Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases |
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Authors: | Raymond John W Willett Peter |
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Affiliation: | (1) Ann Arbor Laboratories, Pfizer Global Research and Development, 2800 Plymouth Road, Ann Arbor, Michigan, 48105, U.S.A;(2) Krebs Institute for Biomolecular Research and Department of Information Studies, University of Sheffield, Western Bank, Sheffield, S10 2TN, U.K |
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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. |
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Keywords: | fingerprint graph matching maximum common edge subgraph maximum overlapping set RASCAL similarity coefficient similarity searching virtual screening |
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