Similarity searching

Abstract Similarity searching is one of the traditional and most widely applied approaches in chemical and pharmaceutical research to select compounds with desired properties from databases. The computational efficiency of many (but not all) similarity search techniques has further increased their popularity as compound databases began to rapidly grow in size. Different methods have been developed for small molecule similarity searching. However, foundations and intrinsic limitations of similarity searching are often not well understood, although a number of similarity methods are rather simplistic. Regardless of methodological details, all similarity search approaches depend on how molecular similarity is evaluated and quantified. In its essence, molecular similarity is a subjective concept and much dependent on how we represent and view molecular structures. Moreover, trying to understand the relationship between molecular similarity, however assessed, and structure‐dependent properties including, first and foremost, biological activity continues to be a challenging problem. Consequently, although similarity searching usually provides a quantitative readout and a ranking of compounds relative to chosen reference molecules, predicting structure–activity relationships on the basis of calculated similarity values often involves subjective criteria and chemical intuition. Thus, similarity searching is still far from being a routine application in database mining. In this review, we first discuss important principles underlying similarity searching, describe its tasks, and introduce major categories of search methods. Then, we focus on molecular fingerprints, the design and application of which can be regarded as a paradigm for the similarity search field. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 260‐282 DOI: 10.1002/wcms.23 This article is categorized under: Computer and Information Science > Databases and Expert Systems