaction that causes degradation of radical cations. From the computed enthalpy of activation (Delta H-double dagger) for a demethylation reaction in PC, the 2,5-dimethyl DMB cation radical would exhibit better kinetic stability in comparison to the other candidates. Finally, this investigation suggests that computational studies of structural properties such as redox potentials, reorganization energies, and the computed reaction energetics (deprotonation and demethylation) of charged species can be used to predict the relative stability of a large set of molecules required for the discovery of novel redox active materials for flow battery applications« less

Local-feature analysis for automated coarse-graining of bulk-polymer molecular dynamics simulations.

PubMed

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.

METAGUI. A VMD interface for analyzing metadynamics and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Biarnés, Xevi; Pietrucci, Fabio; Marinelli, Fabrizio; Laio, Alessandro

2012-01-01

We present a new computational tool, METAGUI, which extends the VMD program with a graphical user interface that allows constructing a thermodynamic and kinetic model of a given process simulated by large-scale molecular dynamics. The tool is specially designed for analyzing metadynamics based simulations. The huge amount of diverse structures generated during such a simulation is partitioned into a set of microstates (i.e. structures with similar values of the collective variables). Their relative free energies are then computed by a weighted-histogram procedure and the most relevant free energy wells are identified by diagonalization of the rate matrix followed by a commitor analysis. All this procedure leads to a convenient representation of the metastable states and long-time kinetics of the system which can be compared with experimental data. The tool allows to seamlessly switch between a collective variables space representation of microstates and their atomic structure representation, which greatly facilitates the set-up and analysis of molecular dynamics simulations. METAGUI is based on the output format of the PLUMED plugin, making it compatible with a number of different molecular dynamics packages like AMBER, NAMD, GROMACS and several others. The METAGUI source files can be downloaded from the PLUMED web site ( http://www.plumed-code.org). Program summaryProgram title: METAGUI Catalogue identifier: AEKH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 117 545 No. of bytes in distributed program, including test data, etc.: 8 516 203 Distribution format: tar.gz Programming language: TK/TCL, Fortran Computer: Any computer with a VMD installation and capable of running an executable produced by a gfortran compiler Operating system: Linux, Unix OS-es RAM: 1 073 741 824 bytes Classification: 23 External routines: A VMD installation ( http://www.ks.uiuc.edu/Research/vmd/) Nature of problem: Extract thermodynamic data and build a kinetic model of a given process simulated by metadynamics or molecular dynamics simulations, and provide this information on a dual representation that allows navigating and exploring the molecular structures corresponding to each point along the multi-dimensional free energy hypersurface. Solution method: Graphical-user interface linked to VMD that clusterizes the simulation trajectories in the space of a set of collective variables and assigns each frame to a given microstate, determines the free energy of each microstate by a weighted histogram analysis method, and identifies the most relevant free energy wells (kinetic basins) by diagonalization of the rate matrix followed by a commitor analysis. Restrictions: Input format files compatible with PLUMED and all the MD engines supported by PLUMED and VMD. Running time: A few minutes.

A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters: Theory and application to microfilaments

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

Effect of peptide length on the conjugation to the gold nanoparticle surface: a molecular dynamic study.

PubMed

Ramezani, Fatemeh; Habibi, Mostafa; Rafii-Tabar, Hashem; Amanlou, Massoud

2015-01-29

Gold nanoparticles now command a great deal of attention for medical applications. Despite the importance of nano-bio interfaces, interaction between peptides and proteins with gold surfaces is not still fully understood, especially in a molecular level. In the present study computational simulation of adsorption of 20 amino acids, in three forms of mono-amino acid, homo di-peptide and homo tri-peptide, on the gold nanoparticles was performed by Gromacs using OPLSAA force field. The flexibility, stability, and size effect of the peptides on the gold nanoparticles were studied as well as the molecular structure of them. According to our results, adsorbed homo tri-peptides on the gold surface had more flexibility, more gyration, and the farthest distance from the GNP in comparison with homo di-peptides and mono-amino acids. Our findings provide new insights into the precise control of interactions between amino acids anchored on the GNPs.

