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What structural features make a molecule a potent opioid receptor agonist?

What structural features make a molecule a potent opioid receptor agonist?



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For instance, take morphine. It is used as a baseline for measuring the potency of opioid agonists. Its structure looks like this:

But then, take heroin, around three times as potent, its structure is this:

6-Monoacetylmorphine is around 30% more potent than heroin itself:

If, however, the acetyl group is bonded to the top instead of the bottom, the resulting substance is less active than heroin. U-47700, a research chemical, has a totally different structure but has around 7.5 times the potency of morphine in animal models:

Desomorphine is 8-10 times more potent as morphine:

Oxymorphone is 10 times as potent as morphine:

The common explanation that I've heard for these substances being potent opioid agonists is that they mimic the endorphins produced in the human brain. However, Beta-Endorphin is 18-33 times more potent than morphine, and its structure is thus:

That looks absolutely nothing like any of the substances mentioned above. How can molecules with structures so radically different from those of endorphins mimic the action of endorphins? And how come U-47700 has a potency similar to the more powerful morphine analogues but looks nothing like them?

But then, there's Fentanyl:

100 times more potent than morphine, making it a more powerful Opioid receptor agonist than the body's own endorphins, and its structure looks nothing like them or any of the other ones so far. Other analogues are even more potent. So what is it about a molecule's structure that makes it a potent opioid? The only structural similarity that I can spot is the presence of a tertiary amine group in the structure. And how does U-47700 have a potency similar to the more powerful morphine analogues?


Specific parts - moieties - of an agonist molecule bind to the receptor protein, causing the receptor to change shape, which in turn initiates a signaling pathway inside the cell.

Some agonists are better at causing the receptor to change to its "optimal shape" for relaying signal. These are called "full agonists".

Other agonists cause a partial change in receptor shape and reduced signal. These are called "partial agonists". The strength of the resulting signal is called "efficacy".

In addition to differences in efficacy between agonists, the parts of the agonist that bind to receptors can have a different chemical makeup and so create a different environment of electrostatic attractions and van der Waals forces between atoms in the agonist and in the atoms in the binding site in the receptor. Agonists that bind more strongly will stay bound to the receptor longer. These are said to have higher "affinity". Agonists that bind more weakly have lower affinity.

It is affinity and efficacy together that determine potency, or how well an agonist works.

In a biological environment, as well, these agonists swim in a pool with other agonist and antagonist molecules. For example, your agonist of interest might do a good job of changing a receptor's shape, but if it binds weakly, it will "pop off" the receptor quickly - perhaps too quickly to trigger the necessary signal. Another, different agonist molecule comes in and binds more tightly, but it doesn't create as strong a signal. Or perhaps a passing antagonist molecule floats around and pops onto the receptor, stopping any signal from that receptor and also keeping any agonist molecules from binding again for a while.

The population of agonists, antagonists, and receptors all change the number and kinds of binding events that take place, which determines whether you get the signal you want, as strong as you want it.

While the opioid molecules you are looking at have different numbers and varieties of atoms, it is the molecule's shape and electrochemistry that matter. Most specifically, it will be the part of the agonist molecule that actually binds to the receptor that matters most: how well it causes a conformal change in the receptor, and how strongly it binds.

These molecules could look very different from one another, but ultimately it is the part of the molecule that binds to the receptor, and how well it binds, that matters.

I don't know about the receptor-ligand kinetics of how different opioids bind to pain receptors, specifically, but hopefully there is some terminology in this answer that helps with further research.


I think you are confusing potency with receptor affinity.

The (unsourced) numbers you indicate appear to be DEA-style "potency", which probably refer to the effective dose (of some kind).

The fentanyl to morphine ratio on the κ-opioid receptor affinity, from human studies is only 1.35 to 1.14 (on average). In contrast the N-methyl fentanyl is estimated from animal studies to have a receptor affinity of around 18,000 (±3,000).

As pointed in the other answer, there numerous other issues besides receptor affinity that affect potency, like bioavailability by the various administration routes.

Receptor affinity alone is somewhat easier to deal with (e.g. in computational chemistry models), e.g. by "molecular docking":

Molecular docking, a type of virtual screening, places compounds or ligands into potential binding poses within the binding site of a biological target and assesses binding affinity with a scoring function. The scoring function evaluates the non-covalent interactions between the ligand and target to provide a binding energy (score) which can be used to rank compounds with increasing binding affinity

It's actually quite difficult to measure receptor affinity in practice; there's a large margin of error, better shown in this graph, from the source that that previous table is based on for human studies.

Also there are three opioid receptors to worry about. (The graph above is for μ.)

I think the reason why fentanyl (and its derivatives) is stronger than morphine in analgesic test is/are largely unknown. According to a 2014 paper

A large number of fentanyl analogs have been synthesized and structure activity relationships revealed, but the knowledge of their action is still incomplete and many questions remain unanswered. In general, the order of activity at receptor parallels that of binding affinity. However, the comparison of ED50 values, for μ- analgesics with their IC50 and Kd numbers at the corresponding binding site does not always correlate with experimental data. How to explain, why fentanyl (6), methylfentanyl (42), sufentanil (88), lofentanil (82) are more potent than it would be suggested from obtained binding values. Another example, the Kd of ohmefentanyl for the μ- site is approximately 5-10-times less than that of morphine, but it is nearly 7000-times more potent than morphine in analgesic tests. There is another contradiction, absence of correlation between lipid solubility and analgesic effect [195,196]. Another observation is that **in general fentanyls are compounds with the highest affinity for the μ-receptor and the most potency at that receptor. However not all fentanyl derivatives are highly μ- selective. They also produce actions through δ- and κ- receptors. Lofentanil (82) is the least and R30490 (90), are the most μ-selective compounds, among fentanyl series. Although their structures are very close, and affinities at the μ-receptor are similar, R30490 displays much lower δ- and κ-affinities than lofentanil.


Development of a Bioavailable μ Opioid Receptor (MOPr) Agonist, δ Opioid Receptor (DOPr) Antagonist Peptide That Evokes Antinociception without Development of Acute Tolerance

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What structural features make a molecule a potent opioid receptor agonist? - Biology

μ opioid receptors mediate the analgesia induced by morphine. Prolonged use of morphine causes tolerance development and dependence. To investigate the molecular basis of tolerance and dependence, the cloned mouse μ opioid receptor with an amino-terminal epitope tag was stably expressed in human embryonic kidney (HEK) 293 cells, and the effects of prolonged opioid agonist treatment on receptor regulation were examined. In HEK 293 cells the expressed μ receptor showed high affinity, specific, saturable binding of radioligands and a pertussis toxin-sensitive inhibition of adenylyl cyclase. Pretreatment (1 h, 3 h, or overnight) of cells with 1 μ M morphine or [ D -Ala 2 MePhe 4 ,Gly(ol) 5 ]enkephalin (DAMGO) resulted in no apparent receptor desensitization, as assessed by opioid inhibition of forskolin-stimulated cAMP levels. In contrast, the morphine and DAMGO pretreatments (3 h) resulted in a 3-4-fold compensatory increase in forskolin-stimulated cAMP accumulation. The opioid agonists methadone and buprenorphine are used in the treatment of addiction because of a markedly lower abuse potential. Pretreatment of μ receptor-expressing HEK 293 cells with methadone or buprenorphine abolished the ability of opioids to inhibit adenylyl cyclase. No compensatory increase in forskolin-stimulated cAMP accumulation was found with methadone or buprenorphine these opioids blocked the compensatory effects observed with morphine and DAMGO. Taken together, these results indicate that methadone and buprenorphine interact differently with the mouse μ receptor than either morphine or DAMGO. The ability of methadone and buprenorphine to desensitize the μ receptor and block the compensatory rise in forskolin-stimulated cAMP accumulation may be an underlying mechanism by which these agents are effective in the treatment of morphine addiction.


Abstract

We have previously described opioid peptidomimetic, 1, employing a tetrahydroquinoline scaffold and modeled on a series of cyclic tetrapeptide opioid agonists. We have recently described modifications to these peptides that confer a μ opioid receptor (MOR) agonist, δ opioid receptor (DOR) antagonist profile, which has been shown to reduce the development of tolerance to the analgesic actions of MOR agonists. Several such bifunctional ligands have been reported, but none has been demonstrated to cross the blood–brain barrier. Here we describe the transfer of structural features that evoked MOR agonist/DOR antagonist behavior in the cyclic peptides to the tetrahydroquinoline scaffold and show that the resulting peptidomimetics maintain the desired pharmacological profile. Further, the 4R diastereomer of 1 was fully efficacious and approximately equipotent to morphine in the mouse warm water tail withdrawal assay following intraperitoneal administration and thus a promising lead for the development of opioid analgesics with reduced tolerance.


RESULTS

Activation-related changes in the DOP

Both agonist-bound structures are in an activated state. Unless otherwise indicated, we will use the higher-resolution BRIL-DOP-KGCHM07 structure for comparison with previously published inactive-state antagonist-bound DOP structures [Protein Data Bank (PDB) 4N6H and 4RWD] (16, 17) and with active-state structures of the MOP (PDB 5C1M and 6DDF) (18, 20) and KOP (PDB 6B73) (19). First, the agonist-bound DOP structures display large outward movements of the intracellular parts of helices V (4.5 Å) and VI (9.4 to 11.2 Å), and a 3.9 Å inward movement of helix VII (Fig. 2A), which is a common feature of the active conformational states of GPCRs (21). The shift of helix VII at the level of residue N314 7.49 [superscripts according to the Ballesteros and Weinstein numbering (22)] (Fig. 3A), which leads to a collapse of the allosteric sodium-binding pocket in active-state GPCR structures (23), is even more pronounced in the determined DOP structures as compared to the active MOP and KOP (Fig. 3B and fig. S1). However, this greater shift of N314 7.49 in the DOP might be affected by three mutations in the sodium-binding pocket (N90 2.45 S, D95 2.50 G, N131 3.35 S) that were introduced during construct design. The activation-related outward movement of helix VI at the level of residue F270 6.44 is greater in the agonist-bound DOP than in the MOP and KOP. On the contrary, the very tips of helix VI (at position 6.28 as a reference) are more tilted by 4 to 6 Å in the active-state MOP and KOP (fig. S1), likely due to the bound G protein or nanobody, respectively, pushing helix VI tips further outward (24).

Fig. 2 Activation-related changes in the DOP.Comparison of conserved activation microswitches of the active-like DOP-KGCHM07 (orange) and DOP-DPI-287 (blue) structures with the inactive DOP-naltrindole structure (yellow, PDB 4N6H). Structural superposition of the (A) overall architecture, (B) PIF motif, (C) NPxxY and DRY motifs, and (D) CWxP motif. Fig. 3 Effects of sodium-binding mutations on receptor function.Comparison of the collapsed sodium-binding pocket in DOP-KGCHM07 (orange) with (A) inactive DOP (yellow, PDB 4N6H) and (B) active MOP (purple, PDB 5C1M) with perspective from the extracellular space. Water molecules are shown as blue spheres and the Na + ion as a yellow sphere. Gi-mediated cAMP signaling of (C) sodium-binding pocket mutants and (D) crystal structure construct mutants with sodium-binding pocket mutations restored to WT residues in response to different KGCHM07 concentrations (signals normalized to WT DOP). β-Arrestin2 recruitment of (E) sodium-binding pocket mutants and (F) crystal structure construct mutants with sodium-binding pocket mutations restored to WT residues in response to different KGCHM07 concentrations (signals normalized to the G95D mutant). Results are expressed as means ± SEM from n = 4 (EPAC) or n = 3 (β-arrestin2) independent experiments, each performed in triplicate.

The rearrangements in the transmembrane helices are accompanied by several changes in the conserved microswitches that are typical for GPCR activation (24, 25). Included are changes in the so-called P-I-F motif, where P225 5.50 moves inward by

1.6 Å, forcing the I136 3.40 side chain to change its rotamer state and facilitating a major rotation of the bulky side chain of F270 6.44 (Fig. 2B) toward helix V by as much as

3.5 Å at the Cγ atoms. For comparison, this movement is only

2.6 Å in the active-state MOP and KOP structures. The P-I-F motif changes are coupled with rearrangements in the NP 7.50 xxY motif, collapsing the sodium-binding pocket, with a

3.5 Å inward shift of N314 7.49 . Another residue of the sodium pocket and the NP 7.50 xxY motif, Y318 7.53 , switches its side-chain rotamer to a downward orientation, opening the intracellular entrance to the sodium pocket (Fig. 2C).

The overall conformation of the conserved DR 3.50 Y motif remains largely unaltered between the active-like agonist-bound and the inactive-state DOP structures (Fig. 2C). Notably, the importance of the DRY motif in maintaining the inactive state in most GPCRs is attributable to a strong salt bridge between D 3.49 and R 3.50 residues. However, in all inactive-state structures of the DOP and other opioid receptors, this salt bridge is already disrupted, displaying distances of >3.5 Å. Moreover, the differences due to activation in the corresponding MOP and KOP structures manifest only in the side-chain reorientation of R 3.50 that directly interacts with the G protein (20) or nanobody (18, 19), which are lacking in the DOP structures. To assess the activation state more rigorously, we evaluated the two new DOP structures along with previously solved opioid receptor structures for their activation-related conformations of microswitches using a GAUGE machine learning–based prediction tool (see Materials and Methods for details). All the microswitches in the new DOP structures, except the DRY motif, were predicted to be in the active-like or fully activated state (table S2).

Sodium pocket mutations allow receptor stabilization and control receptor function

The conserved site involved in binding of the negative allosteric modulator sodium in the DOP (16) was found to be collapsed in both agonist-bound DOP structures, similar to other class A GPCR structures determined in active or active-like states (Fig. 3, A and B) (18, 23). In our case, three mutations in the sodium pocket (N90 2.45 S, D95 2.50 G, N131 3.35 S) apparently facilitated sodium expulsion and the collapse of the pocket, thereby stabilizing the receptor in an active-like state (Supplementary Text). A major decrease in thermostability was seen for agonist-bound DOP constructs lacking any of these mutations, which underlines their critical importance in thermostabilizing the agonist-bound DOP (fig. S2). However, the crystal construct retained high-affinity binding for KGCHM07 (Ki WT, 5.17 ± 1.57 nM Ki crystal construct, 1.24 ± 0.23 nM), DPI-287 (Ki WT, 0.39 ± 0.12 nM Ki crystal construct, 1.86 ± 0.23 nM), and [ 125 I]-deltorphin I (Kd WT, 1.11 nM Kd crystal construct, 4.34 nM), indicating that the authenticity of the agonist-bound DOP binding pocket was not affected by the introduced point mutations (Fig. 1).

It is well established that mutations in the sodium-binding pocket can result in altered signaling properties (16), and our crystal structure construct lacked agonist-induced cyclic adenosine monophosphate (cAMP) response and β-arrestin2 recruitment (Fig. 3, C to F, and table S1). Our mutagenesis studies revealed that the DOP WT with the single point mutation D95 2.50 G could be activated neither by KGCHM07 nor by DPI-287, while the agonist binding affinities were virtually unaltered (table S1). This is in contrast to a previously investigated D95 2.50 A mutation that reduced the potency of the DPI-287–related agonist BW373U86 but maintained G protein signaling and β-arrestin recruitment (16). The G95 2.50 D mutation in the crystal structure construct (reversing residue 2.50 back to WT) restored both cAMP and β-arrestin2 signaling fully (KGCHM07) or partially (DPI-287) (Fig. 3, C to F fig. S3 and table S1).

Our mutagenesis experiments showed elevated basal responses in both cAMP and β-arrestin pathways for the single N131 3.35 S and a triple DOP mutant (N90 2.45 S, D95 2.50 G, N131 3.35 S), suggestive of a constitutively active receptor (Fig. 3, C to F, and fig. S3). In addition, when the signaling abilities of the crystal structure construct were evaluated, the baseline signal levels in both pathways were found to be higher than in the G95 2.50 D mutant (used to normalize the crystal construct mutants) (Fig. 3, C to F, and fig. S3). To further assess the constitutive activity of the crystal structure construct, we performed a titration assay in which the amount of receptor construct DNA increased, while the levels of the biosensor (in this case Gαi1-RLuc2 and Gγ1-GFP10) remained constant (fig. S3). Increasing amounts of the crystal structure construct produced a decay of the signal, indicative of a ligand-independent dissociation of the Gi protein subunits induced by the receptor. A similar decay of the response signal was observed when the DOP WT construct was stimulated with DPI-287, further supporting that the crystal structure construct is constitutively activating the Gi protein signaling pathway.

A common denominator for opioid receptor activation

The new DOP structures provide atomic-level insights into the key components of molecular recognition for small-molecule and peptide agonists. Most of the opioid receptor ligands share a basic, protonated nitrogen atom forming a salt-bridge interaction to D128 3.32 , which itself is connected to a polar network with potential involvement of Y308 7.43 , T101 2.56 , and Q105 2.60 linking helices II, III, and VII. In inactive-state DOP structures, this polar network can extend to Y109 2.64 , involving water-mediated interactions. However, in activated structures, the Y109 2.64 side chain shows a large rotation toward helix I, uncoupling Y109 2.64 from the polar network, a mechanism that appears to be important for DOP activation. In the case of the DOP-DPI-287 complex, the distance for anchoring interactions between the protonated amine and D128 3.32 is

3.5 Å) for the peptide KGCHM07, which shows multiple, direct, or potentially water-mediated interactions with D128 3.32 (Fig. 4, A and C). Another residue of the polar network, Y308 7.43 , forms a direct hydrogen bond to the primary amine of the peptide KGCHM07, while Y308 7.43 does not interact directly with DPI-287’s protonated amine (N4). In both structures, Y308 7.43 positioning is preserved by hydrogen bonds to D128 3.32 , and in DPI-287 by additional π-π stacking interactions with the unsubstituted benzyl moiety (Fig. 4, B and C). At the same time, T101 2.56 helps in maintaining the polar network in the DOP-DPI-287 complex by forming hydrogen bonds with both Y308 7.43 and Q105 2.60 , while the T101 2.56 side chain loses this interaction in the peptide-bound DOP-KGCHM07 complex, which uncouples it from the polar network (Fig. 4, A and C). D128 3.32 mutations to N or A virtually abolished KGCHM07 activity, while the potency of the small-molecule DPI-287 reduced 10-fold for D128 3.32 N [half maximal effective concentration (EC50), 0.060 nM versus 0.61 nM] and 30-fold for D128 3.32 A (EC50, 0.060 nM versus 1.39 nM) (Fig. 4D). Similarly, previous studies on opioid peptides reported that modifications of the N-terminal amine, including its acetylation or substitution by a methyl group, abolished agonistic activities while retaining low nanomolar affinity (26, 27). However, we were unable to determine the affinity of KGCHM07 and DPI-287 for the D128 3.32 mutants, because no [ 125 I]-deltorphin I–specific binding could be observed (table S1).

