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Introducing the 'active search' method for iterative virtual screening


Roman Garnett


Martin Vogt



A method is introduced for sequential similarity searching for active compounds. Given a set of known actives and a screening database, a strategy is devised to optimally rank test compounds by observing the outcome of each iteration before selecting the next compound. This ‘active search’ approach is based upon Bayesian decision theory. A typical ranking procedure used in virtual compound screening corresponds to a myopic approximation to the optimal strategy. Exploratory active search represents a less-myopic approach and is shown to accurately identify a variety of active compounds in iterative virtual screening trials on 120 compound classes. Source code and data for the active search approach presented herein is made freely available.


Garnett, R., Gärtner, T., Vogt, M., & Bajorath, J. (2015). Introducing the 'active search' method for iterative virtual screening. Journal of Computer-Aided Molecular Design, 29(4), 305-314.

Journal Article Type Article
Acceptance Date Feb 1, 2015
Online Publication Date Feb 1, 2015
Publication Date Apr 30, 2015
Deposit Date Feb 16, 2017
Print ISSN 0920-654X
Publisher BMC
Peer Reviewed Peer Reviewed
Volume 29
Issue 4
Pages 305-314
Public URL
Publisher URL