In this article, we review the use of in vitro and in silico affinity fingerprints as novel descriptors for similarity searches in molecular databases and QSAR analyses. An affinity fingerprint for a particular molecule is constructed as a vector of either its binding affinities, docking scores or superpositioning pseudo energies against a reference panel of proteins or small molecules. In contrast to most other molecular descriptors, affinity fingerprints are not directly derived from molecular structures. As such, they offer the possibility to detect similarities amongst molecules independent of their structural scaffolds. In this report we introduce the Flexsim-S method, an extension of our previous work on virtual affinity fingerprints. Moreover, we demonstrate that virtual affinity fingerprint methods are comparable to some popular two-dimensional descriptors in terms of correctly classifying compounds, but complementary with respect to the particular search results (hit lists).