Dataset Information

How mu-Opioid Receptor Recognizes Fentanyl.

ABSTRACT: The opioid crisis has escalated during the COVID-19 pandemic. More than half of the overdose-related deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, crystal structures of mOR complexed with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like synthetic opioids remains lacking. Exploiting the X-ray structure of mOR bound to a morphinan ligand and several state-of-the-art simulation techniques, including weighted ensemble and continuous constant pH molecular dynamics, we elucidated the detailed binding mechanism of fentanyl with mOR. Surprisingly, in addition to the orthosteric site common to morphinan opiates, fentanyl can move deeper and bind mOR through hydrogen bonding with a conserved histidine H297, which has been shown to modulate mOR's ligand affinity and pH dependence in mutagenesis experiments, but its precise role remains unclear. Intriguingly, the secondary binding mode is only accessible when H297 adopts a neutral HID tautomer. Alternative binding modes and involvement of tautomer states may represent general mechanisms in G protein-coupled receptor (GPCR)-ligand recognition. Our work provides a starting point for understanding mOR activation by fentanyl analogs that are emerging at a rapid pace and assisting the design of safer analgesics to combat the opioid crisis. Current protein simulation studies employ standard protonation and tautomer states; our work demonstrates the need to move beyond the practice to advance our understanding of protein-ligand recognition.

SUBMITTER: Vo QN

PROVIDER: S-EPMC7491576 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

How mu-Opioid Receptor Recognizes Fentanyl.

Vo Quynh N QN Mahinthichaichan Paween P Shen Jana J Ellis Christopher R CR

Research square 20200909

The opioid crisis has escalated during the COVID-19 pandemic. More than half of the overdose-related deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, crystal structures of mOR complexed with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like synthetic opioids remains lacking. Exploiting the X-ray structure of mOR bound to a morphinan ligand and several state ...[more]

PMID: 32935088

Similar Datasets

Project description:Interactions of 21 fentanyl derivatives with μ-opioid receptor (μOR) were studied using experimental and theoretical methods. Their binding to μOR was assessed with radioligand competitive binding assay. A uniform set of binding affinity data contains values for two novel and one previously uncharacterized derivative. The data confirms trends known so far and thanks to their uniformity, they facilitate further comparisons. In order to provide structural hypotheses explaining the experimental affinities, the complexes of the studied derivatives with μOR were modeled and subject to molecular dynamics simulations. Five common General Features (GFs) of fentanyls' binding modes stemmed from these simulations. They include: GF1) the ionic interaction between D147 and the ligands' piperidine NH⁺ moiety; GF2) the N-chain orientation towards the μOR interior; GF3) the other pole of ligands is directed towards the receptor outlet; GF4) the aromatic anilide ring penetrates the subpocket formed by TM3, TM4, ECL1 and ECL2; GF5) the 4-axial substituent (if present) is directed towards W318. Except for the ionic interaction with D147, the majority of fentanyl-μOR contacts is hydrophobic. Interestingly, it was possible to find nonlinear relationships between the binding affinity and the volume of the N-chain and/or anilide's aromatic ring. This kind of relationships is consistent with the apolar character of interactions involved in ligand⁻receptor binding. The affinity reaches the optimum for medium size while it decreases for both large and small substituents. Additionally, a linear correlation between the volumes and the average dihedral angles of W293 and W133 was revealed by the molecular dynamics study. This seems particularly important, as the W293 residue is involved in the activation processes. Further, the Y326 (OH) and D147 (Cγ) distance found in the simulations also depends on the ligands' size. In contrast, neither RMSF measures nor D114/Y336 hydrations show significant structure-based correlations. They also do not differentiate studied fentanyl derivatives. Eventually, none of 14 popular scoring functions yielded a significant correlation between the predicted and observed affinity data (R < 0.30, n = 28).

Dataset Information

How mu-Opioid Receptor Recognizes Fentanyl.

Publications

How mu-Opioid Receptor Recognizes Fentanyl.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets