Ligand-based virtual screening using binary kernel discrimination

Chen, B., Harrison, R.F., Hert, J., Mpanhanga, C., Willett, P. and Wilton, D.J. (2005) Ligand-based virtual screening using binary kernel discrimination. Molecular Simulation, 31 (8). pp. 597-604. ISSN 0892-7022

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Abstract

This paper discusses the use of a machine-learning technique called binary kernel discrimination (BKD) for virtual screening in drug- and pesticide-discovery programmes. BKD is compared with several other ligand-based tools for virtual screening in databases of 2D structures represented by fragment bit-strings, and is shown to provide an effective, and reasonably efficient, way of prioritising compounds for biological screening.

Item Type:	Article
Copyright, Publisher and Additional Information:	© 2005 Taylor & Francis. This is an author produced version of a paper subsequently published in Molecular Simulation. Uploaded in accordance with the publisher's self-archiving policy.
Keywords:	Binary kernel discrimination, Circular substructure, Fingerprints, Similarity searching, Virtual screening
Academic Units:	The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) The University of Sheffield > University of Sheffield Research Centres and Institutes > The Krebs Institute for Biomolecular Research (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > Department of Chemistry (Sheffield)
Depositing User:	Beccy Shipman
Date Deposited:	11 Feb 2009 17:41
Last Modified:	08 Feb 2013 16:57
Published Version:	http://dx.doi.org/10.1080/08927020500134177
Status:	Published
Publisher:	Taylor & Francis
Refereed:	Yes
Identification Number:	10.1080/08927020500134177
URI:	http://eprints.whiterose.ac.uk/id/eprint/7691

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