Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy

443 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances (2014, methodology): “, have assessed six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) in order to evaluate docking pose, scoring and thus VS accuracy [90].”
Molecular docking: a powerful approach for structure-based drug discovery. (2011, background): “Various excellent reviews on docking have been published in the past [5, 1114], and many comparison studies were conducted to evaluate the relative performance of the programs [15-18].”
Challenges and advances in computational docking: 2009 in review (2011, methodology): “(47) came to a similar conclusion in their comparison study, where some programs performed better in pose prediction, while others in virtual screening.”
Computational Methods in Drug Discovery (2014, background): “Irwin et al. (2008) created the Directory of Useful Decoys (DUD) dataset designed for high-resolution benchmarking.”
Role of computer-aided drug design in modern drug discovery (2015, background): “Performance of scoring functions varies depending on the purpose (scoring or ranking) and on the protein families and ligand series being considered (Wang et al. 2003; Warren et al. 2006; Cheng et al. 2009; Cross et al. 2009; Xu et al. 2015).”