1. Biochemistry and Chemical Biology
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Controlling opioid receptor functional selectivity by targeting distinct subpockets of the orthosteric site

  1. Rajendra Uprety
  2. Tao Che
  3. Saheem A Zaidi
  4. Steven G Grinnell
  5. Balázs R Varga
  6. Abdelfattah Faouzi
  7. Samuel T Slocum
  8. Abdullah Allaoa
  9. András Varadi
  10. Melissa Nelson
  11. Sarah M Bernhard
  12. Elizaveta Kulko
  13. Valerie Le Rouzic
  14. Shainnel O Eans
  15. Chloe A Simons
  16. Amanda Hunkele
  17. Joan Subrath
  18. Ying Xian Pan
  19. Jonathan A Javitch
  20. Jay P McLaughlin
  21. Bryan L Roth  Is a corresponding author
  22. Gavril W Pasternak
  23. Vsevolod Katritch  Is a corresponding author
  24. Susruta Majumdar  Is a corresponding author
  1. Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, United States
  2. Department of Pharmacology, University of North Carolina, United States
  3. Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, United States
  4. Department of Anesthesiology, Washington University in St. Louis School of Medicine, United States
  5. Department of Quantitative and Computational Biology, Department of Chemistry, Bridge Institute, Michelson Center for Convergent Bioscience, University of Southern California, United States
  6. Division of Molecular Therapeutics, New York State Psychiatric Institute and Departments of Psychiatry, Pharmacology, Columbia University Vagelos College of Physicians & Surgeons, United States
  7. Department of Pharmacodynamics, University of Florida, United States
  8. Department of Anesthesiology, Rutgers New Jersey Medical School, New Jersey, United States
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Cite this article as: eLife 2021;10:e56519 doi: 10.7554/eLife.56519

Abstract

Controlling receptor functional selectivity profiles for opioid receptors is a promising approach for discovering safer analgesics; however, the structural determinants conferring functional selectivity are not well understood. Here, we used crystal structures of opioid receptors, including the recently solved active state kappa opioid complex with MP1104, to rationally design novel mixed mu (MOR) and kappa (KOR) opioid receptor agonists with reduced arrestin signaling. Analysis of structure-activity relationships for new MP1104 analogs points to a region between transmembrane 5 (TM5) and extracellular loop (ECL2) as key for modulation of arrestin recruitment to both MOR and KOR. The lead compounds, MP1207 and MP1208, displayed MOR/KOR Gi-partial agonism with diminished arrestin signaling, showed efficient analgesia with attenuated liabilities, including respiratory depression and conditioned place preference and aversion in mice. The findings validate a novel structure-inspired paradigm for achieving beneficial in vivo profiles for analgesia through different mechanisms that include bias, partial agonism, and dual MOR/KOR agonism.

Introduction

Pain affects almost every person at some point in their lives, and it has been estimated that more than 25 million people in the United States suffer daily from severe pain (Nahin, 2015). Drugs targeting MOR are effective analgesics, but they retain high addiction potential and cause potentially lethal side effects including respiratory depression. As the use of opioid analgesics increased and then came under greater restrictions, so too has their diversion, misuse, and switch to illicit opioids, as ~80% of opioid addicts reported initiating their habit through prescription opioids. The epidemic of opioid abuse caused more than 47,600 deaths in 2017 alone, (Overdose Death Rates, 2019) making drug overdose the leading cause of accidental death in the US. As effective analgesics are essential to minimize the pain and suffering of many diseases, identification of safer analgesic molecular entities with diminished side effects and abuse potential is critical to breaking the vicious cycle fueling the opioid epidemic.

Biased signaling is an important concept in G protein-coupled receptor (GPCR) functional mechanisms, by which distinct downstream signaling pathways can be preferentially activated by agonists working through the same receptor (Law et al., 2013; Pradhan et al., 2012). It has been proposed that opioid ligands showing a preference (bias) for activating only G protein-mediated signal transduction pathways, or against recruiting βarrestin-2, will demonstrate diminished side effects (Raehal and Bohn, 2011; Chiang et al., 2016; Majumdar and Devi, 2018; Faouzi et al., 2020a). However, studies on G protein biased opioid ligands have shown mixed results so far. The first biased ligand, a MOR biased agonist oliceridine (TRV130) (DeWire et al., 2013) has been recently approved by the FDA (FDA Approves New Opioid for Intravenous Use in Hospitals, 2020). It is important to note, however, that TRV130 displays weak G-protein bias in vitro (Schmid et al., 2017) and mixed safety results in rodent models (Austin Zamarripa et al., 2018; Altarifi et al., 2017). Other MOR ligands with greater bias, such as SR17018 (Schmid et al., 2017), show diminished respiratory depression in rodents compared to fentanyl (Gillis et al., 2020a), while PZM21 (Manglik et al., 2016; Kudla et al., 2019) and mitragynine(s) (Váradi et al., 2016; Kruegel et al., 2016; Kruegel et al., 2019; Chakraborty and Majumdar, 2020) display reduced abuse liability (Yue et al., 2018; Hemby et al., 2019). Similarly, some KOR-selective G protein biased ligands such as HS666 (Spetea et al., 2017), 6′GNTI (Rives et al., 2012), and triazole 1.1 (Brust et al., 2016) show a promising separation of place aversion from analgesia, unlike balanced KOR agonists. On the other hand, other KOR ligands such as RB64 (White et al., 2015), HS665 (Spetea et al., 2017), and collybolide (Gupta et al., 2016) retain the aversive properties of balanced KOR agonists despite being G protein biased.

Together, these data suggest that the ‘classical model’ of bias or activation of a single opioid receptor subtype may not be sufficient for achieving an optimal pharmacological profile in vivo. Here, we tested the new hypothesis that dually selective agonist ligands working through the G protein pathway at both MOR and KOR could be synergistically analgesic while mitigating the common liabilities of conventional opioids. Prior evidence shows that simultaneous activation of MOR and KOR may produce synergistic analgesia, while the contrasting side-effects offset respective liabilities (Sutters et al., 1990; Pan, 1998). For example, KOR agonists such as U50,488h, while showing no sign of respiratory depression on their own, Matthes et al., 1998 have been reported to reduce the respiratory depression mediated by icv administration of DAMGO (Dosaka-Akita et al., 1993; Haji and Takeda, 2001). Likewise, nalbuphine, a moderate efficacy MOR partial agonist and high efficacy KOR partial agonist (Schmidt et al., 1985; Peng et al., 2007), is similar in analgesic efficacy to morphine, but shows negligible respiratory effects (Schmidt et al., 1985), suggesting that partial agonism coupled to mixed agonism at MOR/KOR may attenuate MOR-induced respiratory depression.

In this study, we used structure-based computational modeling to facilitate the design of compounds with G protein biased activity at both MOR and KOR. Comparative structural analysis and docking to opioid receptors, including the recent nanobody-stabilized active state KOR complexed with MP1104 (Che et al., 2018; Váradi et al., 2015a), suggested that specific receptor-ligand interactions at the TM5-ECL2 region in the orthosteric ligand pocket may reduce arrestin recruitment at both MOR and KOR (Figure 1A). In vitro characterization and structure-activity relationship studies (SAR) of a variety of new morphinan and fentanyl analogs reported here (Figure 1B), strongly support this hypothesis. In vivo studies of the most potent ligands with dual selectivity to MOR and KOR, partial agonism, and reduced arrestin recruitment, MP1207/MP1208, also show receptor-mediated analgesic actions in mice while negating classical side-effects of opioids, suggesting a new approach toward generating effective analgesics with attenuated opioid-induced adverse effects.

The design concept, structures of ligands synthesized and evaluated at opioids receptors.

(A) Overview of the key hypothesis, suggesting that TM5-ECL2 engagement by morphinan ligand with ring-C chair form leads to preferred G protein signaling, whereas TM2-TM3 engagement and ring-C boat form leads to balanced G protein and arrestin signaling. (B) Structures of the studied m and p-substituted arylamidoepoxymorphinans (MP1104, MP1202, IBNtxA, MP1305, MP1207, MP1208, MP1209, MP1210), m-iodoarylamidomorphinan, (MP1601), methoxycarbonylfentanyl, methoxycarbonyl fentanyl amide MP102 and 6′GNTI.

Results

MP1104 shows arrestin recruitment at both MOR and KOR subtypes

Previously, we used the amidoepoxymorphinan ligand MP1104 (Váradi et al., 2015a) to obtain the human KOR crystal structure in a nanobody-stabilized active state conformation (PDB code 6B73). Functional studies (cAMP and β-arrestin2 recruitment assays) showed that MP1104 robustly recruits β-arrestin2 at mu and kappa opioid receptors (Che et al., 2018). Its bias factors at hMOR and hKOR were determined to be 0.58 (Figure 2A–B and Appendix 1—figure 4B, Appendix 1—table 10) and 0.15 (Figure 2C–D and Appendix 1—figure 4A, Appendix 1—table 10), respectively. Bias factors reported throughout this work quantify preferred activation of a signaling pathway (G protein or βarrestin-2) by the ligand as compared to the prototypic balanced agonists, DAMGO and U50,488h, for MOR and KOR, respectively, A bias factor of >1 signifies compounds with G protein bias, a bias factor of <1 signifies arrestin bias, while compounds with bias factor lacking statistically significant deviation from one are deemed unbiased. The bias factor for each ligand was determined using functional data obtained from cAMP inhibition vs Tango assays or BRET assays, when applicable, by following previously reported methods of calculation (Kenakin et al., 2012).

MP1104 at both MOR and KOR and MP1202 at KOR targets the TM2-TM3 region while MP1202 at MOR targets the TM5-ECL2 region and show distinct signaling properties.

(A-B) MP1104 (red) is a full agonist in hMOR in cAMP inhibition (N = 5) and Tango-arrestin recruitment assays (N = 5) compared to DAMGO (blue). (C–D) MP1104 (red) is a full agonist in hKOR in cAMP inhibition (N = 3) and Tango-arrestin recruitment assays (N = 3) compared to U50,488H (purple). (E–F) The preferred docking pose of MP1104 (boat form, yellow stick) at MOR and MP1104 (boat form, yellow stick) in the active state of KOR. Ring-C of MP1104 in boat form forces the iodophenyl moiety to reside in a region between TM2-TM3 at MOR/KOR. (G–H) MP1202 (red) is a full agonist in hMOR in cAMP inhibition (N = 3) and partial agonist in Tango-arrestin recruitment assays (N = 3) compared to DAMGO (blue). (I–J) MP1202 (green) is a full agonist in hKOR in cAMP inhibition (N = 3) and in Tango-arrestin recruitment assays (N = 3) compared to U50,488h (purple). (K–L) The docking poses of MP1202 (chair form, brown stick) and (boat form, green stick) at an active states of MOR and KOR are shown. At MOR, the saturated ring C in MP1202 leads to interaction of the ligand in the ECL2 and TM5 region leading to a preference of chair form shown by a red arrow. At KOR, MP1202 behaves similar to MP1104 and the flip of ring C conformation from chair to boat is shown by a blue arrow. See Appendix 1—table 7 for values, Appendix 1—figure 4 and Appendix 1—table 10 for bias calculations.

Here, we evaluated the potency and efficacy at G protein activation as well as arrestin recruitment of MP1104 using BRET assays which afford a more precise interrogation of transducer bias (Kruegel et al., 2016) in HEK-293T cells transfected with rodent opioids receptors (mMOR and rKOR). Confirming the cAMP inhibition assay and β-arrestin2 recruitment results obtained for human opioid receptors, MP1104 was found to be arrestin biased at both mMOR (Appendix 1—figure 1A and 4C, Appendix 1—table 11) as well as rKOR (Appendix 1—figure 2A and 4C, Appendix 1—table 11) with bias factors of 0.11 and 0.23, respectively.

Synthesis and evaluation of MP1202: a MOR G biased and KOR agonist recruiting arrestin

In contrast to MP1104, the closely related ligand IBNtxA (Majumdar et al., 2011aFigure 1B) with a hydroxyl (C14-OH) group and a saturated ring C, showed reduced β-arrestin2 recruitment at hMOR while recruiting β-arrestin2 through hKOR activity (Appendix 1—figure 3A-D and 4A-B and Appendix 1—table 10, bias factor = 0.1 at hKOR and 24 at hMOR) (Che et al., 2018). At rodent receptors, we presently confirmed that IBNtxA trended toward reduced potency in the arrestin pathway versus the G protein pathway compared to DAMGO. Interestingly, while we were not able to determine its potency in the arrestin pathway its efficacy (Emax = 75%) was greater than seen in the G protein pathway (Emax = 59%) at mMOR (Appendix 1—figure 3F-G and 4C, Appendix 1—table 11) and IBNtxA showed no bias at rKOR (Appendix 1—figure 3H-I and 4C, Appendix 1—table 11). As a continuation of SAR studies on 6β-amidoepoxymorphinans to identify the structural features responsible for β-arrestin2 recruitment over G protein activation, we here synthesized MP1202 (C14-H instead of C14-OH in IBNtxA) with the saturated cyclohexyl ring C (see synthesis in Appendix 1—scheme 1A). Evaluation of MP1202 in radioligand binding assays in opioid receptor transfected cell lines showed that it retained pan opioid sub-nM binding (Appendix 1—table 1) and sub-nM potency in the G-protein pathway in GTPγS assays (Appendix 1—table 2). At human opioid receptors, MP1202 was similar to IBNtxA and was found to be G protein biased at hMOR (bias factor = 31, Figure 2G–H, Appendix 1—figure 4B and Appendix 1—table 10) while showing β-arrestin2 recruitment and arrestin bias at hKOR (Figure 2I–J, Appendix 1—figure 4A, and Appendix 1—table 10).

At rodent receptors in BRET assays, MP1202 retained β-arrestin2 recruitment at rKOR (Appendix 1—figure 2C and 4C and Appendix 1—table 11), although showing a diminished β-arrestin2 potency at mMOR relative to DAMGO. Similar to IBNtxA a greater efficacy was seen in the arrestin pathway (Emax = 57%) compared to the G protein pathway (Emax = 70%) (Appendix 1—figure 1C).

Predicted engagement of the TM5-ECL2 region promotes G protein bias

Differences in the bias profiles of MP1104, IBNtxA, and MP1202 suggested distinct interaction modes of these ligands at MOR and KOR. We relied on both the ligand-based and the receptor-based structure design approaches to understand the observed pharmacology. In terms of ligand structure, the three ligands have two structural variations among them: the presence/absence of C14-OH and the saturation/unsaturation of ring C (Figure 1B). The similarity of the bias profiles for IBNtxA and MP1202 suggested that C14-OH is not important for bias. However, the contrast between the strong preference of IBNtxA and MP1202 for the G protein pathway compared to MP1104 at MOR suggested a useful SAR between the conformation of the C ring and ligand function. Indeed, we found a strong preference for the unsaturated ring C of MP1104 to be in the boat conformation, based on analysis of similar ligands in the Crystallography Open Database and our quantum mechanics (QM) energy calculations. At the same time, the saturated C rings of both IBNtxA and MP1202 could assume both chair and boat conformations with only a modest preference for chair conformation (Appendix 1—tables 34). To analyze the differences between the boat and chair conformations of the C rings in the context of ligand-receptor interactions, we performed energy-based docking studies for these ligands in all-atom models of the receptors, based on recently solved active-state crystal structures for MOR (Huang et al., 2015) and KOR (Che et al., 2018). Due to the boat-form restriction for the unsaturated ring C, the amidophenyl moiety of the best-scored docking poses for MP1104 in both MOR and KOR occupied a sub-pocket between TM2 and TM3 (Figure 2E and F). In the absence of such conformational limitation for the saturated ring C in IBNtxA and MP1202, both chair and boat conformations of the ring were observed among the top 10 poses ranked by energy score. However, we found that in MOR the best-scored IBNtxA (Appendix 1—figure 3E) and MP1202 (Figure 2K) docking poses consistently adopted the chair conformation of ring C, while in KOR the best-scored poses adopted the boat conformation (Appendix 1—figure 3J and Figure 2L).

These reproducible differences between KOR and MOR can be explained by different physical properties of their TM2/TM3 sub-pockets, which accommodate the hydrophobic amidophenyl arm of these ligands. This sub-pocket is more hydrophobic in KOR because of the presence of the non-conserved V1182.63 residue and a conformational change in the conserved Q1152.60 residue. Although the MOR sub-pocket does share some hydrophobic residues, namely WECL2, V3.28 and I3.29, exposed polar groups of the N1292.63 and Q1262.60 side chains increase the polarity. Therefore, while in KOR the hydrophobic amidophenyl arm of the ligand retains its preference for binding the TM2-TM3 sub-pocket, in MOR it is preferentially redirected toward the TM5-ECL2 region. Apparently, this binding interaction preference of the amidophenyl arm of IBNtxA and MP1202 is reflected in the switching of the ring-C from the chair conformation when bound in MOR to the boat conformation when interacting with KOR. Notably, this concerted switch of ring-C conformation and the amidophenyl ‘arm’ position correlates with the observed signaling bias. Specifically, whereas the chair conformation of IBNtxA and MP1202 in MOR results in the ‘arm’ interactions with the TM5-ECL2 region and favors G protein activation, the boat conformation in KOR results in TM2-TM3 sub-pocket interactions and enhanced preference for balanced agonism or the arrestin pathway. This observation is further corroborated by the activation of the arrestin pathway in both MOR and KOR found for the boat-restricted conformation of the MP1104 ligand.

Structure-inspired design of MP1207 and MP1208 as dual MOR/KOR agonists showing reduced arrestin recruitment

Based on the above analysis, we hypothesized that a structure-inspired design of MP1202 analogs that are G protein biased not only at MOR, but also at KOR would require a switch in preference of amidophenyl arm substituents from the TM2-TM3 sub-pocket to the TM5-ECL2 region in both receptors. To test this hypothesis, we proposed to redesign the MP1202 ligand by introducing a polar or charged moiety at the amidophenyl ‘arm’ to make its interactions at the hydrophobic TM2-TM3 pocket of KOR unfavorable. Further, since the TM5-ECL2 region in KOR is lined by acidic residues D2235.35 and E209ECL2, the presence of basic moieties at the amidophenyl arm would be expected to provide additional favorable interactions to shift its preference toward the TM5-ECL2 region. Interestingly, in the docking pose for 6'GNTI in KOR, a known G protein biased ligand (Rives et al., 2012; Schmid et al., 2013), the guanidino group also occupies the TM5-ECL2 region (Appendix 1—figure 5).

As a part of the computer-assisted design, we proposed a library of analogs where the m-iodo group was swapped with polar groups such as OH, NH2 NMe2, (CH2)nNH2 and (CH2)n-guanidine (n = 1–5 for amine and guanidine modification). Docking of these derivatives into the active state KOR structural model allowed computational predictions of their binding scores and conformational preferences (Appendix 1—table 5). Two analogs, calculated to have the greatest preference for the ring C chair form and interactions with the TM5-ECL2 region at both MOR and KOR MP1207 and MP1208 (Figures 1B, 3C–D and G–H) were selected and synthesized (Appendix 1—scheme 1B).

meta-Amino (MP1207) and meta-guanidino (MP1208) analogs prefer the chair conformation and target the TM5-ECL2 region and are G protein biased agonists at KOR and at MOR show no measurable arrestin recruitment.

(A-B) MP1207 (orange) and MP1208 (green) are full agonists at hKOR in cAMP inhibition (N = 3) and partial agonists in Tango-arrestin recruitment assays (N = 3) compared to U50, 488 (purple). (C–D) Docking results showed that amino methyl (MP1207) or guanidino (MP1208) moieties (replacing the iodo group in MP1202) forced these compounds in chair form preferred confirmation at hKOR (chair form in brown stick and boat form in green stick). Unlike boat MP1202, chair MP1207 at hKOR may form a new salt bridge interaction between amino group and D2235.35 and E209ECL2 pulling amidophenyl moiety away from the hydrophobic pocket between TM2 and TM3 (C). Likewise, chair MP1208 forms salt bridge interactions between guanidino group and D2235.35 as well as with E209ECL2 (D) The flip in conformation of ringC from boat to chair for both MP1207 and MP1208 is shown by a red arrow. (E–F) MP1207 (orange) and MP1208 (green) are partial agonists at hMOR in cAMP inhibition (N = 3). No arrestin recruitment was observed for both agonists in Tango-arrestin recruitment assays (N = 3) compared to DAMGO (blue). (G–H) At hMOR chair forms of MP1207 and MP1208 introduce additional interactions between amino or guanidino group and D218ECL2 and T220ECL2. Thus, biased signaling events of MP1207 and MP1208 are dictated from chair favored binding via the involvement of their m-amino or m-guanidino group with TM5 -ECL2 region. See Appendix 1—table 7 for values, Appendix 1—figure 4 and Appendix 1—table 10 for bias calculations.

Functional studies using cAMP inhibition and Tango assays at human opioid receptors showed that both MP1207 and MP1208 are G protein biased agonists at hKOR with bias factors of 8 and 22 (Figure 3A–B, Appendix 1—figure 4A and Appendix 1—table 10), respectively. At hMOR, recruitment of arrestin was completely abolished for both ligands; however, reduction of cAMP inhibition was also observed, with Emax values of = 33% for MP1207 and 42% for MP1208 compared to DAMGO (Figure 3E–F). In the cAMP assay, the prototypic MOR agonist morphine acted as a full agonist (Emax = 97%) whereas buprenorphine was a partial agonist (Emax = 75%) compared to DAMGO (Appendix 1—table 7). In binding assays, both MP1207 (m-amine group) and MP1208 (m-guanidine group) showed similar affinities at mMOR (Ki = 0.23 nM and 0.34 nM) and mKOR (Ki = 0.39 and 0.28 nM) with substantial selectivity over mDOR (Ki = 15.62 and 19.28 nM) (Appendix 1—table 1). In [35S]GTPγS binding assays both MP1207 and MP1208 were partial agonists at both mKOR and mMOR, still maintaining very high potency at mKOR (EC50 = 1.5 and 1.4 nM) and at mMOR (EC50 = 1.3 and 1.1 nM). At mDOR both MP1207 and MP1208 show only weak efficacy (Appendix 1—tables 2 and 6). Similar results of partial agonism at mMOR (Appendix 1—figure 1D) and rKOR were seen in BRET assays (Appendix 1—figure 2D). The controls morphine (Emax = 110%) and buprenorphine (59%) were found to produce full and partial agonism at mMOR in the same assay, respectively (Appendix 1—table 7). No recruitment of βarrestin-2 was seen with either MP1207 or MP1208 when rodent opioid receptors were used in BRET assays. The arrestin recruitment signal for both MP1207 and MP1208 at hMOR, mMOR and rKOR were too low for the bias factors at these receptors to be calculated.

