Empirical potential structure refinement models

In all these examples, the importance of good simulation and modeling cannot be stressed enough. A variety of methods have been used in this field to simulate the data in the cases studies described above. Blander et al. [4], for example, used a semi-empirical molecular orbital method, MNDO, to calculate the geometries of the free haloaluminate ions and used these as a basis for the modeling of the data by the RPSU model [12]. Badyal et al. [6] used reverse Monte Carlo simulations, whereas Bowron et al. [11] simulated the neutron data from [MMIM]C1 with the Empirical Potential Structure Refinement (EPSR) model [13]. 

Using Monte Carlo, the model is then relaxed using the new potential, resulting in a new calculated g r). The process is then iterated until it reaches convergence. This approach, known as Empirical Potential Structure Refinement (EPSR) has proved very powerful in the study of complex liquids, and of the solvation states of molecules in solution. It is particularly successful when it has as target functions a number (though not necessarily the complete set) of DPDFs from the system in question. 

In order to extract microscopic quantities such as spatial probabilities and RDFs from collected differential cross scattering data, analysis is typically performed following reverse Monte Carlo (RMC) or empirical potential structure refinement (EPSR) procedures [7]. The latter procedure can be viewed as a Monte Carlo simulation of system utilising a model potential similar to a classical molecular mechanics force field. This model potential is modified in order to bring the total structure factor calculated from the model system as close as possible to the ejq)erimental data. From configurations generated with this refined potential, standard quantities (such as RDFs) may be calculated. 

It has also been demonstrated that molecular dynamics can play a useful role in the refinement of protein structures against X-ray data.420a By adding an effective potential that represents the difference between the observed and calculated structure factors (Eq. 99) to the standard empirical potential function (Eq. 6), simulated annealing4206 can be used to automatically refine a crude X-ray structure. In this way much of the manual rebuilding of the model structure, that is, the most time-consuming part of standard structure refinement,421 can be avoided. 

More than 30 years ago Warshel proposed, on the basis of semiempirical simulations, an isomerization mechanism that could explain how this process can occur in the restricted space of the Rh binding pocket (Warshel 1976). Since two adjacent double bonds were found to isomerize simultaneously the mechanism reveal a so-called bicycle pedal motion. Due to the concerted rotation of two double bonds in opposite directions the overall conformational change is minimized and hence this mechanism was found to be space-saving. The empirical valence bond (EVB) method (Warshel and Levitt 1976) was used to compute the excited state potential energy surface of the chromophore during a trajectory calculation where the steric effects of the protein matrix were modeled by specific restraints on the retinal atoms. Since then, Warshel and his coworkers have improved the model employing better structural data and new computational developments (Warshel and Barboy 1982 Warshel and Chu 2001 Warshel et al. 1991). The main refinement of the bicycle pedal mechanism was that the simultaneous rotation of the adjacent double bonds is aborted at a twist of 40° and leads to the isomerization of only one bond (Warshel and Barboy 1982). 

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