Typically the optimal value of the dielectric surface is obtained via benchmarking test against experimental data 20- 24. Indeed once the dielectric function distribution is known, the molecular surface can then be defined as surface with a particular value of the dielectric “constant” 16, 18, 19. In the past, the main motivation for introducing Gaussian-based dielectric function was to smooth the boundary solute-water 14, 16, 17.
#Draw potential energy surfaces using gaussian software how to
The technical question is where to draw the border between solute and the water and the conceptual question is how to treat the solute molecule in absence of the water surrounding.
![draw potential energy surfaces using gaussian software draw potential energy surfaces using gaussian software](https://ars.els-cdn.com/content/image/1-s2.0-S2590141919300315-gr1.jpg)
The question has two components: conceptual and technical.
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While such a model sounds physically more reasonable than the two-dielectric model, it poses the question of how to model the solvation energy. Even more, the protein surface and protein interior are modeled as an inhomogeneous dielectric medium 15. In this implementation, the solute and the water phase are treated on the same footing and there is no sharp dielectric border between them. Following the original work of Nicholls and coworkers 14, recently we reported a smooth Gaussian-based dielectric function implementation in DelPhi 15. Compared to explicit models, implicit models are more efficient, therefore be able to handle much larger systems 10, 13, however, it comes with the price of losing some atomic information and ambiguity of how to describe the dielectric properties of the system, the solute and the water phases.Ī possible solution addressing the above mentioned deficiencies of implicit methods is to develop dielectric function that mimics some of the missing atomic effects. Explicit models treat water as individual molecules in contrast, implicit models average the effect of water phase as continuum media 7- 12. The methods can be grouped into two categories, explicit models and implicit models 6.
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However, these calculations cannot be done analytically for irregularly shaped objects and numerical methods must be applied. Lastly, the possibility of the solute to have local dielectric constant larger than of a bulk water is investigated in a benchmarking test against experimentally determined set of pKa's and it is speculated that side chain rearrangements could result in local dielectric constant larger than 80.Ĭalculations of electrostatic potential and energy of macromolecules are essential to understand the mechanism of biological processes 1- 5. Furthermore, the results are compared with the standard two-media model and it is demonstrated that on average, the standard method overestimates the magnitude of the polar solvation energy by a factor 2.5. The smooth Gaussian-based dielectric function is implemented in the DelPhi finite-difference program, and therefore the sensitivity of the results with respect to the grid parameters is investigated, and it is shown that the calculated polar solvation energy is almost grid independent. Here we examine various aspects of the modeling of polar solvation energy in such inhomogeneous systems in terms of the solute-water boundary and the inhomogeneity of the solute in the absence of water surrounding. Recently we reported a new development, a smooth Gaussian-based dielectric function which treats the entire system, the solute and the water phase, as inhomogeneous dielectric medium (J Chem Theory Comput. However, such an approach treats the biomolecule-water interface as a sharp dielectric border between two homogeneous dielectric media and does not account for inhomogeneous dielectric properties of the macromolecule as well.
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Traditional implicit methods for modeling electrostatics in biomolecules use a two-dielectric approach: a biomolecule is assigned low dielectric constant while the water phase is considered as a high dielectric constant medium.