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Similarity Searching Using 2D Structural Fingerprints

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Chemoinformatics and Computational Chemical Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 672))

Abstract

This chapter reviews the use of molecular fingerprints for chemical similarity searching. The fingerprints encode the presence of 2D substructural fragments in a molecule, and the similarity between a pair of molecules is a function of the number of fragments that they have in common. Although this provides a very simple way of estimating the degree of structural similarity between two molecules, it has been found to provide an effective and an efficient tool for searching large chemical databases. The review describes the historical development of similarity searching since it was first described in the mid-1980s, reviews the many different coefficients, representations, and weightings that can be combined to form a similarity measure, describes quantitative measures of the effectiveness of similarity searching, and concludes by looking at current developments based on the use of data fusion and machine learning techniques.

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  1. Department of Information Studies, The University of Sheffield, Sheffield, UK

    Peter Willett

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  1. , Department of Life Science Informatics, Rheinische Friedrich-Wilhelms-Universitä, Dahlmannstr. 2, Bonn, 53113, Germany

    Jürgen Bajorath

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Willett, P. (2010). Similarity Searching Using 2D Structural Fingerprints. In: Bajorath, J. (eds) Chemoinformatics and Computational Chemical Biology. Methods in Molecular Biology, vol 672. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-839-3_5

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  • DOI: https://doi.org/10.1007/978-1-60761-839-3_5

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