To investigate specificity, MP1207 was counter-screened for agonism against 330 other GPCRs using a Presto-Tango assay. Activity at 3 μM was observed at some other targets; however, no potent activity was confirmed with a full concentration–response experiment at these targets (Appendix 1—figure 6). Since this assay relies on arrestin recruitment and our ligand was found to show limited β-arrestin2 recruitment at its primary targets, MOR and KOR, we further counter-screened MP1207 using radioligand binding assays. MP1207 had a Ki >10 µM affinity at all screened targets except SERT and α2C-adrenoreceptors, which displayed Ki (pKI± SEM) of 356 (6.45 ± 0.091)nM and 2979 (5.53 ± 0.16) nM respectively (Besnard et al., 2012). At MOR, KOR, and DOR the respective values were 0.39 (9.4 ± 0.042), 0.39 (9.4 ± 0.056), and 60.1 (7.22 ± 0.059) showing a 900-fold selectivity for MOR and KOR over the nearest non-opioid target.

Molecular dynamics and additional MP1207 analog design support TM5-ECL2 region role in signaling bias

MP1207 and MP1208 were designed to target the TM5-ECL2 region of KOR via their amidophenyl arm accessing additional interactions with polar residues D2235.35 and E209ECL2 (See Figure 3C–D), capitalizing on the structure-based modeling predictions. We carried out MD simulations on MP1207 in KOR (Figure 4A–B). Over 50% of the cumulative trajectory frames from the two 1000 ns long MD runs had distances between carboxylate oxygens of these acidic residues within 4.5 Å of methyl amine nitrogen atom of MP1207. The methyl amine of MP1207 can form salt bridge interactions with both E209ECL2 and D2235.35 residues, and during MD simulations a fluctuating switch between these two residues was observed. The MD simulations indicate that these salt bridges are possible and moderately stable. These results support our key design hypothesis which posits an interaction between the basic amino and guanidine moieties of MP1207 and MP1208 with the negatively charged D2235.35 and E209ECL2 side chains in TM5-ECL2 region, and an important role of these interactions in reducing preference for the arrestin pathway and/or recruitment.

MD simulations in hKOR with MP1207 show the guanidine group interacts with E209/D223 and analogs of MP1207 not oriented toward TM5-ECL2 region suggest G protein bias of MP1207/08 is dependent on salt-bridge formation in this region.

(A) Docking of MP1202 (green sticks) and MP1207 (yellow sticks) in wild type KOR showing MP1207 chair form engaging D223 and E209 residues in TM5-ECL2 region while MP1202 boat form not engaging this region. (B) Graph plotting distances between methyl nitrogen atom of MP1207 and side-chain carboxylate atoms of Glu209ECL2 and Asp2235.35 during two 1000 ns long MDs runs of MOR-MP1207 complex. Distances of each trajectory frame and running average are plotted for Glu209ECL2 (light orange and orange) and Asp2235.35 (light green and green). (C–D) MP1209 (blue) and MP1210 (light green) are full agonists at hKOR in cAMP inhibition (N = 3) and Tango-arrestin recruitment assays (N = 3) compared to U50,488h (purple). (E–F) Similarly, MP1209 (red) and MP1210 (orange) are partial agonists at hMOR in cAMP inhibition (N = 3). No arrestin recruitment was observed for both agonists in Tango-arrestin recruitment assays (N = 3) compared to DAMGO (blue). Regioselectivity of ring substituent is important for kappa bias. The p-methyl amino and m-methyl alcohol do not form salt-bridge within TM5-ECL2 unlike the m-methyl amino group of MP1207 as a result similar to MP1202 with respect to bias at KOR and lower arrestin signaling at MOR. See Appendix 1—table 7 for values, Appendix 1—figure 4 and Appendix 1—table 10 for bias calculations.

Conversely, the design hypothesis also suggests that the relocation of the amidophenyl arm can be achieved by hampering its interactions in the TM2/TM3 subpocket. Indeed, we had previously shown that a mutation of Y312W7.35 in the TM2-TM3 region of KOR reduces βarrestin-2 recruitment for IBNtxA, which has a similar amidophenyl arm (Che et al., 2018). While the residues in this position do not make direct contact with the receptor in our models, this mutation is likely to impact binding indirectly (See Appendix 1—figure 7I showing Bu72-MOR TM2-TM3 and Appendix 1—figure 7J showing MP1202-KOR TM2-TM3 region interactions).

In the present study, we tested the effects of the Y312W7.35 mutation on MP1202, MP1207 and MP1208. As expected, this mutation in KOR reduced arrestin recruitment by MP1202 to the level observed for MOR, resulting in strong G protein bias (bias factor = 34, Appendix 1—figure 7A&C and L) as opposed to robust β-arrestin2 recruitment in the wild-type KOR (Appendix 1—figure 7B and D). A similar trend was found with MP1207 and 1208, revealing a further reduction of arrestin recruitment at the mutant KOR receptor (Appendix 1—figure 7E-G), down to the level seen in wild type MOR (Appendix 1—figure 7H). These results suggest that similar to IBNtxA, the Y312W7.35 mutation in KOR changes the conformational character of the sub-pocket to a MOR-like shape, possibly by changing the conformation of Q1152.60, and also leads to loss of water-mediated hydrogen bonding with the amido group. Therefore, Y312W7.35 provides an environment that favors the chair conformation, leading to a shift in ligand bias toward G protein activity (Appendix 1—figure 7K).

To further evaluate the role of salt bridges in facilitating ligand conformations with the amidophenyl arm in the TM5-ECL2 region, we synthesized two MP1207 analogs by swapping the m-CH2NH2 with p-CH2NH2 (MP1209) and m-CH2OH (MP1210) (Figure 1B, Appendix 1—scheme 2). Consistent with our predictions (Appendix 1—table 4), the para-substituted and more planar analog, MP1209 and the meta substituted methyl hydroxyl analog (MP1210) which are incapable of forming a salt bridge with D2235.35 and E209ECL2, lost their G protein bias in hKOR and showed no bias (Figure 4C–D, Appendix 1—figure 4A and Appendix 1—table 10) while retaining hMOR null arrestin recruitment (Figure 4E–F). Thus, only when ideal orientation/distances are maintained (i.e. meta-amino/guano) and the amidophenyl arm is accommodated in the TM5-ECL2 region of KOR, is a bias for G protein activity observed. Taken together, the described MD analysis combined with assessment of epoxymorphinan analogs targeting in the TM5-ECL2 region further corroborated our hypothesis that interactions in this region can be critical for G protein bias at KOR.

Design of other morphinan and fentanyl based analogs engaging TM5 support its role in signaling bias

To further explore the hypothesis that TM5 interactions promote G protein bias for scaffolds beyond epoxymorphinans we next examined the fentanyl template. We have published a series of methoxylcarbonyl fentanyl amides previously (Váradi et al., 2015b). We docked a published compound MP102 at MOR and found that the cycloheptyl group is predicted to line up in the TM5 region, a region not accessed by methoxylcarbonyl fentanyl (Appendix 1—figure 8E). We evaluated G protein/arrestin activity of both compounds and found that as expected, methoxylcarbonyl fentanyl showed strong arrestin recruitment and arrestin bias (bias factor = 0.09 at hMOR, Appendix 1—figure 8A-B, C-D and 8 and Appendix 1—table 10) while MP102 targeting TM5 was unable to recruit arrestin at human (Appendix 1—figure 8F-G) and mouse receptors (Appendix 1—figure 8H-I).

Continuing with epoxymorphinan/morphinan SAR, m-iodo analogs MP1305 (methylated OH as C14-OCH3), and MP1601 from morphinan template (devoid of the etheral bridge linking rings A and C) were synthesized (Appendix 1—schemes 3 and 4). Our computational docking studies suggested that ring C of MP1305 prefers the chair form at both MOR and KOR (See Appendix 1—figures 9I, K for details), while MP1601 favors the chair form at MOR and boat form at KOR (Appendix 1—figure 9J,L). Consistent with our docking predictions, MP1305 was found to be G protein biased at MOR and KOR at human receptors with a bias factor of 11 and 4, respectively (Appendix 1—figure 9A-D and 4A-B and Appendix 1—table 10) while MP1601 behaved similar to IBNtxA and MP1202 and showed a preference for the arrestin pathway at hKOR (bias factor = 0.5, Appendix 1—figure 9E-F and 4A and Appendix 1—table 10) while being G protein biased at hMOR (Bias factor = 4, Appendix 1—figure 9G-H and 4B and Appendix 1—table 10).

At rodent receptors, both compounds showed sub-nM affinity and high potencies in [35S]GTPγS assays (Appendix 1—tables 12). Due to very low arrestin signal, it was impossible to calculate the bias factor at rodent receptors from the BRET assays at MOR for both MP1305 and 1601, and for MP1601 at KOR (Appendix 1—figures 1E, 2E). MP1601 was not biased at rKOR, but did demonstrate arrestin bias at hKOR (Appendix 1—figures 12E and 4C and Appendix 1—table 11). These results are again consistent with our hypothesis correlating G protein bias (and reduced recruitment of arrestin) of the morphinan derivatives with their C-ring chair conformation and the resulting positioning of the amidophenyl arm in the TM5-ECL2 region. At the same time, the abolished arrestin recruitment could also be a consequence of partial agonism (see discussion, below).

In vivo pharmacology of MP1207 and MP1208

Antinociception of MP1207 and MP1208 was evaluated in vivo in mice using a standard 55°C warm-water tail withdrawal assay, with the compounds administered supraspinally (icv) since both compounds were not expected to show systemic activity when administered IP because of being positively charged at physiological pH. The antinociceptive ED50 (and 95% CI) values of MP1207 and MP1208 were 6.1 (4.1–8.9) nmol (Figure 5A), and 7.2 (5.0–10.2), nmol respectively, comparable to that of the kappa agonist U50,488h, 8.8 (5.7–13.5) nmol, although slightly higher than the ED50 of morphine, 4.77 (1.49–28.8) nmol, icv. Both drugs showed antinociceptive responses that peaked at 10 min, returning to baseline values 90 min later for MP1207 (Figure 5B) and 60 min for MP1208 (Figure 5C).

MP1207/1208 show MOR/KOR-mediated antinociception without showing place preference or aversion.

(A) Dose-response curve: Groups of C57BL/6J mice were supraspinally (icv) administered MP1207, MP1208, morphine and U50,488h and antinociception measured using the 55°C tail withdrawal assay at peak effect. Data are shown as mean % antinociception (MPE) ± SEM. ED50 (with 95% CI) values = 6.1 (4.1–8.9) nmol, 7.2 (5.0–10.2) nmol, 4.77 (1.49–28.8) nmol, and 8.8 (5.7–13.5) nmol were calculated for MP1207, MP1208, morphine and U50,488h respectively. (B–C) Antinociceptive time course: Effect of MP1207 (B) and MP1208 (C) at doses of 1, 3, 10, 30, and 100 (n = 8 each group, with n = 16 for MP1208 at 30 nmol) with repeated measures over time. (D–E) MP1207/08 analgesia in KO mice: Analgesic effect of MP1207 (30 nmol icv D ) and MP1208 (35 nmol icv, E) was evaluated in groups (n = 8) of WT (C57BL/6J), MOR KO, KOR KO, and DOR KO mice. Antinociception of MP1207/08 remained intact in DOR KO mice while it was attenuated in MOR KO and KOR KO mice. Results for MP1207 were analyzed with one-way ANOVA followed by Dunnett’s post hoc test; F3,28=10.11, p=0.0001.**p=0.005 relative to WT, ****p<0.0001 relative to WT, ns = p>0.05 relative to WT. Similarly, MP1208 results were analyzed with one-way ANOVA followed by Dunnett’s post hoc test, F3,28=15.35, p<0.0001.**p=0.005 relative to WT, ****p<0.0001 relative to WT, ns = p>0.05 relative to WT. All values are expressed as the mean MPE ± SEM. (F) Conditioned place preference or aversion (CPP/CPA): Place conditioning evaluation of MP1207, 1208, morphine, U50,488h, saline and vehicle in C57BL/6J mice after icv administration. Following determination of initial preconditioning preferences (pre-CPP), mice were place‐conditioned daily for 2 days with MP1207 (30 nmol, n = 23 and 100 nmol, n = 24), MP1208 (100 nmol, n = 26), U50,488 (100 nmol, n = 19) or morphine (30 nmol, n = 12) and examined the fourth day for final conditioned place preference (post-CPP). Mean differences in time spent on the drug‐paired side ± SEM are presented. *p=0.03 (morphine) or **p=0.003 (U50,488h), significantly different from matching pre-conditioning preference; unpaired t-test with Welsch’s correction. Both MP1207/08 were neither reinforcing nor aversive in mice.

MP1207 and MP1208 were characterized in detail, studying opioid receptor selectivity and opioid mediated potential adverse effects. We used transgenic knock out (KO) mice lacking MOR, KOR, or DOR to examine the selectivity of MP1207/08’s analgesic actions (Figure 5D–E). MP1207/08 antinociception was found to be significantly attenuated in both MOR KO and KOR KO mice, but remained intact in DOR KO mice. The results were in line with the >40 fold selectivity of MOR and KOR over DOR in our binding assays. Both MP1207 and MP1208 failed to show either rewarding or aversive behavior in mice in a conditioned place preference paradigm at the highest dose that could be tested given their solubility (100 nmol, icv,~15 x analgesic ED50 dose) (Figure 5F). In contrast, morphine (tested at ~5 x the analgesic ED50 dose) and U50,488h (~15 x analgesic ED50 dose) as expected showed place preference and place aversion, respectively (Figure 5F).

MP1207 and MP1208 were further tested for respiratory effects (Figure 6A for MP1207 and 6B for MP1208). As expected, administration of morphine icv or IP decreased respiratory rate while the KOR agonist U50,488h (icv) was without effect (Figure 6C). In contrast, MP1207 at 30 nmol icv and MP1208 at 35 nmol icv (doses selected to be 5x the ED50 dose) each stimulated respiration. At a higher dose of 100 nmol icv, MP1207 still stimulated respiration, although the effect was less than at the lower dose of 30 nmol (Figure 6A). Finally, we examined locomotor activity in the same mice. In WT mice, MP1207 (Figure 6D) and MP1208 (Figure 6E) stimulated locomotor activity at the lower dose of 30 nmol (icv) compared to 100 nmol (icv). As expected, morphine induced hyperlocomotion (Figure 6F), and this hyperlocomotor effect was significantly greater than seen with either MP1207 or MP1208 at equianalgesic doses (Appendix 1—figure 11). ‘Together, these results support that dual MOR and KOR agonism may offset the liabilities characteristic of receptor-selective agonists’.

MP1207/08 show attenuated respiratory depression and locomotor effects compared to morphine in mice.

Mice were administered either saline (n = 15), vehicle (n = 24), morphine (30 mg/kg, IP; n = 12 or 30 nmol; n = 18 or 100 nmol, icv; n = 16), MP1207 (30 nmol; n = 26 or 100 nmol icv, n = 10), MP1208 (100 nmol icv, n = 10) and the breaths (A–C) or ambulations (D–F) measured every minute and averaged in 20 min segments. Data presented as % vehicle response ±.SEM; A–C, breaths per minute (BPM) or (D–F): ambulation (XAMB). (A) MP1207 (30 nmol icv) increased breathing rates at 60 min (**p=0.005), 80 min (**p=0.008), 100 min (*p=0.01), 120 min (***p=0.0001), 140 min (***p=0.0002), and 160 min (***p=0.0002) compared to vehicle. MP1207 (100 nmol icv) showed increased respiration at 120–160 min (*p=0.02) as determined by two-way ANOVA followed by Dunnett’s multiple-comparison test. (B) MP1208 (35 nmol icv) increased respiratory rate similar to MP1207 and significantly different from vehicle at 140 min (**p=0.0018) and 160 min (**p=0.0028) as determined by two-way ANOVA followed by Sidak’s multiple comparison test. (C) Morphine (30 mg/kg, IP) depressed respiration compared to saline, IP at 20–60 min (****p<0.0001), 80 min (**p=0.0011), 100 min (**p=0.0021), and 120 min (*p=0.02). Respiration after U50,488h (30 or 100 nmol icv) did not significantly differ from that of saline, icv. Morphine (30 nmol, icv) showed respiratory depression at 20 min (*p=0.03), 40 min (*p=0.04) while morphine (100 nmol, icv) showed respiratory depression at 20 min (***p=0.0009) and 40 min (*p=0.02) compared to saline, icv. (D–F) Locomotor effect: (D) MP1207 (30 nmol, icv) significantly increased forward ambulations at 120–140 min (****p<0.0001) and 160 min (***p=0.01) and at 160 min (*p=0.01), whereas the 100 nmol, icv dose did not as determined by two-way ANOVA followed by Dunnett’s multiple-comparison test in comparsion to vehicle. (E) MP1208 (35 nmol icv) increased ambulatory activity similar to MP1207 but less than morphine, and significantly different from vehicle at 120 min (**p=0.002) and 140 min (****p=0.0001) as determined by two-way ANOVA followed by Sidak’s multiple comparison test. (F) Morphine at 30 nmol icv showed significant hyperlocomotion (note axis scale) compared to saline at 80 min (*p=0.02), 100 min (*p=0.05), and 160 min (****p<0.0001). Similarly morphine at 100 nmol was significantly different at 80 min (*p=0.01), 100 min (*p=0.0395), 140 min (*p=0.034) and 160 min (****p<0.0001).

Overall, these results demonstrate that MP1207 and MP1208 produce potent antinociception predominantly mediated by KOR and MOR, yet shows a separation of analgesia from some classic opioid side effects such as respiratory depression, conditioned place preference, and aversion, in contrast with the canonical mu and kappa-opioid receptor selective agonists, morphine and U50,488h.

Discussion

This study employs a new structure-based concept for controlling the functional profile of opioid ligands which allows design of biased ligands at KOR and MOR. Agonists so generated show efficient analgesia in vivo, and lack the respiratory depression and aversion/reward liabilities of classical opioid analgesics. Over the last ~15 years, the discovery of G protein biased opioid ligands has been widely considered as a strategy for the development of potent but safer opioid analgesics. In spite of TRV130’s clinical approval, the results pointing to the ability of MOR-specific G protein biased ligands to alleviate opioid side effects has recently been challenged (Kliewer et al., 2019; Hill et al., 2018; Faouzi et al., 2020b). Among the most important recent findings is that the respiratory depressant effects of morphine appear to be β-arrestin 2-independent. Moreover, mice possessing mutations in the MOR C-tail that prevent phosphorylation by GRK and greatly impair recruitment of β-arrestin two retained opioid-induced respiratory depression, constipation, and withdrawal effects. These results contrast with previous data from β-arrestin 2 KO mice (Raehal et al., 2005). Consistent with past results, tolerance was attenuated, and the analgesic duration of action was prolonged in these mutant mice (Kliewer et al., 2020; Bachmutsky et al., 2020; Kliewer et al., 2019). Similarly, putative biased ligands such as PZM21, TRV130 and SR17018 (Gillis et al., 2020a) have recently been reported to have low intrinsic efficacy at G protein signaling when evaluated in assays without receptor reserve, raising the idea that partial agonism, and not arrestin bias, may be critical to the design of improved drugs.

It is clear that ligands with more precisely tuned selectivity and functional profiles are needed to more definitively interrogate the pharmacological mechanisms for insulating opioid analgesia from their notorious side effects. Using recently solved active-state structure of KOR in complex with MP1104 and computational modeling studies of close analogs MP1202 and IBNtxA, we identified two key sites in the binding pockets of both MOR and KOR: (1) a primarily hydrophobic sub-pocket between TM2-TM3 and (2) a region between TM5-ECL2 lined with acidic residues. We also showed that boat or chair conformations of ring C in the MP1104 scaffold can control the switch of the rigid amidophenyl arm between these two sites. Most importantly, the predicted interactions of the ligand amidophenyl arm in the TM2-TM3 sub-pocket correlated with either β-arrestin2 bias or unbiased signaling, while the switch to theTM5-ECL2 site correlated with G protein biased agonism in the opioid receptors. To test the applicability of this observation, we designed MP1207 and MP1208 with basic moieties that are predicted to facilitate interactions with acidic residues in TM5-ECL2. While the ligands retained high-affinity binding and G protein-mediated signaling, they showed dramatically either reduced potency and/or recruitment at arrestin pathway for both MOR and KOR, thus providing support for our rational design strategy for G protein biased agonists. MD simulations coupled with synthesis of other MP1207 analogs (MP1209/1210-polar and uncharged) that did not engage this region further corroborated the critical role of that region in the G-biased signaling of MP1207/08 at KOR. Notably, our design strategy also led to partial agonism for G protein signaling at both MOR and KOR.

Interestingly, the TM5-ECL2 key role in bias is also in line with the docking pose for a known biased kappa ligand 6’GNTI, which has its guanidine group align within the TM5-ECL2 region similar to the amidophenyl arm of our compounds. The TM5-ECL2 region has also been proposed as a region dictating bias at other GPCRs such as 5HT2B serotonin (McCorvy et al., 2018) and D2 dopamine (Chun et al., 2018) receptors, although the specific mechanisms may differ between these receptors.

Interpretation of bias analysis in vitro has its limitations, as discussed recently (Luttrell et al., 2015; Gundry et al., 2017). For most compounds, lack of measurable arrestin signal in one assay (e.g. BRET) usually was corroborated by strong G protein bias measured with another more amplified assay (e.g. Tango or in different species). For some others, the absence of measurable arrestin recruitment precluded calculation of bias factor in both the BRET and Tango assays. In human KOR Tango assays, dose-dependent curves showed a biphasic shape indicating a second wave of signaling at high concentrations of drugs (see Figure 3B, MP1208, Figure 4D, MP1209/10 and Appendix 1—figure 7C, MP1202). It is unlikely this effect was the result of non-specific interactions, as it was not observed in parallel MOR Tango assays, or with the KOR agonist U50,488H. The most plausible explanation for the observed biphasic response could be compounds at high concentrations hitting intracellular receptors, either with a basal pool of internal receptors or with receptors that have been internalized in response to agonist addition. Although further testing of this hypothesis is beyond the scope of this study, it is supported by previous studies showing that large amounts of intracellular GPCRs exist (Che et al., 2020; Stoeber et al., 2018).

It is additionally important to note that MP1207 and MP1208 are partial agonists for G protein signaling, but that the G protein assays that we have employed are more amplified than the arrestin assays, which can lead to apparent increases in G protein signaling efficacy. Morphine is a full agonist (Emax = 109%) and buprenorphine has higher efficacy (Emax = 59%) in our BRET-based amplified assays in mMOR (Appendix 1—table 7) compared to Emax = 70% and 25% for morphine and buprenorphine respectively in non-amplified assays (Gillis et al., 2020a). Thus, we cannot rule out a critical role for partial agonism in the improved in vivo profile observed for these compounds. Indeed such an interpretation would be more in line with recent publications arguing that it is partial agonism and not bias that accounts for the improved safety profiles of low efficacy MOR agonists (Gillis et al., 2020a; Kliewer et al., 2019; Kliewer et al., 2020; Gillis et al., 2020b).

