Force field based simulation approaches

More detailed aspects of protein function can be obtained also by force-field based approaches. Whereas protein function requires protein dynamics, no experimental technique can observe it directly on an atomic scale, and motions have to be simulated by molecular dynamics (MD) simulations. Also free energy differences (e.g. between binding energies of different protein ligands) can be characterised by MD simulations. Molecular mechanics or molecular dynamics based approaches are also necessary for homology modelling and for structure refinement in X-ray crystallography and NMR structure determination. 

Note that can be chosen to be distance dependent. A common approach is to assume that yi is a constant for a distance smaller than a cut-off radius fcut.DPD and to set y,y = 0 otherwise. As calculating random numbers may be a task of relatively significant computational effort in force-field-based MD simulations, it may be sensible to make rcutjDPD smaller than the cut-off radius... 

Many problems in force field investigations arise from the calculation of Coulomb interactions with fixed charges, thereby neglecting possible mutual polarization. With that obvious drawback in mind, Ulrich Sternberg developed the COSMOS (Computer Simulation of Molecular Structures) force field [30], which extends a classical molecular mechanics force field by serai-empirical charge calculation based on bond polarization theory [31, 32]. This approach has the advantage that the atomic charges depend on the three-dimensional structure of the molecule. Parts of the functional form of COSMOS were taken from the PIMM force field of Lindner et al., which combines self-consistent field theory for r-orbitals ( nr-SCF) with molecular mechanics [33, 34]. 

In the first chapter several traditional types of physical models were discussed. These models rely on the physical concepts of energies and forces to guide the actions of molecules or other species, and are customarily expressed mathematically in terms of coupled sets of ordinary or partial differential equations. Most traditional models are deterministic in nature— that is, the results of simulations based on these models are completely determined by the force fields employed and the initial conditions of the simulations. In this chapter a very different approach is introduced, one in which the behaviors of the species under investigation are governed not by forces and energies, but by rules. The rules, as we shall see, can be either deterministic or probabilistic, the latter leading to important new insights and possibilities. This new approach relies on the use of cellular automata. 

As electric fields and potential of molecules can be generated upon distributed p, the second order energies schemes of the SIBFA approach can be directly fueled by the density fitted coefficients. To conclude, an important asset of the GEM approach is the possibility of generating a general framework to perform Periodic Boundary Conditions (PBC) simulations. Indeed, such process can be used for second generation APMM such as SIBFA since PBC methodology has been shown to be a key issue in polarizable molecular dynamics with the efficient PBC implementation [60] of the multipole based AMOEBA force field [61]. 

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