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Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Discov Today. 2006;11(23):1046-53doi: 10.1016/j.drudis.2006.10.005.
Willett, P. (2006). Similarity-based virtual screening using 2D fingerprints. Drug discovery today, 11(23), 1046-53. https://doi.org/10.1016/j.drudis.2006.10.005
Willett, Peter. "Similarity-based virtual screening using 2D fingerprints." Drug discovery today vol. 11,23 (2006): 1046-53. doi: https://doi.org/10.1016/j.drudis.2006.10.005
Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Discov Today. 2006 Dec;11(23):1046-53. doi: 10.1016/j.drudis.2006.10.005. Epub 2006 Oct 20. PMID: 17129822.
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Drug Discov Today. 2006 Dec;11(23):1046-53. doi: 10.1016/j.drudis.2006.10.005. Epub 2006 Oct 20.

Similarity-based virtual screening using 2D fingerprints.

Drug discovery today

Peter Willett

Affiliations

  1. Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, 211 Portobello, Sheffield S1 4DP, UK. [email protected]

PMID: 17129822 DOI: 10.1016/j.drudis.2006.10.005

Abstract

This paper summarizes recent work at the University of Sheffield on virtual screening methods that use 2D fingerprint measures of structural similarity. A detailed comparison of a large number of similarity coefficients demonstrates that the well-known Tanimoto coefficient remains the method of choice for the computation of fingerprint-based similarity, despite possessing some inherent biases related to the sizes of the molecules that are being sought. Group fusion involves combining the results of similarity searches based on multiple reference structures and a single similarity measure. We demonstrate the effectiveness of this approach to screening, and also describe an approximate form of group fusion, turbo similarity searching, that can be used when just a single reference structure is available.

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