When evaluated in animal models, MP1207 and MP1208 demonstrated supraspinal analgesia mediated by MOR and KOR while showing attenuated abuse potential and aversion, as well as lack of respiratory depression. Surprisingly, in contrast to the conventional respiratory depression characteristic of MOR-selective agonists, a modest stimulation was observed. The present data are consistent with evidence suggesting that mixed activation of MOR and KOR may produce potent analgesia with reduced liabilities (Brice‐Tutt et al., 2020). Notably, U50,488h sc and icv not only lack respiratory depression on their own (Matthes et al., 1998), but also reduce DAMGO-induced respiratory depression (Dosaka-Akita et al., 1993), supporting a potential role of KOR agonism in alleviating respiratory depression. Moreover, a report examining co-administration of the KOR agonist nalfurafine with the MOR agonist oxycodone noted the reduction of both self-administration as well as respiratory depression, further suggesting that mixed action MOR/KOR ligands (Townsend et al., 2017) may have a superior safety profile over either classical or biased ligands at a single subtype, similar to the action ascribed presently to MP1207 and MP1208.

Given the uncertainty over a mechanism by which KOR activity blunts MOR-mediated respiratory depression, future respiratory testing of mixed action ligands with MOR and KOR KO mice will be needed. Such testing may also better resolve whether weak MOR agonism alone or a combination MOR-KOR dual partial agonism, rather than the functional selectivity of MP1207 and MP1208 would be sufficient to account for the reduced liabilities presently observed. Similarly, while the present results show more than 40-fold selectivity of both MP1207 and MP1208 for MOR and KOR over DOR, it is plausible that pharmacology of these compounds at higher doses may also involve DOR, which is known to modulate MOR mediated behavioral measures. For instance, mixed action MOR-DOR agonists (Lei et al., 2020) are more effective analgesics in a chronic pain setting, while MOR agonists-DOR antagonists (Váradi et al., 2016) reportedly display less tolerance and physical dependence.

Extending this, buprenorphine, a MOR partial agonist with antagonism at KOR/DOR and weak agonism at NOP shows a ceiling effect in respiratory depression assays (Grinnell et al., 2016; Dahan et al., 2005) supporting the premise that favorable multifunctional pharmacology and MOR partial agonism may reduce undesired liabilities while synergistically optimizing analgesia. Admittedly, buprenorphine still displays hyperlocomotion (Marquez et al., 2007) and an inverted U-shaped dose-response in CPP assays (Marquez et al., 2007), and its pharmacology is complicated by its active metabolite norbuprenorphine, which is less active but more efficacious (Huang et al., 2001) and is known to show respiratory depression (Brown et al., 2012). These limitations point to the value of further refinement in the desired multifunctional pharmacological profile of developed compounds. Here, we find that MP1207/08 are partial agonists for G protein signaling, and the attenuated respiratory depression and place preference and place aversion could also result, at least in part, from the lower intrinsic efficacy of these ligands at both KOR and MOR (Gillis et al., 2020a).

This conjunction of KOR partial agonism with MOR partial agonism may have therapeutic benefits over the more broadly active buprenorphine, for example as shown presently with our probes by blunting MOR mediated respiratory depression.

The structure-based approach in this study allowed rational design of MOR and/or KOR G protein biased ligands with reduced β-arrestin2 recruitment. Leads MP1207 and MP1208 display effective analgesia in vivo with reduced abuse potential and aversion, as well as a lack of respiratory depression. While the relative roles of G protein bias, reduced efficacy at G protein pathways, and the mixed MOR-KOR agonism in the improved profile of these lead compounds are not yet clear and will require further investigation, the new rational design concept and insights gained from the structure-function analysis of these derivatives will help more precise tuning of the pluridimentional functional selectivity profiles of optimal analgesics devoid of opioid liabilities.

Materials and methods

Drugs and materials

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Opiates were provided by the Research Technology Branch of the National Institute on Drug Abuse (Rockville, MD). IBNtxA, MP1104, MP102 and new compounds (MP1202, MP1207-MP12108, MP1305, and MP1601) were synthesized. [125I]BNtxA was prepared as previously described (Pickett et al., 2015). Reagents Na125I and [35S]GTPγS were purchased from Perkin-Elmer (Waltham, MA). Selective opioid antagonists were purchased from Tocris Bioscience. Miscellaneous chemicals and buffers were purchased from Sigma-Aldrich.

Chemistry

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Reagents purchased from Sigma-Aldrich Chemicals, Fisher Scientific, Alfa Aesar; were used without further purification. While performing synthesis, reaction mixtures were purified by silica gel flash chromatography on E. Merck 230–400 mesh silica gel 60 using a Teledyne ISCO CombiFlash Rf instrument with UV detection at 280 and 254 nm. RediSep Rf silica gel normal phase columns were used with a gradient range of 0–10% MeOH in DCM. Reported yields are isolated yields upon purification of each intermediate. Final clean (purity ≥95%, UPLC) compounds were used for the study. NMR spectra were collected using Bruker Avance III 500, or Avance III 600 with DCH CryoProbe instruments. Chemical shifts are reported in parts per million (ppm) relative to residual solvent peaks at the nearest 0.01 for proton and 0.1 for carbon (CDCl3 1H: 7.26, 13C: 77.1; and CD3OD 1H: 3.31, 13C: 49.0). Peak multiplicity is reported as the NMR spectra were processed with MestreNova software, namely s – singlet, d – doublet, t – triplet, q – quartet, m – multiplet for examples. Coupling constant (J) values are expressed in Hz. Mass spectra were obtained at the MSKCC Analytical Core Facility using The Waters Acuity SQD LC MS by electrospray (ESI) ionization. High-resolution mass spectra were obtained using a Waters Acuity Premiere XE TOF LC-MS by electrospray ionization and the accurate masses are reported for the molecular ion [M+H]+. Detail experiments and characterization of the new compounds are included in the supporting information section.

Mice

Male C57BL/6J mice (24–38 g) were purchased from Jackson Laboratories (Bar Harbor, ME). MOR KO, KOR KO, and DOR KO mice were bred in the McLaughlin laboratory at University of Florida. Progenitors of the colonies for MOR KO and KOR KO were obtained from Jackson Labs, whereas the DOR KO mice were a generous gift of Dr. Greg Scherrer. All mice used throughout the manuscript were opioid naïve. All mice were maintained on a 12 hr light/dark cycle with Purina rodent chow and water available ad libitum and housed in groups of five until testing.

Radioligand competition binding assays

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[125I]IBNtxA binding was carried out in membranes prepared from Chinese Hamster Ovary (CHO) cells stably expressing murine clones of mMOR, mDOR, and mKOR, as previously described (Váradi et al., 2015a; Pickett et al., 2015; Váradi et al., 2013). In brief, binding was performed at 25°C for 90 min. Binding in mMOR/CHO was carried out in 50 mM potassium phosphate buffer with 5 mM MgSO4 and 20 μg/mL protein while binding in mKOR/CHO and mDOR/CHO was carried out in 50 mM potassium phosphate pH = 7.0 buffer and 40 μg/mL protein. After the incubation, the reaction was filtered through glass-fiber filters (Whatman Schleicher and Schuell, Keene, NH) and washed (3 × 3 mL of ice-cold 50 mM Tris-HCl, pH 7.4) on a semiautomatic cell harvester. Nonspecific binding was determined by the addition of levallorphan (8 μM) to matching samples and was subtracted from total binding to yield specific binding. Protein concentrations were determined using the Lowry method with BSA as the standard (Lowry et al., 1951). K i values were calculated by nonlinear regression analysis in GraphPad Prism.

[35S]GTPγS functional assay

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[35S]GTPγS binding was performed on membranes prepared from transfected cells stably expressing opioid receptors in the presence and absence of the indicated compound for 60 min at 30°C in the assay buffer (50 mM Tris-HCl, pH 7.4, 3 mM MgCl2, 0.2 mM EGTA, and 10 mM NaCl) containing 0.05 nM [35S]GTPγS; 2 μg/mL each leupeptin, pepstatin, aprotinin, and bestatin; and 30 µM GDP, as previously described (Bolan et al., 2004). After the incubation, the reactions were filtered through glass fiber filters (Whatman Schleicher and Schuell, Keene, NH) and washed (3 × 3 mL of ice-cold buffer, 50 mM Tris-HCl, pH 7.4) on a semi-automatic cell harvester. Filters were transferred into vials with 3 mL of Liquiscint (National Diagnostics, Atlanta, GA), and the radioactivity in vials was determined by scintillation spectroscopy in a Tri-Carb 2900TR counter (PerkinElmer Life and Analytical Sciences). Basal binding was determined in the presence of GDP and the absence of drug. Data was normalized to 100 nM DAMGO, DPDPE, and U50,488h for mMOR, mDOR, and mKOR binding, respectively. EC50, IC50, and %Emax values were calculated by nonlinear regression analysis in GraphPad Prism.

cAMP inhibition assay

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To measure Gαi-mediated cAMP inhibition, HEK 293T (ATCC CRL-11268) cells were co-transfected with human opioid receptor (hMOR/hKOR/hDOR) along with a luciferase-based cAMP biosensor (GloSensor; Promega) and assays were performed similar to previously described (Che et al., 2018; Fenalti et al., 2014). After 16 hr, transfected cells were plated into Poly-lysine coated 384-well white clear bottom cell culture plates in DMEM with 1% dialyzed FBS at a density of 15,000–20,000 cells per 40 μL per well and incubated at 37°C with 5% CO2 overnight. Next day, drug solutions were prepared in freshly prepared buffer [20 mM HEPES, 1 X HBSS, 0.3% bovine serum album (BSA), pH 7.4] at 3X drug concentration. Plates were decanted and received 20 μL per well of drug buffer (20 mM HEPES, 1X HBSS, pH 7.4) followed by addition of 10 μL of drug solution (three wells per condition) for 15 min in the dark at room temperature. To stimulate endogenous cAMP via β adrenergic-Gs activation, 10 μL luciferin (4 mM, final concentration) supplemented with isoproterenol (400 nM, final concentration) were added per well. Cells were incubated in the dark at room temperature for 15 min, and luminescence intensity was quantified using a Wallac TriLux Microbeta (Perkin Elmer) luminescence counter. Results (relative luminescence units) were plotted as a function of drug concentration, normalized to Emax of DAMGO and U50,488h for MOR and KOR respectively; and analyzed using ‘log(agonist) vs. response’ in GraphPad Prism.

Tango β-arrestin recruitment assay

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The Tango assays were performed as previously described (Che et al., 2018). HTLA cells expressing TEV fused-β-Arrestin2 were transfected with human opioid receptors (hMOR/hKOR/hDOR) Tango construct. The next day, cells were plated in DMEM supplemented with dialyzed FBS (1%) in poly-L-lysine coated 384-well white clear bottom cell culture plates at a density of 10,000–15,000 cells/well in a total of 40 µL. The cells were incubated for at least 6 hr before receiving drug stimulation. Drug solutions were prepared in drug buffer (20 mM HEPES, 1×HBSS, 0.3% BSA, pH 7.4) at 3X and added to cells (20 µL per well) for overnight incubation. The same drug solutions were used for the Tango and cAMP assays. The next day, media and drug solutions were removed and 20 µL per well of BrightGlo reagent (Promega, with 1:20 dilution) was added. The plate was incubated for 20 min at room temperature in the dark before counting using a luminescence counter. Results (relative luminescence units) were plotted as a function of drug concentration, normalized to Emax of DAMGO and U50,488h for hMOR and hKOR respectively, and analyzed using ‘log(agonist) vs. response’ in GraphPad Prism.

Bioluminescence resonance energy transfer (BRET) assay

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The BRET assays were performed by following the protocol published previously (Kruegel et al., 2016). In brief, the following cDNA amounts were transfected into HEK-293T cells (5 × 106 cells/plate) in 10 cm dishes using polyethylenimine (PEI) in a 1:1 ratio (diluted in Opti-MEM, Life Technologies): for G-protein activation; 2.5 μg mMOR/mKOR/mDOR, 0.125 μg GαoBRLuc8, 6.25 μg β1, 6.25 μg mVenus-γ2; for arrestin recruitment; 2 μg mMOR/mKOR/mDOR, 0.25 μg Rluc8- arrestin3-Sp1, 5 μg mem-linker-citrine-SH3, 5 μg GRK2. Cells were maintained in HEKS44 293T media described above. The media was changed after 24 hr of the transfection and cells were dissociated and re-suspended in phosphate buffered saline (PBS) at 48 hr of transfection. Approximately 200,000 cells/well were added to a black-framed, white well 96-well plate (Perkin Elmer; Waltham, MA). The microplate was centrifuged, and the cells were resuspended in PBS. For agonist experiments, after 5 min, 5 μM of the luciferase substrate coelenterazine H was added to each well. After 5 min, ligands were added, and the BRET signal was measured 5 min later using PHERAstar FS plate reader. For antagonist competition experiments, cells were pre-incubated with the antagonist at varying concentration for 30 min. Coelenterazine H (5 μM) was then added to each well for 5 min. Following coelenterazine H incubation, a fixed concentration of the reference agonist (5x EC50) was added, and the BRET signal was measured at 30 min using PHERAstar FS plate reader. The signal was quantified by calculating the ratio of the light emitted by the energy acceptor, mVenus (510–540 nm), or citrine (510–540 nm), over the light emitted by the energy donor, RLuc8 (485 nm). This drug-induced BRET signal was normalized to Emax of DAMGO or U50,488h at MOR and KOR respectively. Dose response curves were fit using a three-parameter logistic equation in GraphPad Prism.

Bias determination

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Bias analyses was carried out using the method proposed by Kenakin et al., 2012. that is based on the Black and Leff operational method (Black and Leff, 1983). For this we followed the step-wise protocol described by Gomes et al recently (Gomes et al., 2020). Dose response curves obtained in G protein signaling and arrestin recruitment assays were normalized to that of the standards (DAMGO for MOR and U50,488h for KOR). Data points were fit to the three parameter logistic equation in Prism 7.0 to obtain maximal response (Emax), EC50 values for all ligands for both assays. Transduction coefficients (log (T/KA)) were calculated using the Black and Leff operational model. Log(T/KA) [also referred as Log (RA)] ratios for each ligand in different pathways were determined. Subtract Log(T/KA) ratio of the standard from those of the other ligands to obtain normalized coefficients ΔLog(T/KA). ΔΔLog(T/KA) was determined by subtracting ΔLog(T/KA) ratios from different pathways. The actual value of bias was calculated using anti-Log ΔΔLog(T/KA) values.

Assessment of off-target activity of MP1207 using PRESTO-Tango GPCR-ome

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To identify potential off-target activity of MP1207, we used the National Institutes of Mental Health Psychoactive Drug Screen Program. MP1207 was first tested for activity against 330 non-olfactory GPCRs using the PRESTO-Tango GPCRome screening β-arrestin recruitment assay at 3 μM MP1207. The activity at each receptor was measured in quadruplicate.

Screening of compounds was accomplished using previously described methods with several modifications (Kroeze et al., 2015). First, HTLA cells were plated in DMEM with 2% dialyzed FBS and 10 U/mL penicillin-streptomycin. Next, the cells were transfected using an in-plate PEI method (Longo et al., 2013). PRESTO-Tango receptor DNAs were resuspended in OptiMEM and hybridized with PEI prior to dilution and distribution into 384-well plates and subsequent addition to cells. After overnight incubation, drugs diluted in DMEM with 1% dialyzed FBS were added to cells without replacement of the medium. The remaining steps of the PRESTO-Tango protocol were followed as previously described.

Tail-withdrawal assay

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The 55°C warm-water tail-withdrawal assay was conducted in mice as a measure of acute thermal antinociception as described previously (Reilley et al., 2010). Briefly, each mouse was tested for baseline tail-withdrawal latency prior to drug administration. Following drug administration, the latency for each mouse to withdraw the tail was measured every 10 min until latency returned to the baseline value. A maximum response time of 15 s was utilized to prevent tissue damage. If the mouse failed to display a tail-withdrawal response within 15 s, the tail was removed from the water and the animal was assigned a maximal antinociceptive score of 100%. Data are reported as percent antinociception, calculated by the equation: % antinociception = 100 x [(test latency - baseline latency)/ (15 - baseline latency)]. This was utilized to account for innate variability between mice. Compounds were administered either, interperitoneally (IP) or intracerebroventricularly (icv) and the analgesic action of compounds was assessed at as described previously (Haley and McCORMICK, 1957). To briefly describe icv administration: mice were anesthetized using isoflurane. A small (3 mm) incision was made in the scalp, and the drug (2 µl/mouse) was injected (using a 10 μL Hamilton syringe fitted to a 27-gauge needle) into the right lateral ventricle at the following coordinates: 2 mm caudal to bregma, 2 mm lateral to sagittal suture, and 2 mm in depth.

Respiratory and locomotor effects

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Respiration rates and spontaneous ambulation rates were monitored using the automated, computer-controlled Comprehensive Lab Animal Monitoring System (CLAMS, Columbus Instruments, Columbus, OH) as described previously (Reilley et al., 2010; Cirino et al., 2019). Awake, freely moving adult male mice (C57BL6/J wild-type, MOR KO, and KOR KO) were habituated in closed, sealed individual apparatus cages (23.5 cm x 11/5 cm x 13 cm) for 60 min before testing. A baseline for each animal was obtained over the 60-min period before drug injection, and testing began immediately post-injection. Vehicle, morphine (30 mg/kg, IP or 30 or 100 nmol, icv), or MP1207 (30 or 100 nmol, icv) or MP1208 (35 nmol, icv) were administered (icv or IP) and five min later mice were confined to the CLAMS testing cages for 200 min. Using a pressure transducer built into the sealed CLAMS cage, the respiration rate (breaths/min) of each occupant mouse was measured. Infrared beams located in the floor measured locomotion as ambulations, from the number of sequential breaks of adjacent beams. Data are expressed as percent of vehicle control response.

Conditioned place preference and aversion

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Mice were conditioned with a counterbalanced place conditioning paradigm using similar timing as detailed previously (Váradi et al., 2016). Groups of C57BL/6J mice (n = 18–24) freely explored a three-compartment apparatus for 30 min. The amount of time subjects spent in each compartment was measured over the 30 min testing period. Prior to place conditioning, the animals did not demonstrate significant differences in their time spent exploring the left vs right compartments. During each of the next 2 days, mice were administered vehicle (0.9% saline) and consistently confined in a randomly assigned outer compartment for 40 min, half of each group in the right chamber, half in the left chamber. Four hours later, mice were administered drugs morphine (30 nmol, icv), U50,488h (100 nmol, icv), MP1207 (30 and 100 nmol, icv), MP1208 (100 nmol, icv) or vehicle and were placed to the opposite compartment for 40 min. Conditioned place preference or aversion data are presented as the difference in time spent in drug- and vehicle associated chambers.

Molecular modeling

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The receptor proteins were extracted from the RCSB server for mouse MOR (PDBID: 5c1m), and human KOR (PDBID: 6b73), representing agonist-bound active state of the receptors. All the objects except the receptor protein subunit, the crystallized ligand, and three crystallographic waters important for ligand interactions were deleted from the MOR structure, and the protein was prepared by addition and optimization of hydrogens and optimization of the side chain residues. A similar procedure was also followed for the KOR structure, with an additional step of transplanting and optimizing the three crystallographic water molecules from the active state MOR into active state KOR. Ligands were sketched, assigned formal charges and energy-optimized prior to docking. The ligand docking box for potential grid docking was defined as the whole extracellular half of the protein, and all-atom docking was performed using the energy minimized structures for all ligands with a thoroughness value of 30. The best-scored docking poses, for both chair and boat forms, were further optimized by several rounds of minimization and Monte Carlo sampling of the ligand conformation, including the surrounding side-chain residues (within 5 A° of the ligand) and the three crystallographic water moleculess in the orthosteric sites. All the above molecular modeling operations were performed in ICM-Pro v3.8–5 molecular modeling package. The DFT (B3LYP) QM calculations for boat and chair conformations of ligands were performed using Gaussian03 with two basis sets (LanL2DZ and DGDZVP) using the servers at the High-Performance Computing at the University of Southern California.

The molecular dynamics simulation setup for the MP1207-bound KOR (residues 51-340) model was built using CHARMM-GUI web server (Lee et al., 2016). The CHARMM General Force Field (Kim et al., 2017) was used to generate CHARMM topology and parameter files for MP1207. The ligand-bound receptor system was embedded in a lipid bilayer with a POPC/cholesterol ≈ 9:1 ratio and with an area of 80 Å × 80 Å. The system was solvated with explicit TIP3P water molecules, ionized with 0.15 M Na+ cations, and neutralized with Cl- ions. The resulting simulation system had a total of 79,258 atoms and occupied an initial volume of 80 Å × 80 Å × 119 Å. The CHARMM36 force field (Best et al., 2012) was employed to perform all-atom MD simulations using the GROMACS software package version 2018.1 (Abraham et al., 2015). Following the initial energy minimization of the water boxed, lipid embedded and ionized MP1207-bound KOR system, six short equilibration runs were carried out while gradually decreasing harmonic constraints on lipid and protein heavy atoms for a cumulative run of 15 ns. The particle mesh Ewald algorithm was utilized to calculate long-range electrostatic interactions, and van der Waals interactions were switched off gradually between 10 Å to 12 Å. Periodic boundary conditions were applied to simulation boxes, and simulations were run with integration time step of 2 fs at 310 K. The resulting trajectories from two independent 1000ns long production runs were analyzed using in-built GROMACS analysis tools. All MD simulations and analyses were performed using the servers at the High-Performance Computing at University of Southern California.

Chemistry - synthesis

MP1202, MP1207, MP1208, MP1209, and MP1210

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Synthesis of m-iodoarylamidomorphinans (MP1202) was achieved, by starting with known codeine phthalimide (Váradi et al., 2015a) one in six sequential steps (Appendix 1—scheme 1A). The codeine phthalimides one was prepared from morphine in two steps according to the literature procedures. The reduction of codeine phthalimides in the presence of Pd/C and hydrogen followed by phthalimide group removal using excess of hydrazine hydrate gave the β-dihydrocodeine amine 2 (Crooks et al., 2006; Simon et al., 1994; Simon et al., 1992). The β-dihydrocodeine amine two was treated to m-iodobenzoic acid in the presence coupling reagent HATU with an organic base DIPEA to furnish corresponding m-iodoarylamidomorphinan 3. The m-iodoarylamidomorphinan three was treated with DIAD at 65°C in acetonitrile for 20 hr followed by two equivalents of pyridine hydrochloride (Py.HCl) treatment at room temperature to obtain the m-iodoarylamidonormorphinan 4 (Yuan et al., 2013). N-alkylation of 4 was achieved by heating it with (bromomethyl)cyclopropane in the presence of K2CO3 in DMF to furnish 5. Finally, O-demethylation in five was performed using standard BBr3 demethylation protocol to obtain MP1202 (Váradi et al., 2015a). On the other hand, MP1207–MP1208 were prepared (Appendix 1—scheme 1B) using 6 (β-dihydro N-CPM morphineamine) which was prepared form morphine in seven steps using known protocols (Simon et al., 1994; Simon et al., 1992). In addition, di-Boc-guanidinomethyl benzoic acid eight was prepared by reacting amino methyl benzoic acid with N,N′-di-Boc-1H-pyrazole-1-carboxamidine at 50°C (Robinson and Roskamp, 1997). Next, m-Boc-aminomethyl benzoic acid (Zhang et al., 2014) seven and di-Boc-guanidinomethyl benzoic acid eight were coupled with 6 (β-dihydro N-CPM morphineamine) in DMF in the presence of HATU and DIPEA to obtain corresponding analogs 9–10. Finally, deprotection of Boc group at 9–10 using TFA/DCM in the presence of triethyl silane as a cation scavenger furnished the desired compounds; m-aminomethyl and m-guanidinomethyl arylamidodihydromorphinans MP1207–MP1208. Appendix 1—scheme 2 shows the synthesis of MP1209 and MP1210. Briefly, six was coupled with commercially available 3-(hydroxymethyl)benzoic acid in presence of PyBOP as the coupling agent to give MP1210. Coupling of 6 (β-dihydro N-CPM morphineamine) with p-Boc-aminomethyl benzoic acid and deprotection of Boc group gave final product, MP1209.

