Model hysteresis dimer molecule I: Equilibrium properties

A Hamiltonian system describing hysteresis behavior in a dimeric chemical reaction is modeled in a MD simulation utilizing novel two-body potentials with switches that is particularly suitable for numerical thermodynamical investigations. It is surmized that such reaction mechanisms could exist in nature on the basis of recent experiments, which indicate that electromagnetic hysteresis behavior is exhibited at the molecular level, although experimental interpretations tend to construct models that avoid such mechanisms. Numerical results of various common equilibrium thermodynamical and kinetic properties are presented together with new algorithms that were implemented to compute these quantities, where no unusual thermodynamics was observed for the chemical reaction which might be interpreted as not being “time reversible invariant” and therefore susceptible to manifesting unusual thermodynamical phenomena, which might contradict any of the known laws of thermodynamics. A revision of the concept of “time reversibility” to accommodate the above results is suggested. The general design of the reaction mechanism also allows for the use of conventional potentials and by the utilization of switches, overcomes the bottleneck of computations which involves multi-body interactions. The initial theoretical, program and algorithm development was done at Norwegian University of Science and Technology-NTNU, Institute of Physical Chemistry, (Trondheim, Norway) during a sabbatical visit 2000–2001 financed by University of Malaya. The method of MD used here conforms to the periodic boundary conditions and thermostatting algorithms developed or refined by Ikeshoji and Hafskjold for standard, non-reacting particles. Their approach is non-synthetic using traditional Verlet integration of Newton’s equations of motion.     

Advances in Modeling Sorption and Diffusion of Moisture in Porous Reactive Materials

Water‐vapor‐uptake experiments were performed on a silica‐filled poly(dimethylsiloxane) (PDMS) network and modeled by using two different approaches. The data was modeled by using established methods and the model parameters were used to predict moisture uptake in a sample. The predictions are reasonably good, but not outstanding; many of the shortcomings of the modeling are discussed. A high‐fidelity modeling approach is derived and used to improve the modeling of moisture uptake and diffusion. Our modeling approach captures the physics and kinetics of diffusion and adsorption/desorption, simultaneously. It predicts uptake better than the established method; more importantly, it is also able to predict outgassing. The material used for these studies is a filled‐PDMS network; physical interpretations concerning the sorption and diffusion of moisture in this network are discussed.     

Complex molecular assemblies at hand via interactive simulations

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. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009     

Simulation of multiphase systems utilizing independent force fields to control intraphase and interphase behavior

Fixed‐charge empirical force fields have been developed and widely used over the past three decades for all‐atom molecular simulations. Most simulation programs providing these methods enable only one set of force field parameters to be used for the entire system. Whereas this is generally suitable for single‐phase systems, the molecular environment at the interface between two phases may be sufficiently different from the individual phases to require a different set of parameters to be used to accurately represent the system. Recently published simulations of peptide adsorption to material surfaces using the CHARMM force field have clearly demonstrated this issue by revealing that calculated values of adsorption free energy substantially differ from experimental results. Whereas nonbonded parameters could be adjusted to correct this problem, this cannot be done without also altering the conformational behavior of the peptide in solution, for which CHARMM has been carefully tuned. We have developed a dual‐force‐field approach (Dual‐FF) to address this problem and implemented it in the CHARMM simulation package. This Dual‐FF method provides the capability to use two separate sets of nonbonded force field parameters within the same simulation: one set to represent intraphase interactions and a separate set to represent interphase interactions. Using this approach, we show that interfacial parameters can be adjusted to correct errors in peptide adsorption free energy without altering peptide conformational behavior in solution. This program thus provides the capability to enable both intraphase and interphase molecular behavior to be accurately and efficiently modeled in the same simulation. © 2012 Wiley Periodicals, Inc.     

Quantitative Design of Bright Fluorophores and AIEgens by the Accurate Prediction of Twisted Intramolecular Charge Transfer (TICT)

Inhibition of TICT can significantly increase the brightness of fluorescent materials. Accurate prediction of TICT is thus critical for the quantitative design of high‐performance fluorophores and AIEgens. TICT of 14 types of popular organic fluorophores were modeled with time‐dependent density functional theory (TD‐DFT). A reliable and generalizable computational approach for modeling TICT formations was established. To demonstrate the prediction power of our approach, we quantitatively designed a boron dipyrromethene (BODIPY)‐based AIEgen which exhibits (almost) barrierless TICT rotations in monomers. Subsequent experiments validated our molecular design and showed that the aggregation of this compound turns on bright emissions with ca. 27‐fold fluorescence enhancement, as TICT formation is inhibited in molecular aggregates.     

