LAUSR

MOTIVATION Identification of putative drug targets is a critical step for explaining the mechanism of drug action against multiple targets, finding new therapeutic indications for existing drugs, and unveiling the adverse drug reactions. One important approach is to use the molecular docking. However, its widespread utilization has been hindered by the lack of easy-to-use public servers. Therefore, it is vital to develop a streamlined computational tool for target prediction by molecular docking on a large scale. RESULTS We present a fully automated web tool named CRDS (Consensus Reverse Docking System) which predicts potential interaction sites for a given drug. To improve hit rates, we developed a strategy of consensus scoring. CRDS carries out reverse docking against 5,254 candidate protein structures using three different scoring functions (GoldScore, Vina, and LeDock from GOLD version 5.7.1, AutoDock Vina version 1.1.2, and LeDock version 1.0, respectively), and those scores are combined into a single score named CDS (Consensus Docking Score). The web server provides the list of top fifty predicted interaction sites, docking conformations, ten most significant pathways, and the distribution of consensus scores. AVAILABILITY The web server is available at http://pbil.kaist.ac.kr/CRDS. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.