MP1305

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Synthesis of 14-O-methyl m-iodoarylamidomorphinan MP1305 was achieved by starting with the known ketal 12 in seven sequential steps (Appendix 1—scheme 3). At first, phenolic and ketone groups in naloxone were protected to obtain the ketal 12 prior the methylation of sterically hindered 14-O position (Nagase et al., 2006). The ketal 12 was treated with an excess of NaH at 0°C in DMF and the mixture was heated with iodomethane at 55°C. Then, the ketal protecting group was removed by treating with aqueous HCl in methanol under mild heating conditions resulting in the known 14-O-methyl ketone 13 (Kobylecki et al., 1982). Stereoselective reduction of the ketone 13 using lithium selectride in THF at low temperature furnished corresponding α alcohol 14. The stereocenter inversion at C-6 position, with the introduction of a phthalimide moiety, was achieved using DIAD and PPh3 by employing standard Mitsunobu protocol. Next, phthalimide moiety was removed by treating with excess of hydrazine hydrate in methanol to obtain β amine 15. Then, amine 15 was treated to m-iodobenzoic acid in the presence HATU and DIPEA in DMF followed by 3-O- demethylation of the intermediate using BBr3 in DCM furnished 14-O-methyl m-iodoarylamidomorphinan MP1305.

MP1601

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Synthesis of m-iodoarylamido-4,5-deoxymorphinan MP1601 was achieved from the known ketone 16 (Appendix 1—scheme 4). The ketone 16 was synthesized in five steps using naltrexone by following literature reports (Tius and Kerr, 1992; Hupp and Neumeyer, 2010; Zhang et al., 2007). Reductive amination of the ketone 16 using NH4OAc/NaCNBH3 in methanol gave a racemic mixture of C-6 α/β amines (Majumdar et al., 2011b). Separation of β amine from the α/β mixture while work up, was more problematic then anticipated to isolate in optimum yield. However, upon using a mixture of 10% TEA and 1% MeOH in DCM as a column solvent with a silica gel column chromatography, β amine 17 was isolated in modest yield. The pattern spectral information in proton NMRs of the α and β amines are in agreement with that of close 4,5-epoxymorphinan α/β amines (Jiang et al., 1977). For instance, upon an introduction of amino moiety at C-6 position, the aromatic proton at C-4 position displays a significant downfield shift in comparison to that of ketone 15 (δ = 6.80 ppm C4-HAr). The C-4 proton chemical shift (δ) values in β and α amines are 7.01 and 6.86 ppm, which is about 0.21 and 0.06 ppm downfield shift respectively, indicating that β amino group poses lower effect (Jiang et al., 1977). Next, the β amine 17 was coupled with m-iodobenzoic acid using HATU as a coupling reagent in the presence of TEA to obtain 3-methoxy m-iodoarylamido-4,5-deoxymorphinan 18. Finally, deprotection of 3-methyl group in 18 using BBr3 in DCM furnished the desired m-iodoarylamido-4,5-deoxymorphinan MP1601.

Preparation and characterization of new compounds

(7R,12bS)−9-methoxy-3-methyl-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzo furo[3,2-e]isoquinolin-7-amine (2)

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The known phthalimide 1 (3 g, 7.0 mmol) was dissolved in a stirred solution of DCM (15 mL) in methanol (100 mL). Palladium catalyst (10% Pd/C, 149 mg, 0.2 eq.) was added and the mixture was hydrogenated at 50 psi. After the completion of reaction monitored by mass spectrometry, the solution was filtered through celite, concentrated under reduced pressure, and the crude product was purified by silica gel column chromatography (ISCO, 40 g column) using methanol (5–15%) in DCM to get a white solid (2.7 g; Yield 90%) of the desired phthalimide dihydro intermediate whose spectral data matched with the literature reports. Then, hydrazine hydrate (21.5 mL, 34.5 mmol, 10 eq.) was added to the stirred solution of phthalimide dihydro intermediate (1.48 g, 3.4 mmol) in dry methanol (10 mL) at once at rt and the reaction was continued overnight. The reaction mixture was diluted with DCM (40 mL) and the organic layer washed with brine (2 × 20 mL), dried over anhydrous Na2SO4, filtered and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography (ISCO, 12 g column) using a mixture of methanol in ethyl acetate with small amount of ammonium hydroxide as a base (87%EtOAC/10%MeOH/3%NH4OH) to get a white solid. Finally, the white solid was re-dissolved in EtOAc, filtered, and precipitated by petroleum ether to get (0.96 g; Yield 93%) of the desired product 2. The spectral data of the compound 2 was matched with the literature reports (Váradi et al., 2015a).

3’-Iodo-N-((7R,12bS)−9-methoxy-3-methyl-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)benzamide (3)

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m-Lodobenzoic acid (1.0 g, 4.03 mmol, 1.3 eq.) was added to a stirred solution of β−7,8-dihydro-codeine-NH2 2 (932 mg, 3.10 mmol) in DMF (10 mL) at. HATU (1.5 g, 4.03 mmol, 1.3 eq.) was added to the mixture at rt at once and after 5 min, DIPEA (1.62 mL, 9.31 mmol, 3 eq.) was added. After 20 min, the reaction mixture was diluted with EtOAc (80 mL). The EtOAc layer was washed with brine (5 × 50 mL) to remove DMF, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (0–5%) in DCM to get desired products 3; (977 mg; Yield 59%). 1H NMR (600 MHz, CDCl3) δ = 8.10 (t, J = 1.7 Hz, 1H), 7.85–7.77 (m, 1H), 7.72 (dt, J = 7.9, 1.3 Hz, 1H), 7.13 (t, J = 7.8 Hz, 1H), 6.73 (d, J = 8.2 Hz, 1H), 6.66 (d, J = 8.2 Hz, 1H), 4.56 (d, J = 8.0 Hz, 1H), 3.82 (s, 3H), 3.75 (dq, J = 12.6, 3.3 Hz, 1H), 3.15 (s, 1H), 3.02 (d, J = 18.3 Hz, 1H), 2.57–2.51 (m, 1H), 2.43 (s, 3H), 2.27–2.14 (m, 2H), 2.05–1.98 (m, 1H), 1.87 (s, 1H), 1.70 (ddd, J = 12.3, 3.8, 1.6 Hz, 1H), 1.62–1.49 (m, 1H), 1.38 (qd, J = 13.0, 2.5 Hz, 1H), 1.11 (m, 1H). 13C NMR (151 MHz, CDCl3) δ = 165.8, 143.9, 143.7, 140.2, 136.6, 136.0, 130.1, 126.2, 119.3, 114.1, 94.1, 92.8, 77.2, 77.0, 76.8, 59.5, 56.7, 53.1, 47.2, 43.4, 42.7, 28.7, 24.1, 20.1; HRMS calcd for C25H27IN2O3 [M+H]+, 531.1145; found, 531.1140.

3’-Iodo-N-((7R,12bS)−9-methoxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)benzamide (4)

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The dihydrocodeine iodoaryl amide (952 mg, 1.795 mmol) was added to a stirred solution of DIAD (636 µL. 3.21 mmol, 8 eq.) CH3CN (15 mL) at rt under an argon and the reaction mixture was heated to 65°C for 20 hr. The reaction mixture cooled to rt and pyridine HCl (415 mg, 3.59 mmol, 2 eq.) was added and the reaction was continued for 3 days. The solvent was removed under reduced pressure and the content was redissolved in DCM (30 mL). The DCM layer was washed with brine (2 × 20 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (2–15%) in DCM to get desired products 4; (607 mg; Yield, 66%). 1H NMR (600 MHz, CDCl3) δ = 9.80 (s, 2H), 8.14 (t, J = 1.7 Hz, 1H), 7.80 (dt, J = 7.9, 1.3 Hz, 1H), 7.75 (dt, J = 7.8, 1.3 Hz, 1H), 7.15 (t, J = 7.8 Hz, 1H), 6.81 (d, J = 8.3 Hz, 1H), 6.75 (d, J = 8.2 Hz, 2H), 4.73 (d, J = 8.1 Hz, 1H), 4.00 (t, J = 4.1 Hz, 1H), 3.84 (s, 3H), 3.79 (ddd, J = 12.5, 8.2, 4.6 Hz, 1H), 3.32 (d, J = 19.1 Hz, 1H), 3.21 (dd, J = 13.5, 4.2 Hz, 1H), 3.06 (dd, J = 19.2, 5.9 Hz, 1H), 2.83 (s, 1H), 2.62 (dt, J = 12.4, 3.7 Hz, 1H), 2.18 (td, J = 13.3, 4.6 Hz, 1H), 1.91–1.80 (m, 1H), 1.67 (dd, J = 13.5, 4.1 Hz, 1H), 1.53–1.44 (m, 1H), 1.13–1.03 (m, 1H). 13C NMR (151 MHz, CDCl3) δ = 165.7, 149.8, 144.4, 144.0, 140.4, 136.2, 136.0, 136.0, 130.2, 127.5, 126.4, 123.7, 123.0, 120.4, 115.5, 94.2, 91.8, 56.9, 53.4, 52.6, 52.4, 42.7, 38.7, 37.9, 32.2, 28.0, 25.7, 23.3; ESI-MS m/z: 517.12 [M+H]+.

N-((7R,12bS)−3-(Cyclopropylmethyl)−9-methoxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)−3-iodobenzamide (5)

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Na2CO3 (92.4 mg, 0.87 mmol, 1.5 eq.) and (bromomethyl)cyclopropane (67.6 µL, 0.69 mmol, 1.2 eq.) were added to a stirred solution of dihydronorcodeine 4 (300 mg, 0.581 mmol) in DMF (1 mL) at rt under argon. The, the reaction mixture was heated to 90°C overnight. Then the reaction mixture was cooled to rt and was diluted with EtOAc (20 mL). The EtOAc layer was washed with brine (5 × 20 mL) to remove DMF, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (3–10%) in DCM to get desired products 5; (205 mg; Yield, 62%). 1H NMR (600 MHz, CDCl3) δ = 8.09 (t, J = 1.8 Hz, 1H), 7.79 (dt, J = 7.9, 1.3 Hz, 1H), 7.72 (dt, J = 7.8, 1.3 Hz, 1H), 7.13 (t, J = 7.8 Hz, 1H), 6.72 (d, J = 8.2 Hz, 1H), 6.64 (d, J = 8.2 Hz, 1H), 6.40 (s, 1H), 4.55 (d, J = 8.0 Hz, 1H), 3.82 (s, 3H), 3.75 (ddd, J = 12.4, 8.2, 4.8 Hz, 1H), 3.41 (s, 1H), 2.91 (d, J = 18.3 Hz, 1H), 2.82–2.76 (m, 1H), 2.39 (dd, J = 87.8, 49.2 Hz, 4H), 1.92 (d, J = 16.2 Hz, 1H), 1.70 (ddd, J = 12.3, 3.7, 1.7 Hz, 1H), 1.39 (td, J = 12.9, 2.5 Hz, 1H), 1.12 (qd, J = 12.9, 2.5 Hz, 1H), 0.87 (s, 1H), 0.53 (d, J = 8.0 Hz, 2H), 0.15 (s, 2H). 13C NMR (151 MHz, CDCl3) δ = 171.2, 165.8, 143.8, 140.2, 136.6, 136.0, 130.1, 126.2, 119.2, 94.1, 92.9, 60.4, 59.8, 57.1, 56.6, 53.2, 45.7, 44.0, 28.7, 24.2, 21.1, 20.6, 14.2, 4.0, 3.8; HRMS calcd for C28H31IN2O3 [M+H]+, 571.1458; found, 571.1474.

N-((7R,12bS)−3-(Cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)−3-iodobenzamide (MP1202)

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A solution of BBr3 (7 mL, 7 eq.; 1M in DCM,) was slowly added to a stirred solution of methoxy morphinan 4 (181 mg, 0.31 mmol) in DCM (7 mL) at 0°C under argon. The reaction mixture was stirred for 10 min at 0°C and 20 more minutes at rt. The reaction mixture was quenched with excess of ammonia solution (5%) and the mixture was stirred for one hour. Then, the mixture was diluted with DCM (20 mL). The DCM layer was washed with brine (2 × 20 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (7–15%) in DCM to get desired products MP1202; (111 mg; Yield, 63%). 1H NMR (600 MHz, CDCl3+CD3OD) δ = 8.10 (t, J = 1.7 Hz, 1H), 7.74 (m, 2H), 7.11 (t, J = 7.8 Hz, 1H), 6.62 (d, J = 8.1 Hz, 1H), 6.49 (d, J = 8.1 Hz, 1H), 4.38 (d, J = 7.5 Hz, 1H), 3.80 (ddd, J = 12.7, 7.5, 4.8 Hz, 1H), 3.55 (s, 3H), 3.43–3.23 (m, 2H), 2.82 (d, J = 18.3 Hz, 1H), 2.68 (d, J = 12.1 Hz, 1H), 2.41 (s, 1H), 2.32 (d, J = 18.6 Hz, 2H), 2.08 (d, J = 18.1 Hz, 2H), 1.81–1.76 (m, 2H), 1.61 (m, 1H), 1.56–1.50 (m, 1H), 1.35 (qd, J = 13.0, 2.6 Hz, 1H), 1.09–0.97 (m, 1H), 0.79 (s, 1H), 0.49 (d, J = 8.0 Hz, 2H), 0.10 (dd, J = 14.1, 9.2 Hz, 2H). 13C NMR (151 MHz, CDCl3+CD3OD) δ = 166.7, 142.8, 140.4, 136.2, 136.1, 130.1, 126.4, 119.4, 118.0, 93.9, 93.6, 59.5, 56.8, 52.2, 45.8, 43.7, 2.78, 24.1, 20.3, 3.93, 3.8; HRMS calcd for C27H29IN2O3 [M+H]+, 557.1301; found, 557.1304.

(Z)−3-((2,3-bis(tert-Butoxycarbonyl)guanidino)methyl)benzoic acid (8)

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N,N′-di-Boc-1H-pyrazole-1-carboxamidine (54 mg, 0.17 mmol, 1.1 eq.) and triethyl amine (67 µL, 0.44 mmol, three eq.) were added to a stirred solution of 3-(aminomethyl) benzoic acid hydrochloride (30 mg, 0.16 mmol, 1 eq.) in MeOH (1 mL) at rt under argon. The reaction was heated to 50°C and continued for 7 hr. The solvent was removed under reduced pressure, and the content was diluted with EtOAc (15 mL). Water (15 mL) was added and the mixture was acidified with citric acid (to pH ~3). The organic layer was separated and was washed with brine (15 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of EtOAc (20–50%) in hexanes to get the desired products two as a white solid (46 mg; Yield, 78%); 1H NMR (600 MHz, Chloroform-d) δ = 11.56 (s, 1H), 8.67 (t, J = 5.4 Hz, 1H), 8.11–7.90 (m, 2H), 7.57 (dt, J = 7.8, 1.4 Hz, 1H), 7.46 (t, J = 7.7 Hz, 1H), 4.71 (d, J = 5.3 Hz, 2H), 1.50 (d, J = 17.8 Hz, 18H). 13C NMR (151 MHz, CDCl3) δ = 170.9, 163.5, 156.3, 153.2, 138.0, 133.1, 129.7, 129.6, 129.5, 129.0, 83.4, 79.6, 44.5, 28.3, 28.1.

tert-Butyl (3-(((7R,12bS)−3-(Cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)carbamoyl)benzyl)carbamate (9)

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The Boc aminomethylbenzoic acid 7 (28 mg, 0.11 mmol, 1.3 eq.) was added to a stirred solution of β-dihydro N-CPM morphineamine 6 (28 mg, 0.08 mmol, 1 eq.) in DMF (0.4 mL) at rt under argon. HATU (39 mg, 0.10 mmol, 1.2 eq.) was added to the mixture at rt at once and after 5 min, DIPEA (45 µL, 0.25 mmol, 3 eq.) was added. After 2 hr, the reaction mixture was diluted with EtOAc (15 mL). The EtOAc layer was washed with brine (5 × 15 mL) to remove DMF, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The residue was redissolved in MeOH (0.5 mL) and sodium methoxide in MeOH (0.2 mL, 0.5 M) was added to the mixture. After 15 min, the solvent was removed, redissolved in EtOAc (15 mL), washed with brine, dried over anhydrous Na2SO4, filtered, and the crude product was purified by silica gel column chromatography using a mixture of methanol (3–10%) in DCM to get nine as a white solid, (31 mg, Yield; 66%); 1H NMR (600 MHz, Chloroform-d) δ = 7.80 (s, 1H), 7.45 (d, J = 44.7 Hz, 2H), 7.34 (d, J = 7.6 Hz, 1H), 7.19 (t, J = 7.7 Hz, 1H), 6.72 (d, J = 8.0 Hz, 1H), 6.59 (d, J = 8.1 Hz, 1H), 5.33 (s, 1H), 4.69 (s, 1H), 4.25 (dd, J = 15.2, 5.9 Hz, 1H), 4.16 (dd, J = 15.2, 6.1 Hz, 1H), 3.81 (s, 1H), 3.07 (s, 1H), 2.91 (d, J = 18.3 Hz, 1H), 2.69 (s, 4H), 2.47–2.11 (m, 1H), 1.84 (d, J = 12.6 Hz, 1H), 1.71 (s, 1H), 1.56 (d, J = 32.4 Hz, 1H), 1.43 (s, 9H), 1.25 (s, 1H), 1.06 (q, J = 12.7 Hz, 1H), 0.94–0.77 (m, 1H), 0.65 (s, 2H), 0.29 (br, 2H). 13C NMR (151 MHz, CDCl3) δ = 167.3, 156.2, 143.0, 139.3, 134.3, 130.1, 128.6, 126.7, 125.7, 119.5, 92.4, 79.9, 59.1, 57.5, 52.0, 44.4, 43.1, 31.9, 29.7, 29.6, 29.3, 28.4, 24.0, 22.7, 21.0, 14.1, 4.4. ESI-MS m/z: 560.54 [M+H]+.

2,3-Bis(tert-Butoxycarbonyl)(-N-(7R,12bS)−3-(cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)−3-(guanidinomethyl)benzamide (5)

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The di-Boc-guanoomethylbenzoic acid 8 (32.9 mg, 0.08 mmol, 1.3 eq.) was added to a stirred solution of β-dihydro N-CPM morphineamine 6 (21 mg, 0.06 mmol, 1 eq.) in DMF (0.4 mL) at rt under argon. HATU (29 mg, 0.07 mmol, 1.2 eq.) was added to the mixture at rt at once and after 5 min, DIPEA (33 µL, 0.19 mmol, 3 eq.) was added. After 2 hr, the reaction mixture was diluted with EtOAc (15 mL). The EtOAc layer was washed with brine (5 × 15 mL) to remove DMF, dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The residue was redissolved in MeOH (0.5 mL) and sodium methoxide in MeOH (0.2 mL, 0.5 M) was added to the mixture. After 15 min, the solvent was removed, redissolved in EtOAc (15 mL), washed with brine, dried over anhydrous Na2SO4, filtered, and the crude product was purified by silica gel column chromatography using a mixture of methanol (3–10%) in DCM to get 10 as a white solid (32 mg, Yield; 71%); 1H NMR (600 MHz, Chloroform-d) δ = 11.52 (s, 1H), 8.82 (d, J = 6.9 Hz, 1H), 7.78 (s, 1H), 7.43 (d, J = 7.5 Hz, 1H), 7.29 (d, J = 7.6 Hz, 1H), 7.19 (t, J = 7.7 Hz, 1H), 7.07 (d, J = 14.4 Hz, 1H), 6.82 (d, J = 8.1 Hz, 1H), 6.63 (d, J = 8.2 Hz, 1H), 4.87 (s, 1H), 4.57 (dd, J = 15.4, 6.7 Hz, 1H), 4.44–4.34 (m, 1H), 3.85 (s, 2H), 3.24 (s, 1H), 2.97 (d, J = 18.1 Hz, 1H), 2.74 (s, 3H), 2.48 (s, 1H), 2.37–2.16 (m, 1H), 2.03–1.91 (m, 1H), 1.83 (s, 1H), 1.62 (dd, J = 30.8, 8.7 Hz, 1H), 1.49 (d, J = 6.2 Hz, 18H), 1.37 (dd, J = 13.6, 8.9 Hz, 1H), 1.32–1.21 (m, 1H), 1.13 (q, J = 12.7 Hz, 1H), 0.93–0.78 (m, 1H), 0.68 (s, 2H), 0.37 (d, J = 54.7 Hz, 2H). 13C NMR (151 MHz, CDCl3) δ = 167.0, 163.1, 156.3, 153.2, 143.1, 141.4, 137.9, 133.7, 129.8, 128.6, 126.5, 126.2, 120.0, 118.4, 92.4, 83.5, 80.0, 59.2, 57.9, 52.2, 46.7, 44.0, 43.0, 32.0, 29.7, 29.7, 29.6, 29.5, 29.4, 28.5, 28.3, 28.2, 28.1, 28.0, 23.8, 22.7, 21.1, 14.2, 14.2, 4.5. ESI-MS m/z: 702.55 [M+H]+.

3-(Aminomethyl)-N-((7R,12bS)−3-(cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)benzamide (MP1207)

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Triethylsilane (21 µL, 0.19 mmol, 2.5 eq.) was added to the solution of 9 (30 mg, 0.05 mmol one eq.) in TFA/DCM (1:1, 1 mL) at rt. The reaction was continued for 30 min. Mass spectrometry indicated the reaction was completed. The volatile components were removed under reduced pressure. The content was redissolved in DCM (0.4 mL) and treated with Et2O (3 mL) while shaking resulting in a white precipitation. The precipitate was washed with Et2O (3 mL) and dried under high vacuum to get the desired amino product MP1207 as a white solid (33 mg, Yield 94%); 1H NMR (600 MHz, Deuterium Oxide) δ = 7.79 (dd, J = 7.0, 1.4 Hz, 2H), 7.64 (dt, J = 7.9, 1.4 Hz, 1H), 7.61–7.53 (m, 1H), 6.95–6.85 (m, 1H), 6.85–6.75 (m, 1H), 4.74 (dd, J = 11.0, 8.1 Hz, 1H), 4.23 (s, 3H), 3.77 (ddt, J = 12.2, 8.3, 4.1 Hz, 1H), 3.42 (td, J = 11.6, 9.7, 5.4 Hz, 1H), 3.36–3.26 (m, 1H), 3.20 (d, J = 19.7 Hz, 1H), 3.10–2.95 (m, 2H), 2.76 (td, J = 13.2, 4.0 Hz, 1H), 2.48 (ddd, J = 12.5, 4.6, 2.8 Hz, 1H), 2.14 (td, J = 13.5, 4.7 Hz, 1H), 1.92 (ddd, J = 13.8, 4.2, 1.7 Hz, 1H), 1.87–1.72 (m, 2H), 1.54 (qd, J = 13.1, 2.5 Hz, 1H), 1.19–0.99 (m, 2H), 0.83–0.61 (m, 2H), 0.46–0.28 (m, 2H). 13C NMR (151 MHz, D2O, without TFA peaks) δ = 170.0, 142.1, 139.8, 134.5, 133.1, 132.2, 129.5, 128.0, 127.6, 122.9, 120.5, 92.1, 58.8, 58.6, 51.6, 46.5, 42.6, 42.4, 42.1, 39.7, 32.4, 27.4, 23.1, 20.4, 5.2, 3.6, 3.4, HRMS calcd for C28H34N3O3 [M+H]+, 460.2600; found, 460.2585.

