Solvents MD simulations

In an early work by Mertz and Pettitt, an open system was devised, in which an extended variable, representing the extent of protonation, was used to couple the system to a chemical potential reservoir [67], This method was demonstrated in the simulation of the acid-base reaction of acetic acid with water [67], Recently, PHMD methods based on continuous protonation states have been developed, in which a set of continuous titration coordinates, A, bound between 0 and 1, is propagated simultaneously with the conformational degrees of freedom in explicit or continuum solvent MD simulations. In the acidostat method developed by Borjesson and Hiinenberger for explicit solvent simulations [13], A. is relaxed towards the equilibrium value via a first-order coupling scheme in analogy to Berendsen s thermostat [10]. However, the theoretical basis for the equilibrium condition used in the derivation seems unclear [3], A test using the pKa calculation for several small amines did not yield HH titration behavior [13],... 

Even though all-atom explicit solvent MD simulations are currently becoming feasible for larger systems and for time scales up to hundreds nanoseconds, a vast... 

We have presented a simple protocol to run MD simulations for systems of interest. There are, however, some tricks to improve the efficiency and accuracy of molecular dynamics simulations. Some of these techniques, which are discussed later in the book, are today considered standard practice. These methods address diverse issues ranging from efficient force field evaluation to simplified solvent representations. 

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... 

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. 

FIG. 2 The xy and a 3D projection of a typical osmotic MD simulation system. The semi-permeable membrane walls are in the yz plane. Periodic boundary conditions automatically generate an infinite pair of walls, infinite in the yz (transverse) directions, with alternating solution and solvent cells, each of thickness half the system width. 

Our first exploration of property space was focused on acetylcholine. This molecule was chosen for its interesting structure, major biological role, and the abundant data available on its conformational properties [15]. The behavior of acetylcholine was analyzed by MD simulations in vacuum, in isotropic media (water and chloroform) [16] and in an anisotropic medium, i.e. a membrane model [17]. Hydrated n-octanol (Imol water/4mol octanol) was also used to represent a medium structurally intermediate between a membrane and the isotropic solvents [17]. 

The dynamic profile of carnosine was investigated by comparing MD simulations in isotropic solvents (i.e. water and chloroform) with simulation of the compound bound to serum carnosinase (CNl) [22]. This enzyme is characterized by its distribution in plasma and brain, and its ability to hydrolyze also anserine and homocarnosine [23]. The conformational profile of carnosine can be defined by... 

MD simulations in expHcit solvents are stiU beyond the scope of the current computational power for screening of a large number of molecules. However, mining powerful quantum chemical parameters to predict log P via this approach remains a challenging task. QikProp [42] is based on a study [3] which used Monte Carlo simulations to calculate 11 parameters, including solute-solvent energies, solute dipole moment, number of solute-solvent interactions at different cutoff values, number of H-bond donors and acceptors (HBDN and HBAQ and some of their variations. These parameters made it possible to estimate a number of free energies of solvation of chemicals in hexadecane, octanol, water as well as octanol-water distribution coefficients. The equation calculated for the octanol-water coefficient is ... 

After an MD simulation was performed to obtain the trajectory of the extractant, a molecular mechanics calculation was carried out to evaluate the solute-solvent interaction... 

FIG. 3 MD simulation of the heptane-water interface, (a) Configuration of solvent molecules in a two-phase cell (b) density vs. distance profile along the axis from aqueous phase to heptane phase. 

As discussed in many previous studies of biomolecules, the treatment of electrostatic interactions is an important issue [69, 70, 84], What is less widely appreciated in the QM/MM community, however, is that a balanced treatment of QM-MM electrostatics and MM-MM electrostatics is also an important issue. In many implementations, QM-MM electrostatic interactions are treated without any cut-off, in part because the computational cost is often negligible compared to the QM calculation itself. For MM-MM interactions, however, a cut-off scheme is often used, especially for finite-sphere type of boundary conditions. This imbalanced electrostatic treatment may cause over-polarization of the MM region, as was first discussed in the context of classical simulations with different cut-off values applied to solute-solvent and solvent-solvent interactions [85], For QM/MM simulations with only energy minimizations, the effect of over-polarization may not be large, which is perhaps why the issue has not been emphasized in the past. As MD simulations with QM/MM potential becomes more prevalent, this issue should be emphasized. 

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