Collective Langevin dynamics of conformational motions in proteins

NASA Astrophysics Data System (ADS)

Lange, Oliver F.; Grubmüller, Helmut

2006-06-01

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (˜50ns) was much longer than the 1ns molecular dynamics simulation from which the memory kernel was extracted.

Computer Series, 36: Bits and Pieces, 13.

ERIC Educational Resources Information Center

Moore, John W.

1983-01-01

Eleven computer/calculator programs (most are available from authors) are described. Topics include visualizing molecular vibrations, dynamic nuclear magnetic resonance spectra of two-spin systems, programming utilities for Apple II Plus, gas chromatography simulation for TRS-80, infrared spectra analysis on a calculator, naming chemical…

Tools and procedures for visualization of proteins and other biomolecules.

PubMed

Pan, Lurong; Aller, Stephen G

2015-04-01

Protein, peptides, and nucleic acids are biomolecules that drive biological processes in living organisms. An enormous amount of structural data for a large number of these biomolecules has been described with atomic precision in the form of structural "snapshots" that are freely available in public repositories. These snapshots can help explain how the biomolecules function, the nature of interactions between multi-molecular complexes, and even how small-molecule drugs can modulate the biomolecules for clinical benefits. Furthermore, these structural snapshots serve as inputs for sophisticated computer simulations to turn the biomolecules into moving, "breathing" molecular machines for understanding their dynamic properties in real-time computer simulations. In order for the researcher to take advantage of such a wealth of structural data, it is necessary to gain competency in the use of computer molecular visualization tools for exploring the structures and visualizing three-dimensional spatial representations. Here, we present protocols for using two common visualization tools--the Web-based Jmol and the stand-alone PyMOL package--as well as a few examples of other popular tools. Copyright © 2015 John Wiley & Sons, Inc.

Search for β2 Adrenergic Receptor Ligands by Virtual Screening via Grid Computing and Investigation of Binding Modes by Docking and Molecular Dynamics Simulations

PubMed Central

Bai, Qifeng; Shao, Yonghua; Pan, Dabo; Zhang, Yang; Liu, Huanxiang; Yao, Xiaojun

2014-01-01

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com. PMID:25229694

Comparison and Analysis of 3,4 dihydrocylmandelic acid (DHMA) and noremetanephrine (NMN) on Amyloid-Beta 40 Monomer for treatment of Alzheimer's Disease using Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Choi, Woosung; Jee, Sang Eun; Jang, Seung Soon

Alzheimer's disease (AD) is type of degenerative dementia caused memory loss and behavior problem. Main reason of AD is Amyloid-Beta 40(A β) mostly composed of α -helix form misfolds to insoluble fibrils and soluble oilgomer. This insoluble fibrils aggregate with beta sheet structure and form the plaque which is caused nurotoxicity in brain. Both 3,4 dihydrocylmandelic acid (DHMA) and noremetanephrine (NMN) are the metabolite of norepinephrine in brain . Also these are inhibit the changing formation of fibrils and maintain the α -helix structure. In this computational modeling study, both NMN and DHMA molecules were modified and analyzed for specific effect on the A β-monomer using molecular dynamics simulation. Using molecular dynamic simulation, NMN and DHMA act as modulator on three A β-monomer batches and could observe the conformational changing of these A β-monomer under the physiologocal condition. This computational experiment is designed to compare and analyze both of chemicals for determining which chamecal would be more effective on the conformation of A β 40 monomer.

Quantum optical emulation of molecular vibronic spectroscopy using a trapped-ion device.

PubMed

Shen, Yangchao; Lu, Yao; Zhang, Kuan; Zhang, Junhua; Zhang, Shuaining; Huh, Joonsuk; Kim, Kihwan

2018-01-28

Molecules are one of the most demanding quantum systems to be simulated by quantum computers due to their complexity and the emergent role of quantum nature. The recent theoretical proposal of Huh et al. (Nature Photon., 9, 615 (2015)) showed that a multi-photon network with a Gaussian input state can simulate a molecular spectroscopic process. Here, we present the first quantum device that generates a molecular spectroscopic signal with the phonons in a trapped ion system, using SO 2 as an example. In order to perform reliable Gaussian sampling, we develop the essential experimental technology with phonons, which includes the phase-coherent manipulation of displacement, squeezing, and rotation operations with multiple modes in a single realization. The required quantum optical operations are implemented through Raman laser beams. The molecular spectroscopic signal is reconstructed from the collective projection measurements for the two-phonon-mode. Our experimental demonstration will pave the way to large-scale molecular quantum simulations, which are classically intractable, but would be easily verifiable by real molecular spectroscopy.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations.

