@article{75f9bcbda5d34b349d40220182dd3b05,
title = "Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking",
abstract = "Docking calculations can accelerate drug discovery by predicting the bound poses of ligands for a targeted protein. However, it is not clear which docking methods work best. Furthermore, predicting poses requires steps outside the docking algorithm itself, such as preparation of the protein and ligand, and it is not known which components are most in need of improvement. The Continuous Evaluation of Ligand Protein Predictions (CELPP) is a blinded prediction challenge designed to address these issues. Participants create a workflow to predict protein-ligand binding poses, which is then tasked with predicting 10–100 new protein-ligand crystal structures each week. CELPP evaluates the accuracy of each workflow's predictions and posts the scores online. The results can be used 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.",
keywords = "CELPP, D3R, RCSB PDB, community resource, drug design data resource, drug docking, pose prediction",
author = "Wagner, {Jeffrey R.} and Churas, {Christopher P.} and S. Liu and Swift, {Robert V.} and Michael Chiu and Chenghua Shao and Feher, {Victoria A.} and Burley, {Stephen K.} and Gilson, {Michael K.} and Amaro, {Rommie E.}",
note = "Funding Information: We gratefully acknowledge the early CELPP participants, who provided feedback and developed automated workflows before the challenge was made public. We thank Torsten Schwede and J{\"u}rgen Haas for helpful discussions and for developing the inspirational Continuous Automated Model Evaluation challenge. D3R is supported by NIH grant U01 GM111528 to R.E.A. and M.K.G. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. Funding Information: We gratefully acknowledge the early CELPP participants, who provided feedback and developed automated workflows before the challenge was made public. We thank Torsten Schwede and J?rgen Haas for helpful discussions and for developing the inspirational Continuous Automated Model Evaluation challenge. D3R is supported by NIH grant U01 GM111528 to R.E.A. and M.K.G. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. Conceptualization and Methodology, J.R.W. S.L. R.V.S. V.A.F. S.K.B. M.K.G. and R.E.A.; Software and Validation, J.R.W. C.P.C. S.L. R.V.S. M.C. and C.S.; Investigation, J.R.W. and S.L.; Resources, C.P.C. M.C. C.S. and S.K.B.; Writing ? Original Draft, J.R.W.; Writing ? Review & Editing, J.R.W. S.K.B. M.K.G. and R.E.A.; Supervision and Funding Acquisition, V.A.F. S.K.B. M.K.G. and R.E.A. M.K.G. has an equity interest in, and is a cofounder and scientific advisor of, VeraChem. R.E.A. has equity interest in, and is a cofounder and scientific advisor of Actavalon. V.A.F. has equity interest in Actavalon. Publisher Copyright: {\textcopyright} 2019 Elsevier Ltd",
year = "2019",
month = aug,
day = "6",
doi = "10.1016/j.str.2019.05.012",
language = "English (US)",
volume = "27",
pages = "1326--1335.e4",
journal = "Structure with Folding & design",
issn = "0969-2126",
publisher = "Cell Press",
number = "8",
}