A Docking‐Based Virtual Screen for Bifunctional μ‐Opioid Agonist/δ‐Opioid Antagonist Compounds

Abstract

The opioid receptors are family of G protein‐coupled receptors responsible for the modulation of pain, motor control, and mood. Opioid drugs, such as morphine, typically target the mu opioid receptor to elicit analgesia. However, a plethora of side effects, such as respiratory depression and addiction, manifest alongside their use, limiting their effectiveness in the long term. With the opioid crisis in our midst, the need for the development of a safer opioid with fewer or no side effects for pain management is of utmost importance. Recently, “mixed‐efficacy” bifunctional compounds acting as mu opioid receptor (MOR) agonists and delta opioid receptor (DOR) antagonists have been developed and shown in animal studies to produce analgesia with less potential for the development of tolerance and dependence. Consequently, the discovery of novel scaffolds for such compounds could lead to the development of safer opioid analgesics. Here, we report the development and validation of a sequential ligand‐ and structure‐based virtual screening pipeline. A ligand‐based virtual screen was used to establish an opioid‐enriched, targeted database for subsequent docking with AutoDock Vina. Retrospective virtual screening against a docking‐based benchmark dataset resulted in enrichment factor values from 7.8‐fold to over 10‐fold over random for both MOR and DOR, respectively, validating the efficacy of the model. In a prospective virtual screen, over 13 million compounds from the drug‐like subset of compounds in the ZINC database were screened, after which 360 unique compounds chemically dissimilar to currently‐known opioids were selected by manual inspection or clustering. Experimental validation of high‐scoring candidate compounds is underway to determine affinity and efficacy at MOR and DOR, and selectivity over other receptors.Support or Funding InformationDiscovery of New Treatments for Drug Abuse. Husbands, Stephen. Traynor, John. National Institute of Health (NIH). National Institute on Drug Abuse (NIDA). Project #: 5R01DA007315‐24This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.