Fig. 4 Polar network around D128 3.32 and basic amine positioning as potential hallmark for opioid receptor activation.BRIL-DOP-KGCHM07, orange BRIL-DOP-DPI-287, blue naltrindole DOP antagonist structure (PDB 4N6H), yellow DIPP-NH2 DOP antagonist structure (PDB 4RWD), cyan DAMGO MOP agonist structure (PDB 6DDF), red. (A) Overview of the KGCHM07 peptide binding pocket. The omit FoFc electron density of KGCHM07 is shown in blue mesh (contoured at 3.0 σ). (B) Overview of the DPI-287 binding pocket. The omit FoFc electron density of DPI-287 is shown in orange mesh (contoured at 3.0 σ). (C) Polar network anchoring the basic amine of DOP agonists. (D) Gi-mediated cAMP signaling of D128 3.32 mutants in response to different DOP agonist concentrations (upper panel, KGCHM07 lower panel, DPI-287). (E) Docking poses of DOP agonist peptides (gray) show that all primary amines embedded deeper into the binding pocket (yellow marks), when compared to antagonist DIPP-NH2 (cyan) as indicated by the purple arrow. Similarly, the MOP-DAMGO complex (dark red) is displaced. The cyan arrow indicates related side movements of D 3.32 . For clarity, only residue one (Phe 1 or Dmt 1 ) is depicted, and the surfaces of DOP agonist KGCHM07 and DOP antagonist DIPP-NH2 are shown in orange and green mesh, respectively, to clarify its location in the binding pocket. (F) Docking poses of DOP small-molecule agonists (gray) show all substituted basic amines (N4) that penetrated deeper into the binding pocket, when compared to the antagonist naltrindole (yellow).

The basic amines of KGCHM07 and DPI-287 are embedded deeper (1.9 and 1.4 Å, respectively) into the binding pocket when compared to the equivalent amines of the DOP antagonists DIPP-NH2 (Fig. 4E) and naltrindole (Fig. 4F), resulting in the reorientation of the D128 3.32 side chain and the adjacent polar network. Furthermore, the MOP agonist BU72 (PDB 5C1M) shows the same 1.4 Å amine shift into the binding pocket when compared to a morphinan MOP antagonist (PDB 4DKL). Accordingly, the docking poses of 10 peptide and 7 small-molecule DOP agonists into our new active-like DOP structures (table S3) revealed that all respective amines were located deeper in the binding pocket when compared to DOP antagonists (Fig. 4, E and F, and fig. S4). Hydrophobic contacts with helix V or VII, or both, preclude antagonists such as DIPP-NH2 and naltrindole to extend as deep into the DOP binding pocket as shown for DOP agonists (Fig. 4F and fig. S4). Therefore, we argue that the polar network around D 3.32 plays an essential role in agonist-induced activation at the DOP and propose that the positioning of the basic amine (as opposed to antagonists) deeper into the binding pocket is a hallmark of opioid agonist activity for ligands that contain a basic amine interacting with D 3.32 .

Differences between peptide and small-molecule recognition by the DOP

Besides the abovementioned prevalent salt bridge formation, another important anchor of ligand interaction in opioid receptors is the phenol moiety that is conserved in many peptide and small-molecule ligands. Accordingly, the peptide agonist KGCHM07 contains the N-terminal tyrosine derivative 2,6-dimethyl-L-tyrosine (Dmt 1 ), which was shown to improve binding affinity and activity of peptidic ligands at opioid receptors (28). Its position is similar to the one observed for tyrosine in the active structure of MOP in complex with DAMGO [(D-Ala²,N-Me-Phe 4 , Gly-ol 5 )-enkephalin] (20), but Dmt shows additional hydrophobic contacts in the DOP binding pocket. Three water molecules were found in the KGCHM07 binding pocket, supported by weak electron densities (fig. S5). These are involved in connecting Dmt 1 to helices III, V, and VI via a polar interaction network with K214 5.39 , H278 6.52 , and Y129 3.33 , which is also effectively connected to D-Arg 2 of KGCHM07 (Fig. 4A). Furthermore, our analysis suggests that the positively charged D-Arg 2 can form a water-mediated salt bridge interaction to D210 5.35 (fig. S5), supported by a 17-fold reduction in KGCHM07 binding to the D210 5.35 N mutant. Moreover, [ 125 I]-deltorphin I, which was used as the radiotracer in these experiments, contains D-Ala 2 instead of D-Arg 2 and was not affected by D210 5.35 mutations (table S1). The lower resolution of the DPI-287 structure precluded robust identification of structural water molecules in this case. However, the energy-based prediction of water molecules suggested three tightly bound water molecules at residues H278 6.52 and Y129 3.33 , linking DPI-287 to helices III, V, and VI as likewise observed in the KGCHM07-bound structure (fig. S5).

Our mutagenesis studies showed a binding decrease to the Y129 3.33 F and Y129 3.33 A mutants by

38-fold for KGCHM07 and by about 3-fold and about 5-fold for DPI-287, respectively (table S1). This finding confirms the involvement of Y129 3.33 in water-mediated polar networks in both structures. Similarly, the EC50 in a H278 6.52 A mutant was reduced

10-fold for DPI-287. In addition, the backbone of K214 5.39 is also involved in this polar network, and a K214 5.39 A mutant did not alter the potencies of KGCHM07 or DPI-287. However, single mutations of H278 6.52 A and K214 5.39 A abolished [ 125 I]-deltorphin I binding (table S1), indicating distinct binding pocket differences between the diverse agonists.

The Phe 3 side chain of KGCHM07 extends toward helices II and III and extracellular loop 1 (ECL1) and ECL2 and is positioned in a partially hydrophobic pocket formed by Q105 2.60 , W114 ECL1 , V124 3.28 , L125 3.29 , and C198 ECL2 (Fig. 4A and fig. S4). In the designed DOP fusion protein, a K108 2.63 D mutation was introduced (Supplementary Text) located at the extracellular entrance of the binding pocket. KGCHM07 binds to the K108 2.63 D mutant with virtually unaltered affinity (table S1), and the docking of the KGCHM07 peptide into a DOP model with the K108 2.63 residue as in the WT receptor (table S3) suggests that KGCHM07 binds in the same pose as in the crystal structure. The flexible Sar 4 residue of KGCHM07 adopts an energetically less favorable cis-amide bond to Phe 3 , while all remaining amide bonds are found to be in the trans-conformation. This enables the C-terminal bistrifluoromethylated benzyl moiety to address the ECL3 region and extracellular ends of helices VI and VII. A large side-chain rotation of W284 6.58 by approximately 125°, compared to other DOP structures (Fig. 5, A and B, and fig. S4), opens a hydrophobic pocket consisting of I277 6.51 , F280 6.54 , V281 6.55 , W284 6.58 , I289 ECL3 , R291 ECL3 , and L300 7.35 , harboring the benzyl moiety. This moiety is further stabilized by π-π stacking interactions and a hydrogen bond to W284 6.58 (Fig. 4A).