PubMed

Jung, Jaewoon; Mori, Takaharu; Kobayashi, Chigusa; Matsunaga, Yasuhiro; Yoda, Takao; Feig, Michael; Sugita, Yuji

2015-07-01

GENESIS (Generalized-Ensemble Simulation System) is a new software package for molecular dynamics (MD) simulations of macromolecules. It has two MD simulators, called ATDYN and SPDYN. ATDYN is parallelized based on an atomic decomposition algorithm for the simulations of all-atom force-field models as well as coarse-grained Go-like models. SPDYN is highly parallelized based on a domain decomposition scheme, allowing large-scale MD simulations on supercomputers. Hybrid schemes combining OpenMP and MPI are used in both simulators to target modern multicore computer architectures. Key advantages of GENESIS are (1) the highly parallel performance of SPDYN for very large biological systems consisting of more than one million atoms and (2) the availability of various REMD algorithms (T-REMD, REUS, multi-dimensional REMD for both all-atom and Go-like models under the NVT, NPT, NPAT, and NPγT ensembles). The former is achieved by a combination of the midpoint cell method and the efficient three-dimensional Fast Fourier Transform algorithm, where the domain decomposition space is shared in real-space and reciprocal-space calculations. Other features in SPDYN, such as avoiding concurrent memory access, reducing communication times, and usage of parallel input/output files, also contribute to the performance. We show the REMD simulation results of a mixed (POPC/DMPC) lipid bilayer as a real application using GENESIS. GENESIS is released as free software under the GPLv2 licence and can be easily modified for the development of new algorithms and molecular models. WIREs Comput Mol Sci 2015, 5:310-323. doi: 10.1002/wcms.1220.

Computing the Rotational Diffusion of Biomolecules via Molecular Dynamics Simulation and Quaternion Orientations.

PubMed

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.

Computational modeling of the amphibian thyroid axis ...

EPA Pesticide Factsheets

In vitro screening of chemicals for bioactivity together with computational modeling are beginning to replace animal toxicity testing in support of chemical risk assessment. To facilitate this transition, an amphibian thyroid axis model has been developed to describe thyroid homeostasis during Xenopus laevis pro-metamorphosis. The model simulates the dynamic relationships of normal thyroid biology throughout this critical period of amphibian development and includes molecular initiating events (MIEs) for thyroid axis disruption to allow in silico simulations of hormone levels following chemical perturbations. One MIE that has been formally described using the adverse outcome pathway (AOP) framework is thyroperoxidase (TPO) inhibition. The goal of this study was to refine the model parameters and validate model predictions by generating dose-response and time-course biochemical data following exposure to three TPO inhibitors, methimazole, 6-propylthiouracil and 2-mercaptobenzothiazole. Key model variables including gland and blood thyroid hormone (TH) levels were compared to empirical values measured in biological samples at 2, 4, 7 and 10 days following initiation of exposure at Nieuwkoop and Faber (NF) stage 54 (onset of pro-metamorphosis). The secondary objective of these studies was to relate depleted blood TH levels to delayed metamorphosis, the adverse apical outcome. Delayed metamorphosis was evaluated by continuing exposure with a subset of larvae until a

The Generalized Born solvation model: What is it?

NASA Astrophysics Data System (ADS)

Onufriev, Alexey

2004-03-01

Implicit solvation models provide, for many applications, an effective way of describing the electrostatic effects of aqueous solvation. Here we outline the main approximations behind the popular Generalized Born solvation model. We show how its accuracy, relative to the Poisson-Boltzmann treatment, can be significantly improved in a computationally inexpensive manner to make the model useful in the studies of large-scale conformational transitions at the atomic level. The improved model is tested in a molecular dynamics simulation of folding of a 46-residue (three helix bundle) protein. Starting from an extended structure at 450K, the protein folds to the lowest energy conformation within 6 ns of simulation time, and the predicted structure differs from the native one by 2.4 A (backbone RMSD).

