A comprehensive evaluation of the potential binding poses of fentanyl and its analogs at the l-opioid receptor

Fentanyl and its analogs are selective agonists of the l-opioid receptor (MOR). Among novel synthetic opioids (NSOs), they dominate the recreational drug market and are the main culprits for the opioid crisis, which has been exacerbated by the COVID-19 pandemic. By taking advantage of the crystal structures of the MOR, several groups have investigated the binding mechanism of fentanyl, but have not reached a consensus, in terms of both the binding orientation and the fentanyl conformation. Thus, the binding mechanism of fentanyl at the MOR remains an unsolved and challenging question. Here, we carried out a systematic computational study to investigate the preferred fentanyl conformations, and how these conformations are being accommodated in the MOR binding pocket. We characterized the free energy landscape of fentanyl conformations with metadynamics simulations, and compared and evaluated several possible fentanyl binding conditions in the MOR with long-timescale molecular dynamics simulations. Our results indicate that the most preferred binding pose in the MOR binding pocket corresponds well with the global minimum on the energy landscape of fentanyl in the absence of the receptor, while the energy landscape can be reconfigured by modifying the fentanyl scaffold. The interactions with the receptor may stabilize a slightly unfavored fentanyl conformation in an alternative binding pose. By extending similar investigations to fentanyl analogs, our findings establish a structureactivity relationship of fentanyl binding at the MOR. In addition to providing a structural basis to understand the potential toxicity of the emerging NSOs, such insights will contribute to developing new, safer analgesics. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

Automated summary

Fentanyl and its analogs are selective agonists of the l-opioid receptor, but the binding mechanism of fentanyl at the receptor is still not fully understood. This study used computational methods to investigate the preferred conformations of fentanyl and how they bind to the receptor. The results showed that the most preferred binding pose in the receptor corresponds to the global minimum on the energy landscape of fentanyl, and the interactions with the receptor can stabilize unfavorable fentanyl conformations. These findings provide insights into the potential toxicity of new synthetic opioids and contribute to the development of safer analgesics.