Molecular dynamics extracting information from simulation

An important issue, the significance of which is sometime underestimated, is the analysis of the resulting molecular dynamics trajectories. Clearly, the value of any computer simulation lies in the quality of the information extracted from it. In fact, it is good practice to plan the analysis procedure before starting the simulation, as the goals of the analysis will often detennine the character of the simulation to be performed. 

In a different context, conformational analysis is essential for the analysis of molecular dynamics simulations. As discussed in Chapter 3, the direct output of a molecular dynamics simulation is a set of confonnations ( snapshots ) that were saved along the trajectory. These conformations are subsequently analyzed in order to extract information about the system. However, if, during a long simulation, the molecule moves from one... 

The strategy in a molecular dynamics simulation is conceptually fairly simple. The first step is to consider a set of molecules. Then it is necessary to choose initial positions of all atoms, such that they do not physically overlap, and that all bonds between the atoms have a reasonable length. Subsequently, it is necessary to specify the initial velocities of all the atoms. The velocities must preferably be consistent with the temperature in the system. Finally, and most importantly, it is necessary to define the force-field parameters. In effect the force field defines the potential energy of each atom. This value is a complicated sum of many contributions that can be computed when the distances of a given atom to all other atoms in the system are known. In the simulation, the spatial evolution as well as the velocity evolution of all molecules is found by solving the classical Newton equations of mechanics. The basic outcome of the simulation comprises the coordinates and velocities of all atoms as a function of the time. Thus, structural information, such as lipid conformations or membrane thickness, is readily available. Thermodynamic information is more expensive to obtain, but in principle this can be extracted from a long simulation trajectory. 

Data mining to extract information on dynamics from time series data from experiments and simulations of molecular dynamics. 

The Boltzmann equation must be solved with appropriate boundary conditions to obtain f and f. The full Boltzmann equation has not been solved analytically or numerically. Current approximate methods for extracting the desired information from the Boltzmann equation are covered in detail in a recent reference [2.84]. In view of this review, discussion of these methods will not be given. It is sufficient to indicate some of the principal methods which have been employed. These are moment or integral methods for specific molecular scattering laws, the use of "models" (of which the BGK model is the simplest) for the collisions term J(fgfg), and direct simulation by Monte Carlo or molecular-dynamics techniques. 

Being a molecular dynamics technique, GEMD provides dynamical information such as diffusion coefficients in the coexisting phases [5]. Shown in Fig. 3 are the mean squared displacements of the carbon atoms in -hexane, calculated in coexisting phases with GEMD, compared to the results of the constant temperature molecular dynamics at the same conditions. This shows that diffusion coefficients and other dynamical information can be extracted from GEMD simulations, together with the thermodynamic properties. 

It is interesting to note that the diffraction measurement can only yield one piece of information and it is impossible to evaluate the centres structure factor S CQ) directly from the observations since there is no scattering centre in this position. The complex relationship involving orientational correlations between molecules can only be extracted by comparing the data with model simulations no molecular dynamics calculations have been reported for this liquid and therefore the details are not known. 

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