Cross-Classified Multilevel Modelling of the Effectiveness of Similarity-Based Virtual Screening

Authors
Lucyantie Mazalan, Andrew Bell, Laura Sbaffi, Peter Willett
Year
2017
Journal
ChemMedChem, , 1
DOI
10.1002/cmdc.201700487
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 study 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.

Number of levels
4
Software used
Model data structure
Response types
Multivariate response model?
No
Longitudinal data?
No
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Impact

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Paper submitted by
Andrew Bell, Sheffield Methods Institute, University of Sheffield, andrew.j.d.bell@sheffield.ac.uk
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