Predicting opioid receptor binding affinity of pharmacologically unclassified designer substances using molecular docking

Journal Article · Thu May 24 00:00:00 EDT 2018 · PLoS ONE

DOI:https://doi.org/10.1371/journal.pone.0197734· OSTI ID:1627863

Ellis, Christopher R. ^[1]; Kruhlak, Naomi L. ^[2]; Kim, Marlene T. ^[2]; Hawkins, Edward G. ^[2]; Stavitskaya, Lidiya ^[2]

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1. U.S. Food and Drug Administration (FDA), Silver Spring, MD (United States). Center for Drug Evaluation and Research; DOE/OSTI
2. U.S. Food and Drug Administration (FDA), Silver Spring, MD (United States). Center for Drug Evaluation and Research

Opioids represent a highly-abused and highly potent class of drugs that have become a significant threat to public safety. Often there are little to no pharmacological and toxicological data available for new, illicitly used and abused opioids, and this has resulted in a growing number of serious adverse events, including death. The large influx of new synthetic opioids permeating the street-drug market, including fentanyl and fentanyl analogs, has generated the need for a fast and effective method to evaluate the risk a substance poses to public safety. In response, the US FDA’s Center for Drug Evaluation and Research (CDER) has developed a rapidly-deployable, multi-pronged computational approach to assess a drug’s risk to public health. A key component of this approach is a molecular docking model to predict the binding affinity of biologically uncharacterized fentanyl analogs to the mu opioid receptor. The model was validated by correlating the docking scores of structurally diverse opioids with experimentally determined binding affinities. Fentanyl derivatives with subnanomolar binding affinity at the mu receptor (e.g. carfentanil and lofentanil) have significantly lower binding scores, while less potent fentanyl derivatives have increased binding scores. The strong correlation between the binding scores and the experimental binding affinities suggests that this approach can be used to accurately predict the binding strength of newly identified fentanyl analogs at the mu receptor in the absence of in vitro data and may assist in the temporary scheduling of those substances that pose a risk to public safety.

• Research Organization: Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC)
• Grant/Contract Number: SC0014664
• OSTI ID: 1627863
• Journal Information: PLoS ONE, Journal Name: PLoS ONE Journal Issue: 5 Vol. 13; ISSN 1932-6203
• Publisher: Public Library of Science
• Country of Publication: United States
• Language: English

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60 APPLIED LIFE SCIENCES
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