The similarity-based virtual screening (a kind of ligand-based virtual screening) assumes that all compounds in a database that are similar to a query compound have similar biological activity. Although this hypothesis is not always valid, quite often the set of retrieved compounds is considerably enriched with actives. To achieve high efficacy of similarity-based screening of databases containing millions of compounds, molecular structures are usually represented by molecular screens (structural keys) or by fixed-size or variable-size molecular fingerprints. Molecular screens and fingerprints can contain both 2D- and 3D-information. However, the 2D-fingerprints, which are a kind of binary fragment descriptors, dominate in this area. Fragment-based structural keys, like MDL keys, are sufficiently good for handling small and medium-sized chemical databases, whereas processing of large databases is performed with fingerprints having much higher information density. Fragment-based Daylight, BCI, and UNITY 2D (Tripos) fingerprints are the best known examples. The most popular similarity measure for comparing chemical structures represented by means of fingerprints is the Tanimoto (or Jaccard) coefficient T. Two structures are usually considered similar if T > 0.85 (for Daylight fingerprints). However, it is a common misunderstanding that a similarity of T > 0.85 reflects similar bioactivities in general ("the 0.85 myth").