Equilibrated simulation

Figure 3- Snapshot from an equilibrated simulation of a smectic bilayer system sodium ions (A), decanoate ions (chain with forked end) and decanol molecules (linear chain). The projection of all atoms is given.

Equilibration of the interface, and the establislnnent of equilibrium between the two phases, may be very slow. Holcomb et al [183] found that the density profile p(z) equilibrated much more quickly than tire profiles of nonnal and transverse pressure, f yy(z) and f jfz), respectively. The surface tension is proportional to the z-integral of Pj z)-Pj z). The bulk liquid in the slab may continue to contribute to this integral, indicatmg lack of equilibrium, for very long times if the initial liquid density is chosen a little too high or too low. A recent example of this kind of study, is the MD simulation of the liquid-vapour surface of water at temperatures between 316 and 573 K by Alejandre et al [184]. 

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... 

The SMD simulations were based on an NMR structure of the Ig domain 127 of the cardiac titin I-band (Improta et ah, 1996). The Ig domains consist of two /9-sheets packed against each other, with each sheet containing four strands, as shown in Fig. 8b. After 127 was solvated and equilibrated, SMD simulations were carried out by fixing one terminus of the domain and applying a force to the other in the direction from the fixed terminus to the other terminus. Simulations were performed as described by Eq. (1) with V = 0.5 A/ps and if = 10 ksT/A 414 pN/A. The force-extension profile from the SMD trajectory showed a single force peak as presented in Fig. 8a. This feature agrees well with the sawtooth-shaped force profile exhibited in AFM experiments. 

The first term represents the forces due to the electrostatic field, the second describes forces that occur at the boundary between solute and solvent regime due to the change of dielectric constant, and the third term describes ionic forces due to the tendency of the ions in solution to move into regions of lower dielectric. Applications of the so-called PBSD method on small model systems and for the interaction of a stretch of DNA with a protein model have been discussed recently ([Elcock et al. 1997]). This simulation technique guarantees equilibrated solvent at each state of the simulation and may therefore avoid some of the problems mentioned in the previous section. Due to the smaller number of particles, the method may also speed up simulations potentially. Still, to be able to simulate long time scale protein motion, the method might ideally be combined with non-equilibrium techniques to enforce conformational transitions. 

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. 

Figure 7-15. Healing and equilibration phase of a typical MD simulation, In the ideal case, the temperature should fluctuate around the desired value (here 298 K), and the potential energy should remain constant. Remember that the total energy is the sum of potential and kinetic energy, the latter being directly coupled to the temperature of the system,...

A rn uleculur dynam ics si in illation can li ave tli rcc distinct time and teiTi pcratii re periods h eating, simulation (niri). an d eoolin g. If yon wan t to meast re equilibrium properties of a molectilar system. yon can divide til e sitn 11 lation period into two parts equilibration and data collection. ... 

In many molecular dynamics simulations, equilibration is a separate step that precedes data collection. Equilibration is generally necessary lo avoid introducing artifacts during the healing step an d to en su re th at the trajectory is aciii ally sim u laiin g eq u i librium 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 1 0-20 ps. Suggested tim es range from. 5 ps to nearly 100 ps for medium-si/ed proteins. 

Th e sim u lation or run tim e m eludes time for the system lo equilibrate at Ibe simulation temperature plus tbe time for data collection, while the trajectory evolves. Simulation timesdepend on the time scale of tbc property you are investigating. 

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... 

Rappe A K and W A Goddard III 1991. Charge Equilibration for Molecular Dynamics Simulations. Journal of Physical Chemistry 95 3358-3363. 

Variation in Verlet order parameter during the equilibration phase of a molecular dynamics simulation of... 

The radial distribution function can also be used to monitor the progress of the equilibration. This function is particularly useful for detecting the presence of two phases. Such a situation is characterised by a larger than expected first peak and by the fact that g r) does not decay towards a value of 1 at long distances. If two-phase behaviour is inappropriate then the simulation should probably be terminated and examined. If, however, a two-phase system is desired, then a long equilibration phase is usually required. 

---