N-((7R,12bS)−3-(Cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)−3-(guanidinomethyl)benzamide (MP1208)

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Triethylsilane (35.6 µL, 0.22 mmol, 5 eq.) was added to the solution of 10 (31 mg, 0.04 mmol, 1 eq.) in TFA/DCM (1:1, 1 mL) at rt. The reaction was continued for 30 min. Mass spectrometry indicated the reaction was completed. The volatile components were removed under reduced pressure. The content was redissolved in DCM (0.4 mL) and treated with Et2O (3 mL) while shaking resulting in a white precipitation. The precipitate was washed with Et2O (3 mL) and dried under high vacuum to get the desired amino product MP1208 as a white solid (28 mg, Yield 87%);1H NMR (600 MHz, Deuterium Oxide) δ = 7.64–7.51 (m, 2H), 7.48–7.28 (m, 2H), 6.86–6.49 (m, 2H), 4.68–4.57 (m, 1H), 4.37 (d, J = 5.7 Hz, 2H), 4.12 (dd, J = 5.7, 2.8 Hz, 1H), 3.66 (ddd, J = 12.7, 8.2, 4.3 Hz, 1H), 3.31 (td, J = 16.6, 15.0, 5.9 Hz, 1H), 3.22–3.15 (m, 1H), 3.10 (dd, J = 19.8, 3.2 Hz, 1H), 3.00–2.85 (m, 2H), 2.65 (td, J = 13.2, 4.2 Hz, 1H), 2.38 (ddd, J = 12.3, 4.4, 2.7 Hz, 1H), 2.04 (td, J = 13.5, 4.6 Hz, 1H), 2.00–1.92 (m, 0H), 1.87–1.76 (m, 1H), 1.76–1.62 (m, 1H), 1.43 (tdd, J = 13.9, 10.4, 5.3 Hz, 1H), 0.98 (tdd, J = 13.7, 8.9, 4.8 Hz, 2H), 0.71–0.58 (m, 2H), 0.34–0.19 (m, 2H). 13C NMR (151 MHz, D2O, without TFA peaks) δ = 170.3, 156.8, 142.2, 139.7, 136.7, 134.2, 130.3, 129.2, 128.0, 126.3, 125.5, 122.9, 120.5, 118.1, 92.1, 58.8, 58.6, 51.6, 46.5, 44.1, 42.1, 39.7, 32.4, 27.4, 23.1, 20.4, 5.2, 3.6, 3.4. HRMS calcd for C29H36N5O3 [M+H]+, 502.2818; found, 502.2816.

4-(Aminomethyl)-N-((4R,4aR,7R,7aR,12bS)−3-(cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methano[1]benzofuro[3,2-e]isoquinolin-7-yl)benzamide (MP1209)

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To a suspension of PyBOP (70 mg, 0.135 mmol, 2.2 eq.) in THF (100 mL) were sequentially added a solution of 4-(((tert-butoxy carbonyl)amino)methyl)benzoic acid (34 mg, 0.135 mmol, 2.2 eq.) in THF (100 mL) and NEt(iPr)2 (24 mL, 0.135 mmol, 2.2 eq.) and the resulting mixture was stirred for 40 min at rt. This solution was subsequently added via cannula to a suspension of solution of β-dihydro N-CPM morphineamine 6 (20 mg, 0.061 mmol, 1.0 eq.) in THF (100 mL) and the mixture was stirred at rt overnight. To the crude mixture methanol and potassium carbonate were added and stirring was continued for 2 hr. After filtration the solvent was removed on a rotary evaporator, and the crude product was loaded on a 4 g Silica Gold column. Chromatography was performed with 5% to 10% MeOH (containing 10% concentrated NH4OH solution) gradient in 6 min. The desired Boc protected intermediate eluted around 5–6 min. Deprotection of the Boc protected amine (11) was achieved in 3 hr using 4N HCl in dioxane. The product was obtained as a white powder after removal of the solvent and trituration with diethyl ether (25 mg, 76%). 1H NMR (400 MHz, CDCl3) δ: 7.92 (dd, J = 8.3, 2.1 Hz, 2H), 7.60–7.53 (m, 2H), 6.79–6.67 (m, 2H), 4.78 (dd, J = 8.0, 1.9 Hz, 1H), 4.18 (s, 3H), 3.88–3.71 (m, 1H), 3.64 (d, J = 1.9 Hz, 2H), 3.51–3.39 (m, 1H), 3.38–3.28 (m, 1H), 3.20 (d, J = 19.0 Hz, 1H), 3.06–2.92 (m, 2H), 2.73 (td, J = 13.0, 4.0 Hz, 1H), 2.63 (d, J = 12.2 Hz, 1H), 2.26 (td, J = 13.5, 4.7 Hz, 1H), 1.95–1.71 (m, 3H), 1.69–1.49 (m, 1H), 1.24–1.06 (m, 3H), 0.78 (dd, J = 10.7, 7.5 Hz, 2H), 0.58–0.43 (m, 2H). 13C NMR (101 MHz, CDCl3) δ: 164.45, 139.51, 138.14, 133.32, 131.56, 125.44, 124.54, 124.52, 124.29, 117.92, 116.55, 114.77, 87.95, 63.45, 55.79, 55.34, 48.72, 39.16, 39.09, 36.66, 29.62, 24.71, 20.07, 17.26, 2.17. HRMS calcd for C28H33N3O3 [M+H]+, 460.2594; found, 460.2599.

N-((4R,4aR,7R,7aR,12bS)−3-(cyclopropylmethyl)−9-hydroxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methano[1]benzofuro[3,2-e]isoquinolin-7-yl)−3-(hydroxymethyl)benzamide (MP1210)

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To a suspension of PyBOP (70 mg, 0.135 mmol, 2.2 eq.) in THF (100 mL) were sequentially added a solution of 3-(hydroxymethyl)benzoic acid (21 mg, 0.135 mmol, 2.2 eq.) in THF (100 mL) and NEt(iPr)2 (24 mL, 0.135 mmol, 2.2 eq.) and the resulting mixture was stirred for 40 min at rt. This solution was subsequently added via cannula to a suspension of solution of β-dihydro N-CPM morphineamine 6 (20 mg, 0.061 mmol, 1.0 eq.) in THF (100 mL) and the mixture was stirred at rt overnight. To the crude mixture methanol and potassium carbonate were added and stirring was continued for 2 hr. After filtration, the solvent was removed on a rotary evaporator, and the crude product was loaded on a 4 g Silica Gold column. Chromatography was performed with 5% to 20% MeOH (containing 10% concentrated NH4OH solution) gradient in 12 min. The desired product eluted around 11–12 min (15 mg, Yield 51%). 1H NMR (400 MHz, CDCl3) δ: 8.27 (s, 1H), 8.20 (d, J = 7.7 Hz, 1H), 7.97 (d, J = 7.7 Hz, 1H), 7.89 (dt, J = 10.6, 5.1 Hz, 1H), 7.19 (d, J = 8.3 Hz, 1H), 7.09 (d, J = 8.1 Hz, 1H), 5.14 (s, 2H), 5.09–5.03 (m, 1H), 4.87 (s, 5H), 4.40–4.29 (m, 1H), 4.26 (s, 1H), 3.82 (d, J = 14.1 Hz, 1H), 3.55 (d, J = 11.7 Hz, 1H), 3.44 (s, 1H), 3.32 (s, 1H), 3.20 (s, 1H), 3.16 (s, 1H), 3.03 (s, 1H), 2.91 (s, 1H), 2.68–2.63 (m, 0H), 2.62 (s, 1H), 2.34 (d, J = 13.3 Hz, 1H), 2.25 (d, J = 13.1 Hz, 1H), 2.13 (d, J = 13.1 Hz, 1H), 1.97 (q, J = 13.1 Hz, 1H), 1.63–1.52 (m, 2H), 1.15 (d, J = 8.1 Hz, 2H), 0.83 (d, J = 13.5 Hz, 2H).13C NMR (101 MHz, CDCl3) δ: 169.20, 143.41, 142.19, 141.22, 134.71, 130.51, 128.80, 126.51, 125.92, 120.05, 118.79, 93.14, 64.24, 59.50, 58.21, 52.41, 46.80, 43.52, 40.79, 33.97, 28.81, 24.26, 21.39, 7.49, 4.65, 4.46. HRMS calcd for C28H32N2O4 [M+H]+, 461.2435; found, 460.2440.

(4aS,7S,12bS)−3-(Cyclopropylmethyl)−4a,9-dimethoxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-ol (13)

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A solution of Li-selectride (1.3 mL, 1.3 mmol, 2 eq. 1M in THF) was slowly added to the stirred solution of known ketone (Kobylecki et al., 1982) 12 (320 mg, 0.86 mmol) in THF (5 mL) at −78°C. The reaction mixture was continued at the temperature for 90 min. The reaction mixture was quenched with cold methanol (0.2 mL) at −78°C and the cold bath was removed and is continued stirring for 10 min to warm up to rt. Then, the product was extracted four times (4 × 20 mL) using DCM. The organic layer was dried over anhydrous sodium sulfate, filtered, and concentrated under reduced pressure. The crude product was purified by silica column (ISCO flash column) using methanol (1–2%) in DCM. The product fraction was concentrated and dried under high vacuum to get desired products 13; (240 mg, Yield 75%); 1H NMR (600 MHz, Chloroform-d) δ = 6.71 (d, J = 8.2 Hz, 1H), 6.58 (d, J = 8.2 Hz, 1H), 4.66 (dd, J = 4.8, 1.1 Hz, 1H), 4.22 (dt, J = 9.4, 4.6 Hz, 1H), 3.87 (s, 3H), 3.53 (d, J = 6.0 Hz, 1H), 3.29 (s, 3H), 3.12 (d, J = 18.3 Hz, 1H), 2.65 (dd, J = 12.0, 5.2 Hz, 1H), 2.53–2.40 (m, 2H), 2.38 (dd, J = 18.4, 6.1 Hz, 1H), 2.28–2.10 (m, 2H), 1.88–1.73 (m, 1H), 1.66 (ddt, J = 14.7, 8.4, 4.0 Hz, 1H), 1.42 (ddd, J = 12.3, 3.8, 1.6 Hz, 1H), 1.16–1.02 (m, 2H), 0.93–0.84 (m, 1H), 0.62–0.43 (m, 2H), 0.16 – −0.06 (m, 2H). ESI-MS m/z: 372.4 [M+H]+.

(4aS,7R,12bS)−3-(Cyclopropylmethyl)−4a,9-dimethoxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-amine (14)

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Phthalimide (36.4 mg, 0.24 mmol, 2 eq.) and triphenylphosphine (48.7 mg, 0.18 mmol, 1.5 eq.) were added to a stirred solution of alcohol 13 (46 mg, 0.12 mmol) in THF (1 mL.) under argon. Diisopropyl azodicarboxylate (36.8 µL, 0.18 mmol, 1.5 eq.) was added drop wise to the reaction mixture at 0°C and the reaction was continued for overnight. The reaction mixture was quenched with water (0.5 mL) and the mixture was stirred for 10 min at rt. The organic solvent was removed under reduced pressure. The residue was treated with 2% aqueous citric acid (1 mL), and dilute HCl (0.1 M, 1 mL) solutions. The mixture was washed with Et2O (3 × 2 mL). Then, the aqueous layer was basified (~ pH = 10) using an ammonia solution. The product was extracted in CHCl3 (3 × 5 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using methanol (1–5%) in DCM to obtain white solid of phthalimides intermediates (19 mg, 32%) upon drying. Then, hydrazine hydrate (23.8 µL, 10 eq.) was added to the stirred solution of the phthalimide intermediate in methanol (2 mL) at once heated to 50°C for 90 min to complete the reaction. The reaction mixture was diluted with DCM (4 mL) and the product was extracted in dilute HCl (3 × 2 mL), the aqueous layer was basified with dilute NH4OH (5%) and the amine is extracted in DCM (3 × 2 mL). The DCM layer was dried over anhydrous Na2SO4, filtered and concentrated under reduced pressure to get the desired product 14 (14 mg, yield; quantitative, which was used without further purification); 1H NMR (600 MHz, Chloroform-d) δ 6.69 (d, J = 8.2 Hz, 1H), 6.59 (d, J = 8.1 Hz, 1H), 4.30 (d, J = 6.9 Hz, 1H), 3.86 (s, 3H), 3.55 (d, J = 5.1 Hz, 1H), 3.25 (s, 3H), 3.11 (d, J = 18.2 Hz, 1H), 2.69–2.52 (m, 2H), 2.52–2.26 (m, 4H), 2.05 (td, J = 12.1, 3.9 Hz, 1H), 1.82 (dt, J = 14.3, 3.3 Hz, 1H), 1.63 (qd, J = 12.8, 2.7 Hz, 1H), 1.52–1.39 (m, 1H), 1.36–1.20 (m, 2H), 1.20–1.05 (m, 1H), 0.87 (tt, J = 8.9, 7.1, 3.3 Hz, 1H), 0.64–0.43 (m, 2H), 0.24–0.09 (m, 2H). ESI-MS m/z: 371.37 [M+H]+.

N-((4aS,7R,12bS)−3-(Cyclopropylmethyl)−9-hydroxy-4a-methoxy-2,3,4,4a,5,6,7,7a-octahydro-1H-4,12-methanobenzofuro[3,2-e]isoquinolin-7-yl)−3-iodobenzamide (MP1305)

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m-Iodobenzoic acid (8.86 mg, 0.035 mmol, 1.3 eq.) was added to a stirred solution of β-amine 14 (12 mg, 0.032 mmol) in DMF (0.2 mL) at. HATU (14.7 mg, 0.038 mmol, 1.3 eq.) was added to the mixture at rt at once and after 5 min, DIPEA (16.9 µL, 3 eq.) was added and the reaction was continued for 1 hr. Then, the reaction mixture was diluted with EtOAc (5 mL) and the EtOAc layer was washed with brine (5 × 3 mL) to remove DMF. The organic layer was dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (1–2%) in DCM to obtain white solid of methoxy intermediates (10 mg, 52%) upon drying. Then, BBr3 solution (116 µL, 0.116 mmol, 7 eq., 1M in DCM) was added to a stirred solution of methoxy intermediate (10 mg, 0.016 mmol) in DCM (2 mL) at 0°C under argon. The reaction mixture was continued for 10 min at 0°C and 20 more minutes at rt. The, reaction mixture was diluted with DCM (8 mL) and quenched with excess of NH4OH (5%, 2 mL) and the mixture was stirred for 1 hr. The DCM layer was washed with brine (2 × 2 mL), dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure. The crude product was purified by silica gel column chromatography using a mixture of methanol (5–10%) in DCM to get desired products MP1305 (4.9 mg, Yield 26%); 1H NMR (600 MHz, Methanol-d 4) δ = 8.21 (t, J = 1.7 Hz, 1H), 8.02–7.75 (m, 1H), 7.25 (t, J = 7.8 Hz, 1H), 6.69 (q, J = 8.2 Hz, 2H), 4.71 (d, J = 7.7 Hz, 1H), 4.09 (s, 1H), 3.87 (ddd, J = 12.7, 7.7, 5.2 Hz, 1H), 2.82 (s, 3H), 2.73–2.35 (m, 4H), 2.06 (d, J = 14.6 Hz, 1H), 1.87–1.61 (m, 2H), 1.56–1.27 (m, 3H), 1.02 (s, 1H), 0.68 (d, J = 55.0 Hz, 3H), 0.37 (s, 3H). 13C NMR (151 MHz, MeOD) δ = 168.30, 143.52, 141.68, 137.67, 137.48, 131.39, 127.62, 120.51, 119.10, 94.71, 92.55, 76.95, 59.48, 56.11, 54.81, 53.48, 29.51, 24.91, 24.50, 23.97, 5.64, 3.31,–0.03. HRMS calcd for C38H31IN2O4 [M+H]+, 587.1407; found, 587.1388.

(4bR,6R,8aS)−6-Amino-11-(cyclopropylmethyl)−3-methoxy-5,6,7,8,9,10-hexahydro-8aH-9,4b-(epiminoethano)phenanthren-8a-ol (16)

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NH4OAc (802.4 mg, 10.41 mmol, 20 eq.) was added to a stirred solution of known ketone (Zhang et al., 2007) 15 (177.7 mg, 0.52 mmol) in dry MeOH (4 mL) under argon at rt. The mixture was stirred for 8 hr. Then, NaCNBH3 (163.6 mg, 2.60 mmol, 5 eq.) was added to the reaction mixture and the reaction was continued for overnight. The solvent was evaporated under reduced pressure and the content was stirred with aqueous HCl (1M, 10 mL) for 2 hr at rt. The aqueous layer was diluted with water (20 mL), basified with concentrated NH4OH solution (to pH ~10) and then the product was extracted in DCM (3 × 15 mL). The combined DCM layer was washed with brine (10 mL), dried over anhydrous Na2SO4, filtered and concentrated. The crude product was purified by silica gel column chromatography using a mixture of 10% TEA, and 1% MeOH in DCM. The β amine is more polar than α counterpart on using the condition, which was eluted later and upon drying furnished a white solid of the desired product 16 (β, 90 mg, Yield 51%); 1H NMR (600 MHz, CDCl3) δ = 6.99 (d, J = 8.4 Hz, 1H), 6.86 (d, J = 2.6 Hz, 1H), 6.69 (dd, J = 8.4, 2.6 Hz, 1H), 4.65 (s, 1H), 3.78 (s, 3H), 3.00–2.91 (m, 2H), 2.77–2.66 (m, 2H), 2.56–2.48 (m, 1H), 2.38–2.27 (m, 2H), 2.15 (dd, J = 13.2, 3.6 Hz, 1H), 2.07–2.00 (m, 2H), 1.80 (dd, J = 13.2, 11.8 Hz, 1H), 1.63 (p, J = 4.8 Hz, 2H), 1.54–1.41 (m, 2H), 1.09–1.00 (m, 1H), 0.86–0.78 (m, 1H), 0.50 (dd, J = 8.1, 1.7 Hz, 2H), 0.12–0.06 (m, 2H). 13C NMR (151 MHz, CDCl3) δ = 158.4, 142.8, 128.3, 128.1, 111.1, 111.0, 68.7, 60.3, 59.4, 55.4, 46.4, 44.2, 42.3, 40.9, 37.0, 32.6, 31.2, 24.6, 9.6, 4.0, 3.9. ESI-MS m/z: 343.2 [M+H]+.

N-((4bR,6R,8aS)−11-(Cyclopropylmethyl)−8a-hydroxy-3-methoxy-6,7,8,8a,9,10-hexahydro-5H-9,4b-(epiminoethano)phenanthren-6-yl)−3-iodobenzamide (17)

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DIPEA (203 µL, 1.16 mmol, 3 eq.) and β-amine 16 (80 mg, 0.23 mmol) were added to the stirred solution of m-iodobenzoic acid (86.9 mg, 0.35 mmol, 1.5 eq.) dissolved in DMF (1 mL) at rt under an argon atmosphere. The reaction mixture was cooled to 0°C and HATU (133.2 mg, 0.35 mmol, 1.3 eq.) was added to the reaction mixture. After stirring the reaction mixture for 4 hr at 0°C to rt, the reaction mixture was poured into EtOAc (15 mL) and was washed with brine (5 × 15 mL). The EtOAc layer was dried over Na2SO4, filtered; and concentrated under reduced pressure. Then, the residue was purified by silica gel column chromatography using 2–5% MeOH in DCM. The desired product fractions were concentrated under reduced pressure and dried under high vacuum to get amorphous solid of the product 17 (110 mg, Yield 83%); 1H NMR (600 MHz, MeOD) δ = 8.20 (t, J = 1.7 Hz, 1H), 7.91 (dt, J = 7.9, 1.3 Hz, 1H), 7.83 (dt, J = 7.8, 1.3 Hz, 1H), 7.26 (t, J = 7.8 Hz, 1H), 7.22–7.17 (m, 2H), 6.88 (dd, J = 8.5, 2.5 Hz, 1H), 4.04–3.98 (m, 1H), 3.89 (s, 3H), 3.85 (s, 1H), 3.31–3.21 (m, 3H), 3.02 (d, J = 12.5 Hz, 1H), 2.90 (s, 1H), 2.68 (s, 1H), 2.56–2.43 (m, 2H), 2.13 (t, J = 12.7 Hz, 1H), 2.07–1.98 (m, 1H), 1.82–1.70 (m, 3H), 1.36–1.32 (m, 1H), 1.12 (dd, J = 8.8, 4.2 Hz, 1H), 0.83 (d, J = 8.7 Hz, 1H), 0.76 (td, J = 8.8, 4.6 Hz, 1H), 0.51 (s, 2H). 13C NMR (151 MHz, MeOD) δ = 168.1, 161.0, 141.5, 138.0, 137.5, 131.3, 130.2, 127.6, 115.1, 111.1, 94.6, 69.6, 62.5, 58.7, 55.9, 46.5, 42.2, 35.8, 31.7, 27.4, 25.4, 6.0, 3.4. ESI-MS m/z: 569.2 [M+H]+.

