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Use of Structure−Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection
Abstract
An evaluation of a variety of structure-based clustering methods for use in compound selection is presented. The use of MACCS, Unity and Daylight 2D descriptors; Unity 3D rigid and flexible descriptors and two in-house 3D descriptors based on potential pharmacophore points, are considered. The use of Ward's and group-average hierarchical agglomerative, Guénoche hierarchical divisive, and Jarvis−Patrick nonhierarchical clustering methods are compared. The results suggest that 2D descriptors and hierarchical clustering methods are best at separating biologically active molecules from inactives, a prerequisite for a good compound selection method. In particular, the combination of MACCS descriptors and Ward's clustering was optimal.
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Metadata
- Authors
- Brown, R. D., & Martin, Y. C.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 1996-01-01
- Volume
- 36
- Issue
- 3
- Pages
- 572-584
- ISSN
- 0095-2338 (ISSN-L)
- OpenAlex
- W2005685204
- Cited by
- 625
- References
- 0
- FWCI
- 59.26
- Type
- journal article
- Language
- en
- Open access
- closed
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