Incorporation of the TIP4P water model into a continuum solvent for computing solvation free energy

NASA Astrophysics Data System (ADS)

Yang, Pei-Kun

2014-10-01

The continuum solvent model is one of the commonly used strategies to compute solvation free energy especially for large-scale conformational transitions such as protein folding or to calculate the binding affinity of protein-protein/ligand interactions. However, the dielectric polarization for computing solvation free energy from the continuum solvent is different than that obtained from molecular dynamic simulations. To mimic the dielectric polarization surrounding a solute in molecular dynamic simulations, the first-shell water molecules was modeled using a charge distribution of TIP4P in a hard sphere; the time-averaged charge distribution from the first-shell water molecules were estimated based on the coordination number of the solute, and the orientation distribution of the first-shell waters and the intermediate water molecules were treated as that of a bulk solvent. Based on this strategy, an equation describing the solvation free energy of ions was derived.

Protein Aggregation and Molecular Crowding: Perspectives From Multiscale Simulations.

PubMed

Musiani, F; Giorgetti, A

2017-01-01

Cells are extremely crowded environments, thus the use of diluted salted aqueous solutions containing a single protein is too simplistic to mimic the real situation. Macromolecular crowding might affect protein structure, folding, shape, conformational stability, binding of small molecules, enzymatic activity, interactions with cognate biomolecules, and pathological aggregation. The latter phenomenon typically leads to the formation of amyloid fibrils that are linked to several lethal neurodegenerative diseases, but that can also play a functional role in certain organisms. The majority of molecular simulations performed before the last few years were conducted in diluted solutions and were restricted both in the timescales and in the system dimensions by the available computational resources. In recent years, several computational solutions were developed to get close to physiological conditions. In this review we summarize the main computational techniques used to tackle the issue of protein aggregation both in a diluted and in a crowded environment. © 2017 Elsevier Inc. All rights reserved.

The Application of Ligand-Mapping Molecular Dynamics Simulations to the Rational Design of Peptidic Modulators of Protein-Protein Interactions.

PubMed

Tan, Yaw Sing; Spring, David R; Abell, Chris; Verma, Chandra S

2015-07-14

A computational ligand-mapping approach to detect protein surface pockets that interact with hydrophobic moieties is presented. In this method, we incorporated benzene molecules into explicit solvent molecular dynamics simulations of various protein targets. The benzene molecules successfully identified the binding locations of hydrophobic hot-spot residues and all-hydrocarbon cross-links from known peptidic ligands. They also unveiled cryptic binding sites that are occluded by side chains and the protein backbone. Our results demonstrate that ligand-mapping molecular dynamics simulations hold immense promise to guide the rational design of peptidic modulators of protein-protein interactions, including that of stapled peptides, which show promise as an exciting new class of cell-penetrating therapeutic molecules.

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

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.

Substellar fragmentation in self-gravitating fluids with a major phase transition

NASA Astrophysics Data System (ADS)

Füglistaler, A.; Pfenniger, D.