Fig. 5 Activation-related changes in the ECL3 region of the DOP and structural basis for DPI-287 selectivity.Comparison of ECL3 conformations between (A) inactive (naltrindole, yellow, PDB 4N6H and DIPP-NH2, cyan, PDB 4RWD) and (B) active DOP binding pockets (DOP-KGCHM07, orange DOP-DPI-287, blue). (C) Alignment of agonist-bound opioid receptor binding pockets. Pocket-forming residues are shown as sticks, with labels indicating Ballesteros-Weinstein nomenclature (22) and red numbers pointing to nonconserved residues. Note that the E 6.58 side chain of the KOP is not resolved in the KOP structure. (D) Opioid receptor sequence alignment of the nonconserved ECL3 (light red box) and the region close to the extracellular ends of helices VI and VII. The amino acids of MOP (E312) and KOP (H304) corresponding to DOP’s R291 in the ECL3 region are highlighted in light red.

Structural basis for the selectivity of DOP agonists

The activated conformation of the DOP reveals contraction of the orthosteric binding pocket around the agonists. Helix VI moves into the agonist-binding pocket by 1.6 Å, while helix VII undergoes a 2.5 Å sideways movement (fig. S1). These helix movements close to the binding pocket result in conformational changes in the ECL3 region as compared to antagonist binding pockets. In the inactive state, R291 ECL3 stabilizes the ECL3 region by forming hydrogen bonds with the carbonyl functions of V287 6.61 and W284 6.58 (Fig. 5A) (16). In the KGCHM07-bound structure, a large movement (10.0 Å based on the guanidine carbon) of R291 ECL3 into the binding pocket can be observed, resulting in the disruption of this hydrogen bond network (Fig. 5B). The side chain of R291 ECL3 is, therefore, more flexible in the agonist-bound DOP, and its electron densities only allowed us to model the full R291 ECL3 residue in chain A of the BRIL-DOP-KGCHM07 structure, where it forms a lid over the hydrophobic pocket harboring KGCHM07’s bistrifluoromethylated benzyl moiety. Although KGCHM07 is not DOP-selective because it also activates MOP (13), our BRIL-DOP-KGCHM07 structure reveals that R291 ECL3 is accessible to the agonist binding pocket and is likely to play a role in the selectivity of DOP-binding peptides, as the MOP has a glutamic acid and the KOP has a histidine in the same position (Fig. 5D).

The small-molecule DPI-287 is

10-fold selective for DOP over MOP (Ki DOP, 0.39 ± 0.12 nM Ki MOP, 3.17 ± 0.27 nM). Our docking studies revealed that more selective analogs bind in the same binding pose as DPI-287, as described in the next section (Fig. 6), revealing that the N,N-diethylbenzamide moiety interacts with the nonconserved extracellular ends of helices VI and VII. The amide forms multiple hydrophobic contacts within a pocket consisting of V281 6.55 , F280 6.54 , W284 6.58 , and L300 7.35 (Figs. 4B and 5C). Structural comparison with other opioid receptors reveals that the N,N-diethylbenzamide moiety of DPI-287 and analogs cannot occupy the same receptor space in the MOP and KOP as in the DOP due to steric interactions in positions 6.58 [charged in the case of MOP (K305) and KOP (E297)] and 7.35 (W320 in the MOP and Y312 in the KOP) (Fig. 5, C and D). Therefore, any larger substitution of L300 7.35 would prevent beneficial hydrophobic contacts due to steric clashes. On the other hand, replacing W284 6.58 with charged side chains would also make the subpocket less favorable for forming hydrophobic interactions.

Fig. 6 Docking pose of DPI-287–related DOP agonists.(A) Alignment of the docking pose of the selected DPI-287 analogs BW373U86, SNC-80, and SNC-162 (all gray) with DPI-287 (blue). The blue box indicates the moiety with differences between these three docked analogs. (B) Docking pose of a DPI-287 analog with N-3,4-(methylenedioxy)benzyl substitution (green) and lacking the phenolic hydroxy function into a DOP model derived from the DOP-DPI-287 structure with G95 2.50 D, S131 3.35 N, and D108 2.63 K reversed to WT, superimposed with DPI-287 (blue). The surface of the derivative is shown in green, and the black arrow indicates that the ligand is able to penetrate deeper into the entrance of the former sodium-binding pocket. (C) Superposition of the docking poses of DPI-130 (brown) and DPI-3290 (yellow) with DPI-287 suggests that the rotated W284 6.58 is essential for DOP binding. (D) Chemical structures and DOP binding properties (human opioid receptors) of (+)-BW373U86, SNC-80, and SNC-162 (29). (E) Chemical structures and binding properties (rat opioid receptors) of DPI-130 and DPI-3290 (32).

Structure-activity relationship of benzamide DOP agonists

The two new structures of DOP bound to a peptide and small-molecule agonist provide the structural basis for evaluating the key fingerprints that determine DOP selectivity. We performed molecular docking of several small-molecule analogs of DPI-287 at the DOP, MOP, and KOP (table S3). Docking of the selected DPI-287 analogs (+)-BW373U86, SNC-80, and SNC-162 (Fig. 6D) showed that these ligands assume the same orientation as that of DPI-287 with comparable docking scores at the DOP, whereas they exhibited much weaker docking scores at the MOP and KOP. Within this series of compounds, the phenolic hydroxy function of (+)-BW373U86 was either methylated (SNC-80) or removed (SNC-162), which interferes with their ability to form polar interactions. Previous work reported a reduced DOP affinity of these ligands by approximately twofold and approximately sevenfold, respectively, which is in agreement with the decrease of DPI-287 binding to mutants of Y129 3.33 , one residue that interacts with the phenolic function of DPI-287 (table S1). Increased DOP selectivity was observed with phenolic moiety lacking (Fig. 6D) (29). However, the DOP docking poses of the respective benzyl moieties of SNC-80 and SNC-162 are overlapping with the phenol ring of DPI-287 in the new crystal structure (Fig. 6A), indicating that the water-mediated phenol interactions are not as important in the DOP as in the MOP.

