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Title: Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

Abstract

The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

Authors:
 [1];  [1];  [2];  [3];  [1];  [3];  [1]
+ Show Author Affiliations
  1. Univ. of Tennessee, Knoxville, TN (United States)
  2. Univ. of Kentucky, Lexington, KY (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1337049
Alternate Identifier(s):
OSTI ID: 1398017
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Bioorganic and Medicinal Chemistry
Additional Journal Information:
Journal Volume: 24; Journal Issue: 20; Journal ID: ISSN 0968-0896
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES

Citation Formats

Evangelista, Wilfredo, Weir, Rebecca, Ellingson, Sally, Harris, Jason B., Kapoor, Karan, Smith, Jeremy C., and Baudry, Jerome. Ensemble-based docking: From hit discovery to metabolism and toxicity predictions. United States: N. p., 2016. Web. doi:10.1016/j.bmc.2016.07.064.
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Evangelista, Wilfredo, Weir, Rebecca, Ellingson, Sally, Harris, Jason B., Kapoor, Karan, Smith, Jeremy C., & Baudry, Jerome. Ensemble-based docking: From hit discovery to metabolism and toxicity predictions. United States. https://doi.org/10.1016/j.bmc.2016.07.064
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Evangelista, Wilfredo, Weir, Rebecca, Ellingson, Sally, Harris, Jason B., Kapoor, Karan, Smith, Jeremy C., and Baudry, Jerome. Fri . "Ensemble-based docking: From hit discovery to metabolism and toxicity predictions". United States. https://doi.org/10.1016/j.bmc.2016.07.064. https://www.osti.gov/servlets/purl/1337049.
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@article{osti_1337049,
title = {Ensemble-based docking: From hit discovery to metabolism and toxicity predictions},
author = {Evangelista, Wilfredo and Weir, Rebecca and Ellingson, Sally and Harris, Jason B. and Kapoor, Karan and Smith, Jeremy C. and Baudry, Jerome},
abstractNote = {The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.},
doi = {10.1016/j.bmc.2016.07.064},
journal = {Bioorganic and Medicinal Chemistry},
number = 20,
volume = 24,
place = {United States},
year = {Fri Jul 29 00:00:00 EDT 2016},
month = {Fri Jul 29 00:00:00 EDT 2016}
}
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Publisher's Version of Record
https://doi.org/10.1016/j.bmc.2016.07.064
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    Computationally identified novel agonists for GPRC6A
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