2015-06-01

Context. The observation of various ices in cold molecular clouds, the existence of ubiquitous substellar, cold H2 globules in planetary nebulae and supernova remnants, or the mere existence of comets suggest that the physics of very cold interstellar gas might be much richer than usually envisioned. At the extreme of low temperatures (≲10 K), H2 itself is subject to a phase transition crossing the entire cosmic gas density scale. Aims: This well-known, laboratory-based fact motivates us to study the ideal case of a cold neutral gaseous medium in interstellar conditions for which the bulk of the mass, instead of trace elements, is subject to a gas-liquid or gas-solid phase transition. Methods: On the one hand, the equilibrium of general non-ideal fluids is studied using the virial theorem and linear stability analysis. On the other hand, the non-linear dynamics is studied using computer simulations to characterize the expected formation of solid bodies analogous to comets. The simulations are run with a state-of-the-art molecular dynamics code (LAMMPS) using the Lennard-Jones inter-molecular potential. The long-range gravitational forces can be taken into account together with short-range molecular forces with finite limited computational resources, using super-molecules, provided the right scaling is followed. Results: The concept of super-molecule, where the phase transition conditions are preserved by the proper choice of the particle parameters, is tested with computer simulations, allowing us to correctly satisfy the Jeans instability criterion for one-phase fluids. The simulations show that fluids presenting a phase transition are gravitationally unstable as well, independent of the strength of the gravitational potential, producing two distinct kinds of substellar bodies, those dominated by gravity (planetoids) and those dominated by molecular attractive force (comets). Conclusions: Observations, formal analysis, and computer simulations suggest the possibility of the formation of substellar H2 clumps in cold molecular clouds due to the combination of phase transition and gravity. Fluids presenting a phase transition are gravitationally unstable, independent of the strength of the gravitational potential. Arbitrarily small H2 clumps may form even at relatively high temperatures up to 400-600 K, according to virial analysis. The combination of phase transition and gravity may be relevant for a wider range of astrophysical situations, such as proto-planetary disks. Figures 33-44 are available in electronic form at http://www.aanda.org

Generalized Born Models of Macromolecular Solvation Effects

NASA Astrophysics Data System (ADS)

Bashford, Donald; Case, David A.

2000-10-01

It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

Computation of the properties of liquid neon, methane, and gas helium at low temperature by the Feynman-Hibbs approach.

PubMed

Tchouar, N; Ould-Kaddour, F; Levesque, D

2004-10-15

The properties of liquid methane, liquid neon, and gas helium are calculated at low temperatures over a large range of pressure from the classical molecular-dynamics simulations. The molecular interactions are represented by the Lennard-Jones pair potentials supplemented by quantum corrections following the Feynman-Hibbs approach. The equations of state, diffusion, and shear viscosity coefficients are determined for neon at 45 K, helium at 80 K, and methane at 110 K. A comparison is made with the existing experimental data and for thermodynamical quantities, with results computed from quantum numerical simulations when they are available. The theoretical variation of the viscosity coefficient with pressure is in good agreement with the experimental data when the quantum corrections are taken into account, thus reducing considerably the 60% discrepancy between the simulations and experiments in the absence of these corrections.

Computational approach for designing thermostable Candida antarctica lipase B by molecular dynamics simulation.

PubMed

Park, Hyun June; Park, Kyungmoon; Kim, Yong Hwan; Yoo, Young Je

2014-12-20

Candida antarctica lipase B (CalB) is one of the most useful enzyme for various reactions and bioconversions. Enhancing thermostability of CalB is required for industrial applications. In this study, we propose a computational design strategy to improve the thermostability of CalB. Molecular dynamics simulations at various temperatures were used to investigate the common fluctuation sites in CalB, which are considered to be thermally weak points. The RosettaDesign algorithm was used to design the selected residues. The redesigned CalB was simulated to verify both the enhancement of intramolecular interactions and the lowering of the overall root-mean-square deviation (RMSD) values. The A251E mutant designed using this strategy showed a 2.5-fold higher thermostability than the wild-type CalB. This strategy could apply to other industry applicable enzymes. Copyright © 2014 Elsevier B.V. All rights reserved.

A Model of In vitro Plasticity at the Parallel Fiber—Molecular Layer Interneuron Synapses

PubMed Central

Lennon, William; Yamazaki, Tadashi; Hecht-Nielsen, Robert

2015-01-01

Theoretical and computational models of the cerebellum typically focus on the role of parallel fiber (PF)—Purkinje cell (PKJ) synapses for learned behavior, but few emphasize the role of the molecular layer interneurons (MLIs)—the stellate and basket cells. A number of recent experimental results suggest the role of MLIs is more important than previous models put forth. We investigate learning at PF—MLI synapses and propose a mathematical model to describe plasticity at this synapse. We perform computer simulations with this form of learning using a spiking neuron model of the MLI and show that it reproduces six in vitro experimental results in addition to simulating four novel protocols. Further, we show how this plasticity model can predict the results of other experimental protocols that are not simulated. Finally, we hypothesize what the biological mechanisms are for changes in synaptic efficacy that embody the phenomenological model proposed here. PMID:26733856

Simulation of the single-vibronic-level emission spectrum of HPS.

