Predicting opioid receptor binding affinity of pharmacologically unclassified designer substances using molecular docking.
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ABSTRACT: 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 doc
SUBMITTER: Ellis CR
PROVIDER: S-EPMC5967713 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
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