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SCISSORS: Practical Considerations

Molecular similarity has been effectively applied to many problems in cheminformatics and computational drug discovery, but modern methods can be prohibitively expensive for large-scale applications. The SCISSORS method rapidly approximates measures of pairwise molecular similarity such as ROCS and...

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Bibliographic Details
Published in:Journal of chemical information and modeling 2014-01, Vol.54 (1), p.5-15
Main Authors: Kearnes, Steven M, Haque, Imran S, Pande, Vijay S
Format: Article
Language:English
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Summary:Molecular similarity has been effectively applied to many problems in cheminformatics and computational drug discovery, but modern methods can be prohibitively expensive for large-scale applications. The SCISSORS method rapidly approximates measures of pairwise molecular similarity such as ROCS and LINGO Tanimotos, acting as a filter to quickly reduce the size of a problem. We report an in-depth analysis of SCISSORS performance, including a mapping of the SCISSORS error distribution, benchmarking, and investigation of several algorithmic modifications. We show that SCISSORS can accurately predict multiconformer similarity and suggest a method for estimating optimal SCISSORS parameters in a data set-specific manner. These results are a useful resource for researchers seeking to incorporate SCISSORS into molecular similarity applications.
ISSN:1549-9596
1549-960X
DOI:10.1021/ci400264f