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Clustering files of chemical structures using the Székely–Rizzo generalization of Ward's method by Thibault Varin; Ronan Bureau; Christoph Mueller; Peter Willett is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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Ward's method is extensively used for clustering chemical structures represented by 2D fingerprints. This paper compares Ward clusterings of 14 datasets (containing between 278 and 4332 molecules) with those obtained using the Sze ́kely-Rizzo clustering method, a generalization of Ward's method. The clusters resulting from these two methods were evaluated by the extent to which the various classifications were able to group active molecules together, using a novel criterion of clustering effectiveness. Analysis of a total of 1400 classifications (Ward and Sze ́kely-Rizzo clustering methods, 14 different datasets, 5 different fingerprints and 10 different distance coefficients) demonstrated the general superiority of the Sze ́kely-Rizzo method. The distance coefficient first described by Soergel performed extremely well in these experiments, and this was also the case when it was used in simulated virtual screening experiments.

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Author

Thibault Varin; Ronan Bureau; Christoph Mueller; Peter Willett

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 1093-3263)

Published

2009

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Physical Sciences)