(+)-BW373U86 differs from the cocrystallized DPI-287 only by its N4-allyl moiety but occupies the same position as DPI-287, while the allyl group overlaps with DPI-287’s N4-benzyl moiety. In contrast, the bulkier N4-benzyl group of DPI-287 extends further into the entrance of the sodium-binding pocket. Conformational changes of W274 6.48 of the CW 6.48 xP motif are essential for opening up the required space for the benzyl moiety (Fig. 2D). Moreover, it has been shown that substitution of the benzyl group with even larger residues like the N-3,4-(methylenedioxy)benzyl moiety (Fig. 6B) can be beneficial for DOP affinity (30). The docking pose of this analog reveals that it can penetrate further into the entrance of the sodium-binding pocket with only minor adjustment in the pocket-lining side chains, stabilized by a hydrogen bond to S311 7.46 (Fig. 6B). These findings indicate that the sodium-binding pocket can be targeted by ligand interactions in the DOP, as suggested for other GPCRs (23). However, the functional activity of ligands can be affected by further intrusion into the sodium pocket, as recently shown for the leukotriene B4 receptor in complex with a bitopic ligand protruding deep into the sodium pocket. That ligand no longer activated the receptor but acted as an antagonist with inverse agonistic activity (31). The two N-(3-fluorophenyl)-N-methylbenzamide derivatives DPI-130 and DPI-3290 (32) differ from DPI-287 mostly in the bulkier benzamide moiety in the meta-position of the phenyl ring (Fig. 6E). Our docking studies show that the rotation of the W284 6.58 side chain, as observed in the DOP-KGCHM07 complex, can open up space for the 3-fluorophenyl moiety and stabilize it via π-π stacking interactions (Fig. 6C).

The piperazine ring of DPI-287 is represented in the energy-minimized chair conformation with axial methyl groups. Moreover, a conformational energy assessment predicted the axial methyl conformations as more favorable than the equatorial ones (−153.43 kJ/mol versus −109.81 kJ/mol). Methyl groups in the axial position are able to form hydrophobic contacts to Y129 3.33 , M132 3.36 , I304 7.39 , and Y308 7.43 , thereby perfectly occupying the additional binding pocket space. Furthermore, all docked analogs with the same trans-dimethyl substitutions showed axial methyl conformations (Figs. 4F and 6, A to C).


Conclusions

In the present study AN81 (H-Dmt-D-Arg-Aba-Gly-NH2) exhibits the strongest analgesic effect, when administered systemically, which suggests that this peptidomimetic has the capacity to penetrate the highly selective blood brain barrier. Moreover, this opioid tetrapeptide analogue is characterized by a long duration of action after subcutaneous injection and proved to be more active than a very similar structure with a NMe-D-Ala residue in the second position of the sequence, i.e. BVD03. This conformationally restricted peptide ligand proved in turn to be more potent that its "ring opened" analogue BVD02.

Unfortunately, AN81 appeared to still induce the development of tolerance after repetitive administration over a time period of five days when tested in the hot water tail-flick test. When compared to morphine, the induced tolerance was however markedly lower. A similar result was obtained for the bifunctional opioid agonist-NK1R antagonist ligand, SBCHM01. This peptidic chimera was, in analogy with the 'pure' opioid ligands, capable of reaching and activating opioid receptors in the CNS, but it lost its antinociceptive potency completely upon chronic injection as determined in the hot water tail-flick assay.

The apparent inability of SBCHM01 to suppress tolerance development appears to oppose recent reports by Vanderah and coworkers [43] which indicate that a hybrid opioid-NK1 octapeptide ligand (TY005) was able to attenuate tolerance development related to sustained opioid pathophysiology in an hyperalgesic model after central (i.t.) administration, as opposed to this study in which i.v. administration was used in an acute pain model. For a general clinical applicability, an important goal in pain research consists of the discovery and development of improved analgesic drugs which could be administered systemically. Hence, we are convinced that unravelling the cause of this intriguing discrepancy is important and will consequently be the target of our future SAR studies.


Are opioids always the answer?

While there are plenty of ideas for opioid-based medicines out there, there is no perfect solution. As Stein notes: &ldquoAt the moment, none of these strategies has produced any compounds that have no side effects.&rdquo But even if we do find the perfect opioid, will it provide the pain relief patients are looking for? A study of 240 patients, published in March 2018, showed that opioids were no better at reducing pain in patients with chronic back, knee and hip problems than non-opioids [7]
.

At the moment, none of these strategies has produced any compounds that have no side effects

&ldquoWe know that [opioids] can be very useful for acute pain, in other words pain that is associated with either trauma or surgery or at the end of life, [but there is] a real lack of efficacy in longer term conditions,&rdquo says Knaggs. &ldquoMost of the [opioid] trials that have been conducted have been for no more than three to four months and, on that basis, effectiveness has been extrapolated over a very long period, which of course is not necessarily [always] the case.&rdquo

&ldquoThere is no high quality evidence that opioids actually help [with chronic pain], and really that is the main issue,&rdquo Knaggs adds. &ldquoChronic pain is a very complex beast and most medicines that we have only interact with one single receptor, or one part of that very complex neurological pathway, so it&rsquos perhaps not surprising that this is the case.&rdquo

&ldquoI think we need a much bigger toolbox for managing pain rather than every person who comes in with an ache gets an opiate &mdash that&rsquos ridiculous, but that&rsquos where we have been,&rdquo says Bohn. But new pain solutions, such as selective COX-2 inhibitors, have also proved to be problematic with serious cardiovascular side effects and many have been removed from the market.

