Interpretation of simulated

E. I. Ette, A. W. Kelman, C. W. Howie, and B. Whiting, Interpretation of simulation studies for efficient estimation of population pharmacokinetic parameters. Ann Pharma-cother 27 1034-1039 (1993) and Correction 27 1548 (1993). 

Finally the decision about the best implementation solution depends on available resources at the broad sense an integrated model tends to expand to a huge, not transparent formation with extremely long development times (Schmitz et al. 2003). Problems of data availability to set a great number of model parameters will arise. Very long simulation time and an adequate interpretation of simulation results as well as a non trivial validation of a model are the unavoidable challenges connected with this approach. 

One of the difficulties in theoretical studies of the hydrodynamic effects on vesicle dynamics is the no-slip boundary condition for the embedding fluid on the vesicle surface, which changes its shape dynamically under the effect of flow and curvature forces. In early studies, a fluid vesicle was therefore modeled as an ellipsoid with fixed shape [194]. This simplified model is still very useful as a reference for the interpretation of simulation results. 

BE 1313 Vibration interpretation using simulations and the intelligence of networks Mr. Ian Jennings MONmON Ltd... 

That simulation study [49] aimed at a microscopic interpretation of single molecule atomic force microscope (AFM) experiments [50], in which unbinding forces between individual protein-ligand complexes have been m( asured... 

To enable an atomic interpretation of the AFM experiments, we have developed a molecular dynamics technique to simulate these experiments [49], Prom such force simulations rupture models at atomic resolution were derived and checked by comparisons of the computed rupture forces with the experimental ones. In order to facilitate such checks, the simulations have been set up to resemble the AFM experiment in as many details as possible (Fig. 4, bottom) the protein-ligand complex was simulated in atomic detail starting from the crystal structure, water solvent was included within the simulation system to account for solvation effects, the protein was held in place by keeping its center of mass fixed (so that internal motions were not hindered), the cantilever was simulated by use of a harmonic spring potential and, finally, the simulated cantilever was connected to the particular atom of the ligand, to which in the AFM experiment the linker molecule was connected. 

How can we apply molecular dynamics simulations practically. This section gives a brief outline of a typical MD scenario. Imagine that you are interested in the response of a protein to changes in the amino add sequence, i.e., to point mutations. In this case, it is appropriate to divide the analysis into a static and a dynamic part. What we need first is a reference system, because it is advisable to base the interpretation of the calculated data on changes compared with other simulations. By taking this relative point of view, one hopes that possible errors introduced due to the assumptions and simplifications within the potential energy function may cancel out. All kinds of simulations, analyses, etc., should always be carried out for the reference and the model systems, applying the same simulation protocols. 

Molecular dynamics simulations provide information about the motion of molecules, which facilitates the interpretation of experimental results and allows the statistically meaningful sampling of (thermodynamic) data. 

One of the major uses of molecular simulation is to provide useful theoretical interpretation of experimental data. Before the advent of simulation this had to be done by directly comparing experiment with analytical (mathematical) models. The analytical approach has the advantage of simplicity, in that the models are derived from first principles with only a few, if any, adjustable parameters. However, the chemical complexity of biological systems often precludes the direct application of meaningful analytical models or leads to the situation where more than one model can be invoked to explain the same experimental data. 

A dynamic transition in the internal motions of proteins is seen with increasing temperamre [22]. The basic elements of this transition are reproduced by MD simulation [23]. As the temperature is increased, a transition from harmonic to anharmonic motion is seen, evidenced by a rapid increase in the atomic mean-square displacements. Comparison of simulation with quasielastic neutron scattering experiment has led to an interpretation of the dynamics involved in terms of rigid-body motions of the side chain atoms, in a way analogous to that shown above for the X-ray diffuse scattering [24]. 

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 methodological advances just presented have brought the field of nucleic acid force field calculations to a point where results from the calculations can be used with reasonable confidence to aid in the interpretation of experimental data as well as to be used for scientific investigations that are not accessible to experiment. Accordingly, a number of studies based on MD simulations, as well as other methods, have been undertaken to study a wide array of biologically relevant events associated with DNA. A brief overview of some of these efforts follows. 

Molecular dynamics simulations have also been used to interpret phase behavior of DNA as a function of temperature. From a series of simulations on a fully solvated DNA hex-amer duplex at temperatures ranging from 20 to 340 K, a glass transition was observed at 220-230 K in the dynamics of the DNA, as reflected in the RMS positional fluctuations of all the DNA atoms [88]. The effect was correlated with the number of hydrogen bonds between DNA and solvent, which had its maximum at the glass transition. Similar transitions have also been found in proteins. 

Electric field measurement at the boundary of a metal container filled with charged material. Examples include pipelines and storage vessels. The electric field can be used to calculate charge density (3-5.1). Eield meters can also be lowered into containers such as silos to determine the local fields and polarities. Quantitative interpretation of the reading requires correction for field intensification and is sometimes accomplished using computer simulations. 

The interpretation of the results and the quality of the design from the pulsation study, whether performed on the analog simulator or with digital computer simulation, depends quite heavily on the experience and skill of the analyst performing the study, A purchaser of a compressor system who may be a novice at this type of analysis should give serious consideration to using the services of a competent consultant. 

A final comment on the interpretation of stochastic simulations We are so accustomed to writing continuous functions—differential and integrated rate equations, commonly called deterministic rate equations—that our first impulse on viewing these stochastic calculations is to interpret them as approximations to the familiar continuous functions. However, we have got this the wrong way around. On a molecular level, events are discrete, not continuous. The continuous functions work so well for us only because we do experiments on veiy large numbers of molecules (typically 10 -10 ). If we could experiment with very much smaller numbers of molecules, we would find that it is the continuous functions that are approximations to the stochastic results. Gillespie has developed the stochastic theory of chemical kinetics without dependence on the deterministic rate equations. 

A kinetic model which accounts for a multiplicity of active centres on supported catalysts has recently been developed. Computer simulations have been used to mechanistically validate the model and examine the effects on Its parameters by varying the nature of the distrlbultons, the order of deactivation, and the number of site types. The model adequately represents both first and second order deactivating polymerizations. Simulation results have been used to assist the interpretation of experimental results for the MgCl /EB/TlCl /TEA catalyst suggesting that... 

Computer simulations have been useful for validating a kinetic model that Is not easily tested. The model was equally capable of describing multi-site polymerizations which can undergo either first or second order deactivation. The model parameters provided reasonably accurate kinetic information about the Initial active site distribution. Simulation results were also used as aids for Interpretation of experimental data with encouraging results. 

The use of computer simulations to study internal motions and thermodynamic properties is receiving increased attention. One important use of the method is to provide a more fundamental understanding of the molecular information contained in various kinds of experiments on these complex systems. In the first part of this paper we review recent work in our laboratory concerned with the use of computer simulations for the interpretation of experimental probes of molecular structure and dynamics of proteins and nucleic acids. The interplay between computer simulations and three experimental techniques is emphasized (1) nuclear magnetic resonance relaxation spectroscopy, (2) refinement of macro-molecular x-ray structures, and (3) vibrational spectroscopy. The treatment of solvent effects in biopolymer simulations is a difficult problem. It is not possible to study systematically the effect of solvent conditions, e.g. added salt concentration, on biopolymer properties by means of simulations alone. In the last part of the paper we review a more analytical approach we have developed to study polyelectrolyte properties of solvated biopolymers. The results are compared with computer simulations. 

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