Virtual screening with docking is an integral component of drug design, particularly during hit finding phases. While successful prospective studies of virtual screening exist, it remains a significant challenge to identify best practices a priori due to the many factors that influence the final outcome, including targets, data sets, software, metrics, and expert knowledge of the users. This study investigates the extent to which ligand-based methods can be applied to improve structure-based methods. The use of ligand-based methods to modulate the number of hits identified using the protein–ligand complex and also the diversity of these hits from the crystallographic ligand is discussed. In this study, 40 CDK2 ligand complexes were used together with two external data sets containing both actives and inactives from GlaxoSmithKline (GSK) and actives and decoys from the Directory of Useful Decoys (DUD). Results show how ligand-based modeling can be used to select a more appropriate protein conformation for docking, as well as to assess the reliability of the docking experiment. The time gained by reducingthe pool of virtual screening candidates via ligand-based similaritycan be invested in more accurate docking procedures, as well as indownstream labor-intensive approaches (e.g., visual inspection) maximizingthe use of the chemical and biological information available. Thisprovides a framework for molecular modeling scientists that are involvedin initiating virtual screening campaigns with practical advice tomake best use of the information available to them.
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