Molecular motion and relaxation studies of aliphatic polyureas by thermal windowing thermally stimulated depolarization current technique

Molecular motion and relaxation studies using a thermal windowing thermally stimulated depolarization current (TW‐TSDC) were performed for aliphatic polyureas 7 and 9. Global thermally stimulated depolarization current gave three characteristic major peaks corresponding to the α, β, and γ relaxation modes at 78.5, −44, and −136°C for polyurea 7 and at 80, −50, and −134°C for polyurea 9, respectively. The α relaxation is related to the large‐scale molecular motion due to micro‐Brownian motion of long‐range segments. This relaxation is significantly related to the glass‐transition temperature. The β relaxation is caused by the local thermal motion of long‐chain segments. The γ relaxation is caused by the limited local motion of hydrocarbon sections. Temperature dependence of relaxation times was expressed well using Vogel–Tammann–Fulcher (VTF) expression. 3‐D simulation of dielectric constants of dielectric strength and loss factor were performed in the frequency range from 10⁻⁶ to 10⁴ Hz and temperature range from −150 to 250°C, using the relaxation parameters obtained from the TW‐TSDC method. © 2000 John Wiley & Sons, Inc. J Polym Sci B: Polym Phys 38: 88–94, 2000     

Rapid determination of RMSDs corresponding to macromolecular rigid body motions

Finding the root mean sum of squared deviations (RMSDs) between two coordinate vectors that correspond to the rigid body motion of a macromolecule is an important problem in structural bioinformatics, computational chemistry, and molecular modeling. Standard algorithms compute the RMSD with time proportional to the number of atoms in the molecule. Here, we present RigidRMSD, a new algorithm that determines a set of RMSDs corresponding to a set of rigid body motions of a macromolecule in constant time with respect to the number of atoms in the molecule. Our algorithm is particularly useful for rigid body modeling applications, such as rigid body docking, and also for high‐throughput analysis of rigid body modeling and simulation results. We also introduce a constant‐time rotation RMSD as a similarity measure for rigid molecules. A C++ implementation of our algorithm is available at http://nano‐d.inrialpes.fr/software/RigidRMSD . © 2014 Wiley Periodicals, Inc.     

Collective motion artifacts arising in long‐duration molecular dynamics simulations

We tested a variety of molecular dynamics simulation strategies in long‐duration (up to several nanoseconds) constant‐temperature simulations of liquid water under periodic boundary conditions. Such long durations are necessary to achieve adequate conformational sampling in simulations of membrane assemblies and other large biomolecular systems. Under a variety of circumstances, serious artifacts arise in the form of spurious collective behavior that becomes obvious only after the simulation has gone at least several hundred picoseconds. The potential energy of the system drops and the system changes from a liquid to an icy or glassy state. The underlying cause is accumulated center‐of‐mass motion of the system, coupled with velocity rescaling associated with constant‐temperature control. The velocity rescaling in the constant‐temperature algorithm reduces the thermal velocity as the net center‐of‐mass velocity grows, effectively causing the kinetic energy of the system to drain from thermal motions into coordinated motions. We found that the incidence and magnitude of the underlying artifactual motion leading to the spurious transition is mediated by: choice of method for computing electrostatic interactions; choice of ensemble; size of the simulation cell; SHAKE tolerance; frequency of nonbonded pairlist updating; and closeness of coupling to the temperature bath. The appearance of the spurious transition can be avoided by periodically subtracting net center‐of‐mass motion during the dynamics, or by improving the accuracy of the simulation by means of tightening SHAKE tolerance and updating nonbonded pairlists every timestep. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 121–131, 2000     

GENESIS 1.1: A hybrid‐parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms

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.     