N-((4bR,6R,8aS)−11-(Cyclopropylmethyl)−3,8a-dihydroxy-6,7,8,8a,9,10-hexahydro-5H-9,4b-(epiminoethano)phenanthren-6-yl)−3-iodobenzamide (MP1601)

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A solution of BBr3 (874 µL, 0.87 mmol, 5 eq.) was added to the stirred solution of methyl ether 17 (100 mg, 0.17 mmol) dissolved in DCM (4 mL) at 0°C under an argon atmosphere. The reaction was continued at 0°C for 10 min and then at rt for 20 min. The reaction mixture was diluted with DCM (5 mL) and treated with aqueous NH4OH (5%, 2 mL) for 1 hr. The, the DCM layer was separated and was washed with saturated solution of NaHCO3 (2 × 10 mL), brine (5 mL), dried over anhydrous Na2SO4, filtered; and concentrated under reduced pressure. Then, the residue was purified by silica gel column chromatography using 10–15% MeOH in DCM. The desired product fractions were concentrated under reduced pressure and dried under high vacuum to get amorphous solid of MP1601; (72 mg, Yield 74%); 1H NMR (600 MHz, CDCl3) δ = 8.06 (d, J = 1.8 Hz, 1H), 7.83–7.72 (m, 1H), 7.67 (dt, J = 7.6, 1.2 Hz, 1H), 7.14 (t, J = 7.8 Hz, 1H), 7.03 (d, J = 2.5 Hz, 1H), 6.95 (d, J = 8.3 Hz, 1H), 6.71 (dd, J = 8.3, 2.4 Hz, 1H), 6.09 (s, 1H), 4.02 (tdt, J = 11.9, 8.1, 4.2 Hz, 1H), 3.02 (d, J = 18.2 Hz, 1H), 2.75 (d, J = 18.0 Hz, 1H), 2.59 (s, 1H), 2.45–2.27 (m, 3H), 2.14 (t, J = 15.5 Hz, 1H), 2.04 (d, J = 5.9 Hz, 1H), 1.95–1.74 (m, 3H), 1.63 (td, J = 13.3, 4.4 Hz, 1H), 1.55 (d, J = 13.4 Hz, 1H), 1.31–1.16 (m, 1H), 1.14–1.03 (m, 1H), 0.86 (d, J = 16.2 Hz, 1H), 0.52 (d, J = 8.0 Hz, 2H), 0.13 (s, 2H). 13C NMR (151 MHz, CDCl3) δ = 165.3, 140.3, 136.6, 136.0, 130.3, 128.6, 126.1, 114.1, 112.0, 94.3, 68.8, 60.2, 59.3, 45.8, 44.1, 41.8, 36.3, 30.8, 27.9, 24.5, 4.0, 3.9. HRMS calcd for C27H32IN2O3 [M+H]+, 559.1458; found, 559.1457.

Appendix 1

Appendix 1—table 1 shows the receptor affinities of arylamidomorphinans in opioid transfected cell lines. a Competition studies were performed with the indicated compounds against 125IBNtxA (0.1 nM) in membranes from CHO cells stably expressing the indicated cloned mouse opioid receptors. K i values were calculated from the IC50 values and represent the means ± SEM of at least three independent replications. b Literature values (Váradi et al., 2015a).

Appendix 1—table 1
Receptor affinities of arylamidomorphinans in mouse opioid receptor transfected cell lines.
Compd. Ki [nM]a
mMOR mKOR mDOR
IBNtxA 0.11 ± 0.02 0.03 ± 0.001 0.24 ± 0.05
MP1104 0.021 ± 0.00 0.0064 ± 0.0 0.08 ± 0.01
MP1202 0.071 ± 0.031 0.11 ± 0.064 1.3 ± 0.8
MP1207 0.23 ± 0.02 0.39 ± 0.05 15.62 ± 2.64
MP1208 0.34 ± 0.01 0.28 ± 0.02 19.28 ± 6.48
MP1305 0.25 ± 0.02 2.5 ±0.3 11.7 ± 1.4
MP1601 0.2 ± 0.01 2.13 ± 0.3 5.37 ± 0.9
Morphine 4.60 ± 1.81b _ _
DAMGO 3.34 ± 0.43b _ _
U50, 488h _ 0.73 ± 0.32b _
DPDPE _ _ 1.39 ± 0.67b

Appendix 1—table 2 shows the [35S]GTPγS Functional assaysa in transfected cell lines.aEfficacy data were determined using an agonist induced stimulation of [35S]GTPγS binding assay. Efficacy is represented as EC50 (nM) and percent maximal stimulation (Emax) relative to standard agonist DAMGO (mMOR), DPDPE (mDOR), or U50,488H (mKOR) at 1 µM. To determine the antagonistic properties of a compound, membranes were incubated with 100 nM of the appropriate agonist by varying its concentrations. Results are presented as nM ± SEM from three independent experiments performed as triplicate.bBuprenorphine data from Grinnell et al., 2016. c95% CL dFull agonist compared to 1 µM DAMGO.

Appendix 1—table 2
[35S]GTPγS Functional assays in mouse opioid receptor transfected cell lines.
Compd. mMOR mKOR mDOR
EC50 (nM) Emax (%) EC50 (nM) Emax (%) EC50 (nM) Emax (%) IC50 (nM)
IBNtxA 0.49 ± 0.12 101 ± 3 0.22 ± 0.02 102 ± 4 4.08 ± 0.67 95 ± 2 -
MP1104 0.21 ± 0.03 103 ± 2 0.027 ± 0.002 104 ± 2 0.41 ± 0.11 88 ± 0 -
MP1202 0.32 ± 0.03 68 ± 1 0.13 ± 0.02 94 ± 5 4 ± 1.6 71 ± 2 -
MP1207 1.29 ±0.65 41 ± 1 1.52 ± 0.07 39.3 ± 1.3 nd 10-15% 27.34±1.95
MP1208 1.13 ± 0.05 54 ± 0.7 1.36 ± 0.23 43 ± 0.8 nd 10-15% 11.39±0.3
MP1305 0.7 ± 0.1 81.2 ± 16 7.4 ± 1.8 42.2 ± 5.3 31.7 ± 3.6 22± 0.9 -
MP1601 0.5 ± 0.2 45 ± 4.6 3 ± 0.7 72 ± 4.5 10 ± 1.6 67 ± 3.9 -
DAMGO 3.4 ± 0.2 - - - - - -
U50,488h - - 9.5 ± 1.8 - - - - -
DPDPE - - - - 16.2 ± 5.1 - -
Morphine 14.77±3.9 102±5 - - - - -
Buprenorphineb 1.8(1.3,2.3)c Full agonistd - - - - -

Appendix 1—table 3 shows the energies calculated by computational QM calculations.

Appendix 1—table 3
Energies for boat and chair conformations calculated by computational QM calculations for ligands.
Ligand (Basis set) Energy(Chair – Boat)
HF
Energy(Chair – Boat) kcal/mol Energy(Chair – Boat) kJ/mol
MP1104 (LanL2DZ) 0.03671637 23.0396323 96.3988294
MP1104 (DGDZVP) 0.03493887 21.9242457 91.7320032
IBNtxA (LanL2DZ) −0.0014450 −0.90674184 −3.7938475
IBNtxA (DGDZVP) −0.0016583 −1.040599833 −4.353869701
MP1202 (LanL2DZ) −0.01402513 −8.8009031585 −36.822978815
MP1202 (DGDZVP) −0.011652 −7.31174652 −30.59234743997

Appendix 1—table 4 showing the best docking scores of each ligand with a chair or a boat conformation at active state human mu and kappa opioid receptors.

Appendix 1—table 4
Best docking scores of each ligand with a chair or a boat conformation at active state human mu and kappa opioid receptors.
Drugs MP1104 IBNtxA MP1202 MP1207 MP1208 MP1305 MP1601 6'GNTI MP1209 MP1210
Docking score of Chair/hMOR -36.22 -52.42 -55.04 -69.74 -38.63 -40.61 -51.03 -44.17
Boat /hMOR -48.28 -31.36 -49.44 -50.81 -67.72 -28.83 -38.23 -43.67 -36.18
Chair /hKOR -46.93 -47.82 -55.99 -86.24 -46.77 -46.08 -64.86 -57.63 -53.91
Boat /hKOR -55.06 -49.51 -52.42 -45.9 -65.88 -44.87 -47.54 -60.77 -55.43

Appendix 1—table 5 shows the docking scores for proposed analogs of MP1202, where m-iodo group is substituted with a polar moiety (R).

Appendix 1—table 5
Docking scores for proposed analogs of MP1202, where m-iodo group is substituted with a polar moiety (R).
Serial R Chair score Boat score Scores for chair preference
 1 -mNH2 −55.35 −58.47 +3.12
 2 -mN(CH3)2 −51.81 −48.34 −3.47
 3 -mOH −54.81 −57.34 +2.53
4 (MP1207) -mCH2NH2 −55.99 −45.9 −10.09
 5 -mCH2CH2NH2 −59.42 −51.79 −7.63
 6 -mCH2CH2CH2NH2 −64.07 −49.91 −14.16
 7 -mCH2CH2CH2CH2NH2 −52.42 −49.67 −2.75
 8 -mgaunidine −76.29 −66.34 −9.95
9 (MP1208) -mCH2guanidine −86.24 −65.88 −20.36
 10 -mCOguanidine −82.09 −77.53 −4.56
 11 -pCH2NH2 −57.63 −60.77 +3.14
 12 -mCH2OH −53.91 −55.43 +1.5

Appendix 1—table 6 shows the functional studies at DOR using cAMP inhibition and Tango-arrestin and BRET assays. The functional data of each assay using human delta opioid receptor (hDOR) and mouse delta opioid receptor (mDOR) were normalized to Emax of corresponding controls DPDPE or DADLE. Results were analyzed using a three-parameter logistic equation in GraphPad Prism and the data are presented as mean EC50(pEC50 ± SEM) with Emax% ± SEM for assays run in triplicate; CTRL.; control compound and nd; results could not be determined because of no measurable arrestin recruitment signal.

Appendix 1—table 6
Functional data at hDOR and mDOR.
Functional data at hDOR and mDOR
Compd. cAMP inhibition Arrestin recruitment
EC50,nM (pEC50± SEM) Emax%± SEM EC50,nM (pEC50± SEM) Emax%± SEM
IBNtxA 0.43 (9.3 ± 0.03) 106 ± 1 14.1(7.8 ± 0.06) 224±5
DPDPE (CTRL.) 0.69 (9.1 ± 0.07) 100 ± 2 2.99(8.5 ± 0.04) 100±1.5
MP1104 0.40 (9.4 ± 0.04) 99 ± 1.1 3.73 (8.4 ± 0.06) 189 ± 5.5
DADLE (CTRL.) 0.66(9.2 ± 0.05) 100 ± 1.3 0.349 (9.45 ± 0.10) 100 ± 3.2
MP1202 8.18(8.1 ± 0.06) 99 ± 2.2 18.14(7.7 ± 0.25) 26 ± 3.1
DADLE (CTRL.) 1.45(8.8 ± 0.06) 100 ± 2 8.41(8.1 ± 0.08) 100 ± 2.7
MP1207 11.4 (7.9 ± 0.1) 38 ± 2 64.06(7.2 ± 0.23) 34 ± 3.7
MP1208 2.49 (8.6 ± 0.13) 39 ±1.8 3624.0(5.5 ± 0.27) 62±16.7
DADLE (CTRL.) 0.48 (9.3 ± 0.05) 100 ±1.5 1.41 (8.8 ± 0.07) 100±2.3
MP1305 74.18 (7.1 ± 0.08) 71 ± 2.4 227.5(6.6 ± 0.06) 89 ± 2.8
MP1601 2.76(8.6 ± 0.06) 106 ± 2.3 86.7(7.1 ± 0.06) 203±5.4
DPDPE(CTRL.) 0.69 (9.1 ± 0.07) 100 ± 2 2.99(8.5 ± 0.04) 100±1.5
B. Functional data at mDOR using BRET assays
Compd. G protein activation Arrestin recruitment
EC50,nM (pEC50± SEM) Emax%± SEM EC50,nM (pEC50± SEM) Emax%± SEM
IBNtxA 0.48(9.3 ± 0.10) 108 ± 3.7 26.6(7.5 ± 0.2) 88 ± 6.8
DPDPE(CTRL.) 2.72(8.5 ± 0.09) 100 ± 3 184.3(6.73 ± 0.1) 100 ± 6.4
MP1104 1.4(8.9 ± 0.06) 91 ± 1.7 26.0(7.6 ± 0.11) 40 ± 1.7
DPDPE(CTRL.) 1.3(8.9 ± 0.04) 100 ± 1.2 98.0(7.0 ± 0.04) 100 ± 1.8
MP1202 7.03(8.1 ± 0.15) 103 ± 4.6 524.8(6.3 ± 0.20) 26 ± 2.3
DPDPE(CTRL.) 2.19(8.6 ± 0.10) 100 ± 3.5 109.3(6.7 ± 0.06) 100 ± 3
MP1207 116.4(6.9 ± 0.12) 52 ± 2.3 nd nd
MP1208 26.6(7.6 ± 0.20) 58 ± 3.3 nd nd
MP1305 40.4(7.4 ± 0.20) 105 ± 5.9 nd nd
MP1601 6.27(8.2 ± 0.20) 105 ± 6.7 9.0 (8.0 ± 0.33) 16 ± 1.4
DPDPE(CTRL.) 0.44(9.3 ± 0.13) 100 ± 2.5 21.8 (7.6 ± 0.04) 100 ± 1.3

Appendix 1—table 7 shows the functional binding data of the compounds at opioid receptors (hMOR, hKOR and mMOR). The functional data of each assay using human mu opioid receptor (hMOR), human kappa opioid receptor (hKOR), and mouse mu opioid receptor (mMOR) were normalized to Emax of corresponding controls. Results were analyzed using a three-parameter logistic equation in GraphPad Prism and the data are presented as mean EC50(pEC50 ± SEM) with Emax% ± SEM for assays run in triplicate; CTRL.; control compound.

Appendix 1—table 7
Gprotein & arrestin pathway potency and efficacy of ligands at hMOR, hKOR and mMOR.
Receptors Compounds cAMP inhibition (Gi) assay Arrestin recruitment (Tango) assay Figure
EC50 (pEC50± SEM) Emax%± SEM EC50 (pEC50± SEM) Emax%± SEM
hMOR MP1104 0.074 (10.13 ± 0.05) nM 94±1 0.573(9.24±0.08) nM 90±2.28 Figure 2A–B
DAMGO 0.84(9.07±0.08) nM 100 13.9 (7.86±0.06) nM 100
hKOR MP1104 0.00327 (11.49±0.035) nM 10±1.64 0.03944(10.4±0.06) nM 117 ± 2 Figure 2C–D
U50488h 0.089(10.05±0.04) nM 100 3.6(8.44±0.04) nM 100
hMOR MP1202 0.077 (10.11 ± 0.06) nM 92±1.4 26.8(7.57±0.1) nM 53±2 Figure 2G–H
DAMGO 3.78(8.4±0.06) nM 100 58.8(7.23±0.06) nM 100
hKOR MP1202 0.00139 (11.86±0.05) nM, 97.9±2.5 0.0457(10.34±0.05) nM 101±1 Figure 2I–J
U50,488h 0.006 (10.2±0.056) nM 100 3.6(8.44±0.04) nM 100
hKOR MP1207 0.11 (9.98 ± 0.07) nM 90±1.7 3.97(8.4±0.18) nM 37±2 Figure 3A–B
MP1208 0.14 (9.9 ± 0.07) nM 96±1.9 16.41(7.79±0.14) nM 48±2.4
U50,488h 0.64(9.2±0.06) nM 100 7.55(8.12±0.06) nM 100
hMOR MP1207 0.034 (10.47 ± 0.15) nM 33±1.4 nd nd Figure 3E–F
MP1208 0.008 (8.73 ± 0.12) nM 42±1.3 nd nd
U50,488h 1.86(8.73±0.06) nM 100
hKOR MP1209 0.024 (10.6 ± 0.05) nM 100±1.23 0.37(9.43 ± 0.19) nM 67±3 Figure 4E–F
MP1210 0.025 (10.6 ± 0.05) nM 101.1±1.1 1.16 (8.94 ± 0.17) nM 63±3.3
U50,488h 0.05 (10.29±0.06) nM 100 7.85 (8.11±0.1) nM. 100
hMOR MP1209 0.25(9.61 ± 0.04) nM 98.5±0.96 nd nd Figure 4G–H
MP1210 0.15(9.81 ± 0.05) nM 94.6±0.98 nd nd
DAMGO 0.2 (9.7±0.06) nM 100
hMOR Methoxycarbonyl fentanyl 0.099 (10 ± 0.06) nM 103±1.8 18.94 (7.7±0.1) nM 194±8 Appendix 1—figure 8A–B
DAMGO 2.58 (8.59±0.07) nM 100 404.1(6.39±0.05) nM 100
hMOR MP102 19.7(7.7 ± 0.08) nM 87±2.66 nd nd Appendix 1—figure 8F–G
DAMGO 2.58 (8.59±0.07) nM 100
Morphine 21.8 (7.66 ± 0.08) nM 97±3.06 888 (6.05±0.25) nM 25.32±4.4
hMOR DAMGO 8.1 (8.09 ± 0.06) nM 100 140.7 (6.85±0.08) nM 100
Buprenorphine 0.7 (10.14 ± 0.11) pM 75±2.36 1.79 (8.75±0.13) nM 43±2
DAMGO 4.36 (8.36 ± 0.08) nM 100 22 (7.64±0.063) nM 100
Receptors Compounds G protein activation (BRET) assay Arrestin recruitment (BRET) assay Figure
EC50 (pEC50± SEM) Emax%± SEM EC50 (pEC50± SEM) Emax%± SEM
mMOR MP1207 3.61 (8.44 ± 0.26) nM 42±2.6 nd nd Figure 3I–J
MP1208 2.27 (8.64 ± 0.29) nM 41±3 nd nd
DAMGO 3.27(8.49±0.08) nM 100
DAMGO 9.09 (8.04 ± 0.13) nM 100
mMOR Morphine 9.09 (8.04 ± 0.13) nM 109±3.1
Buprenorphine 1.17 (8.93 ± 0.14) nM 59±2.4

Appendix 1—table 8 shows the functional binding data of the compounds at rodent opioid receptors (mMOR and rKOR).The functional data of each assay using mouse mu opioid receptor (mMOR) and rat kappa opioid receptor (rKOR) were normalized to Emax of corresponding controls. Results were analyzed using a three-parameter logistic equation in GraphPad Prism and the data are presented as mean EC50(pEC50 ± SEM) with Emax% ± SEM for assays run in triplicate; CTRL.; control compound.

Appendix 1—table 8
Gprotein & arrestin pathway potency and efficacy of ligands at mMOR and rKOR.
Receptors Compound G protein activation (BRET) assay Arrestin recruitment (BRET) assay Figure
EC50 (pEC50± SEM) Emax%± SEM EC50 (pEC50± SEM) Emax%± SEM
mMOR MP1104 0.66 (9.2±0.11) nM 62±2 0.285 (9.55±0.12) nM 53 ± 1.6 Appendix 1—figure 1A
DAMGO 7.3 (8.1±0.07) nM 100 31.5 (7.5±0.06) nM 100
IBNtxA 0.054(10.3 ± 0.02) nM 59±2.2 11.32(4.9±0.3) µM 75±13.9 Appendix 1—figure 1B
DAMGO 12.9(7.8±0.06) nM 100 0.77(6.11±0.16) µM 100
MP1202 0.63 (9.2±0.09) nM 61±1.5 3140 (5.5±0.28) nM 53 ± 1.6 Appendix 1—figure 1C
DAMGO 6.31 (8.2±0.07) nM 100 114 (6.9±0.15) nM 100
MP1207 3.61 (8.44 ± 0.26) nM 42±2.6 nd nd Appendix 1—figure 1D
MP1208 2.27 (8.64 ± 0.29) nM 41±3 nd nd
DAMGO 3.27(8.49±0.08) nM 100
MP1305 0.74(9.1 ± 0.12) nM 72±2 nd nd Appendix 1—figure 1E
DAMGO 3.3(8.4±0.08) nM 100
MP1601 2.2(8.6 ± 0.3) nM 49±3 nd nd
DAMGO 0.9(9.0±0.1) nM 100
rKOR MP1104 0.073 (10.14±0.04) nM 93±1 1.14(8.94±0.07) nM 89 ± 2.6 Appendix 1—figure 2A
U50, 488h 1.05(8.98±0.03) nM 100 110(6.95±0.05) nM 100
IBNtxA 0.064(10.2 ± 0.1) nM 101±2.3 1.23(8.9±0.02) nM 133±7.3 Appendix 1—figure 2B
U50, 488h 27.7(7.6±0.01)nM 100 345.6(6.4±0.03) nM 100
MP1202 0.134(9.87±0.09) nM 104±2 1.44(8.84±0.25) nM 77 ± 5 Appendix 1—figure 2C
U50, 488h 4.79 (8.32±0.07) nM 100 235(6.63±0.18) nM 100
MP1207 1.13 (8.95 ± 0.31) nM 32±2.3 nd nd Appendix 1—figure 2D
MP1208 1.1(8.97 ± 0.29) nM 40±2.4 nd nd
U50, 488h 82.6(7.1±0.09) nM 100
MP1305 5.04 (8.3 ± 0.32) nM 35±3 nd nd Appendix 1—figure 2E
U50, 488h 40.3(7.4±0.07) nM 100
MP1601 8.9(8.1 ± 0.12) nM 75±3 56.5(7.2±0.23) nM 37±3
U50, 488h 26.7(7.6±0.09) nM 100 169.6(6.7±0.07) nM 100
mMOR IBNtxA 0.054(10.3 ± 0.02) nM 59±2.2 11.32(4.9±0.3) µM 75±13.9 Figure 3F–G
DAMGO 12.9(7.8±0.06) nM 100 0.77(6.11±0.16) µM 100
rKOR IBNtxA 0.064(10.2 ± 0.1) nM 101±2.3 1.23(8.9±0.02) nM 133±7.3 Figure 3H–I
U50, 488h 27.7(7.6±0.01) nM 100 345.6(6.4±0.03) nM 100
mMOR Methoxycarbonyl fentanyl 0.21(9.7 ± 0.04) nM 109±0.94 1.96(8.71±0.11) nM 63±1.8 Appendix 1—figure 7C–D
DAMGO 1.73(8.76±0.05) nM 100 110.1(6.96±0.06) nM 100
MP102 404.5 (6.39 ± 0.2) nM 78±7 nd nd Appendix 1—figure 7E
DAMGO 3.27(8.5±2) nM 100

Appendix 1—table 9 shows the functional binding data of the compounds at human opioid receptors (hMOR, hKOR and Y312W-hKOR). The functional data of each assay using human mu opioid receptor (hMOR), human kappa opioid receptor (hKOR), and Y312W human kappa opioid receptor mutant (Y312W-hKOR) were normalized to Emax of corresponding controls. Results were analyzed using a three-parameter logistic equation in GraphPad Prism and the data are presented as mean EC50(pEC50 ± SEM) with Emax% ± SEM for assays run in triplicate; CTRL.; control compound.