PubMed

Mok, Daniel K W; Lee, Edmond P F; Chau, Foo-tim; Dyke, John M

2014-05-21

We have computed the potential energy surfaces of the X¹A' and ùA" states of HPS using the explicitly correlated multi-reference configuration interaction (MRCI-F12) method, and Franck-Condon factors between the two states, which include anharmonicity and Duschinsky rotation, with the aim of testing the assignment of the recently reported single-vibronic-level (SVL) emission spectrum of HPS [R. Grimminger, D. J. Clouthier, R. Tarroni, Z. Wang, and T. J. Sears, J. Chem. Phys. 139, 174306 (2013)]. These are the highest level calculations on these states yet reported. It is concluded that our spectral simulation supports the assignments of the molecular carrier, the electronic states involved and the vibrational structure of the experimental laser induced fluorescence, and SVL emission spectra proposed by Grimminger et al. [J. Chem. Phys. 139, 174306 (2013)]. However, there remain questions unanswered regarding the relative electronic energies of the two states and the geometry of the excited state of HPS.

Lenard-Balescu calculations and classical molecular dynamics simulations of electrical and thermal conductivities of hydrogen plasmas

DOE PAGES

Whitley, Heather D.; Scullard, Christian R.; Benedict, Lorin X.; ...

2014-12-04

Here, we present a discussion of kinetic theory treatments of linear electrical and thermal transport in hydrogen plasmas, for a regime of interest to inertial confinement fusion applications. In order to assess the accuracy of one of the more involved of these approaches, classical Lenard-Balescu theory, we perform classical molecular dynamics simulations of hydrogen plasmas using 2-body quantum statistical potentials and compute both electrical and thermal conductivity from out particle trajectories using the Kubo approach. Our classical Lenard-Balescu results employing the identical statistical potentials agree well with the simulations.

OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation.

PubMed

Eastman, Peter; Friedrichs, Mark S; Chodera, John D; Radmer, Randall J; Bruns, Christopher M; Ku, Joy P; Beauchamp, Kyle A; Lane, Thomas J; Wang, Lee-Ping; Shukla, Diwakar; Tye, Tony; Houston, Mike; Stich, Timo; Klein, Christoph; Shirts, Michael R; Pande, Vijay S

2013-01-08

OpenMM is a software toolkit for performing molecular simulations on a range of high performance computing architectures. It is based on a layered architecture: the lower layers function as a reusable library that can be invoked by any application, while the upper layers form a complete environment for running molecular simulations. The library API hides all hardware-specific dependencies and optimizations from the users and developers of simulation programs: they can be run without modification on any hardware on which the API has been implemented. The current implementations of OpenMM include support for graphics processing units using the OpenCL and CUDA frameworks. In addition, OpenMM was designed to be extensible, so new hardware architectures can be accommodated and new functionality (e.g., energy terms and integrators) can be easily added.

OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation

PubMed Central

Eastman, Peter; Friedrichs, Mark S.; Chodera, John D.; Radmer, Randall J.; Bruns, Christopher M.; Ku, Joy P.; Beauchamp, Kyle A.; Lane, Thomas J.; Wang, Lee-Ping; Shukla, Diwakar; Tye, Tony; Houston, Mike; Stich, Timo; Klein, Christoph; Shirts, Michael R.; Pande, Vijay S.

2012-01-01

OpenMM is a software toolkit for performing molecular simulations on a range of high performance computing architectures. It is based on a layered architecture: the lower layers function as a reusable library that can be invoked by any application, while the upper layers form a complete environment for running molecular simulations. The library API hides all hardware-specific dependencies and optimizations from the users and developers of simulation programs: they can be run without modification on any hardware on which the API has been implemented. The current implementations of OpenMM include support for graphics processing units using the OpenCL and CUDA frameworks. In addition, OpenMM was designed to be extensible, so new hardware architectures can be accommodated and new functionality (e.g., energy terms and integrators) can be easily added. PMID:23316124

Computer simulation of liquid metals

NASA Astrophysics Data System (ADS)

Belashchenko, D. K.

