Computational chemistry electrostatic interactions

Pratt L R and Hummer G (eds) 1999 Simulation and theory of electrostatic interactions in solution computational chemistry, biophysics and aqueous solutions AlP Conf. Proc. (Sante Fe, NM, 1999) vol 492 (New York American Institute of Physics)... 

Halgren T A 1996b. Merck Molecular Force Field II MMEF94 van der Waals and Electrostatic Parameters for Intermolecular Interactions. Journal of Computational Chemistry 17 520-552. 

Paschual-Ahuir J L, E Silla, J Tomasi and R Bonaccorsi 1987. Electrostatic Interaction of a Solute with a Continuum. Improved Description of the Cavity and of the Surface Cavity Bound Charge Distribution. Journal of Computational Chemistry 8 778-787. 

Pratt, L. R., and Rempe, S. B. (1999). Quasi-chemical theory and implicit solvent models for simulations. In Simulation and Theory of Electrostatic Interactions in Solution. Computational Chemistry, Biophysics, and Aqueous Solutions (L. R. Pratt and G. Hummer, eds.), vol. 492 of AIP Conference Proceedings, pp. 172-201. American Institute of Physics, Melville, NY... 

As a spherical system increases in size, its volume grows as the cube of the radius while its surface grows as the square. Thus, in a truly macroscopic system, surface effects may play little role in the chemistry under study (there are, of course, exceptions to this). However, in a typical simulation, computational resources inevitably constrain the size of the system to be so small that surface effects may dominate tlie system properties. Put more succinctly, the modeling of a cluster may not tell one much about tlie behavior of a macroscopic system. This is particularly true when electrostatic interactions are important, since the energy associated witli tliese interactions has an r dependence. 

As we learn about physical chemistry, we extend that understanding to new systems of interest, but the transition from simple molecules to more complicated systems is limited by our human abilities. We can imagine a butane molecule and imagine both how and why different conformers are preferred. When we tackle pentane or combinations of functional groups, however, it becomes difficult to simultaneously consider the relative effects of electrostatics, steric interactions, and bulk properties, such as solubilities. Fortunately, we can construct models in software that allow us to properly treat all of these interactions. The scientific field of molecular modeling or. more generally, computational chemistry is the practice of simulation of molecular systems with sufficient detail to address a question of interest. 

The methods today more in use in computational chemistry belong to the ASC, MPE, GB and FD families. For every type of method there are now QM versions, many thus far limited to infinite isotropic distributions. Several of those methods may introduce, via the effective Hamiltonian or with less formal procedures, solute-solvent interaction effects of non electrostatic origin. 

The analysis techniques used were FTIR to study this effect and the optional use of theoretical calculations to justify the obtained results by means of computational chemistry tools. Using QSAR properties, we can obtain an estimate of the activity of a chemical from its molecular structure only. The QSARs have been successfully applied to predict soil sorption coefficients of non-polar and nonionizable organic compounds, including many pesticides. Sorption of organic chemicals in soils or sediments is usually described by sorption coefficients. The molecular electrostatic potential (MESP) was calculated using the AMBER/AM 1 method. These methods give information about the proper region by which compounds have intermolecular interactions between their units. 

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