Optimization of a Series of Mu Opioid Receptor (MOR) Agonists with High G Protein Signaling Bias

Kennedy, Nicole; Schmid, Cullen L.; Ross, Nicolette C.; Lovell, Kimberly M.; Yue, Zhizhou; Chen, Yen Ting; Cameron, Michael D.; Bohn, Laura M.; Bannister, Thomas D.

doi:10.1021/acs.jmedchem.8b01136

Cited by 53 publications

(55 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A recent report, however, challenges the bias hypothesis as a mechanism for the lower respiratory depression potential of SR-17018 compared to morphine (also see Table 1 ). In 2018, a follow-up study from the same groups looked at iteratively optimizing and expanding the SARs of this series (with modification of the substituents and the central ring size) while analyzing bias factors, which the authors referred to as “bias-focused SAR study” [ 34 ]. This work also shed light on other DMPK parameters such as cytochrome P450 inhibition, suitable half-life, and even microsomal stability.…”

Section: Mor Biased Agonismmentioning

confidence: 99%

Biased Opioid Ligands

2020

View full text Add to dashboard Cite

Achieving effective pain management is one of the major challenges associated with modern day medicine. Opioids, such as morphine, have been the reference treatment for moderate to severe acute pain not excluding chronic pain modalities. Opioids act through the opioid receptors, the family of G-protein coupled receptors (GPCRs) that mediate pain relief through both the central and peripheral nervous systems. Four types of opioid receptors have been described, including the μ-opioid receptor (MOR), κ-opioid receptor (KOR), δ-opioid receptor (DOR), and the nociceptin opioid peptide receptor (NOP receptor). Despite the proven success of opioids in treating pain, there are still some inherent limitations. All clinically approved MOR analgesics are associated with adverse effects, which include tolerance, dependence, addiction, constipation, and respiratory depression. On the other hand, KOR selective analgesics have found limited clinical utility because they cause sedation, anxiety, dysphoria, and hallucinations. DOR agonists have also been investigated but they have a tendency to cause convulsions. Ligands targeting NOP receptor have been reported in the preclinical literature to be useful as spinal analgesics and as entities against substance abuse disorders while mixed MOR/NOP receptor agonists are useful as analgesics. Ultimately, the goal of opioid-related drug development has always been to design and synthesize derivatives that are equally or more potent than morphine but most importantly are devoid of the dangerous residual side effects and abuse potential. One proposed strategy is to take advantage of biased agonism, in which distinct downstream pathways can be activated by different molecules working through the exact same receptor. It has been proposed that ligands not recruiting β-arrestin 2 or showing a preference for activating a specific G-protein mediated signal transduction pathway will function as safer analgesic across all opioid subtypes. This review will focus on the design and the pharmacological outcomes of biased ligands at the opioid receptors, aiming at achieving functional selectivity.

show abstract

Section: Mor Biased Agonismmentioning

confidence: 99%

Biased Opioid Ligands

2020

View full text Add to dashboard Cite

show abstract

“…Recently, our lab reported on a series of biased MOR agonists surveying many degrees of bias from 0.4-to 100-fold preference as measured by either GTPgS binding or cAMP accumulation versus either barr2 recruitment PathHunter enzymatic complementation (Eurofins DiscoverX, Fremont, CA) or recruitment of green fluorescent protein-conjugated barr2 (59,60). The compounds are N-benzylpiperidine 4benzimidazolones, and an example of SR-17018 is shown in Figure 2.…”

Section: Development Of Agonists That Promote G Protein Signaling Ovementioning

confidence: 99%

Toward Directing Opioid Receptor Signaling to Refine Opioid Therapeutics

Grim

Acevedo‐Canabal

Bohn

2020

Biological Psychiatry

Self Cite

View full text Add to dashboard Cite

The mu opioid receptor (MOR) is a diversely regulated target for the alleviation of pain in the clinical setting. However, untoward side effects such as tolerance, dependence, respiratory suppression, constipation, and abuse liability detract from the general activation of these receptors. Studies in genetically modified rodent models suggest that activating G protein signaling pathways while avoiding phosphorylation of the receptor or recruitment of b-arrestin scaffolding proteins could preserve the analgesic properties of MOR agonists while avoiding certain side effects. With the development of novel MOR "biased" agonists, which lead to preferential activation of G protein pathways over receptor phosphorylation, internalization, or interaction with other effectors, this hypothesis can be tested in a native, physiological setting. Overall, it is clear that the MOR is not a simple on-off switch and that the diverse means by which the receptor can be regulated may present an opportunity to refine therapeutics for the treatment of pain.

show abstract

“…Most excitingly, fentanyl has its place also in the most up-to-date trends of pain pharmacology that is in the research on biased μOR agonists which holds promise for finding strong analgesics without adverse effects. Although fentanyl itself or sufentanil are able to very effectively elicit unwanted (connected to adverse effects) β-arrestin recruitment [ 18 ], structurally close lie compounds with much higher preference for G-protein activation [ 19 ]. Another fascinating possibility for developing safer analgesic agents opens up with pH-dependent opioid agonists.…”

Section: Introductionmentioning

confidence: 99%

Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis

et al. 2019

View full text Add to dashboard Cite

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).

show abstract

Optimization of a Series of Mu Opioid Receptor (MOR) Agonists with High G Protein Signaling Bias

Cited by 53 publications

References 32 publications

Biased Opioid Ligands

Biased Opioid Ligands

Toward Directing Opioid Receptor Signaling to Refine Opioid Therapeutics

Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis

Contact Info

Product

Resources

About