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Introducing the 'active search' method for iterative virtual screening

: Garnett, R.; Gärtner, T.; Vogt, M.; Bajorath, J.


Journal of computer aided molecular design 29 (2015), Nr.4, S.305-314
ISSN: 0920-654X
Deutsche Forschungsgemeinschaft DFG
GA 1615/1-1
Fraunhofer IAIS ()

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.