Similarity-based virtual screening using 2D fingerprints

This paper summarizes recent work at the University of Sheffield on virtual screening methods that use 2D fingerprint measures of structural similarity. A detailed comparison of a large number of similarity coefficients demonstrates that the well-known Tanimoto coefficient remains the method of choi...

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Bibliographic Details
Published in:Drug discovery today 2006-12, Vol.11 (23), p.1046-1053
Main Author: Willett, Peter
Format: Article
Language:English
Subjects:
Biological and medical sciences
Chemistry, Pharmaceutical - methods
Chemistry, Pharmaceutical - statistics & numerical data
Databases, Factual - statistics & numerical data
Databases, Factual - trends
Drug Design
General pharmacology
Humans
Medical sciences
Pharmaceutical technology. Pharmaceutical industry
Pharmacology. Drug treatments
Quantitative Structure-Activity Relationship
United Kingdom
User-Computer Interface
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Summary:This paper summarizes recent work at the University of Sheffield on virtual screening methods that use 2D fingerprint measures of structural similarity. A detailed comparison of a large number of similarity coefficients demonstrates that the well-known Tanimoto coefficient remains the method of choice for the computation of fingerprint-based similarity, despite possessing some inherent biases related to the sizes of the molecules that are being sought. Group fusion involves combining the results of similarity searches based on multiple reference structures and a single similarity measure. We demonstrate the effectiveness of this approach to screening, and also describe an approximate form of group fusion, turbo similarity searching, that can be used when just a single reference structure is available. This paper discusses the use of binary-encoded fragment substructures to scan databases to find molecules that are structurally similar to a bioactive query compound.
ISSN:1359-6446
1878-5832
DOI:10.1016/j.drudis.2006.10.005