Molecular dynamics simulation atom motions

A molecular system at room temperature is accurately characterized by its motion. Molecular dynamics simulations calculate the future positions and velocities of atoms based upon their current values. You can obtain qualitative and quantitative data from HyperChem molecular dynamics simulations. 

By integrating the Newtonian Equations of Motion, Molecular Dynamics simulations are able to describe the behavior of particles in a certain system within the observed period of time. The interaction of the atoms is described by the potential energy fxmction of the given force field [e.g. Amber (Cornell et al, 1995), CHARMM (Brooks et al., 1983), GROMOS (Scott et al., 1999), OPLS (Jorgensen Rives, 1988)]. Nowadays, there is an ongoing effort to ameliorate these parameters in a need for models being as less artificial as possible. 

Molecular dynamics simulations ([McCammon and Harvey 1987]) propagate an atomistic system by iteratively solving Newton s equation of motion for each atomic particle. Due to computational constraints, simulations can only be extended to a typical time scale of 1 ns currently, and conformational transitions such as protein domains movements are unlikely to be observed. 

A molecular dynamics simulation samples the phase space of a molecule (defined by the position of the atoms and their velocities) by integrating Newton s equations of motion. Because MD accounts for thermal motion, the molecules simulated may possess enough thermal energy to overcome potential barriers, which makes the technique suitable in principle for conformational analysis of especially large molecules. In the case of small molecules, other techniques such as systematic, random. Genetic Algorithm-based, or Monte Carlo searches may be better suited for effectively sampling conformational space. 

The explicit definition of water molecules seems to be the best way to represent the bulk properties of the solvent correctly. If only a thin layer of explicitly defined solvent molecules is used (due to hmited computational resources), difficulties may rise to reproduce the bulk behavior of water, especially near the border with the vacuum. Even with the definition of a full solvent environment the results depend on the model used for this purpose. In the relative simple case of TIP3P and SPC, which are widely and successfully used, the atoms of the water molecule have fixed charges and fixed relative orientation. Even without internal motions and the charge polarization ability, TIP3P reproduces the bulk properties of water quite well. For a further discussion of other available solvent models, readers are referred to Chapter VII, Section 1.3.2 of the Handbook. Unfortunately, the more sophisticated the water models are (to reproduce the physical properties and thermodynamics of this outstanding solvent correctly), the more impractical they are for being used within molecular dynamics simulations. 

Molecular dynamics is a simulation of the time-dependent behavior of a molecular system, such as vibrational motion or Brownian motion. It requires a way to compute the energy of the system, most often using a molecular mechanics calculation. This energy expression is used to compute the forces on the atoms for any given geometry. The steps in a molecular dynamics simulation of an equilibrium system are as follows ... 

Molecular Dynamics and Monte Carlo Simulations. At the heart of the method of molecular dynamics is a simulation model consisting of potential energy functions, or force fields. Molecular dynamics calculations represent a deterministic method, ie, one based on the assumption that atoms move according to laws of Newtonian mechanics. Molecular dynamics simulations can be performed for short time-periods, eg, 50—100 picoseconds, to examine localized very high frequency motions, such as bond length distortions, or, over much longer periods of time, eg, 500—2000 ps, in order to derive equiUbrium properties. It is worthwhile to summarize what properties researchers can expect to evaluate by performing molecular simulations ... 

Molecular modeling is an indispensable tool in the determination of macromolecular structures from NMR data and in the interpretation of the data. Thus, state-of-the-art molecular dynamics simulations can reproduce relaxation data well [9,96] and supply a model of the motion in atomic detail. Qualitative aspects of correlated backbone motions can be understood from NMR structure ensembles [63]. Additional data, in particular residual dipolar couplings, improve the precision and accuracy of NMR structures qualitatively [12]. 

The first reaction filmed by X-rays was the recombination of photodisso-ciated iodine in a CCI4 solution [18, 19, 49]. As this reaction is considered a prototype chemical reaction, a considerable effort was made to study it. Experimental techniques such as linear [50-52] and nonlinear [53-55] spectroscopy were used, as well as theoretical methods such as quantum chemistry [56] and molecular dynamics simulation [57]. A fair understanding of the dissociation and recombination dynamics resulted. However, a fascinating challenge remained to film atomic motions during the reaction. This was done in the following way. 

In some situations we have performed finite temperature molecular dynamics simulations [50, 51] using the aforementioned model systems. On a simplistic level, molecular dynamics can be viewed as the simulation of the finite temperature motion of a system at the atomic level. This contrasts with the conventional static quantum mechanical simulations which map out the potential energy surface at the zero temperature limit. Although static calculations are extremely important in quantifying the potential energy surface of a reaction, its application can be tedious. We have used ah initio molecular dynamics simulations at elevated temperatures (between 300 K and 800 K) to more efficiently explore the potential energy surface. 

Which model provides the best representation for local mobility in a particular group remains unclear, as a detailed picture of protein dynamics is yet to be painted. This information is not directly available from NMR measurements that are necessarily limited by the number of experimentally available parameters. Additional knowledge is required in order to translate these experimental data into a reliable motional picture of a protein. At this stage, molecular dynamic simulations could prove extremely valuable, because they can provide complete characterization of atomic motions for all atoms in a molecule and at all instants of the simulated trajectory. This direction becomes particularly promising with the current progress in computational resources, when the length of a simulated trajectory approaches the NMR-relevant time scales [23, 63, 64]. 

Molecular dynamics simulations yield an essentially exact (within the confines of classical mechanics) method for observing the dynamics of atoms and molecules during complex chemical reactions. Because the assumption of equilibrium is not necessary, this technique can be used to study a wide range of dynamical events which are associated with surfaces. For example, the atomic motions which lead to the ejection of surface species during keV particle bombardment (sputtering) have been identified using molecular dynamics, and these results have been directly correlated with various experimental observations. Such simulations often provide the only direct link between macroscopic experimental observations and microscopic chemical dynamics. 

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