Simulation from molecular dynamics

Postma, J.P.M., Berendsen, H.J.C., Straatsma, T.P. Intramolecular vibrations from molecular dynamics simulations of liquid water. Journal de Physique C7 (1984) 31-40. 

Creveld, L., Amadei, A., Van Schaik, C., Pepermans, R., De Vlieg, J., Berendsen, H.J.C. Identification of functional and unfolding motions of cutinase as obtained from molecular dynamics computer simulations. Submitted (1998). 

Hermans, J., Subramaniam, S. The free energy of xenon binding to myoglobin from molecular dynamics simulation. Isr. J. Chem. 27 (1986) 225-227... 

It is appropriate to consider first the question of what kind of accuracy is expected from a simulation. In molecular dynamics (MD) very small perturbations to initial conditions grow exponentially in time until they completely overwhelm the trajectory itself. Hence, it is inappropriate to expect that accurate trajectories be computed for more than a short time interval. Rather it is expected only that the trajectories have the correct statistical properties, which is sensible if, for example, the initial velocities are randomly generated from a Maxwell distribution. 

Mesoscale simulations model a material as a collection of units, called beads. Each bead might represent a substructure, molecule, monomer, micelle, micro-crystalline domain, solid particle, or an arbitrary region of a fluid. Multiple beads might be connected, typically by a harmonic potential, in order to model a polymer. A simulation is then conducted in which there is an interaction potential between beads and sometimes dynamical equations of motion. This is very hard to do with extremely large molecular dynamics calculations because they would have to be very accurate to correctly reflect the small free energy differences between microstates. There are algorithms for determining an appropriate bead size from molecular dynamics and Monte Carlo simulations. 

V Daggett, M Levitt. A model of the molten globule state from molecular dynamics simulations. Pi-oc Natl Acad Sci USA 89 5142-5146, 1992. 

AG Anderson, J Hermans. Microfoldmg Conformational probability map for the alanine dipeptide in water from molecular dynamics simulations. Proteins 3 262-265, 1988. 

The relative intensities of the bands in the transmission and RAIR spectra were used to determine the orientation of the long axis of the 4-MPP molecules with respect to the normal to the gold surface. It was found that this tilt angle was about 21°, a value that was similar to that obtained from molecular dynamics simulations [11]. 

The function / incorporates the screening effect of the surfactant, and is the surfactant density. The exponent x can be derived from the observation that the total interface area at late times should be proportional to p. In two dimensions, this implies R t) oc 1/ps and hence x = /n. The scaling form (20) was found to describe consistently data from Langevin simulations of systems with conserved order parameter (with n = 1/3) [217], systems which evolve according to hydrodynamic equations (with n = 1/2) [218], and also data from molecular dynamics of a microscopic off-lattice model (with n= 1/2) [155]. The data collapse has not been quite as good in Langevin simulations which include thermal noise [218]. 

Results concerning thermodynamic properties which we have obtained from molecular dynamics simulation with these potentials and the transition temperatures of the martensite - austenite transition we found, have been published elsewhere. ... 

This section provides an alternative measurement for a material parameter the one in the ensemble averaged sense to pave the way for usage of continuum theory from a hope that useful engineering predictions can be made. More details can be found in Ref. [15]. In fact, macroscopic flow equations developed from molecular dynamics simulations agree well with the continuum mechanics prediction (for instance. Ref. [16]). 

Methods for simulating restrained x>ray refinement data from molecular dynamics trajectories. 

FIG. 23 Surface pressure vs. area/molecule isotherms at 300 K from molecular dynamics simulations of Karaborni et al. (Refs. 362-365). All are for hydrocarbon chains with carboxylate-like head groups, (a) (filled squares) A 20-carbon chain, (b) (filled circles) A 16-carbon chain with a square simulation box the curve is shifted 5 A to the right, (c) (open squares) A 16-carbon chain with a nonsquare box with dimensions in the ratio xly = (3/4) to fit a hexagonal lattice the curve is shifted 5 A to the right. (Reproduced with permission from Ref. 365. Copyright 1993 American Chemical Society.)... 

FIG. 26 Optimized structure of a water monolayer on mica obtained from molecular dynamic simulations by Odelius et al. The water molecules and the first layer of sihca tetrahedra of the mica substrate are shown in a side view in the top. K ions are the large dark balls. The bottom drawing shows a top view of the water. Oxygen atoms are dark, hydrogen atoms light. Notice the ordered icelike structure and the absence of free OH groups. All the H atoms in the water are involved in a hydrogen bond to another water molecule or to the mica substrate. (From Ref. 73.)... 

