Drugs bind to targets in the aqueous environment. Polar drugs are well solavated in water and often pay an enthalpic desolvation penalty upon binding to the protein. Thus, one may enhance binding of a drug by reducing its aqueous solvation free energy. This is usually done by creating a more hydrophobic analog. If the hydrophobic group is poorly solvated in water but faces hydrophobic pocket in the protein, the equilibrium will be shifted toward binding. But how can we predict aqueous solvation free energies?
One approach to model solvent effects is to surround the solute with a small number of explicit solvent molecules during the calculation. For example, one could optimize the structure of the ligand such as acetylcholine by placing a couple of solvent molecules near the carbonyl oxygen, and building a solvent shell around positively charged trimethylamine moiety; such calculation would correctly predict that the free enerergy of solavtion of acetylcholine is favorable. However, the magnitude of the solvent effect depends strongly on details: factors such as the number of water molecules and their placement affects results greatly. Addition of a second layer of solvent might mitigate this problem but then the number of solvent molecules is so large that typical QM calculations become unfeasible.
Alternative approach is to describe solvation by its average effect that mainly arises from dipolar interactions. In this model, the polar solute polarizes the surrounding dielectric medium. The polarized medium acts as a reaction field that interacts with the solute. The advantage of such approach is simplicity inn setting up the computations but specific interactions, such as strong hydrogen bonding with the solvent is difficult to model. Furthermore, geometry optimization in the presence of polarizable continuum is not as efficient as geometry optimization in the gas phase, and it is not uncommon that optimizations of certain geometries fail when a specific implementation of reaction field is chosen. In Gaussian, the implicit solvent model calculation is invoked via the SCRF keyword.
The goal of the following exercise is to estimate the free energy of solavtion of chorismate and prephenate in water using an implicit solvent model. The energy difference will give the recation enthalpy in the aqueous environmemt. You will use using an explicit Polarizable Continuum Model (PCM), which is known to yield reasonably accurate solvation free energies. In the tutorial, you will be performing a single-point calculation at the PM3 gas phase geometry. Note that usually one would need to reoptimize the structures in the presence of the solvent because the geometry of flexible polar molecules depends on their environment. We will use Gaussian 03 for these calculation.