Virtual Screening Using Binary Kernel Discrimination: Analysis of Pesticide Data
David J. Wilton, Robert F. Harrison, Peter Willett, John S. Delaney, Kevin W. Lawson, Graham W. Mullier · Journal of Chemical Information and Modeling · 2006
This paper discusses the use of binary kernel discrimination (BKD) for identifying potential active compounds in lead-discovery programs. BKD was compared with established virtual screening methods in a series of experiments using pesticide data from the Syngenta corporate database. It was found to be superior to methods based on similarity searching and substructural analysis but inferior to a support vector machine. Similar conclusions resulted from application of the methods to a pesticide data set for which categorical activity data were available.