There is difficulty in defining the absolute mobilities of the constituent ions in a molten salt, since it does not contain fixed particles that could serve as a coordinate reference. Experimental means for measuring external transport numbers or external mobilities are scarce, although the zone electromigration method (layer method) and the improved Hittorf method may be used. In addition, external mobilities in molten salts cannot be easily calculated, even from molecular dynamics simulation. 

The self-exchange velocity (SEV), which can be calculated from molecular dynamics simulation, has reproduced the Chemla effect. Fur-... 

Further progress in understanding membrane instability and nonlocality requires development of microscopic theory and modeling. Analysis of membrane thickness fluctuations derived from molecular dynamics simulations can serve such a purpose. A possible difficulty with such analysis must be mentioned. In a natural environment isolated membranes assume a stressless state. However, MD modeling requires imposition of special boundary conditions corresponding to a stressed state of the membrane (see Refs. 84,87,112). This stress can interfere with the fluctuations of membrane shape and thickness, an effect that must be accounted for in analyzing data extracted from computer experiments. 

Monte Carlo simulation shows [8] that at a given instance the interface is rough on a molecular scale (see Fig. 2) this agrees well with results from molecular-dynamics studies performed with more realistic models [2,3]. When the particle densities are averaged parallel to the interface, i.e., over n and m, and over time, one obtains one-dimensional particle profiles/](/) and/2(l) = 1 — /](/) for the two solvents Si and S2, which are conveniently normalized to unity for a lattice that is completely filled with one species. Figure 3 shows two examples for such profiles. Note that the two solvents are to some extent soluble in each other, so that there is always a finite concentration of solvent 1 in the phase... 

The flat interface model employed by Marcus does not seem to be in agreement with the rough picture obtained from molecular dynamics simulations [19,21,64-66]. Benjamin examined the main assumptions of work terms [Eq. (19)] and the reorganization energy [Eq. (18)] by MD simulations of the water-DCE junction [8,19]. It was found that the electric field induced by both liquids underestimates the effect of water molecules and overestimates the effect of DCE molecules in the case of the continuum approach. However, the total field as a function of the charge of the reactants is consistent in both analyses. In conclusion, the continuum model remains as a good approximation despite the crude description of the liquid-liquid boundary. 

Fig. 5.5. Illustration of the coarse-graining procedure for a united atom chain. The chain is a segment of PE at 509 K from molecular dynamics simulations with the united atom model [Eqs. (5.7)—(5.11)]. One coarse-grained bond represents the end-to-end distance of n = 5 consecutive united atom bonds. From [32]...

Ding YB, Bernardo DN, Kroghjespersen K, Levy RM (1995) Solvation free-energies of small amides and amines from molecular-dynamics free-energy perturbation simulations using pairwise additive and many-body polarizable potentials. J Phys Chem 99(29) 11575—11583... 

Patel S, Mackerell AD, Brooks CL (2004) CHARMM fluctuating charge force field for proteins II -Protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model. J Comput Chem 25(12) 1504-1514... 

Colombo, G., Roccatano, D., and Mark, A. E. (2002). Folding and stability of the three-stranded beta-sheet peptide betanova Insights from molecular dynamics simulations. Proteins Strud. Fund. Genet. 46, 380—392. 

Peter, C. Oostenbrink, C. van Dorp, A. van Gunsteren, W. F., Estimating entropies from molecular dynamics simulations, J. Chem. Phys. 2004,120, 2652-2661... 

Simonson, T. Perahia, D., Microscopic dielectric properties of cytochrome c from molecular dynamics simulations in aqueous solution, J. Am. Chem. Soc. 1995, 117, 7987-8000... 

Hermans, J. Pathiaseril, A. Anderson, A., Excess free-energy of liquids from molecular-dynamics simulations — application to water models, J. Am. Chem. Soc. 1988,110, 5982-5986. 

Pan, Y. P. Daggett, V., Direct comparison of experimental and calculated folding free energies for hydrophobic deletion mutants of chymotrypsin inhibitor. 2 Free energy perturbation calculations using transition and denatured states from molecular dynamics simulations of unfolding, Biochemistry 2001,40, 2723-2731. 

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