One of the fastest approaches to filter compound libraries (in particular, large and ultra-large libraries) is similarity searching which is based on the similarity principle. With the caveat of potential activity cliffs in compound data sets similarity searching has been quite effective to rapidly filter libraries and identify active compounds that are further selected by more refined methods. Similarity searching depends on a suitable molecular or structural representation that is used as a basis to quantify the compound similarity (in conjunction with a similarity coefficient).