Steric complementarity is a prerequisite for ligand-receptor recognition; this implies that drugs with a common receptor binding site should possess sterically similar binding surfaces. This principle is used as the basis for an automatic and unbiased method that superposes molecules. One molecule is rotated and translated to maximize the overlap between the two molecular surface volumes. A fast grid-based method is used to determine the extent of this overlap, and this is optimized using simulated annealing. Matches with high steric similarity scores are then sorted on the basis of both hydrogen-bond and electrostatic similarity between the matched molecules. Flexible molecules are treated as a set of rigid representative conformers. The algorithm has correctly predicted superpositions between a number of paris of molecules, according to crystallographic data from ligands that have been co-crystallized at common enzyme binding sites.