Appendix 1—table 9
cAMP & arrestin potency and efficacy at hMOR, hKOR and Y312W-hKOR of select ligands.
Receptors Compounds cAMP inhibition (Gi) assay Arrestin recruitment (Tango) assay Figure
EC50 (pEC50± SEM) Emax%± SEM EC50 (pEC50± SEM) Emax%± SEM
hMOR IBNtxA 0.07(10.2 ± 0.006) nM 95±2 5.86(8.2±0.002) nM 29±0.02 Appendix 1—figure 3A-B
DAMGO 0.99(9.0±0.007) nM 100 14.16(7.9±0.003) nM 100
hKOR IBNtxA 2.46 (11.6 ± 0.037) pM 101±1.79 0.013(10.9±0.07) nM 109±1.8 Appendix 1—figure 3C-D
U50488h 0.089(10.05±0.042) nM 100 3.63(8.4±0.03) nM 100
Y312W-hKOR MP1202 0.21 (10.69 ± 0.07)pM 101±1.5 3.4(8.5±0.14) nM 55±2.6 Appendix 1—figure 7A,C
U50,488h 2.7(8.56±0.06)nM 100 0.63(7.2±0.06) nM 100
WT-hKOR MP1202 0.0457(10.34±0.05) nM 101±1 Appendix 1—figure 7B,D
U50,488h 3.6(8.44±0.04) nM 100
WT-hMOR MP1202 26.8(7.57±0.1) nM 53±2
DAMGO 58.8(7.23±0.06) nM 100
Y312W-hKOR MP1207 0.16 (9.8 ± 0.08) nM 95±1.8 nd nd Appendix 1—figure 7E,G
MP1208 0.36 (10.44 ± 0.05) pM 97±1 nd nd
U50,488h 0.92(9.04±0.04)nM 100 14(7.85±0.1) nM 100
WT-hKOR MP1207 3.97(8.4±0.18) nM 37±2 nd nd Appendix 1—figure 7F
MP1208 16.41(7.79±0.14) nM 48±2.4 nd nd
U50,488h 7.55(8.12±0.06) nM 100
hKOR MP1305 0.72 (9.14 ± 0.05) nM 102±1.2 25.72(7.6±0.04) nM 75±1 Appendix 1—figure 9A-B
U50, 488h 0.076(10.11±0.04) nM 100 3.6(8.44±0.04) nM 100
hMOR MP1305 0.12(9.9 ± 0.12) nM 69±1.8 16.4(7.8±0.3) nM 21±3 Appendix 1—figure 9C-D
DAMGO 3.88(8.4±0.05) nM 100 168.1(6.77±0.09) nM 100
hKOR MP1601 0.17(9.76 ± 0.05) nM 109±1 3.23(8.49±0.07) nM 107±3 Appendix 1—figure 9E-F
U50, 488h 0.077(10.11±0.04) nM 100 3.6(8.44±0.04) nM 100
hMOR MP1601 0.1(9.99 ± 0.09) nM 69±1 4.02(8.4±0.2) nM 27±2 Appendix 1—figure 9G-H
DAMGO 3.88(8.4±0.05) nM 100 168.1(6.77±0.09) nM 100

Appendix 1—table 10 shows the bias analysis of ligands at human opioid receptors (nd: not determined; ns compared to control).

Appendix 1—table 10
Bias analysis of ligands at human opioid receptors.
Drug Receptor cAMP Tango ΔlogRA ΔlogRA ΔΔlog RA Bias factor Figure
Log RA LogRA cAMP Tango (cAMP-Tango) (cAMP-Tango)
U50,488h hKOR 10.09±0.035 8.29±0.019 0±0.049 0±0.027 0±0.056 1 Appendix 1—figure 4A
MP1104 hKOR 11.44±0.034 10.45±0.019 1.35±0.048 2.16±0.027 -0.81±0.055 0.15
U50,488h hKOR 10.22±0.051 8.44±0.004 0±0.072 0±0.006 0±0.070 1 Appendix 1—figure 4A
MP1202 hKOR 11.88±0.050 10.30±0.004 1.66±0.072 1.856±0.006 -0.19±0.072 nd
U50,488h hKOR 10.06±0.036 8.36±0.011 0±0.051 0±0.015 0±0.050 1 Appendix 1—figure 4A
IBNtxA hKOR 11.59±0.036 10.89±0.010 1.53±0.050 2.53±0.015 -1.002±0.052 0.10
U50,488h hKOR 9.175±0.004 8.14±0.007 0±0.005 0±0.010 0±0.012 1 Appendix 1—figure 4A
MP1207 hKOR 9.902±0.004 7.97±0.024 0.73±0.006 -0.176±0.025 0.903±0.026 8.00
U50,488h hKOR 9.176±0.004 8.14±0.008 0±0.005 0±0.011 0±0.012 1 Appendix 1—figure 4A
MP1208 hKOR 9.83±0.004 7.447±0.020 0.65±0.005 -0.697±0.022 1.35±0.022 22
U50,488h hKOR 10.42±0.06 8.37±0.22 0±0.084 0±0.31 0±0.32 1 Appendix 1—figure 4A
MP1209 hKOR 10.55±0.06 8.735±0.220 0.13±0.084 0.368±0.31 -0.238±0.32 nd
U50,488h hKOR 10.39±0.06 8.096±0.084 0±0.081 0±0.12 0±0.144 1 Appendix 1—figure 4A
MP1210 hKOR 10.59±0.06 8.576±0.156 0.2±0.081 0.48±0.18 -0.28±0.19 nd
U50,488h hKOR 10.010±0.012 8.507±0.026 0±0.017 0±0.037 0±0.041 1 Appendix 1—figure 4A
MP1305 hKOR 9.22±0.012 7.17±0.025 -0.79±0.017 -1.341±0.036 0.55±0.04 4
U50,488h hKOR 10.03±0.014 8.414±0.009 0±0.020 0±0.012 0±0.023 1 Appendix 1—figure 4A
MP1601 hKOR 9.85±0.014 8.51±0.009 -0.19±0.020 0.097±0.012 -0.282±0.023 0.52
DAMGO hMOR 9.102±0.009 7.925±0.013 0±0.012 0±0.019 0±0.022 1 Appendix 1—figure 4B
MP1104 hMOR 10.12±0.009 9.18±0.013 1.018±0.012 1.26±0.019 -0.24±0.022 0.58
DAMGO hMOR 8.44±0.011 7.18±0.001 0±0.015 0±0.001 0±0.015 1 Appendix 1—figure 4B
MP1202 hMOR 9.99±0.012 7.24±0.002 1.55±0.016 0.058±0.002 1.49±0.016 31
DAMGO hMOR 8.86±0.075 7.82±0.060 0±0.106 0±0.084 0±0.135 1 Appendix 1—figure 4B
IBNtxA hMOR 9.99±0.081 7.572±0.25 1.14±0.11 -0.25±0.25 1.38±0.28 24
DAMGO hMOR 8.62±0.054 6.78±0.010 0±0.076 0±0.014 0±0.077 1 Appendix 1—figure 4B
MP1305 hMOR 9.79±0.053 6.89±0.048 1.17±0.076 0.109±0.049 1.059±0.090 11
DAMGO hMOR 8.40±0.001 6.78±0.009 0±0.002 0±0.012 0±0.013 1 Appendix 1—figure 4B
MP1601 hMOR 9.84±0.002 7.65±0.035 1.44±0.002 0.87±0.036 0.57±0.036 4
U50,488h WT hKOR 10.22±0.051 8.44±0.004 0±0.072 0±0.006 0±0.070 1 Appendix 1—figure 7L
MP1202 WT hKOR 11.88±0.050 10.30±0.004 1.66±0.072 1.856±0.006 -0.19±0.072 nd
U50,488h Y312W-hKOR 8.568±0.005 7.559±0.051 0±0.007 0±0.072 0±0.073 1 Appendix 1—figure 7L
MP1202 Y312W-hKOR 10.63±0.005 8.091±0.051 2.062±0.007 0.532±0.073 1.53±0.073 34
DAMGO hMOR 8.563±0.004 5.037±0.176 0±0.006 0±0.249 0±0.249 1 Appendix 1—figure 8J
Methoxycarbonyl hMOR 10.020±0.004 7.546±0.184 1.457±0.006 2.509±0.255 -1.052±0.255 0.09
fentanyl

Appendix 1—table 11 shows the bias analysis of ligands at rodent opioid receptors (nd:not determined; ns compared to control).

Appendix 1—table 11
Bias analysis of ligands at rodent opioid receptors.
Drug Receptor BRET-G BRET-Arr ΔlogRA ΔlogRA ΔΔlog RA Bias factor Figure
Log RA LogRA BRET-G BRET-arr (BRETG-BRETArr) (BRETG-BRETArr)
U50,488h rKOR 9.003±0.044 7.14±0.034 0±0.062 0±0.047 0±0.078 1 Appendix 1—figure 4C
MP1104 rKOR 10.07±0.047 8.84±0.033 1.067±0.064 1.702±0.047 -0.64±0.079 0.23
U50,488h rKOR 8.312±0.077 6.798±0.168 0±0.109 0±0.238 0±0.261 1 Appendix 1—figure 4C
MP1202 rKOR 9.906±0.088 8.791±0.171 1.594±0.117 1.993±0.239 -0.399±0.27 nd
U50,488h rKOR 7.55±0.103 5.988±0.222 0±0.146 0±0.313 0±0.345 1 Appendix 1—figure 4C
IBNtxA rKOR 10.19±0.141 8.846±0.266 2.64±0.175 2.858±0.346 -0.218±0.388 nd
U50,488h rKOR 7.593±0.012 6.783±0.005 0±0.016 0±0.007 0±0.018 1 Appendix 1—figure 4C
MP1601 rKOR 7.917±0.018 7.113±0.052 0.324±0.052 0.33±0.052 -0.006±0.057 nd
DAMGO mMOR 8.56±0.12 7.873±0.06 0±0.176 0±0.09 0±0.197 1 Appendix 1—figure 4C
MP1104 mMOR 8.917±0.12 9.196±0.06 0.357±0.173 1.323±0.09 -0.966±0.195 0.11
DAMGO mMOR 8.713±0.013 7.291±0.044 0±0.019 0±0.063 0±0.066 1 Appendix 1—figure 8J
Methoxycarbonyl mMOR 9.697±0.013 8.464±0.045 0.984±0.019 1.173±0.063 -0.189±0.066 nd
fentanyl
Appendix 1—figure 1
Characterization of ligands (MP1104, IBNtxA, MP1202, MP1207, MP1208, MP1305, and MP1601) at mouse mu opioid receptor (mMOR) using BRET assays-chemical structure, docking in MOR, G protein activity, and arrestin recruitment.

(A) MP1104 targets the TM2-TM3 region and is arrestin-biased at mMOR: The preferred docking pose of MP1104 (boat form, yellow stick) at an active state of MOR is shown. Ring C of MP1104 in boat form forces the iodophenyl moiety to reside in a region between TM2-TM3. MP1104 (red) is a partial agonist in mMOR measuring G protein activation (N = 4) and arrestin recruitment (N = 4) compared to DAMGO (blue) in BRET assays. (B) IBNtxA targets the TM5-ECL2 region while showing reduced arrestin potency at mMOR compared to DAMGO: The docking poses of IBNtxA (chair form, orange stick) at an active state of MOR is shown. The saturated ringC in IBNtxA leads to interaction of the ligand in the ECL2 and TM5 region, which leads to a preference of chair form in our docking studies. At mMOR, it is a partial agonist for G protein signaling (N = 4) compared to DAMGO (blue) while showing reduced arrestin potency compared to DAMGO (N = 4) in BRET assays. (C) MP1202 targets the TM5-ECL2 region and shows reduced arrestin potency at mMOR compared to DAMGO. The preferred docking pose of MP1202 (chair form, orange stick) at an active state of MOR. The saturated ringC in MP1202 leads to interaction of the ligand in the ECL2 and TM5 region. MP1202 (red) is a partial agonist for G-signaling (N = 5) in mMOR and reduced arrestin potency (N = 5) compared to DAMGO (blue) in BRET assays. (D) MP1207 and MP1208 target the TM5-ECL2 region and show no arrestin recruitment at mMOR: Docking results showed that m-aminomethyl (MP1207) or m-guanidinomethyl (MP1208) moieties (replacing an iodo group in MP1202) forced these compounds in chair form preferred confirmation at MOR (chair form in orange stick and boat form in green stick). MP1207 (orange) and MP1208 (green) are partial agonists at mMOR in BRET assays (N = 3) compared to DAMGO (blue). At MOR, chair forms of MP1207 and MP1208 introduce additional interactions between m-amino or m-guanidino group and D218ECL2 and T220ECL2. No arrestin recruitment was observed for both agonists (N = 3). (E) MP1305 and MP1601 target the TM5-ECL2 region and show no arrestin recruitment at mMOR. Chair and boat forms of MP1305 and MP1601 at an active state MOR (in cyan) are shown. Docking modes of MP1305 and MP1601 are analogous and they both maintain chair confirmation at MOR. In BRET assays using mMOR, MP1305 (green) and MP1601 (red) are partial agonists for G-signaling (N = 3) compared to DAMGO (blue) with no measurable arrestin recruitment (N = 3). In summary, targeting TM5-ECL2 and ring C taking chair form leads to reduced arrestin signaling at MOR in both rodents as well as human receptors with analogs. See Appendix 1—table 8 for values, Appendix 1—figure 4 and Appendix 1—table 11 for bias calculations.

Appendix 1—figure 2
Characterization of ligands (MP1104, IBNtxA, MP1202, MP1207, MP1208, MP1305 and MP1601) at rat kappa opioid receptor (rKOR) using BRET assays-chemical structures, docking in MOR, G protein activity, and arrestin recruitment.

A) MP1104 targets the TM2-TM3 region and is arrestin biased at rKOR: The preferred docking pose of MP1104 (boat form, yellow stick) at an active state of KOR is shown. The iodophenylamido moiety aligns in the hydrophobic pocket between TM2 and TM3 in KOR, a cavity lined with V1182.63, W124ECL1, and L1353.29. In addition, polar residue Q1152.60 adopts a slightly different conformation which allows more room for the hydrophobic moiety. Such increase in hydrophobic nature of the KOR binding pocket may well be associated yielding the best docking scores of MP1104 in its boat conformation. MP1104 (red) is a full agonist in rKOR in BRET assays measuring G protein activation (N = 6) and arrestin recruitment (N = 6) compared to U50,488H (purple). (B) IBNtxA prefers the boat form at KOR and is not biased for any pathway at mKOR: The docking poses of IBNtxA (chair form, orange stick) and (boat form, green stick) at an active state of KOR are shown. At rKOR, the iodophenylamido moiety of IBNtxA aligns in the hydrophobic pocket between TM2 and TM3 in KOR, a cavity lined with V1182.63, W124ECL1 and L1353.29. In BRET assays using rKOR, IBNtxA is a full agonist for G protein (N = 3) as well as Arrestin signaling (N = 3) compared with U50,488H (purple). (C) MP1202 prefers the boat form at KOR and is not biased for any pathway at rKOR. The preferred docking pose of MP1104 (boat form, yellow stick) and MP1202 (chair form, orange stick) at an active state of KOR. The iodophenylamido moiety aligns in the hydrophobic pocket between TM2 and TM3 in KOR, a cavity lined with V1182.63, W124ECL1, and L1353.29. In addition, polar residue Q1152.60 adopts a slightly different conformation allowing more room for the hydrophobic moiety. Such increase in hydrophobic nature of the KOR binding pocket may well be associated yielding the best docking scores of both MP1104, IBNtxA and MP1202 with their boat conformation. MP1202 (green) is a full agonist in rKOR measuring G protein activation (N = 3) and arrestin recruitment (N = 9) compared to U50,488H (purple) in BRET assays. (D) m-Aminomethyl (MP1207) and m-guanidinomethyl (MP1208) analogs prefer the chair conformation and target the TM5-ECL2 region and show no arrestin recruitment at KOR. Docking results showed that m-amino methyl (MP1207) or m-guanidinomethyl (MP1208) moieties (replacing an iodo group in MP1202) forced these compounds in chair form preferred confirmation at KOR (chair form in orange stick and boat form in green stick). Unlike boat MP1202, chair MP1207 at KOR may form a new salt bridge interaction between amino group and D2235.35 and E209A pulling the amidophenyl moiety away from the hydrophobic pocket between TM2 and TM3. Likewise, chair MP1208 forms salt bridge interactions between guanidino group and D2235.35 as well as with E209ECL2. MP1207 (orange) and MP1208 (green) are partial agonists for G-signaling (N = 3) at rKOR in BRET assays compared to U50,488H (purple). No arrestin recruitment was observed for both agonists (N = 5) against U50,488H as a control at rKOR. (E) MP1305 showed no arrestin recruitment and MP1601 was not biased for any pathway at rKOR: Chair and boat forms of MP130) and MP1601 at an active state KOR (in gray) are shown. Both MP1305 (green) and MP1601 (black) are partial agonists for G-signaling (N = 3) at rKOR in BRET assays compared to U50,488H (blue). No arrestin recruitment was observed for MP1305 (N = 6) while MP1601 was a partial agonist for arrestin signaling pathway (N = 6). In summary, targeting TM5-ECL2 and ring C taking chair form leads to preference for G protein pathway at KOR in both rodents as well as human receptors with analogs. See Appendix 1—table 8 for values, Appendix 1—figure 4 and Appendix 1—table 11 for bias calculations.

Appendix 1—figure 3
IBNtxA is arrestin biased at KOR but shows G protein biased agonism at MOR.

(A–B) At hMOR, IBNtxA (orange) is a G protein biased agonist compared with DAMGO (blue) (N = 4). (C–D) At hKOR, IBNtxA (pink) is a full agonist in cAMP inhibition (N = 3) and Tango-arrestin recruitment assays (N = 3) compared to U50,488H (purple). (F–G) However, at mMOR, it is a partial agonist in G-signaling assays (N = 4) and shows reduced arrestin potency (N = 4) compared to DAMGO (blue) in BRET assays. (H–I) In BRET assays using rKOR, IBNtxA is a full agonist in both G-signaling (N = 3) and arrestin signaling assays (N = 3) compared with U50,488H (purple). (E and J) The docking poses of IBNtxA (chair form, orange stick) and (boat form, green stick) at an active state of MOR and KOR are shown. At MOR, the saturated ring C in IBNtxA leads to interaction of the ligand in the ECL2 and TM5 region leading to a preference of chair form shown by a red arrow. At KOR, the iodophenylamido moiety of IBNtxA aligns in the hydrophobic pocket between TM2 and TM3 in KOR, a cavity lined with V1182.63, W124ECL1 and L1353.29 similar to MP1202. This flip of ring C conformation from chair to boat is shown by a blue arrow. Preference for chair form correlates with G protein bias while preference for boat form correlates with increased arrestin signaling or no preference for any pathway. See Appendix 1—table 9 for values, Appendix 1—figure 4 and Appendix 1—tables 1011 for bias calculations.

Appendix 1—figure 4
Bias plots for ligands at hKOR (A), hMOR (B) using cAMP and Tango assay and at rKOR /mMOR (C) using BRET assays.

Bias analysis for signaling was performed as described in Materials and methods. Data analyzed against DAMGO and/or U50,488h for each ligand using unpaired t-test with Welch’s correction. At hKOR, MP1104 (**p=0.0015); IBNtxA (***p=0.0002) showed preference for arrestin over G-signaling while MP1209, 1210, 1305 and 1601 showed no preference for any signaling pathway. MP1209 (***p=0.0001) and MP1208 (****p<0.0001) were G-biased. At hMOR, MP1104 (*p=0.0427) preferred arrestin pathway while MP1202 (****p=<0.0001); IBNtxA (**p=0.0089); MP1601 (**p=0.0017) and MP1305 (***p=0.001) were G-biased. At rKOR, MP1104 (***p=0.0002) preferred arrestin pathway while IBNtxA, MP1202, 1601 and 1305 showed no preference for any signaling pathway. At mMOR, MP1104 (**p=0.0021) showed preference for arrestin pathway. To summarize bias factors suggest that in spite of differences in assays and species tested, ligands which engage TM5-ECL2 region of MOR/KOR and where ringC takes chair conformation.

Appendix 1—figure 5
The preferred docking pose of known KOR biased ligand 6′GNTI (chair form, orange stick) at an active state of KOR with the guanidino group engaging a region between TM5 and ECl2.

Note: possible engagement of residues D223 and E209 similar to MP1207 and MP1208 in TM5-ECL2 region.

Appendix 1—figure 6
MP1207 is selective for opioid receptors in the GPCRome screen.

MP1207 was screened against 330 non-olfactory GPCRs for agonism in the arrestin recruitment TANGO assay. Each point shows luminescence normalized to basal level at a given GPCR at 3 µM MP1207 dose (>3000 higher dose than the binding affinity at opioid receptors), with vertical lines indicating the standard error of the mean. MP1207 induces an increase in signal twofold over basal at opioid receptors predominantly at KOR and DOR and much less at MOR. Results show selectivity for opioid receptors over non-opioid targets when tested at >10µM and >1500 fold higher than the binding affinity and agonistic potency at opioid receptors. The low signal at MOR is consistent with null arrestin recruitment at MOR. Several potential targets (GPR111, MAS1L, GPR75) did not show dose-dependent increase in signal and probably represent screening false positives.

Appendix 1—figure 7
Mutation of KOR Y312W leads to a receptor mimicking MOR arrestin recruitment.

MP1202 flips to a G protein biased agonist and arrestin recruitment for MP1207 and MP1208 is reduced. (A and C) At Y312W-hKOR, MP1202 (light green) is a G-biased agonist in cAMP inhibition (N = 3) (A) and Tango-arrestin recruitment assays (N = 3) (C) compared to U50,488H (pink). (B) At WT-hKOR, MP1202 (purple) acts as a full agonist for arrestin recruitment (N = 3). (D) At WT-hMOR, MP1202 (red) acts as a partial agonist for arrestin recruitment (N = 3). (E and G) At Y312W-hKOR, MP1207 (light green) and 1208 (dark green) show full agonism in cAMP inhibition (N = 3) (E) and reduced arrestin measurement in Tango-arrestin recruitment assays (N = 3) (G) compared to U50,488H (pink). (F) At WT-KOR, MP1207 (orange) and MP1208 (green) act as partial agonists for arrestin recruitment (N = 3) compared to control U50,488H (purple). (H) At WT-MOR, no arrestin recruitment (N = 3) was observed for both agonists MP1207 and MP1208. (I) Conformation of selected residues seen in high resolution active state MOR structure along with crystallographic waters around TM2-TM3 region and crystallized ligand (BU72). MOR, conformation of conserved Q2.60 is maintained by a rather extensive hydrogen-bonding network mediated by W7.35 and at least four tightly bound waters as found in the crystal structure. (J) Conformation of selected residues and MP1202 seen in active state KOR structure, along with modeled waters around TM2-TM3 region. In KOR, no crystallographic waters were resolved in the structure, the non-conserved residues, including Y7.35 instead of W7.35, would rearrange water network and change conformation of Q2.60, paramount for ligand binding. A theoretical water network was modeled using SampleFlood method of ICM Molsoft in the orthosteric ligand site, and resulting waters were optimized via several rounds of extensive conformational sampling. As a result of significant difference observed in the water network, compared to MOR, KOR’s Q1152.60 moves further inwards and is positioned between D1383.32 and Y3127.43, and this new position of Q1152.60 is stabilized via a water-mediated hydrogen bond with Y3127.35. (K) Docking poses of chair and boat conformations of MP1202 in Y312W KOR mutant. The chair form (−56.53) is favored over boat form (−53.75) at this mutant receptor for MP1202. (L) Bias plots for U50,488h and MP1202 at hKOR and Y312W hKOR mutant. MP1202 is not significantly different from U50,488h with respect bias for G over βarrestin-2 signaling at wild type receptor while at the hKOR mutant it shows G-biased signaling. Data are mean± SEM from N = 3 replicates. Data analyzed using unpaired t-test with Welch’s correction,***p=0.0001. See Appendix 1—table 9 for values, Appendix 1—figure 4 and Appendix 1—table 10 for bias calculations.

