PT  - JOURNAL ARTICLE
AU  - Jeffrey R. Wagner
AU  - Christopher P. Churas
AU  - Shuai Liu
AU  - Robert V. Swift
AU  - Michael Chiu
AU  - Chenghua Shao
AU  - Victoria A. Feher
AU  - Stephen K. Burley
AU  - Michael K. Gilson
AU  - Rommie E. Amaro
TI  - Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking
AID  - 10.1101/469940
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 469940
4099  - http://biorxiv.org/content/early/2018/11/18/469940.short
4100  - http://biorxiv.org/content/early/2018/11/18/469940.full
AB  - Docking calculations can be used to accelerate drug discovery by providing predictions of the poses of candidate ligands bound to a targeted protein. However, studies in the literature use varied docking methods, and it is not clear which work best, either in general or for specific protein targets. In addition, a complete docking calculation requires components beyond the docking algorithm itself, such as preparation of the protein and ligand for calculations, and it is difficult to isolate which aspects of a method are most in need of improvement. To address such issues, we have developed the Continuous Evaluation of Ligand Protein Predictions (CELPP), a weekly blinded challenge for automated docking workflows. Participants in CELPP create a workflow to predict protein-ligand binding poses, which is then tasked with predicting 10-100 new (never before released) protein-ligand crystal structures each week. CELPP evaluates the accuracy of each workflow’s predictions and posts the scores online. CELPP is a new cyberinfrastructure resource to identify the strengths and weaknesses of current approaches, help map docking problems to the algorithms most likely to overcome them, and illuminate areas of unmet need in structure-guided drug design.