Molecular dynamics simulation time-dependent properties

Zigmond, 1988). The ATP-hydrolysis that accompanies actin polymerization, ATP —> ADP + Pj, and the subsequent release of the cleaved phosphate (Pj) are believed to act as a clock (Pollard et ah, 1992 Allen et ah, 1996), altering in a time-dependent manner the mechanical properties of the filament and its propensity to depolymerize. Molecular dynamics simulations suggested a so-called back door mechanism for the hydrolysis reaction ATP ADP - - Pj in which ATP enters the actin from one side, ADP leaves from the same side, but Pj leaves from the opposite side, the back door (Wriggers and Schulten, 1997b). This hypothesis can explain the effect of the toxin phalloidin which blocks the exit of the putative back door pathway and, thereby, delays Pi release as observed experimentally (Dancker and Hess, 1990). 

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 many molecular dynamics simulations, equilibration is a separate step that precedes data collection. Equilibration is generally necessary to avoid introducing artifacts during the heating step and to ensure that the trajectory is actually simulating equilibrium properties. The period required for equilibration depends on the property of interest and the molecular system. It may take about 100 ps for the system to approach equilibrium, but some properties are fairly stable after 10-20 ps. Suggested times range from 5 ps to nearly 100 ps for medium-sized proteins. 

The molecular dynamics method is useful for calculating the time-dependent properties of an isolated molecule. However, more often, one is interested in the properties of a molecule that is interacting with other molecules. With HyperChem, you can add solvent molecules to the simulation explicitly, but the addition of many solvent molecules will make the simulation much slower. A faster solution is to simulate the motion of the molecule of interest using Langevin dynamics. 

The computational efficiency of a FF approach also enables simulations of dynamical behavior—molecular dynamics (MD). In MD, the classical equations of motion for a system of N atoms are solved to generate a search in phase space, or trajectory, under specified thermodynamic conditions (e.g., constant temperature or constant pressure). The trajectory provides configurational and momentum information for each atom from which thermodynamic properties such as the free energy, or time-dependent properties such as diffusion coefficients, can be calculated. 

The extension of density functional theory (DFT) to the dynamical description of atomic and molecular systems offers an efficient theoretical and computational tool for chemistry and molecular spectroscopy, namely, time-dependent DFT (TDDFT) [7-11]. This tool allows us to simulate the time evolution of electronic systems, so that changes in molecular structure and bonding over time due to applied time-dependent fields can be investigated. Its response variant TDDF(R)T is used to calculate frequency-dependent molecular response properties, such as polarizabilities and hyperpolarizabilities [12-17]. Furthermore, TDDFRT overcomes the well-known difficulties in applying DFT to excited states [18], in the sense that the most important characteristics of excited states, the excitation energies and oscillator strengths, are calculated with TDDFRT [17, 19-26]. 

In order to determine a system thermodynamically, one has to specify some independent parameters (e.g. N, T, P or V) besides the composition of the system. The most common choice in MC simulation is to specify N, V and T resulting in the canonical ensemble, where the Helmholtz free energy A is the natural thermodynamical potential. However, MC calculations can be performed in any ensemble, where the suitable choice depends on the application. It is straightforward to apply the Metropolis MC algorithm to a simple electric double layer in the iVFT ensemble. It is however, not so efficient for polymers composed of more than a few tens of monomers. For long polymers other algorithms should be considered and the Pivot algorithm [21] offers an efficient alternative. MC simulations provide thermodynamic and structural information, but time-dependent properties are not accessible. If kinetic or time-dependent properties are of interest one has to use molecular dynamic or brownian dynamic simulations. 

The time-dependent properties of the molecular dynamics simulation are characteristic of a material element flowing through the shock wave, within the approximations made in the derivation of the method. Therefore, the spatial profile of the simulated shock wave can be reconstructed by calculating the position of a material element x at time t,... 

In the late 1980s we have seen the use of molecular dynamics simulations [29-39] to derive time-dependent properties such as diffusion coefficients and mean square... 

Molecular dynamics generates configurations of the system that are connected in time and so an MD simulation can be used to calculate time-dependent properties. This is a major advantage of molecular dynamics over the Monte Carlo method. Time-dependent properties are often calculated as time correlation coefficients. 

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