Layer-by-Layer Formation of Oligoelectrolyte Multilayers: A Combined Experimental and Computational Study

For the first time, the combination of experimental preparation and results of fully atomistic simulations of an oligoelectrolyte multilayer (OEM) made of poly(diallyl dimethyl ammonium chloride)/poly(styrene sulfonate sodium salt) (PDADMAC/PSS) is presented. The layer-by-layer growth was carried out by dipping silica substrates in oligoelectrolyte solutions and was modeled by means of atomistic molecular dynamics simulations with a protocol that mimics the experimental procedure up to the assembly of four layers. Measurements of OEM thickness, surface roughness and amount of adsorbed oligoelectrolyte chains obtained from both approaches are compared. A good agreement between simulated and experimental results was found, with some deviations due to intrinsic limitations of both methods. However, the combination of information extracted from simulations to support the analysis of experimental data can overcome such restrictions and improve the interpretation of experimental results. On the other hand, processes dominated by slower kinetics, such as the destabilization of adsorbed layers upon equilibration with the surrounding environment, are out of reach for the simulation modeling approach, but they can be investigated by monitoring in situ the oligoelectrolyte adsorption during the assembly process. This demonstrates how the synergistic use of simulation and experiments improves the knowledge of OEM properties down to the molecular scale.     

Low-temperature vapor-liquid equilibria from parallelized molecular dynamics simulations. Application to 1- and 2-methylnaphthalene

A parallelized sampling version of the Gibbs Ensemble (Mol. Phys. 2000, 98, 1887) has been implemented to predict low-temperature vapor-liquid equilibria of 1- and 2-methylnaphthalene modeled by anisotropic united atom potentials. The simulation were performed at the low temperature of 364.2 K at which common direct simulation methods fail due to particle transfer problems. The simulation results are compared with published results obtained from the Gibbs-Duhem integration method and with experimental data. Both methods are compared and discussed in terms of computational efficiency and with respect to their future use at other thermodynamic conditions.     

Study on growth rate of TiO2 nanostructured thin films: simulation by molecular dynamics approach and modeling by artificial neural network

Effects of the deposition process parameters on the thickness of TiO₂ nanostructured film were simulated using the molecular dynamics (MD) approach and modeled by the artificial neural network (ANN) and regression method. Accordingly, TiO₂ nanostructured film was prepared experimentally with the sol–gel dip‐coating method. Structural instabilities can be expected, due to short‐ and/or long‐range intermolecular forces, leading to the surface inhomogeneities. In the MD simulation, the Morse potential function was used for the inter‐atomic interactions, and equations of motion for atoms were solved by Verlet algorithm. The effect of the withdrawal velocity, drying temperature and number of deposited layers were studied in order to characterize the film thickness. The results of MD simulations are reasonably consistent with atomic force microscopy, scanning electron microscopy and Dektak surface profiler. Finally, the outputs from experimental data were analyzed by using the ANN in order to investigate the effects of deposition process parameters on the film thickness. In this case, various architectures have been checked using 75% of experimental data for training of the ANN. Among the various architectures, feed‐forward back‐propagation network with trainer training algorithm was found as the best architecture. Based on the R‐squared value, the ANN is better than the regression model in predicting the film thickness. The statistical analysis for those results was then used to verify the fitness of the complex process model. Based on the results, this modeling methodology can explain the characteristics of the TiO₂ nanostructured thin film and growth mechanism varying with process conditions. © 2013 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.     

Operator splitting algorithm for isokinetic SLLOD molecular dynamics

We apply an operator splitting method to develop a simulation algorithm that has complete analytical solutions for the Gaussian thermostated SLLOD equations of motion [D. J. Evans and G. P. Morriss, Phys. Rev. A 30, 1528 (1984)] for a system under shear. This leads to a homogeneous algorithm for performing both equilibrium and nonequilibrium isokinetic molecular dynamics simulation. The resulting algorithm is computationally efficient. In particular, larger integration time steps can be used compared to simulations with regular Gaussian thermostated SLLOD equations of motion. The utility and accuracy of the algorithm are demonstrated through application to the Weeks-Chandler-Anderson fluid. Although strict conservation of the kinetic energy suppresses thermal fluctuations in the system, this algorithm does not allow simulations at lower shear rates than those normally afforded by older nonequilibrium molecular dynamics simulations.     

Q‐DockLHM: Low‐resolution refinement for ligand comparative modeling

The success of ligand docking calculations typically depends on the quality of the receptor structure. Given improvements in protein structure prediction approaches, approximate protein models now can be routinely obtained for the majority of gene products in a given proteome. Structure‐based virtual screening of large combinatorial libraries of lead candidates against theoretically modeled receptor structures requires fast and reliable docking techniques capable of dealing with structural inaccuracies in protein models. Here, we present Q‐Dock^LHM, a method for low‐resolution refinement of binding poses provided by FINDSITE^LHM, a ligand homology modeling approach. We compare its performance to that of classical ligand docking approaches in ligand docking against a representative set of experimental (both holo and apo) as well as theoretically modeled receptor structures. Docking benchmarks reveal that unlike all‐atom docking, Q‐Dock^LHM exhibits the desired tolerance to the receptor's structure deformation. Our results suggest that the use of an evolution‐based approach to ligand homology modeling followed by fast low‐resolution refinement is capable of achieving satisfactory performance in ligand‐binding pose prediction with promising applicability to proteome‐scale applications. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Symplectic molecular dynamics simulations on specially designed parallel computers

