scholarly journals How µ-Opioid Receptor Recognizes Fentanyl

Author(s):  
Quynh N. Vo ◽  
Paween Mahinthichaichan ◽  
Jana Shen ◽  
Christopher R. Ellis

AbstractIn 2019, drug overdose has claimed over 70,000 lives in the United States. More than half of the deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, the crystal structures of mOR in complex 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 forming a salt-bridge with Asp1473.32 in the orthosteric site common to morphinan opiates, fentanyl can move deeper and bind mOR through hydrogen bonding with a conserved histidine His2976.52, 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 His297 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 the molecular basis of mOR activation by fentanyl which has many analogs emerging at a rapid pace. The knowledge may also inform 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.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Quynh N. Vo ◽  
Paween Mahinthichaichan ◽  
Jana Shen ◽  
Christopher R. Ellis

AbstractRoughly half of the drug overdose-related deaths in the United States are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, X-ray crystal structures of mOR in complex with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like opioids remains lacking. Exploiting the X-ray structure of BU72-bound mOR and several molecular simulation techniques, we elucidated the detailed binding mechanism of fentanyl. Surprisingly, in addition to the salt-bridge binding mode common to morphinan opiates, fentanyl can move deeper and form a stable hydrogen bond with the conserved His2976.52, which has been suggested to modulate mOR’s ligand affinity and pH dependence by previous mutagenesis experiments. Intriguingly, this secondary binding mode is only accessible when His2976.52 adopts a neutral HID tautomer. Alternative binding modes may represent a general mechanism in G protein-coupled receptor-ligand recognition.


2020 ◽  
Author(s):  
Quynh Vo ◽  
Paween Mahinthichaichan ◽  
Jana Shen ◽  
Christopher Ellis

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.


2021 ◽  
Author(s):  
Cheng Zhang ◽  
Heng Liu ◽  
Dapeng Sun ◽  
Alexander Myasnikov ◽  
Marjorie Damian ◽  
...  

Abstract The 'hunger hormone' ghrelin activates the ghrelin receptor GHSR to stimulate food intake and growth hormone secretion and regulate reward signaling. Acylation of ghrelin at Ser3 is required for its agonistic action on GHSR. Synthetic agonists of GHSR are under clinical evaluation for disorders related to appetite and growth hormone dysregulation. Here, we report high-resolution cryo-EM structures of the GHSR-Gi signaling complex with ghrelin and the non-peptide agonist ibutamoren as an investigational new drug. Our structures together with mutagenesis data reveal the molecular basis for the binding of ghrelin and ibutamoren. The structural comparison suggests a salt bridge and an aromatic cluster near the agonist-binding pocket as important structural motifs in receptor activation. Notable variations of the Gi binding mode are observed in our cryo-EM analysis, indicating the highly dynamic nature of Gi-coupling to GHSR. Our results provide a framework for understanding GHSR signaling and developing new GHSR agonist drugs.


2018 ◽  
Author(s):  
Zhuoyao Chen ◽  
Sarah Picaud ◽  
Panagis Filippakopoulos ◽  
Vincenzo D’Angiolella ◽  
Alex N. Bullock

SUMMARYBTB-Kelch proteins form the largest subfamily of Cullin-RING E3 ligases, yet their substrate complexes are mapped and structurally characterized only for KEAP1 and KLHL3. KLHL20 is a related CUL3-dependent ubiquitin ligase linked to autophagy, cancer and Alzheimer’s disease that promotes the ubiquitination and degradation of substrates including DAPK1, PML and ULK1. We identified a ‘LPDLV’-containing recruitment site in the DAPK1 death domain and determined the 1.1 Å crystal structure of a KLHL20-DAPK1 complex. DAPK1 binds to KLHL20 as a loose helical turn that inserts deeply into the central pocket of the Kelch domain to contact all six blades of the β-propeller. Here, KLHL20 forms a salt bridge as well as hydrophobic interactions that include a tryptophan and cysteine residue ideally positioned for covalent inhibitor development. The structure highlights the diverse binding modes of circular substrate pockets versus linear grooves and suggests a novel E3 ligase for protac-based drug design.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tingting Tang ◽  
Christin Hartig ◽  
Qiuru Chen ◽  
Wenli Zhao ◽  
Anette Kaiser ◽  
...  

AbstractThe human neuropeptide Y (NPY) Y2 receptor (Y2R) plays essential roles in food intake, bone formation and mood regulation, and has been considered an important drug target for obesity and anxiety. However, development of drugs targeting Y2R remains challenging with no success in clinical application yet. Here, we report the crystal structure of Y2R bound to a selective antagonist JNJ-31020028 at 2.8 Å resolution. The structure reveals molecular details of the ligand-binding mode of Y2R. Combined with mutagenesis studies, the Y2R structure provides insights into key factors that define antagonistic activity of diverse antagonists. Comparison with the previously determined antagonist-bound Y1R structures identified receptor-ligand interactions that play different roles in modulating receptor activation and mediating ligand selectivity. These findings deepen our understanding about molecular mechanisms of ligand recognition and subtype specificity of NPY receptors, and would enable structure-based drug design.


2020 ◽  
Vol 5 (5) ◽  
pp. 1175-1187
Author(s):  
Rachel Glade ◽  
Erin Taylor ◽  
Deborah S. Culbertson ◽  
Christin Ray

Purpose This clinical focus article provides an overview of clinical models currently being used for the provision of comprehensive aural rehabilitation (AR) for adults with cochlear implants (CIs) in the Unites States. Method Clinical AR models utilized by hearing health care providers from nine clinics across the United States were discussed with regard to interprofessional AR practice patterns in the adult CI population. The clinical models were presented in the context of existing knowledge and gaps in the literature. Future directions were proposed for optimizing the provision of AR for the adult CI patient population. Findings/Conclusions There is a general agreement that AR is an integral part of hearing health care for adults with CIs. While the provision of AR is feasible in different clinical practice settings, service delivery models are variable across hearing health care professionals and settings. AR may include interprofessional collaboration among surgeons, audiologists, and speech-language pathologists with varying roles based on the characteristics of a particular setting. Despite various existing barriers, the clinical practice patterns identified here provide a starting point toward a more standard approach to comprehensive AR for adults with CIs.


2017 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>


2018 ◽  
Author(s):  
Samuel Gill ◽  
Nathan M. Lim ◽  
Patrick Grinaway ◽  
Ariën S. Rustenburg ◽  
Josh Fass ◽  
...  

<div>Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes.</div><div><br></div><div>In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.</div>


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