Molecular dynamics simulation advantage

The principal idea behind the CSP approach is to use input from Classical Molecular Dynamics simulations, carried out for the process of interest as a first preliminary step, in order to simplify a quantum mechanical calculation, implemented in a subsequent, second step. This takes advantage of the fact that classical dynamics offers a reasonable description of many properties of molecular systems, in particular of average quantities. More specifically, the method uses classical MD simulations in order to determine effective... 

One of the main advantages of the stochastic dynamics methods is that dramatic tirn savings can he achieved, which enables much longer stimulations to he performed. Fc example, Widmalm and Pastor performed 1 ns molecular dynamics and stochastic dynamic simulations of an ethylene glycol molecule in aqueous solution of the solute and 259 vvatc jnolecules [Widmalm and Pastor 1992]. The molecular dynamics simulation require 300 hours whereas the stochastic dynamics simulation of the solute alone required ju 24 minutes. The dramatic reduction in time for the stochastic dynamics calculation is du not only to the very much smaller number of molecules present hut also to the fact the longer time steps can often he used in stochastic dynamics simulations. 

Molecular dynamics calculations are more time-consuming than Monte Carlo calculations. This is because energy derivatives must be computed and used to solve the equations of motion. Molecular dynamics simulations are capable of yielding all the same properties as are obtained from Monte Carlo calculations. The advantage of molecular dynamics is that it is capable of modeling time-dependent properties, which can not be computed with Monte Carlo simulations. This is how diffusion coefficients must be computed. It is also possible to use shearing boundaries in order to obtain a viscosity. Molec-... 

In a normal molecular dynamics simulation with repeating boundary conditions (i.e., periodic boundary condition), the volume is held fixed, whereas at constant pressure the volume of the system must fluemate. In some simulation cases, such as simulations dealing with membranes, it is more advantageous to use the constant-pressure MD than the regular MD. Various schemes for prescribing the pressure of a molecular dynamics simulation have also been proposed and applied [23,24,28,29]. In all of these approaches it is inevitable that the system box must change its volume. 

The concentration of salt in physiological systems is on the order of 150 mM, which corresponds to approximately 350 water molecules for each cation-anion pair. Eor this reason, investigations of salt effects in biological systems using detailed atomic models and molecular dynamic simulations become rapidly prohibitive, and mean-field treatments based on continuum electrostatics are advantageous. Such approximations, which were pioneered by Debye and Huckel [11], are valid at moderately low ionic concentration when core-core interactions between the mobile ions can be neglected. Briefly, the spatial density throughout the solvent is assumed to depend only on the local electrostatic poten-... 

The availability of thermodynamically reliable quantities at liquid interfaces is advantageous as a reference in examining data obtained by other surface specific techniques. The model-independent solid information about thermodynamics of adsorption can be used as a norm in microscopic interpretation and understanding of currently available surface specific experimental techniques and theoretical approaches such as molecular dynamics simulations. This chapter will focus on the adsorption at the polarized liquid-liquid interfaces, which enable us to externally control the phase-boundary potential, providing an additional degree of freedom in studying the adsorption of electrified interfaces. A main emphasis will be on some aspects that have not been fully dealt with in previous reviews and monographs [8-21]. 

This volume of Modem Aspects covers a wide spread of topics presented in an authoritative, informative and instructive manner by some internationally renowned specialists. Professors Politzer and Dr. Murray provide a comprehensive description of the various theoretical treatments of solute-solvent interactions, including ion-solvent interactions. Both continuum and discrete molecular models for the solvent molecules are discussed, including Monte Carlo and molecular dynamics simulations. The advantages and drawbacks of the resulting models and computational approaches are discussed and the impressive progress made in predicting the properties of molecular and ionic solutions is surveyed. 

The semi-empirical bond polarization model is a powerful tool for the calculation of, 3C chemical shift tensors. For most molecules the errors of this model are in the same order of magnitude as the errors of ab initio methods, under the condition that the surrounding of the carbon is not too much deformed by small bond angles. A great advantage of the model is that bond polarization calculations are very fast. The chemical shift tensors of small molecules can be estimated in fractions of a second. There is also virtually no limit for the size of the molecule. Systems with a few thousand atoms can be calculated with a standard PC within a few minutes. Possible applications are repetitive calculations during molecular dynamics simulations for the interpretation of dynamic effects on 13C chemical shift distribution. 

The main advantage of the MFA is that it permits one to dramatically reduce the computational requisites associated with the study of solvent effects. This allows one to focus attention on the solute description, and it consequently becomes possible to use calculation levels similar to those usually employed in the study of systems and processes in the gas phase. Furthermore, in the case of ASEP/MD this high level description of the solute is combined with a detailed description of the solvent structure obtained from molecular dynamics simulations. Thanks to these features ASEP/MD [8] enables the study of systems and processes where it is necessary to have simultaneously a good description of the electron correlation of the solute and the explicit consideration of specific solute-solvent interactions, such as for VIS-UV spectra [9] or chemical reactivity [10]. 

There are presently several groups around the world conducting molecular dynamics simulations of micellization and liquid crystallization of more or less realistic models of water, hydrocarbon, and surfactants. The memory and speed of a supercomputer required to produce reliably equilibrated microstructures constitute a challenge not yet met, in my opinion. By taking advantage of identified or hypothesized elemental structures one can, however, hope to learn a great deal about the dynamics and stability of the various identified microstructures. 

In this chapter, we present new results based on semi-empirical quantum calculations (PM3) that include solvation and charging effects simultaneously on the same model SFA.71 These calculations were carried out in HyperChem 5.0 (Hypercube, Inc.). Solvation was carried out with two approaches. In the first approach, the neutral, gas-phase SFA model was simulated, then this molecule was deprotonated at each of four carboxylic acid sites. Finally, a solvation sphere of H20 molecules was used to surround the anionic SFA and the structure obtained via molecular dynamics simulations and energy minimizations as an isolated nanodroplet. This approach has the advantage of allowing maximum flexibility of the model SFA. Larger model systems may require long simulation runs to sample all available conformations, but isolation of the SFA and water allows each component to move more freely. 

Since the dielectric continuum representation of the solvent has significant limitations, the molecular dynamics simulation of PCET with explicit solvent molecules is also an important direction. One approach is to utilize a multistate VB model with explicit solvent interactions [34-36] and to incorporate transitions among the adiabatic mixed electronic/proton vibrational states with the Molecular Dynamics with Quantum Transitions (MDQT) surface hopping method [39, 40]. The MDQT method has already been applied to a one-dimensional model PCET system [39]. The advantage of this approach for PCET reactions is that it is valid in the adiabatic and non-adiatic limits as well as in the intermediate regime. Furthermore, this approach is applicable to PCET in proteins as well as in solution. 

The particular iterative technique chosen by Car and Parrinello to iteratively solve the electronic structure problem in concert with nuclear motion was simulated annealing [11]. Specifically, variational parameters for the electronic wave function, in addition to nuclear positions, were treated like dynamical variables in a molecular dynamics simulation. When electronic parameters are kept near absolute zero in temperature, they describe the Bom-Oppenheimer electronic wave function. One advantage of the Car-Parrinello procedure is rather subtle. Taking the parameters as dynamical variables leads to robust prediction of values at a new time step from previous values, and cancellation in errors in the value of the nuclear forces. Another advantage is that the procedure, as is generally true of simulated annealing techniques, is equally suited to both linear and non-linear optimization. If desired, both linear coefficients of basis functions and non-linear functional parameters can be optimized, and arbitrary electronic models employed, so long as derivatives with respect to electronic wave function parameters can be calculated. 

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