We present our database-screening tool SLIDE, which is capable of screening large data sets of organic compounds for potential ligands to a given binding site of a target protein. Its main feature is the modeling of induced complementarity by making adjustments in the protein side chains and ligand upon binding. Mean-field theory is used to balance the conformational changes in both molecules in order to generate a shape-complementary interface. Solvation is considered by prediction of water molecules likely to be conserved from the crystal structure of the ligand-free protein, and allowing them to mediate ligand interactions, if possible, or including a desolvation penalty when they are displaced by ligand atoms that do not replace the lost hydrogen bonds. A data set of over 175 000 organic molecules was screened for potential ligands to the progesterone receptor, dihydrofolate reductase, and a DNA-repair enzyme. In all cases the screening time was less than a day on a Pentium II processor, and known ligands as well as highly complementary new potential ligands were found.