Computational functional group affinity mapping of proteins is of utility for ligand design in the context of database screening, fragment-based design and lead compound optimization. The SILCS methodology allows for the generation of functional group affinity maps (FragMaps) of proteins that take into account contributions from protein desolvation, functional group desolvation, protein flexibility as well as direct interactions of the functional groups with the protein. Boltzmann transformation of the maps yields Grid Free Energy (GFE) FragMaps that may be used both qualitatively and quantitatively to direct ligand design. To allow for the application of the SILCS approach to deep and occluded pockets in proteins an oscillating μex Grand Canonical Monte Carlo (GCMC) approach was developed that allows for insertions of small solute molecules in the presence of an explicit aqueous environment. Combining the GCMC method with MD simulations for the inclusion of protein flexibility allows for the determination of GFE Fragmaps in occluded pockets. An overview of the GCMC/MD SILCS methodology along with application of the method to T4-lysozyme pocket mutants, nuclear receptors and GPCRs will be presented.