Molecular dynamics simulation strategy

D. Brown, J. H. R. Clarke, M. Okuda and T. Yamazaki, A domain decomposition strategy for molecular dynamics simulations on distributed memory machines . Comp. Phys. Comm., Vol 74, 67-80, 1993. 

Molecular dynamics simulations can overcome energy barriers and provide information about the time-dependent motion of molecu lar system s. You can use various strategies to set up an d run a molecular dynamics simulation, depending on your objective. Th IS section defines man y of these strategies and discusses specific consideration s in settingup a simulation. 

In general, Langevin dynamics simulations run much the same as molecular dynamics simulations. There are differences due to the presence of additional forces. Most of the earlier discussions (see pages 69-90 and p. 310-327 of this manual) on simulation parameters and strategies for molecular dynamics also apply to Langevin dynamics exceptions and additional considerations are noted below. 

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. 

The strategy in a molecular dynamics simulation is conceptually fairly simple. The first step is to consider a set of molecules. Then it is necessary to choose initial positions of all atoms, such that they do not physically overlap, and that all bonds between the atoms have a reasonable length. Subsequently, it is necessary to specify the initial velocities of all the atoms. The velocities must preferably be consistent with the temperature in the system. Finally, and most importantly, it is necessary to define the force-field parameters. In effect the force field defines the potential energy of each atom. This value is a complicated sum of many contributions that can be computed when the distances of a given atom to all other atoms in the system are known. In the simulation, the spatial evolution as well as the velocity evolution of all molecules is found by solving the classical Newton equations of mechanics. The basic outcome of the simulation comprises the coordinates and velocities of all atoms as a function of the time. Thus, structural information, such as lipid conformations or membrane thickness, is readily available. Thermodynamic information is more expensive to obtain, but in principle this can be extracted from a long simulation trajectory. 

The development of multiscale simulation techniques that involve the atomistic modeling of various structures and processes still remains at its early stage. There are many problems to be solved associated with more accurate and detailed description of these structures and processes. These problems include the development of efficient and fast methods for quantum calculations at the atomistic level, the development of transferable interatomic potentials (especially, reactive potentials) for molecular dynamic simulations, and the development of strategies for the application of multiscale simulation methods to other important processes and materials (optical, magnetic, sensing, etc.). 

We think that judicious application of molecular simulation tools for the calculation of thermophysical and mechanical properties is a viable strategy for obtaining some of the information required as input to mesoscale equations of state. Given a validated potential-energy surface, simulations can serve as a complement to experimental data by extending intervals in pressure and temperature for which information is available. Furthermore, in many cases, simulations provide the only realistic means to obtain key properties e.g., for explosives that decompose upon melting, measurement of liquid-state properties is extremely difficult, if not impossible, due to extremely fast reaction rates, which nevertheless correspond to time scales that must be resolved in mesoscale simulations of explosive shock initiation. By contrast, molecular dynamics simulations can provide converged values for those properties on time scales below the chemical reaction induction times. Finally,... 

Biochemistry and Molecular Biophysics, Vol. I, pp. 39-58, D. L. Beveridge and R. Lavery, Eds., Adenine Press, Guilderland, New York, 1991. Search Strategies, Minimization Algorithms, and Molecular Dynamics Simulations for Exploring Conformational Spaces of Nucleic Acids. 

This review will present an overview of current molecular mechanics techniques and discuss some of their limitations. We will then look at knowledge-based protein prediction strategies and examine the incorporation of such empirical rules into refinement methodologies for model protein systems. More comprehensive reviews of molecular dynamics simulations, knowledge-based protein modeling, and protein folding simulations are available. - " ... 

The next chapter, by Kvamme and Kuznetsova, presents a theoretical approach to molecular-level processes taking place at the W/0 interface. The chapter comprises state-of-the-art concepts, experimental results, and atomic-level computer simulations of processes de-terming the stability of the dispersions. Parallels are drawn to lipid bilayers. A strategy suitable for molecular dynamics simulation of water-in-crude-oil emulsions is presented, with most of its constituents elements proved by computer simulations of less complex systems. 

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