Experimental procedure molecular dynamics simulation

P. Zumbusch, W. Kulcke, G. Brunner. Use of alternating electric fields as antifouling strategy in ultrafiltration of biological suspensions. Introduction of a new experimental procedure for crossflow filtration. J Memb Sci 142-.15 (1998). R. L. Rowley, T. D. Shupe, M. W. Schuck. A direct method for determination of chemical potential with molecular dynamics simulations. 1. Pure components. Mol Phys 52 841, 1994. 

DD can be monitored by a variety of experimental techniques. They involve thermodynamic, dilatometric, and spectroscopic procedures. Molecular dynamics (MD) simulations also become applicable to self-assembled systems to some extent see the review in Ref. 2. Spectroscopic methods provide us with molecular parameters, as compared with thermodynamic ones on the macroscopic level. The fluorescence probing method is very sensitive (pM to nM M = moldm ) and informs us of the molecular environment around the probes. However, fluorescent molecules are a kind of drug and the membrane... 

Molecular dynamics (MD) simulations are a class of molecular mechanics calculation which directly model the motions of molecular systems, often providing considerable information which cannot be obtained by any other technique, theoretical or experimental. MD simulations have only recently been applied to problems of carbohydrate conformation and motions, but it is likely that this technique will be widely used for modeling carbohydrates in the future. This paper introduces the basic techniques of MD simulations and illustrates the types of information which can be gained from such simulations by discussing the results of several simulations of sugars. The importance of solvation in carbohydrate systems will also be discussed, and procedures for including solvation in molecular dynamics simulations will be introduced and again illustrated from carbohydrate studies. 

Empirical potentials are only applicable with certainty over the range of interatomic distances used in the fitting procedure, which can lead to problems if the potential is used in a calculation that accesses distances outside this range. This can happen in defect calculations, molecular dynamics simulations or lattice dynamics calculations at high temperature and/or pressure. In addition experimental data is required and thus direct calculation is the only method available when there is no relevant experimental data. It may, of course, be possible to take potentials derived for one system and transfer them to another. This method has been successful with potentials derived for binary oxides (Lewis and Catlow, 1985 Bush et al., 1994) being transferred to ternary systems (Lewis and Catlow, 1985 Price et al., 1987 Cormack et al., 1988 Purton and Catlow, 1990 Bush et al., 1994). 

Figure 4.5 From the result of a molecular dynamics simulation, the x-ray scattering intensity was calculated, and from it (r), given in the broken curve, was derived, by using exactly the same procedure as was used to treat experimental x-ray scattering intensities. The solid curve is the C-C atom pair distribution function calculated directly from the simulation result. (From Mondello et al.13)...

Perhaps a sensible procedure is to consider an approach which incorporates both interatomic potentials (classical forces) and fully quantum mechanical methods. One can compute the properties of smaller systems with quantum mechanical approaches and establish the accuracy, or inaccuracy, of interatomic potentials. For example, some elastic anomalies have been reported for a-cristobalite. These elastic anomalies indicated the presence of a negative Poisson ratio in this crystalline form of silica. With the use of interatomic potentials, it is a trivial matter to compute these properties. If the anomalies are confirmed via such calculations, it is likely that the experimental measurements are accurate, and more computationally intense calculations with quantum forces are merited. Another useful role of interatomic potentials is to perform molecular dynamics simulations, e.g., to examine the amorphization of quartz under pressure. One can easily compute the free energy of large systems as a function of both temperature and pressure via interatomic potentials. Sueh calculations can be useful as guides if interpreted in a judicious fashion. 

As it is assured that the conformations generated with the Marcelja field are consistent with experimental data, the procedure employing the overlay method and the continuous Marcelja model is a powerful tool for preparation of the initial coordinates of biomembrane simulations. By applying a short molecular dynamics simulation to the initial coordinates prepared by this procedure, the long equilibration time necessary to obtain results consistent with experiments is well circumvented. 

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