2013-12-01

Methods for and the results of the computer simulation of liquid metals are reviewed. Two basic methods, classical molecular dynamics with known interparticle potentials and the ab initio method, are considered. Most attention is given to the simulated results obtained using the embedded atom model (EAM). The thermodynamic, structural, and diffusion properties of liquid metal models under normal and extreme (shock) pressure conditions are considered. Liquid-metal simulated results for the Groups I - IV elements, a number of transition metals, and some binary systems (Fe - C, Fe - S) are examined. Possibilities for the simulation to account for the thermal contribution of delocalized electrons to energy and pressure are considered. Solidification features of supercooled metals are also discussed.

Modelling the spread of innovation in wild birds.

PubMed

Shultz, Thomas R; Montrey, Marcel; Aplin, Lucy M

2017-06-01

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms. © 2017 The Author(s).

Hardware accelerator for molecular dynamics: MDGRAPE-2

NASA Astrophysics Data System (ADS)

Susukita, Ryutaro; Ebisuzaki, Toshikazu; Elmegreen, Bruce G.; Furusawa, Hideaki; Kato, Kenya; Kawai, Atsushi; Kobayashi, Yoshinao; Koishi, Takahiro; McNiven, Geoffrey D.; Narumi, Tetsu; Yasuoka, Kenji

2003-10-01

We developed MDGRAPE-2, a hardware accelerator that calculates forces at high speed in molecular dynamics (MD) simulations. MDGRAPE-2 is connected to a PC or a workstation as an extension board. The sustained performance of one MDGRAPE-2 board is 15 Gflops, roughly equivalent to the peak performance of the fastest supercomputer processing element. One board is able to calculate all forces between 10 000 particles in 0.28 s (i.e. 310000 time steps per day). If 16 boards are connected to one computer and operated in parallel, this calculation speed becomes ˜10 times faster. In addition to MD, MDGRAPE-2 can be applied to gravitational N-body simulations, the vortex method and smoothed particle hydrodynamics in computational fluid dynamics.

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE PAGES

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk; ...

2017-11-07

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Constant-pH Molecular Dynamics Simulations for Large Biomolecular Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radak, Brian K.; Chipot, Christophe; Suh, Donghyuk

We report that an increasingly important endeavor is to develop computational strategies that enable molecular dynamics (MD) simulations of biomolecular systems with spontaneous changes in protonation states under conditions of constant pH. The present work describes our efforts to implement the powerful constant-pH MD simulation method, based on a hybrid nonequilibrium MD/Monte Carlo (neMD/MC) technique within the highly scalable program NAMD. The constant-pH hybrid neMD/MC method has several appealing features; it samples the correct semigrand canonical ensemble rigorously, the computational cost increases linearly with the number of titratable sites, and it is applicable to explicit solvent simulations. The present implementationmore » of the constant-pH hybrid neMD/MC in NAMD is designed to handle a wide range of biomolecular systems with no constraints on the choice of force field. Furthermore, the sampling efficiency can be adaptively improved on-the-fly by adjusting algorithmic parameters during the simulation. Finally, illustrative examples emphasizing medium- and large-scale applications on next-generation supercomputing architectures are provided.« less

Exploring the Origin of Differential Binding Affinities of Human Tubulin Isotypes αβII, αβIII and αβIV for DAMA-Colchicine Using Homology Modelling, Molecular Docking and Molecular Dynamics Simulations

