We have used four large datasets to determine the extent to which Two-Dimensional (2D) structural similarity of chemical compounds predicts how similarly they bind to proteins. Structures of 1750, 1853, 1377, and 407 inhibitors for trypsin, thrombin, factor Xa (fXa), and urokinase-type Plasminogen Activator (uPA), respectively, with their observed binding affinities were collected from various literature sources. We also obtained calculated binding affinities for the datasets using an in-house docking program. Plots of the differences in affinity for all pairs of compounds versus their 2D similarity values were generated. All datasets with both observed and calculated affinities clearly exhibit structure -activity relationships (neighborhood behavior), though notable differences among plots are also observed. Guidelines for application of 2D similarity in structure-based virtual screening are discussed in the context of the results obtained.