Solvation explicit solvent models

In between the implicit and explicit solvent models, there are mixed models, such as the solvation shell approximation.67-69 This model describes explicitly only the first solvation shell molecules and treats as implicit the solvent region beyond the first solvation shell. Such treatment both provides the information about the solvent structure near the solute and allows for faster computation. 

Along with deciding whether to use implicit or implicit-explicit solvent models, a specific level of theory and basis set must be used for the calculation of the change in free energy of solvation. Similar to the gas-phase free energy, there are a variety of methods and it can be difficult to determine what combination is the most accurate. Further discussion can be found in Section 4. 

Table 12.1 Solvation energies calculated with the differential geometry nonpolar solvation model for a set of 11 alkanes in comparison with an explicit solvent model [154]...

Generally, methods for calculating can be represented by two main categories implicit or explicit solvent models [38, 47-58]. The main difference between these two categories is the representation of the solvent strueture around the solute. Implicit Continuum Solvent Models (ICSMs) treat the solvent around the solvated molecule as a structureless polarizable medium characterized by a dielectric constant, e [49, 59,60]. In turn, in explicit solvent models (ESMs) both solute and solvent molecules in the solute-solvent systems are described at the atomistic level. There are two... 

In many cases explicit solvent models are more useful than implicit models. Examples include simulations in which a detailed picture of solvent structure is one of the goals and cases for which there is evidence that a particular structural feature of the solvent is playing a key role (e.g., a specific water-macromolecule hydrogen bond), although explicit representation of some water molecules combined with implicit solvation may suffice. MD simulations used to study kinetic, or time-dependence, properties of macromolecular processes, comprise another important example. 

As shown above the size of the explicit water simulations can be rather large, even for a medium sized protein as in the case of the sea raven antifreeze protein (113 amino acid residues and 5391 water). Simulations of that size can require a large amount of computer memory and disk space. If one is interested in the stability of a particular antifreeze protein or in general any protein and not concerned with the protein-solvent interactions, then an alternative method is available. In this case the simulation of a protein in which the explicit waters are represent by a structureless continuum. In this continuum picture the solvent is represented by a dielectric constant. This replacement of the explicit solvent model by a continuum is due to Bom and was initially used to calculate the solvation free energy of ions. For complex systems like proteins one uses the Poisson-Boltzmann equation to solve the continuum electrostatic problem. In... 

Operating fuel cell involves solvent environment, and it is important to study water formation reaction under solvent conditions to understand the solvation effects on overall reaction kinetics. Adding water molecules explicitly or entire water bilayer to unit cells of simulating catalyst is considered as explicit solvent model. This method, however, does not resemble fully saturated system, and water molecules are introduced during the simulation that directly participates in the ORR [148]. Poisson-Boltzmann implicit solvent model is a method to resemble solvent as a continuum rather than individual molecules in explicit models [160,162]. This method is computationally inexhaustive and accurate enough to reproduce reliable results for the atomistic energy calculations. 

It is often the case that the solvent acts as a bulk medium, which affects the solute mainly by its dielectric properties. Therefore, as in the case of electrostatic shielding presented above, explicitly defined solvent molecules do not have to be present. In fact, the bulk can be considered as perturbing the molecule in the gas phase , leading to so-called continuum solvent models [14, 15]. To represent the electrostatic contribution to the free energy of solvation, the generalized Bom (GB) method is widely used. Wilhin the GB equation, AG equals the difference between and the vacuum Coulomb energy (Eq. (38)) ... 

It is possible to go beyond the SASA/PB approximation and develop better approximations to current implicit solvent representations with sophisticated statistical mechanical models based on distribution functions or integral equations (see Section V.A). An alternative intermediate approach consists in including a small number of explicit solvent molecules near the solute while the influence of the remain bulk solvent molecules is taken into account implicitly (see Section V.B). On the other hand, in some cases it is necessary to use a treatment that is markedly simpler than SASA/PB to carry out extensive conformational searches. In such situations, it possible to use empirical models that describe the entire solvation free energy on the basis of the SASA (see Section V.C). An even simpler class of approximations consists in using infonnation-based potentials constructed to mimic and reproduce the statistical trends observed in macromolecular structures (see Section V.D). Although the microscopic basis of these approximations is not yet formally linked to a statistical mechanical formulation of implicit solvent, full SASA models and empirical information-based potentials may be very effective for particular problems. 

For solvent models where the cavity/dispersion interaction is parameterized by fitting to experimental solvation energies, the use of a few explicit solvent molecules for the first solvation sphere is not recommended, as the parameterization represents a best fit to experimental data without any explicit solvent present. 

Presently, only the molecular dynamics approach suffers from a computational bottleneck [58-60]. This stems from the inclusion of thousands of solvent molecules in simulation. By using implicit solvation potentials, in which solvent degrees of freedom are averaged out, the computational problem is eliminated. It is presently an open question whether a potential without explicit solvent can approximate the true potential sufficiently well to qualify as a sound protein folding theory [61]. A toy model study claims that it cannot [62], but like many other negative results, it is of relatively little use as it is based on numerous assumptions, none of which are true in all-atom representations. 

---