Molecular mechanisms of fentanyl mediated β-arrestin biased signaling

Abstract

The development of novel analgesics with improved safety profiles to combat the opioid epidemic represents a central question to G protein coupled receptor structural biology and pharmacology: What chemical features dictate G protein or {beta}-arrestin signaling? Here we use adaptively biased molecular dynamics simulations to determine how fentanyl, a potent {beta}-arrestin biased agonist, activates the -opioid receptor (OR). The resulting fentanyl-bound pose provides rational insight into a wealth of historical structure-activity-relationship on its chemical scaffold. We found that fentanyl and the synthetic opioid peptide DAMGO require M153 to induce {beta}-arrestin coupling, while M153 was dispensable for G protein coupling. We propose and validate a mechanism where the n-aniline ring of fentanyl mediates OR {beta}-arrestin through a novel M153 \"microswitch\" by synthesizing fentanyl-based derivatives that exhibit complete, clinically desirable, G protein biased coupling. Together, these results provide molecular insight into fentanyl mediated {beta}-arrestin biased signaling and a rational framework for further optimization of fentanyl-based analgesics with improved safety profiles.\n\nAuthor SummaryThe global opioid crisis has drawn significant attention to the risks associated with over-use of synthetic opioids. Despite the public attention, and perhaps in-line with the profit-based incentives of the pharmaceutical industry, there is no public structure of mu-opioid receptor bound to fentanyl or fentayl derivatives. A publicly available structure of the complex would allow open-source development of safer painkillers and synthetic antagonists. Current overdose antidotes, antagonists, require natural products in their synthesis which persists a sizable barrier to market and develop better antidotes. In this work we use advance molecular dynamics techniques to obtain the bound geometry of mu-opioid receptor with fentanyl (and derivatives). Based on our in-silico structure, we synthesized and tested novel compounds to validate our predicted structure. Herein we report the bound state of several dangerous fentanyl derivatives and introduce new derivatives with signaling profiles that may lead to lower risk of respiratory depression.