I think we need a much bigger toolbox for managing pain rather than every person who comes in with an ache gets an opiate &mdash that&rsquos ridiculous, but that&rsquos where we have been

Pasternak agrees that new targets do need to be considered, such as dopamine, serotonin and cannabinoid receptors. &ldquoFor chronic pain, people are looking at nerve growth factor (NGF) blockers, either [targeting] receptors directly or [finding] antibody drugs that can sequester the NGF. They have shown that this works.&rdquo

Source: Courtesy of Gavril Pasternak

Gavril Pasternak, clinician and pharmacologist at the Memorial Sloan Kettering Cancer Center in New York, is hoping to selectively activate a sub-type of the μ receptor to try to eliminate side effects

But Knaggs suggests that pharmaceuticals may not be the answer for chronic pain at all. &ldquoWhen you experience pain for longer periods of time, the emotional and affective components become much more established and important, so actually dealing with those is probably equally important to providing pain relief.&rdquo Knaggs also suggests that a lack of physical activity often exacerbates a pain problem. &ldquoFrom what we know about persistent pain, it&rsquos that sensitisation within the nervous system that is a problem and not ongoing tissue damage. The best way to deal with that sensitisation is to be as active as possible, but that is a very difficult message for a lot of patients.&rdquo

The extent of the opioid epidemic in the United States may not reach UK shores, but we certainly cannot be complacent. NHS Digital figures show that, in England, the number of patients admitted to hospital for overdosing on prescription opioid painkillers more than doubled between 2005&ndash2006 and 2016&ndash2017, from 4,891 to 11,660. The pharmacological challenge to create safer and less addictive opioid drugs remains important. &ldquoI&rsquom pretty optimistic that there will be a way to find better analgesic drugs, maybe within the next five to ten years,&rdquo says Stein.

Until then, says Pasternak, we should remember that opioids &ldquocan be extraordinarily effective and provide pain relief in situations that cannot be treated any other way&rdquo.

&ldquoWe have to be careful who we give [pain relief] to and how we give it to them these drugs need to be used but need to be used appropriately and wisely.&rdquo

New opioid pipeline
DrugScientist or companyTargetMechanismDevelopment stage
Olinvo (oliceridine, TRV130)Trevena Inc.Mu (μ) opioid receptorBiased agonistCompleted phase 3
Korsuva (CR845/difelikefalin)Cara TherapeuticsKappa ( ĸ ) opioid receptorActs on peripheral nervous systemPhase 3
6 piperidine-based SR-agonistsLaura Bohn, Scripps Floridaμ opioid receptorBiased agonistBasic research
RB-64 and other compoundsBryan Roth, University of North Carolina at Chapel Hill School of Medicineĸ opioid receptorBiased agonistBasic research
BU08028Stephen Husbands, University of Bathμ opioid receptor and nociception (NOP) receptorμ and NOP receptor agonistBasic research
IBNtxA (3-iodobenzoyl-6β-naltrexamide), naltrexone derivativeGavril Pasternak, Memorial Sloan-Kettering Cancer Center, New YorkTruncated μ receptorsAgonist for 6-transmembrane variants of μ receptorBasic Research
(±)-N-(3-fluoro-1-phenethylpiperidin-4-yl)-N-phenylpropionamide NFEPPChristoph Stein, Charité Hospital, Berlinμ opioid receptorActivated only in acidic inflammed tissuesBasic research
BMS-986122John Traynor, University of Michiganμ opioid receptorAllosteric modulation of the μ opioid receptorBasic research


Results

Salvinorin A Selectively Inhibits KOR Binding.

To identify Salvinorin A's molecular target, we screened Salvinorin A (10 μM) at a large panel of mainly cloned human GPCRs, transporters, and ligand-gated ion channels by using the resources of the NIMH-PDSP. For comparison, we screened the same molecular targets with the prototypic hallucinogen LSD, also at 10 μM. As shown in Fig. 1 and in supporting information, Salvinorin A inhibited only [ 3 H]-bremazocine-labeled KORs and did not significantly inhibit binding to cloned human μ (MOR) or δ opioid (DOR) receptors or any of the 48 other molecular targets screened. Ki determinations (Table 1) showed that Salvinorin A was a potent agonist of KOR and guinea pig (gp)KOR. Additionally, Salvinorin A had Ki values >5,000 nM at the gpMORs and gpDORs (Table 1). These results indicate that Salvinorin A is, to our knowledge, the first naturally occurring κ opioid selective ligand. By comparison, LSD potently inhibits the binding of a large number of biogenic amine receptors (Fig. 1) with Kis <50 nM for several GPCRs (data not shown). Interestingly, Salvinorin A had no detectable affinity for the 5-HT2A serotonin receptor and did not activate 5-HT2A receptors (not shown), which represent the main molecular target responsible for the classical hallucinogens such as LSD, N,N′-dimethyltryptamine, psilocybin, mescaline, and 4-bromo-2,5-dimethoxyphenylisopropylamine (20, 21).

Salvinorin A is a potent and selective κ opioid ligand

Salvinorin A Represents a Structurally Novel KOR Ligand.

Because Salvinorin A represents a structurally novel hallucinogen, we next performed molecular modeling studies to provide insights into how this compound might interact with KORs. A previously reported model of the KOR complexed with the KOR-selective agonist U69593 was used as a starting point (22). This model has the advantage that it was derived from a set of distance constraints between potential hydrogen bond-forming pairs unique to the opioid receptor sequences themselves. The result thus does not depend directly on any direct experimental structural data for rhodopsins. Although this model was constructed before the publication of the crystal structure of rhodopsin (23), it is remarkable that the overall configurations are quite similar (rms deviation = 4 Δ by fitting the helix C-α atoms of identical residues in both sequences). The U69593 KOR complex places the arylacetamide portion of the ligand in a position analogous to the tyramine moiety with the carbonyl hydrogen bonded to Y139 (22). The only structural similarity between U69593 and Salvinorin A (Fig. 2A) is the presence of an aromatic ring and the amide and ester carbonyl groups separated by a short linkage. Because of this similarity, and the nearly complete lack of similarity of salvinorin and any known KOR ligand, the salvinorin crystal structure (5) was initially docked by superimposition of aromatic centroids and the carbonyl atoms of salvinorin with those of bound U69593. The role of the carbonyl functionality for arylacetamide ligands as a hydrogen bond acceptor has been demonstrated experimentally (24) and indirectly supports the proposed role of Y139 and its interaction with the lactone carbonyl of salvinorin. Multiple sterically allowed complexes were generated by using a systematic conformational search about all rotatable Y139 bonds, a dummy bond between a Y139 OH hydrogen atom, and salvinorin carbonyl, following a previously described method (18). Candidate complexes were evaluated interactively for steric fit and hydrogen bond donating properties of the receptor cavity visualized as a Connolly channel plot color coded for hydrogen-bonding potential.

