Explicit solvent calculations

The primary problem with explicit solvent calculations is the significant amount of computer resources necessary. This may also require a significant amount of work for the researcher. One solution to this problem is to model the molecule of interest with quantum mechanics and the solvent with molecular mechanics as described in the previous chapter. Other ways to make the computational resource requirements tractable are to derive an analytic equation for the property of interest, use a group additivity method, or model the solvent as a continuum. 

Del Buono GS, Figueirido FE, Levy RM (1994) Intrinsic pKas of ionizable residues in proteins An explicit solvent calculation for lysozyme. Proteins 20 85-97. 

The main benefits of this approach are that (i) this is a molecular theory, and that (ii) due to the spherical symmetry of the correlation fnnctions in the ID RISM approach, the computational costs are significantly rednced compared to explicit solvent methods and high-dimensional molecular theories like 3D RISM [80-82, 93], MOZ [82, 83], and MDFT [69, 70]. For an average drug-like molecule a ID RISM calculation of solvation free energy takes less than a minute on a desktop PC [67, 71, 72, 92]. This time scale is already comparable with the compntational time scale for continuum methods (seconds). We note that an explicit solvent calculation for the same kind of molecules would take between honrs and days [38,47-58]. 

The rigorous way to deal with solvent effects on molecular properties is to carry out quantum-mechanical calculations on a system consisting of a solute molecule surrounded by many solvent molecules. One repeats the calculations for various orientations of the solvent molecules and takes a suitable average over orientations to find average properties at a particular temperature and pressure. Such a calculation is usually impractical. Calculations that include a number of individual solvent molecules are called explicit solvent calculations, and discussion of these is omitted (see Cramer, Chapter 12 for details). 

A second idea to save computational time addresses the fact that hydrogen atoms, when involved in a chemical bond, show the fastest motions in a molecule. If they have to be reproduced by the simulation, the necessary integration time step At has to be at least 1 fs or even less. This is a problem especially for calculations including explicit solvent molecules, because in the case of water they do not only increase the number of non-bonded interactions, they also increase the number of fast-moving hydrogen atoms. This particular situation is taken into account... 

The most accurate calculations are those that use a layer of explicit solvent molecules surrounded, in turn, by a continuum model. This adds the additional... 

Also use constant dielectric for MM+ and OPLS calculations. Use the distance-dependent dielectric for AMBER and BlO-t to mimic the screening effects of solvation when no explicit solvent molecules are present. The scale factor for the dielectric permittivity, 8, can vary from 1 to 80. HyperChem sets 8 to 1.5 for MM-t. Use 1.0 for AMBER and OPLS, and 1.0-2.5 for BlO-t. 

As for the dielectric constant, when explicit solvent molecules are included in the calculations, a value of 1, as in vacuum, should be used because the solvent molecules themselves will perform the charge screening. The omission of explicit solvent molecules can be partially accounted for by the use of an / -dependent dielectric, where the dielectric constant increases as the distance between the atoms, increases (e.g., at a separation of 1 A the dielectric constant equals 1 at a 3 A separation the dielectric equals 3 and so on). Alternatives include sigmoidal dielectrics [80] however, their use has not been widespread. In any case, it is important that the dielectric constant used for a computation correspond to that for which the force field being used was designed use of alternative dielectric constants will lead to improper weighting of the different electrostatic interactions, which may lead to significant errors in the computations. 

Another way is to reduce the magnitude of the problem by eliminating the explicit solvent degrees of freedom from the calculation and representing them in another way. Methods of this nature, which retain the framework of molecular dynamics but replace the solvent by a variety of simplified models, are discussed in Chapters 7 and 19 of this book. An alternative approach is to move away from Newtonian molecular dynamics toward stochastic dynamics. 

Over the next decade a number of efforts were made to apply MD simulations using explicit solvent representations to DNA. A number of these calculations were performed... 

Initial atomistic calculations on nucleic acids were perfonned in the absence of an explicit solvent representation, as discussed earlier. To compensate for this omission, various... 

The second generation force fields for nucleic acids were designed to be used with an explicit solvent representation along with inclusion of the appropriate ions [28,29]. In addition, efforts were made to improve the representation of the conformational energetics of selected model compounds. Eor example, the availability of high level ab initio calculations on the conformational energetics of the model compound dimethylphosphate yielded... 

Essential for MD simulations of nucleic acids is a proper representation of the solvent environment. This typically requires the use of an explicit solvent representation that includes counterions. Examples exist of DNA simulations performed in the absence of counterions [24], but these are rare. In most cases neutralizing salt concentrations, in which only the number of counterions required to create an electrically neutral system are included, are used. In other cases excess salt is used, and both counterions and co-ions are included [30]. Though this approach should allow for systematic smdies of the influence of salt concentration on the properties of oligonucleotides, calculations have indicated that the time required for ion distributions around DNA to properly converge are on the order of 5 ns or more [31]. This requires that preparation of nucleic acid MD simulation systems include careful consideration of both solvent placement and the addition of ions. 

If all nuclei are assigned and the spectral parameters for the conformational analysis are extracted, a conformation is calculated - usually by distance geometry (DG) or restrained molecular dynamics calculations (rMD). A test for the quality of the conformation, obtained using the experimental restraints, is its stability in a free MD run, i.e. an MD without experimental restraints. In this case, explicit solvents have to be used in the MD calculation. An indication of more than one conformation in fast equilibrium can be found if only parts of the final structure are in agreement with experimental data [3]. Relaxation data and heteronuclear NOEs can also be used to elucidate internal dynamics, but this is beyond the scope of this article. 

Restrained MD (rMD) is followed by the use of MD in explicit solvent, i.e. the conformation as determined above is taken into a box containing many solvent molecules around the molecule. Subsequently, simulated annealing (SA) and energy minimizahon steps are performed to draw the molecule into the global energy minimum. An MD run (the so-called trajectory) over at least 150ps to Ins is followed and a mean structure is calculated from such a trajectory. The con-formahon must be stable under this condihon even when the experimental constraints are removed. 

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