Functional group placement in protein binding sites: a comparison of GRID and MCSS

One approach to combinatorial ligand design begins by determining optimal locations (i.e., local potential energy minima) for functional groups in the binding site of a target macromolecule. MCSS and GRID are two methods, based on significantly different algorithms, which are used for this purpose. A comparison of the two methods for the same functional groups is reported. Calculations were performed for nonpolar and polar functional groups in the internal hydrophobic pocket of the poliovirus capsid protein, and on the binding surface of the src SH3 domain. The two approaches are shown to agree qualitatively; i.e., the global characteristics of the functional group maps generated by MCSS and GRID are similar. However, there are significant differences in the relative interaction energies of the two sets of minima, a consequence of the different functional form used to evaluate polar interactions (electrostatics and hydrogen bonding) in the two methods. The single sphere representation used by GRID affords only positional information, supplemented by the identification of hydrogen bonding interactions. By contrast, the multi-atom representation of most MCSS groups yields in both positional and orientational information. The two methods are most similar for small functional groups, while for larger functional groups MCSS yields results consistent with GRID but superior in detail. These results are in accord with the somewhat different purposes for which the two methods were developed. GRID has been used mainly to introduce functionalities at specific positions in lead compounds, in which case the orientation is predetermined by the structure of the latter. The orientational information provided by MCSS is important for its use in the de novo design of large, multi-functional ligands, as well as for improving lead compounds.