Large-scale screening of human cloned GPCRs reveals Salvinorin A is selective for KOR. Shown is the mean percent inhibition of radioligand binding or functional activity (metabotropic glutamate receptors only) to 50 receptors and transporters for LSD (yellow bars) and Salvinorin A (red bars) tested at 10 μM. With the exception of the rat β1 and β2 adrenergic and bovine dopamine transporter (DAT) all of the assays were performed with cloned human receptors heterologously expressed (see Materials and Methods and supporting information on the PNAS web site for details). As can be seen (arrow), Salvinorin A inhibited only KOR binding at 10 μM. See Table 5 for details. SERT, serotonin transporter NET, norepinephrine transporter DAT, dopamine transporter rGABAA, rat GABA-A receptor.

Only one family of complexes allowed simultaneous hydrogen bond formation between the receptor side chains and ligand features shown in Fig. 2C (see Table 3 for additional modeling results and details of modeling procedures). In this orientation, the furan substituent of Salvinorin A pointed toward TM1 and TM2, the 4-methoxycarbonyl toward TM5 and TM6, with the A and C rings toward the extra- and intracellular sides, respectively (Fig. 2D and supporting information). Not unexpectedly, there is very little atom-by-atom correspondence between bound U69593 and Salvinorin A, although both occupy a similar space (Fig. 2B). Docking of salvinorin into hydrogen bond potential-coded Connolly channels defining the binding sites of the MOR and DOR models (22) indicates that salvinorin is sterically compatible with each in slightly different binding modes but could not as readily accommodate the four-point hydrogen bond donor/acceptor scheme (Fig. 2D) seen with the KOR receptor (e.g., the KOR models could accommodate the furan oxygen and 4-methoxycarbonyl functionality but not the 2-acetoxy group). Residues potentially forming the salvinorin-binding site of the KOR receptor model are listed in Table 4. The identities of 11 of these are conserved in both the MOR and DOR, whereas the remaining seven are variable. The variable residues cause significant alterations in the steric and electronic characteristics of MOR and DOR in the regions analogous to the salvinorin-binding site of the KOR. The substantial differences in the region of the salvinorin-binding site between the KOR and MOR/DOR receptors are consistent with the observed KOR selectivity of salvinorin.

The proposed KOR salvinorin-binding site model is also consistent with what little is known about the structural features of salvinorin required for psychotropic activity. For example, the one-position carbonyl of salvinorin is not able to form specific donor/acceptor contacts with residues in the receptor model, partially because of its sterically hindered environment, and is not essential for psychotropic activity (25). The 2-acetoxy group of salvinorin does make specific donor/acceptor contacts in the model and is required for activity (5). Interestingly, a three-dimensional search of the National Cancer Society Database using the pharmacophore features and geometries derived from salvinorin docked with the KOR model produced splendidin (26) and deoxydeoxygedunin (27) (not shown). Splendidin was originally isolated from Salvia splendens, a species distinct from S. divinorum and from which salvinorin is derived. S. splendens has been reported to have psychotropic activity.

Salvinorin A Is a Potent KOR Agonist at Recombinant KORs and KORs Expressed in Situ.

We next examined the agonist/antagonist properties of Salvinorin A by using two model systems: KOR stably expressed in human embryonic kidney-293 cells and gpKOR expressed in situ in guinea pig brain. As shown in Fig. 3, Salvinorin A was a potent KOR agonist with an EC50 for inhibition of adenylate cyclase of 1.05 nM as compared with an EC50 for the KOR agonist U69593 of 1.2 nM (Table 2). Salvinorin A was also a potent agonist at gpKOR expressed in situ with an EC50 for [ 35 S]GTP[γS] binding of 235 nM with U69593 having an EC50 of 377 nM (Table 2). Taken together, these results indicate that Salvinorin A represents, to our knowledge, the first nonnitrogenous KOR-selective agonist.

Salvinorin A is a potent KOR agonist. A shows that Salvinorin A potently inhibits 3H-bremazocine binding to cloned KORs, whereas B shows the ability of Salvinorin A to inhibit forskolin-stimulated adenylate cyclase in KOR-393 cells. Data represent the mean ± SD of triplicate determinations from a representative experiment that has been replicated three times. For the inhibition of forskolin-stimulated cyclase activity, an EC50 value of 1 ± 0.5 nM was calculated for Salvinorin A, compared with an EC50 value of 1.2 ± 0.6 nM for U69593.

Salvinorin A is a potent κ-opioid agonist: [ 35 S]GTP-γ-S studies using guinea pig brain caudate membranes


Translating advances in opioid receptor research to the opioid crisis

Here we described how the development of new tools and approaches advanced our knowledge of opioid receptor function. Nanobody technology coupled with innovations in microscopy are providing high resolution maps of receptor structure, which with high throughput computation, can be used to hasten the development of novel opioids that lack adverse effects. The same technology is providing a window through which opioid receptor activation and trafficking between cellular compartments can be visualized. This is reframing our perspective of the cellular consequences of agonist binding to opioid receptors and revealing novel cellular mechanisms that can be targeted. Advances in genetics are identifying granular distinctions in receptors that could be a basis for understanding individual differences in vulnerabilities. Genetic models and tools that allow manipulation of receptor levels and activity reveal important information on the distinct functions of the different opioid receptors. Similarly, the β-arrestin knockout mouse is an example of a genetic model that has been pivotal in the concept of biased opioid receptor signaling. Though many scientific questions still remain unresolved (Table 1), the new advances, by revealing molecular and cellular fundamentals of opioid receptor function, bring us closer to understanding the mechanisms by which opioids produce tolerance, physical dependence and addiction and towards developing a rational therapeutic design of safe, effective opioid analgesics.


Introduction

Figure 1. Structures of ligands related to 14-O-methyloxymorphone (1), naloxone (7), and naltrexone (8). CPM, cycloproplymethyl Ph, phenyl.

Abbreviations: CHO, Chinese hamster ovary CNS, central nervous system DAMGO, [ d -Ala 2 ,Me-Phe 4 ,Gly-ol 5 ]enkephalin DMF, N,N-dimethylformamide DPDPE, [ D -Pen 2 , D -Pen 5 ]enkephalin HEPES, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid GDP, guanosine diphosphate [ 35 S]GTPγS, guanosine-5′-O-(3-[ 35 S]thio)-triphosphate MPLC, medium pressure liquid chromatography SAR, structure−activity relationship Tris, tris-(hydroxymethyl)-aminomethane U69,593, 5α,7α,8β-(−)-N-methyl-N-[7-(1-pyrrolidinyl)-1-oxaspiro(4−5)dec-8-yl]benzeneacetamide.

Chemistry