Temperature, molecular dynamics system

Quenched dynamics can trap structures in local minima. To prevent this problem, you can cool the system slowly to room temperature or some appropriate lower temperature. Then run room temperature molecular dynamics simulations to search for conformations that have lower energies, closer to the starting structure. Cooling a structure slowly is called simulated annealing. 

The simplest method that keeps the temperature of a system constant during an MD simulation is to rescale the velocities at each time step by a factor of (To/T) -, where T is the current instantaneous temperature [defined in Eq. (24)] and Tq is the desired temperamre. This method is commonly used in the equilibration phase of many MD simulations and has also been suggested as a means of performing constant temperature molecular dynamics [22]. A further refinement of the velocity-rescaling approach was proposed by Berendsen et al. [24], who used velocity rescaling to couple the system to a heat bath at a temperature Tq. Since heat coupling has a characteristic relaxation time, each velocity V is scaled by a factor X, defined as... 

To construct Nose-Hoover constant-temperature molecular dynamics, an additional coordinate, s, and its conjugate momentum p, are introduced. The Hamiltonian of the extended system of the N particles plus extended degrees of freedom can be expressed... 

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. 

The molecular configuration is a function of time. Molecular systems are not stationary molecules vibrate, rotate, and tumble. Force field calculations and the properties predicted by them are based on a. stationary model. What is needed is some way to predict what motions the atoms within a molecule will undergo at various temperatures. Molecular dynam-ics (MD) simulations use classical mechanics—force field methods—to study the atomic and molecular motions to predict macroscopic properties. "... 

Consider for example (1) high-friction Langevin processes, and (2) (Nose-Hoover) constant temperature molecular dynamics. For both cases the dynamics is reversible and the transfer operator is self-adjoint. For type (1) examples, conditions (Cl) and (C2) are known to be satisfied under rather weak condition on the potential [2]. For type (2) examples, it is unknown whether or not the conditions are satisfied however, it is normally assumed in molecular dynamics that they are valid for realistically complex systems in solution. 

M. Ferrario and J. P. Ryckaert, Mol. Phys., 54, 587 (1985). Constant Pressure-Constant Temperature Molecular Dynamics Simulations for Rigid and Partially Rigid Molecular Systems. 

To obtain the average values of properties of the particles at a fixed temperature and examine dependence of the conformations on temperature, we used Nose-Hoover chain (NHC) constant temperature molecular dynamics [228]. The initial configmations of the steady state of the amorphous PE particle were used at a start of the NHC simulations the initial values of the Cartesian momenta were given random orientation in phase space with magnitudes chosen so that the total kinetic energy was the equipartition theorem expectation value [229]. The NHC quasi-Hamiltonian for this system can be written,... 

Thus, a comparison between HPLC-derived lipophilicity indices and calculated log P values for a series of 8-substituted xanthines showed a clear influence of conformational effects. 8 In this case, Rekker s method was unable to take 3D effects into account, but the difference between experimental and predicted values was structure dependent rather than constant. Conformational analyses confirmed that a smaller than predicted lipophilicity was associated with folded conformers stabilized by hydrophobic and van der Waals forces and having part of their nonpolar surface masked from the aqueous phase. A 4D theoretical approach (log P calculations by MLP for conformers generated by high temperature molecular dynamics) suggests that these effects should be lower in an w-octanol/water system than in RP-HPLC. Indeed, the n-octanol/water system is not the most suitable model to study intramolecular interactions in nonpolar media because a surprisingly high proportion of water is dissolved in the w-octanol. Recall, however, that w-octanol, despite some limitations, was selected by many workers in the field as a model for biological membranes. 

Because of the large size of the systems studied, simple analytical potential energy functions must be used. Thus, almost all of the studies that simulate biological systems at the allatom level do so using molecular mechanics. In order to simulate these systems at a finite temperature, molecular dynamics and Monte Carlo simulation methods must be employed. 

Monte Carlo simulations generate a large number of confonnations of tire microscopic model under study that confonn to tire probability distribution dictated by macroscopic constrains imposed on tire systems. For example, a Monte Carlo simulation of a melt at a given temperature T produces an ensemble of confonnations in which confonnation with energy E. occurs witli a probability proportional to exp (- Ej / kT). An advantage of tire Monte Carlo metliod is tliat, by judicious choice of tire elementary moves, one can circumvent tire limitations of molecular dynamics techniques and effect rapid equilibration of multiple chain systems [65]. Flowever, Monte Carlo... 

A typical molecular dynamics simulation comprises an equflibration and a production phase. The former is necessary, as the name imphes, to ensure that the system is in equilibrium before data acquisition starts. It is useful to check the time evolution of several simulation parameters such as temperature (which is directly connected to the kinetic energy), potential energy, total energy, density (when periodic boundary conditions with constant pressure are apphed), and their root-mean-square deviations. Having these and other variables constant at the end of the equilibration phase is the prerequisite for the statistically meaningful sampling of data in the following production phase. 

A molecular system at room temperature is accurately characterized hy its tnoLiori. Molecular dynamics simulations calculate the future position s an d velocities of atom s based upon their current values. You can obtain qiialitative and quantitative data from HyperCh etn molecular dytiatn ics sirn ulation s. 

In a molecular dynamics calculation, you can add a term to adjust the velocities, keeping the molecular system near a desired temperature. During a constant temperature simulation, velocities are scaled at each time step. This couples the system to a simulated heat bath at Tq, with a temperature relaxation time of "r. The velocities arc scaled bv a factor X. where... 

The heating phase is used to take a molecular system smoothly from lower tern peratiires, indicative of a static initial (possibly optim i/ed ) structure, to th e temperature T at which it is desired to perform the molecular dynamics simulation. The run phase then consLitn tes a sim n lation at tern peratnre T. If th e heating h as been done carefully, it may be possible to skip the equilibration phase... 

The correct treatment of boundaries and boundary effects is crucial to simulation methods because it enables macroscopic properties to be calculated from simulations using relatively small numbers of particles. The importance of boundary effects can be illustrated by considering the following simple example. Suppose we have a cube of volume 1 litre which is filled with water at room temperature. The cube contains approximately 3.3 X 10 molecules. Interactions with the walls can extend up to 10 molecular diameters into the fluid. The diameter of the water molecule is approximately 2.8 A and so the number of water molecules that are interacting with the boundary is about 2 x 10. So only about one in 1.5 million water molecules is influenced by interactions with the walls of the container. The number of particles in a Monte Carlo or molecular dynamics simulation is far fewer than 10 -10 and is frequently less than 1000. In a system of 1000 water molecules most, if not all of them, would be within the influence of the walls of the boundary. Clecirly, a simulation of 1000 water molecules in a vessel would not be an appropriate way to derive bulk properties. The alternative is to dispense with the container altogether. Now, approximately three-quarters of the molecules would be at the surface of the sample rather than being in the bulk. Such a situation would be relevcUit to studies of liquid drops, but not to studies of bulk phenomena. 

---