Simulation 35 pages

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Carson, J. S. II. Introduction to modeling and simulation. In Proceedings of the 36th conference on Winter simulation, pages 9-16, 2004. 

Robinson, S. Conceptual modeling for simulation issues and research requirements. In Proceedings of the 38th conference on Winter simulation, pages 792-800, 2006. 

Sargent, R. G. Verification, validation, and accreditation verification, validation, and accreditation of simulation models. In Proceedings of the 32nd conference on Winter simulation, pages 50-59, 2000. 

S. Junco. Real- and complex-power bond graph modeling of the induction motor. In Proceeding of the International Conference on Bond Graph Modeling and Simulation, pages 323-328, San Francisco, CA, 1999. 

R. W. Pastor. Techniques and applications of Langevin dynamics simulations. In G. R. Luckhurst and C. A. Veracini, editors. The Molecular Dynamics of Liquid Crystals, pages 85-138. Kluwer Academic, Dordrecht, The Netherlands, 1994. 

G. Ramachandran and T. Schlick. Beyond optimization Simulating the dynamics of supercoiled DNA by a macroscopic model. In P. M. Pardalos, D. Shal-loway, and G. Xue, editors. Global Minimization of Nonconvex Energy Functions Molecular Conformation and Protein Folding, volume 23 of DIM ACS Series in Discrete Mathematics and Theoretical Computer Science, pages 215-231, Providence, Rhode Island, 1996. American Mathematical Society. 

E. Barth, M. Mandziuk, and T. Schlick. A separating framework for increasing the timestep in molecular dynamics. In W. F. van Gunsteren, P. K. Weiner, and A. J. Wilkinson, editors. Computer Simulation of Biomolecular Systems Theoretical and Experimental Applications, volume III, chapter 4, pages 97-121. ESCOM, Leiden, The Netherlands, 1997. 

In general, Laiigeviii dynamics sim illation s run much the same as nioleciilar dynamics simulations. There are differences due Lo the presence of additional forces. Most of the earlier discussions (see pages 69-yO an d p. 3 10-327 of this man ual) on simulation parameters and strategies for molecular dyn amics also apply to Lan gevin dynamics exceptions and additional con sideraiion s are noted below. 

You can use any ah initio SCT calciilalion and all Ihe semi-empiri-cal methods, except Extended Hiickel. for molecular dynamics simulations. The procedures and considerations are similar for sim u lation s using molecular mech anics m eihods (see Molecular Dynamics" on page 69). 

In light of the differences between a Morse and a harmonic potential, why do force fields use the harmonic potential First, the harmonic potential is faster to compute and easier to parameterize than the Morse function. The two functions are similar at the potential minimum, so they provide similar values for equilibrium structures. As computer resources expand and as simulations of thermal motion (See Molecular Dynamics , page 69) become more popular, the Morse function may be used more often. 

To reach equilibrium temperature quickly before starting the equilibration phase of a simulation (see Equilibration and Data Collection on page 74). 

If the Bath relaxation constant, t, is greater than O.I ps, you should be able to calculate dynamic properties, like time correlation functions and diffusion constants, from data in the SNP and/or CSV files (see Collecting Averages from Simulations on page 85). 

After initial heating and equilibration, the trajectory may be stable for thousands of time points. During this phase of a simulation, you can collect data. Snapshots and CSV files (see Collecting Averages from Simulations on page 85) store conformational and numeric data that you can later use in thermodynamic calculations. 

For a constant temperature simulation, a molecular system is coupled to a heat bath via a Bath relaxation constant (see Temperature Control on page 72). When setting this constant, remember that a small number results in tight coupling and holds the temperature closer to the chosen temperature. A larger number corresponds to weaker coupling, allowing more fluctuation in temper-... 

High temperature simulations require special consideration in choosing the sampling interval (see Step size on page 89). 

Often you need to add solvent molecules to a solute before running a molecular dynamics simulation (see also Solvation and Periodic Boundary Conditions on page 62). In HyperChem, choose Periodic Box on the Setup menu to enclose a solute in a periodic box filled appropriately with TIP3P models of water molecules. 

The temperature of a simulation depends on your objectives. You might use high temperatures to search for additional conformations of a molecule (see Quenched Dynamics on page 78). Room temperature simulations generally provide dynamic properties of molecules such as proteins, peptides, and small drug molecules. Low temperatures (<250 K) often promote a molecule to a lower energy conformation than you could obtain by geometry optimization alone. 

To integrate the Langevin equation, HyperChem uses the method of M.P. Allen and D.J. Tildesley, Computer Simulation of Liquids, Clarendon Press, Oxford, 1987 Ch.9, page 261 ... 

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