Mazalan, L., Bell, A.J. orcid.org/0000-0002-8268-5853, Sbaffi, L. et al. (1 more author) (2018) Cross-classified multilevel modelling of the effectiveness of similarity-based virtual screening. ChemMedChem, 13 (6). pp. 582-587. ISSN 1860-7179
Abstract
The screening effectiveness of a chemical similarity search depends on a range of factors, including the bioactivity of interest, the types of similarity coefficient and fingerprint that comprise the similarity measure, and the nature of the reference structure that is being searched against a database. This paper introduces the use of cross-classified multilevel modelling as a way to investigate the relative importance of these four factors when carrying out similarity searches on the ChEMBL database. Two principal conclusions can be drawn from the analyses: that the fingerprint plays a more important role than the similarity coefficient in determining the effectiveness of a similarity search; and that comparative studies of similarity measures should involve many more reference structures than has been the case in much previous work.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 Wiley. This is an author produced version of a paper subsequently published in ChemMedChem. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | chemical fingerprints; cross-classified multilevel modelling; similarity coefficients; similarity searching; virtual screening |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 Oct 2017 10:11 |
Last Modified: | 14 Dec 2023 12:48 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/cmdc.201700487 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:123173 |