PubMed Central

Panda, Dulal; Kunwar, Ambarish

2016-01-01

Tubulin isotypes are found to play an important role in regulating microtubule dynamics. The isotype composition is also thought to contribute in the development of drug resistance as tubulin isotypes show differential binding affinities for various anti-cancer agents. Tubulin isotypes αβII, αβIII and αβIV show differential binding affinity for colchicine. However, the origin of differential binding affinity is not well understood at the molecular level. Here, we investigate the origin of differential binding affinity of a colchicine analogue N-deacetyl-N-(2-mercaptoacetyl)-colchicine (DAMA-colchicine) for human αβII, αβIII and αβIV isotypes, employing sequence analysis, homology modeling, molecular docking, molecular dynamics simulation and MM-GBSA binding free energy calculations. The sequence analysis study shows that the residue compositions are different in the colchicine binding pocket of αβII and αβIII, whereas no such difference is present in αβIV tubulin isotypes. Further, the molecular docking and molecular dynamics simulations results show that residue differences present at the colchicine binding pocket weaken the bonding interactions and the correct binding of DAMA-colchicine at the interface of αβII and αβIII tubulin isotypes. Post molecular dynamics simulation analysis suggests that these residue variations affect the structure and dynamics of αβII and αβIII tubulin isotypes, which in turn affect the binding of DAMA-colchicine. Further, the binding free-energy calculation shows that αβIV tubulin isotype has the highest binding free-energy and αβIII has the lowest binding free-energy for DAMA-colchicine. The order of binding free-energy for DAMA-colchicine is αβIV ≃ αβII >> αβIII. Thus, our computational approaches provide an insight into the effect of residue variations on differential binding of αβII, αβIII and αβIV tubulin isotypes with DAMA-colchicine and may help to design new analogues with higher binding affinities for tubulin isotypes. PMID:27227832

Long Range Debye-Hückel Correction for Computation of Grid-based Electrostatic Forces Between Biomacromolecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mereghetti, Paolo; Martinez, M.; Wade, Rebecca C.

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulatemore » solutions of bovine serum albumin and of hen egg white lysozyme.« less

Microscopic approaches to liquid nitromethane detonation properties.

PubMed

Hervouët, Anaïs; Desbiens, Nicolas; Bourasseau, Emeric; Maillet, Jean-Bernard

2008-04-24

In this paper, thermodynamic and chemical properties of nitromethane are investigated using microscopic simulations. The Hugoniot curve of the inert explosive is computed using Monte Carlo simulations with a modified version of the adaptative Erpenbeck equation of state and a recently developed intermolecular potential. Molecular dynamic simulations of nitromethane decomposition have been performed using a reactive potential, allowing the calculation of kinetic rate constants and activation energies. Finally, the Crussard curve of detonation products as well as thermodynamic properties at the Chapman-Jouguet (CJ) point are computed using reactive ensemble Monte Carlo simulations. Results are in good agreement with both thermochemical calculations and experimental measurements.

Molecular-Level Computational Investigation of Mechanical Transverse Behavior of p-Phenylene Terephthalamide (PPTA) Fibers

DTIC Science & Technology

2013-01-01

fabricated today are based on polymer matrix composites containing Kevlarw KM2 reinforcements , the present work will deal with generic PPTA fibers . In...Multi-length scale enriched continuum-level material model for Kevlarw- fiber reinforced polymer-matrix composites”, Journal of Materials...mechanical transverse behavior of p-phenylene terephthalamide (PPTA) fibers Purpose – A series of all-atom molecular-level computational analyses is

Multilevel summation with B-spline interpolation for pairwise interactions in molecular dynamics simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardy, David J., E-mail: dhardy@illinois.edu; Schulten, Klaus; Wolff, Matthew A.

2016-03-21

The multilevel summation method for calculating electrostatic interactions in molecular dynamics simulations constructs an approximation to a pairwise interaction kernel and its gradient, which can be evaluated at a cost that scales linearly with the number of atoms. The method smoothly splits the kernel into a sum of partial kernels of increasing range and decreasing variability with the longer-range parts interpolated from grids of increasing coarseness. Multilevel summation is especially appropriate in the context of dynamics and minimization, because it can produce continuous gradients. This article explores the use of B-splines to increase the accuracy of the multilevel summation methodmore » (for nonperiodic boundaries) without incurring additional computation other than a preprocessing step (whose cost also scales linearly). To obtain accurate results efficiently involves technical difficulties, which are overcome by a novel preprocessing algorithm. Numerical experiments demonstrate that the resulting method offers substantial improvements in accuracy and that its performance is competitive with an implementation of the fast multipole method in general and markedly better for Hamiltonian formulations of molecular dynamics. The improvement is great enough to establish multilevel summation as a serious contender for calculating pairwise interactions in molecular dynamics simulations. In particular, the method appears to be uniquely capable for molecular dynamics in two situations, nonperiodic boundary conditions and massively parallel computation, where the fast Fourier transform employed in the particle–mesh Ewald method falls short.« less