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Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking

32 Pages Posted: 7 Jan 2019 Sneak Peek Status: Published

See all articles by Jeffrey R. Wagner

Jeffrey R. Wagner

University of California, San Diego (UCSD) - Drug Design Data Resource

Christopher P. Churas

University of California, San Diego (UCSD) - Drug Design Data Resource

Shuai Liu

University of California, San Diego (UCSD) - Drug Design Data Resource

Robert V. Swift

University of California, San Diego (UCSD) - Drug Design Data Resource

Michael Chiu

University of California, San Diego (UCSD) - Drug Design Data Resource

Chenghua Shao

Rutgers, The State University of New Jersey - RCSB Protein Data Bank

Victoria A. Feher

University of California, San Diego (UCSD) - Drug Design Data Resource

Stephen K. Burley

Rutgers, The State University of New Jersey - RCSB Protein Data Bank

Michael K. Gilson

University of California, San Diego (UCSD) - Skaggs School of Pharmacy and Pharmaceutical Sciences

Rommie E. Amaro

University of California, San Diego (UCSD) - Department of Chemistry and Biochemistry

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Abstract

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.

Suggested Citation

Wagner, Jeffrey R. and Churas, Christopher P. and Liu, Shuai and Swift, Robert V. and Chiu, Michael and Shao, Chenghua and Feher, Victoria A. and Burley, Stephen K. and Gilson, Michael K. and Amaro, Rommie E., Continuous Evaluation of Ligand Protein Predictions: A Weekly Community Challenge for Drug Docking (November 27, 2018). Available at SSRN: https://ssrn.com/abstract=3291330 or http://dx.doi.org/10.2139/ssrn.3291330
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Jeffrey R. Wagner

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Christopher P. Churas

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Shuai Liu

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Robert V. Swift

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Michael Chiu

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Chenghua Shao

Rutgers, The State University of New Jersey - RCSB Protein Data Bank

185 South Orange Avenue
Newark, NJ 07103
United States

Victoria A. Feher

University of California, San Diego (UCSD) - Drug Design Data Resource

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

Stephen K. Burley

Rutgers, The State University of New Jersey - RCSB Protein Data Bank

185 South Orange Avenue
Newark, NJ 07103
United States

Michael K. Gilson

University of California, San Diego (UCSD) - Skaggs School of Pharmacy and Pharmaceutical Sciences ( email )

La Jolla, CA
United States

Rommie E. Amaro (Contact Author)

University of California, San Diego (UCSD) - Department of Chemistry and Biochemistry ( email )

9500 Gilman Drive #0761
La Jolla, CA 92093-0761
United States

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