We have developed a computer program for molecular dynamics (MD) simulation that implements the Split Integration Symplectic Method (SISM) and is designed to run on specialized parallel computers. The MD integration is performed by the SISM, which analytically treats high-frequency vibrational motion and thus enables the use of longer simulation time steps. The low-frequency motion is treated numerically on specially designed parallel computers, which decreases the computational time of each simulation time step. The combination of these approaches means that less time is required and fewer steps are needed and so enables fast MD simulations. We study the computational performance of MD simulation of molecular systems on specialized computers and provide a comparison to standard personal computers. The combination of the SISM with two specialized parallel computers is an effective way to increase the speed of MD simulations up to 16-fold over a single PC processor.     

A generalized Langevin dynamics approach to model solvent dynamics effects on proteins via a solvent-accessible surface. The carboxypeptidase A inhibitor protein as a model

A generalized Langevin dynamics (GLD) scheme is derived for (bio)macromolecules having internal structure, arbitrary shapes and a size larger than solvent molecules (i.e. proteins). The concept of solvent-accessible surface area (SASA) is used to incorporate solvent effects via external forces thereby avoiding its explicit molecular representation. A simulation algorithm is implemented in the GROMOS molecular dynamics (MD) program including random forces and memory effects, while solvation effects enter via derivatives of the surface area. The potato carboxypeptidase inhibitor (PCI), a small protein, is used to numerically test the approach. This molecule has N- and C-terminal tails whose structure and fluctuations are solvent dependent. A 1-ns MD trajectory was analyzed in depth. X-ray and NMR structures are used in conjunction with MD simulations with and without explicit solvent to gauge the quality of the results. All the analyses showed that the GLD simulation approached the results obtained for the MD simulation with explicit simple-point-charge-model water molecules. The SASAs of the polar atoms show a natural exposure towards the solvent direction. A FLS solvent simulation was completed in order to sense memory effects. The approach and results presented here could be of great value for developing alternatives to the use of explicit solvent molecules in the MD simulation of proteins, expanding its use and the time-scale explored. Received: 2 February 2000 / Revised: 12 March 2000 / Accepted: 26 May 2000 / Published online: 2 November 2000     

Modeling,Simulation, and Implementation of Solar‐Driven Water‐Splitting Devices

An integrated cell for the solar‐driven splitting of water consists of multiple functional components and couples various photoelectrochemical (PEC) processes at different length and time scales. The overall solar‐to‐hydrogen (STH) conversion efficiency of such a system depends on the performance and materials properties of the individual components as well as on the component integration, overall device architecture, and system operating conditions. This Review focuses on the modeling‐ and simulation‐guided development and implementation of solar‐driven water‐splitting prototypes from a holistic viewpoint that explores the various interplays between the components. The underlying physics and interactions at the cell level is are reviewed and discussed, followed by an overview of the use of the cell model to provide target properties of materials and guide the design of a range of traditional and unique device architectures.     

Multi‐Resolution Simulation of Biomolecular Systems: A Review of Methodological Issues

Theoretical‐computational modeling with an eye to explaining experimental observations in regard to a particular chemical phenomenon or process requires choices concerning essential degrees of freedom and types of interactions and the generation of a Boltzmann ensemble or trajectories of configurations. Depending on the degrees of freedom that are essential to the process of interest, for example, electronic or nuclear versus atomic, molecular or supra‐molecular, quantum‐ or classical‐mechanical equations of motion are to be used. In multi‐resolution simulation, various levels of resolution, for example, electronic, atomic, supra‐atomic or supra‐molecular, are combined in one model. This allows an enhancement of the computational efficiency, while maintaining sufficient detail with respect to particular degrees of freedom. The basic challenges and choices with respect to multi‐resolution modeling are reviewed and as an illustration the differential catalytic properties of two enzymes with similar folds but different substrates with respect to these substrates are explored using multi‐resolution simulation at the electronic, atomic and supra‐molecular levels of resolution.