We present an integrated docking environment that allows for iterative and interactive detailed analysis of many docking solutions. All docking information is stored in an ORACLE database. New scoring schemes (e.g. target-specific scoring functions) as well as various types of filters can be easily defined and tested within this environment. As an example application we investigated the validity of the following hypothesis: If a docking procedure can lead to enrichments significantly better than random then a bias towards (partially) correct placements should be detectable. Such bias in terms of a preference for certain interacting groups within the active site can be used to select a set of receptor-based pharmacophore constraints, which in turn might be used to enhance the docking procedure. As a proof of concept for this approach we performed docking studies on three targets: thrombin, the cyclin-dependent kinase 2 (CDK2) and the angiotensin converting enzyme (ACE). We docked a set of known active compounds with standard FlexX and derived three sets of target-specific receptor-based pharmacophore constraints by statistical analysis of the predicted placements. Applying these receptor-based constraints in a virtual screening protocol utilizing FlexX-Pharm led to significantly improved enrichments.