Raymond, J.W. and Willett, P. (2002) Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases. Journal of Computer-Aided Molecular Design, 16 (1). pp. 59-71. ISSN 1573-4951
Abstract
This paper reports an evaluation of both graph-based and fingerprint-based measures of structural similarity, when used for virtual screening of sets of 2D molecules drawn from the MDDR and ID Alert databases. The graph-based measures employ a new maximum common edge subgraph isomorphism algorithm, called RASCAL, with several similarity coefficients described previously for quantifying the similarity between pairs of graphs. The effectiveness of these graph-based searches is compared with that resulting from similarity searches using BCI, Daylight and Unity 2D fingerprints. Our results suggest that graph-based approaches provide an effective complement to existing fingerprint-based approaches to virtual screening.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2002 Springer. This is an author produced version of a paper published in Journal of computer aided molecular design. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | fingerprint, graph matching, maximum common edge subgraph, maximum overlapping set, RASCAL, similarity coefficient, similarity searching, virtual screening |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield) |
Depositing User: | Sherpa Assistant |
Date Deposited: | 11 Jan 2008 16:03 |
Last Modified: | 08 Feb 2013 16:55 |
Published Version: | http://dx.doi.org/10.1023/A:1016387816342 |
Status: | Published |
Publisher: | Springer Netherlands |
Refereed: | Yes |
Identification Number: | 10.1023/A:1016387816342 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:3567 |