The analysis of individual systems provided interesting insight for the interpretation of the results and their possible use for drug discovery and design. Therefore, the availability of a rapid analysis method such as the WaterKit protocol can have a beneficial impact in the wide adoption of GIST-based methods for the routine analysis of biologically and therapeutically relevant targets. For some systems studied here, Wa-terKit tends to identify more easily well-defined locations for water molecules compared to MD simulations. Uncertainty and divergence appear to be related to less favorable E sw values associated with water molecules lacking a stable and well-defined position. Observations of this nature are particularly important in the context of docking applications, having a way to assess results confidence is a crucial factor. In the retrospective analysis, WaterKit appears to be also effective at capturing some of the features of known ligands biding in the sites considered (Fig. 10, 5,6). The water positions predicted by WaterKit recapitulate key ligand pharmacophoric features of well-characterized targets, such as HSP-90 (6), HIV-1 protease (Fig. ), influenza neuraminidase (Fig. ), and streptavidin (Fig. ).