Appendix 1—figure 8
Methoxycarbonyl fentanyl amide analog MP102 targeting TM5 in MOR shows no arrestin recruitment compared to methoxycarbonyl fentanyl at mMOR in BRET assays.

(A-B) Methoxycarbonyl fentanyl (red) is a full agonist at hMOR in cAMP (N = 3) and arrestin recruitment assays (N = 3) compared to DAMGO (blue). (C–D) Methoxycarbonyl fentanyl (red) is a full agonist at mMOR in BRET G protein activation (N = 4) and partial agonist in arrestin recruitment assays (N = 4) compared to DAMGO (blue). (E) Molecular docking of MP102 (green stick) engaging TM5 region and methoxycarbonyl fentanyl (yellow stick) not occupying TM5 region in hMOR. and chemical structures of methoxycarbonyl fentanyl and methoxycarbonyl fentanyl amide, MP102. (F-G) MP102 (purple) is a full agonist at mMOR in cAMP assays (N = 3) and shows no arrestin recruitment assays (N = 3) compared to DAMGO (blue). (H–I) Similarly, MP102 (purple) is a partial agonist at mMOR in BRET G protein activation assays (N = 3) and shows no arrestin recruitment assays (N = 6) compared to DAMGO (blue). (J) Bias plots for DAMGO and methoxycarbonyl fentanyl at hMOR and mMOR. Methoxycarbonyl fentanyl is arrestin biased at hMOR and shows no preference for any pathway at mMOR. Data are mean± SEM from N = 3 replicates and is analyzed using unpaired t-test with Welch’s correction,***p=0.0001. See Appendix 1—tables 7– eight for values, and Appendix 1—table 10 and Appendix 1—table 11 for bias calculations.

Appendix 1—figure 9
At human receptors, MP1305 is G-biased at MOR and KOR whereas MP1601 is G-biased at MOR and arrestin biased at KOR.

(A-B) MP1305 (green) is a full agonist at hKOR in cAMP inhibition (N = 6) and partial agonist in Tango-arrestin recruitment assays (N = 6) compared to U50,488H (purple) at hKOR. (C–D) MP1305 (red) is a partial agonist at hMOR in cAMP inhibition (N = 3) and partial agonist in Tango-arrestin recruitment assays (N = 3) compared to DAMGO (blue). (E–F) MP1601 (orange) is a full agonist at hKOR in cAMP inhibition (N = 6) and Tango-arrestin recruitment assays (N = 6) compared to U50,488H (purple). (G–H) Similarly, MP1601 (purple) is a partial agonist at hMOR in cAMP inhibition (N = 3) and Tango-arrestin recruitment assays (N = 3) compared to DAMGO (blue). (I–J) Molecular docking of MP1305 and MP1601 with a chair (orange stick) or a boat confirmation (green stick) at hKOR and hMOR. (K–L) Chair and boat forms of MP1305 and MP1601 at an active state hKOR (in gray) and Chair and boat forms of MP1305 and MP1601 at an active state hMOR (in cyan). Preferred docking modes of MP1305 and MP1601 are analogous and they both maintain chair confirmation at hMOR and are biased toward G protein, while being balanced agonists at hKOR taking boat conformation. See Appendix 1—table 9 for values, Appendix 1—figures 4 and Appendix 1—table 10 for bias calculations.

Appendix 1—figure 10
MP1305 is G protein biased at KOR.

Docking pose for ligands inside active state KOR shown in white carbon sticks and white ribbon representations. (A–B) MP1202 in KOR favors boat conformation. (C–D) MP1305 in KOR favors chair conformation. 14th-position-Methoxy of MP1305 causes sidechain of Q1152.60 residue to undergo a conformational change, when compared to ligands with non-Methoxy substitutions at 14th-position (shown in cyan colored carbon sticks representation). (E) IBNtxA in KOR favors boat conformation. (F) Stabilization of IBNtxA in boat form through internal hydrogen-bonding between 14-OH and amide and with Q1152.60 is shown. The docked and energy minimized pose of MP1305 shows the substitution of 14-OH with larger methoxy group displaces the conserved Q1152.60 of KOR. In ligands with 14-OH, the Q1152.60 residue of KOR is directed toward the ligand and forms hydrogen bonds with the 14-OH. In the case of MP1305, the methoxy group pushes Q1152.60 residue away to avoid steric clashes, and the polar terminus of the side chain ends up in the previously hydrophobic TM2-TM3 sub-pocket of KOR. Furthermore, due to internal ligand sterics, the internal hydrogen bond between the amide and 14-OH, as seen in compounds such as IBNtxA, is not possible for MP1305. The combination of these two factors, increasing polarity of the hydrophobic TM2-TM3 sub-pocket (an effect similar to Y312W6.35 KOR sub-pocket mutation- and lack of an internal hydrogen bond stabilizing the boat form, shifts the equilibrium toward the chair form for MP1305).

Appendix 1—figure 11
MP1207 and 1208 show significantly less hyperlocomotion compared to morphine.

Mice were administered icv either morphine (30 nmol; n = 18), MP1207 (30 nmol; n = 26) or MP1208 (35 nmol; n = 10) and the ambulation of each group of mice monitored using the CLAMS/Oxymax system. Morphine (30 nmol, icv) significantly increased forward ambulation in comparsion to MP1207 at 80 min (**p=0.002), 100 min (**p=0.01), 140 min (*p=0.03), and 160 min (****p<0.0001) as determined by two-way ANOVA followed by Dunnett’s multiple-comparison test. Similarly, significant morphine-induced increases in ambulation as compared to the response of MP1208 were observed at 80 min (#p=0.0249), 100 min (#p=0.0497), and 160 min (####p<0.0001) as determined by two-way ANOVA followed by Dunnett’s multiple-comparison test.

Appendix 1—scheme 1
Synthesis of m-arylamido dihydromorphinans MP1202 (A), MP1207, MP1208 (B).
Appendix 1—scheme 2
Synthesis of m-arylamido dihydromorphinans MP1210 and p-arylamido dihydromorphinan analog, MP1209.
Appendix 1—scheme 3
Synthesis of 14-O-methyl m-iodoarylamidomorphinan MP1305.
Appendix 1—scheme 4
Synthesis of m-iodoarylamido-4,5-deoxymorphinan MP1601.

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Decision letter

  1. Olga Boudker
    Senior and Reviewing Editor; Weill Cornell Medicine, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This paper will be of broad interest to scientists studying GPCR signaling, opioid pharmacology, and pain and addiction. The authors use computational modeling to develop dual G protein biased MOR-KOR agonists with reduced side effect profiles. The premise is novel, and the data support well the key conclusions.

Decision letter after peer review:

Thank you for submitting your article "Controlling opioid receptor functional selectivity by targeting distinct subpockets of the orthosteric" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Olga Boudker as the Senior and Reviewing Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

As the editors have judged that your manuscript is of interest, but as described below that additional experiments are required before it is published, we would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv (if it is not already there) along with this decision letter and a formal designation that the manuscript is "in revision at eLife". Please let us know if you would like to pursue this option. (If your work is more suitable for medRxiv, you will need to post the preprint yourself, as the mechanisms for us to do so are still in development.)

To date, the majority of biased drug development strategies have focused on increasing bias at individual receptors in order to reduce adverse effects while maintaining or enhancing the beneficial effects of receptor activation. Although conceptually promising, the clinical effects of single receptor biased ligands have been equivocal. The approach used in this manuscript is to developed selective ligands that are G protein biased at two different receptors, the mu and kappa opioid receptor (MOR, KOR). The premise is that G protein bias at each receptor may minimize adverse effects associated with MOR or KOR activation individually. Furthermore, co-activation of KOR will enhance the pain-relieving properties and minimize the rewarding properties of MOR activation. The crystal structure of activated MOR and KOR is used to identify regions within these receptors that confer G protein bias vs. a more balanced profile. The computational modeling shows that engagement of the TM2-TM3 pocket correlates with balanced agonists, while the TM5-ECL2 site correlates with G protein biased agonists at MOR and KOR. Also, the use of mutational analysis adds a level of rigor to the experimental design. Importantly, you have made several MOR-KOR G protein biased ligands, and show that one of these (MP1207) has effective antinociceptive properties without reward-seeking behaviors, and rather than respiratory depression it produces stimulation. This work could have significant utility in guiding future efforts to develop safer analgesics. Overall, all reviewers were enthusiastic about the work. Several significant weaknesses were identified and would need to be addressed. Below is a summary of the major points followed by the comments from individual reviewers.

1) All reviewers have agreed that the in vivo work has significant weaknesses. However, it is essential for the paper. Mostly, the reviewers were concerned that you are overly focused on the G protein bias while ignoring efficacy. It remains unclear whether G protein bias might confer benefits as opposed to other mechanisms such as partial agonism. A key issue is that comparisons are made between different opioid drugs that are administered differently and used at different relative doses. This makes it more challenging to make conclusions about each agonist's relative propensity to cause a particular effect. Three possible solutions to this:1) you provide further explanations/existing data as to why this experimental approach was taken and why you can draw the conclusions you make; 2) you repeat experiments using more consistent doses/administration routes; 3) you revise the discussion of these data so that any statement regarding the relative effect of agonists is qualified by the limitations we have highlighted.

2) The physiological experiments use the partial agonist morphine as a standard for comparison, while the cell-based and in-vitro assays all use the full agonists DAMGO or U50,488 as references. Morphine and/or buprenorphine should be included in the cell-based assays or the GTPγS assay to get an idea of the relative efficacy and affinity compared to these compounds. The comparison would allow for a less ambiguous interpretation of the data. Additionally, the GTPγS activity table (Appendix 1—table 2) is important and should be in the main manuscript- with morphine included.

3) There are some questions about the potential rewarding effects of MP-120. Locomotor effects of MP-120 appear to be highest at the lower dose and at a later time point. Locomotor stimulation often corresponds with increased mesolimbic dopamine release, which can also underlie the rewarding properties of a ligand. It would be important to reconcile this dose and timing with the conditioning experiment to more clearly determine if MP-120 has rewarding properties.

4) Data analysis in the in vitro experiments is not satisfactory. The finding that by targeting a sub-pocket in the receptors can allow the “rational” design of biased ligands is potentially important. However, unless you provide details about how these biased values are derived and provide errors and statistical analysis it is impossible to say if these findings are robust.

Reviewer 1:

1) For the tail flick experiment could you please include the time course in the supplementary data? It would be good to see the peak time for anti-nociceptive effects relative to respiratory depression and locomotor stimulation.

2) For the CPP experiments I think you should test 30 nmol of MP1207 since this lower dose had a greater effect on locomotor stimulation which is associated with mesolimbic dopamine release. Also the timing for conditioning should be discussed. Locomotor stimulation peaks around 120 min, while conditioning for CPP was done 0-40 min following infusion.

3) The authors hypothesize that the respiratory stimulation induced by MP1207 is due to KOR activation. What does a "standard" KOR agonist like U50,488 do in this assay? Also, could you please discuss what respiratory stimulation might mean clinically.

4) The data with the MOR and KOR knockouts add a level of rigor to the study. However, I'm not sure that it necessarily adds clarity. I think expressing the data in Figure 6F and G, as area under the curves as well would help with the analysis. Also, in the KOR KO, MP1207 doesn't show respiratory depression as a traditional MOR agonist would. Could you please discuss this further? Is there are reason to not do these types of experiments with MOR and KOR antagonists?

Reviewer 2:

1) The physiological experiments use the partial agonist morphine as a standard for comparison while the cell-based and in-vitro assays all use the full agonists DAMGO or U50,488 as references. Morphine should be included in the cell-based assays, or the GTPγS assay at a minimum, to get an idea of the relative efficacy and affinity compared to morphine. This would allow for a more complete interpretation of the data. Additionally, the GTPγS activity table (Appendix 1—table 2), is important and should be in the main manuscript- with morphine included.

2) The respiratory depression data is confounded by the increased locomotion rate (measured at the same time) induced by the new compounds, perhaps due to KOR agonist actions. Increased movement will increase the respiratory rate and introduce artifacts into the respiration measurements. This is clear with 100 nmol morphine in Figure 6D. It is not clear how these complications were addressed.

3) It's not clear that the doses chosen for respiratory depression and CPP are equianalgesic with morphine with respect to MOR activity. A full dose response in the KOR knockout (Figure 6B) would help with interpretation of the respiratory depression data.

4) Comparing IP morphine with icv MP1207 in the CPP assay is also questionable.

5) Recent work with a "G protein biased" MOR mouse (Kliewer et al., 2019) is an elegant study that raises serious questions about the G protein bias and on-target opioid effects. Is there any evidence that arrestin signaling can actually cause respiratory depression or place preference? This should be addressed.

6) It's unclear if there is any statistical threshold for calling an agonist "biased". The bias factor provides a nice number showing an extent of apparent bias but it's not clear what the line is between biased and not biased as it seems like a continuum with an arbitrary cutoff.

7) It's also unclear if statistical tests were performed for the respiration and locomotion data in Figure 6D and E. Were none of these points significant? That would affect interpretation of these data.

Reviewer 3:

1) The final sentence of the Abstract that suggests that dual G protein biased MOR/KOR signalling provides better therapeutic profiles does not entirely fit with the data set or indeed, the discussion of these data by the authors. I suggest the authors rewrite this such that while dual Mu/Kappa engagement appears to be beneficial there is no definitive causal link with bias (or indeed evidence that it is not important).

2) The Introduction quotes bias factors from different studies. No explanation is given in the Introduction text as to what these values are or what they might mean. Values based on methodologies using the Black and Leff operational model developed by Kenakin, Christopoulos and Ehlert to generate log[Tau/KA] are relative values subject to the experimental system used. Different studies will have used different cell backgrounds, different receptor expression levels, different assays/approaches to measure signalling events and even different reference agonists. The comparison of bias factors across different studies is likely not meaningful and such quantitative comparisons should be removed from the Introduction.

3) Bias factors are quoted throughout the manuscript but the work up to these values is not provided nor an explanation as to what they mean. Presumably, a bias factor >1 means bias toward cAMP inhibition and < 1 means bias towards arrestin recruitment. I notice that often ligands with a bias factor of < 1 are described as balanced rather than arrestin biased? The authors are using a methodology based on the operational model of agonism. We need to see the various steps that have been used to calculate these values including the Log[tau/KA], deltaLog[tau/KA] (which should be compared with appropriate statistical methods and deltadeltaLog[tau/KA] values). The bias factors are presented without error associated with them so it is impossible to evaluate the significance of such values, and ultimately this means that we cannot assess the robustness of these findings. This information is needed for publication. I would also like to see a more detailed description of the use of this analysis in the Materials and methods rather than the citation of the Kenakin and Christopoulos methodology paper.

4) Some of the curve fitting in some of the figure panels needs to be addressed. For example, in Figure 1C the lower asymptote of MP1104 is not defined at all and the concentration-response curve appears to start below zero. How was the lower asymptote of this curve defined? The same issue is true for the IBtxA curve at the hKOR G protein assay (S3C) and MP1202 in Figure 2I. In Appendix 1—figure 1 the maximal response of IBNtxA and MP1202 in the arrestin assay are not defined so it is not clear how this not has been fitted or how EC50 and Emax have been estimated. The same is true for IBNtxA in S3G. Fitting data in this way will likely impact bias calculations too. In some cases (eg. IBtxA) there are some compelling reversals of the order of potency with DAMGO as qualitative indicators of bias but in some cases I am not sure if reliable quantitative estimates of bias can be derived from these data.

5) DAMGO is less potent in the arrestin recruitment assay as compared to the cAMP assay indicating the former is more weakly coupled to the MOR and/or less amplified. The same is true for the reference agonist U50,488 at the KOR. In such systems, a partial agonist may give a robust response in the highly coupled endpoint but a weak response or no response in the weakly coupled endpoint. From these data, I would say that the authors cannot definitively call such examples “G protein biased”. This includes MP1207 and MP1208 at the MOR (Figure 3 and Appendix 1—figure 1), MP1209 and 1210 “G protein biased” at the MOR (Figure 4), MP1306 and MP1601 at the mMOR (Appendix 1—figure 1). Indeed, the [35S]GTPgS data for some of these ligands does indicate that these ligands are partial agonists for G protein activation too. The possibility that partial agonism might account for these observations is acknowledged in the Discussion. I recommend that the descriptions of these ligands as G protein biased in the Results text is toned down to be consistent with this ambiguity. MP1207 and MP1208 have been assigned bias values (8 and 23) in S2D but, given that no response is observed in the arrestin assay, it is not clear how these bias factors have been derived. The boxes in various figures that define such ligands as “G protein-biased” is at odds with the above ambiguity and should be removed.

6) The authors should provide further characterization/description of the double mutant is needed in order to interpret their data. Is it efficiently expressed at the cell surface and how does this expression compare to WT? How does the affinity and potency of the reference agonist change at this mutant? Indeed, given that bias is always expressed relative to the action of the reference agonist can the authors be sure that these mutations have altered the bias of MP1207/8 but not U50,488? How does U50,488 bind the receptor in terms of interaction with TM2/ECL2?

7) The figures legends are excessively long due to the inclusion of potency data for each agonist in each panel. These data should be presented in a table as the authors have done for their DOR data. In the figures more detail is needed regarding the data shown. Is this grouped data or is this an individual experiment? The authors should clarify if the numbers in parentheses are pEC50 plus minus SEM. The authors should provide the number of individual experiments and the number of replicates within each experiment for each data set. This information is available for some but not all data sets.

8) All in vivo data is shown as % decreases or as %MPE. Baseline values for each group should be given to show that they were not different in both analgesia and respiratory depressant assays. I would strongly encourage including raw data from these experiments as a supplementary table.

9) Drug administration route: In the in vivo experiments there are instances in which drugs are compared in the same assay but are administered differently. The reason for this needs further explanation. The basis for chosen doses needs further clarification. In the CPA/CPP experiments it is not clear why IP morphine/U50,488h is compared to ICV MP1207 drug administration. Unless there is evidence that this route results in appreciable concentrations of MP1207 in the circulating plasma you are not comparing like with like. It is a significant confound in this experiment when trying to demonstrate improvement over morphine in particular. Routes of administration and factors such as ability to cross the blood-brain barrier will, naturally, determine the measured effects of an opioid. This may be problematic when comparing the effects of opioid administered via different routes. Indeed, given the importance of peripheral opioid receptors for analgesia, tolerance and constipation it is difficult to predict the relative therapeutic benefits of a drug based on ICV data alone. This should be discussed.

10) In measurements of respiratory depression, a dose of 10 mg/kg morphine IP is used. Without a correlate in the other assays it is not clear why this is a useful comparator for the action of ICV MP1207. Similarly, U50,488h is also administered IP in this assay but ICV in the antinociception assay. The 30 nmol and 100 nmol ICV dose of morphine used in respiration are in excess of the maximal concentration of morphine used in the tail-flick assay. 10 nM ICV morphine would seem a more logical concentration to use for comparison with 30 nmol MP1207. This is also true for measurements of locomotor activity.

11) Data was taken at the point of peak antinociception for each drug, but it is not clear if these drugs peak at the same timepoint. The duration of an analgesic effect is also important information to know. The authors should supply supplementary data showing the time course of analgesia.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Controlling opioid receptor functional selectivity by targeting distinct subpockets of the orthosteric site" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Olga Boudker as the Senior and Reviewing Editor. The following individual involved in review of your submission has agreed to reveal their identity: Amynah A Pradhan (Reviewer #1).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

Summary:

This paper will be of broad interest to scientists studying GPCR signaling, opioid pharmacology, and/or pain and addiction. The authors use computational modeling to develop dual G protein biased MOR-KOR agonists with reduced side effect profiles. The premise is novel and the key claims are well supported by the data.

Revisions:

All reviewers agree that the manuscript has been significantly improved. Only minor additional concerns listed below were raised:

1) Since these agonists appear to be slightly more partial than buprenorphine (adding this reference agonist was helpful), it would be useful to discuss what is known about buprenorphine in respiratory depression, CPP and hyperlocomotion assays- with the caveat that the buprenorphine metabolite norbuprenorphine may be biologically relevant. This may help strengthen the case that partial KOR agonism is beneficial relative to the weak MOR agonism KOR antagonism of bup.

2) It appears there is some weak DOR agonism/ antagonism and that both MP1207/1208 can bind to DOR with only slightly lower affinity than MOR and KOR. DOR antagonism is known to modulate some MOR-mediated behaviors, so there is the potential for DOR agonism to play a role in some of the behaviors reported, which should be acknowledged.

3) "Together, these results support that dual MOR and KOR agonism may offset the liabilities characteristic of receptor-selective agonists".

4) The results are consistent with the dual MOR/KOR agonism hypothesis. Still, they might not differentiate weak MOR agonism from MOR/KOR agonism unless they are also done in the KOR knockout mice as was done for analgesia. Therefore, the language should be toned down.

5) Throughout the manuscript, the authors refer to bias factors. For example, MP1104 is said to have bias factors of 0.58 and 0.15 at MOR and KOR. Bias factors are not absolute values and are relative to the reference agonist used. Readers unfamiliar with bias factors will have no idea what these values mean unless they go to the Materials and methods section and then read a couple of papers cited there. The first time these bias factors are used, the authors need to explain more clearly how they were derived and what exactly they mean. Specifically: A) That at the MOR this is relative to the action of the agonist DAMGO and at the KOR, this is relative to the action of the agonist U50,488h – this is in the Materials and methods but needs to be stated in the text. B) That in all cases in the manuscript, you are comparing G protein signaling with arrestin recruitment so that bias factors greater than 1 means bias towards G protein and less than 1 means bias towards arrestin. C ) Where your values of Log bias are not significantly different from zero (so your bias factors are around 1) you need to state that the ligand is not biased.

6) In some cases, the analysis shows that some of the ligands show bias towards arrestin, but this is not highlighted in the text. Instead, it seems to be stated that the ligand shows robust at recruiting arrestin (e.g., MP1104, IBNtxa @ the KOR). This is not the case for G protein biased ligands. Why the difference? It is less confusing if bias is described the same way in both directions.

7) The statement that IBNtxa induces minimal arrestin recruitment at the MOR is at odds with the Appendix 1—figure 3, which shows that this ligand can induce a robust level of recruitment to 70% of that of DAMGO – the interesting thing is that the ligand is more potent than DAMGO in the G protein assay but less potent than DAMGO in the arrestin assay.

8) Similarly, the statement that MP1202 shows diminished arrestin recruitment is at odds with Appendix 1—figure 1C as the maximum effect of the ligand at arrestin recruitment is not reached at the highest concentration used – indeed, it would appear that MP1202 is less potent in the arrestin assay, but relative to DAMGO, may be more efficacious in this assay as compared to the cAMP assay.

9) Some of the concentration-response curves appear to be biphasic and not well fitted to the concentration-response curve shown in the relevant figure: Figure 3B, 1208; Figure 4D, 1209 and 1210, Figure S7C, 1202; Figure S7F, 1208; maybe Figure S7G, 1208; Figure S9D, 1305. Can the authors provide an explanation for this? Can they rule out some sort of non-specific effect occurring when these ligands are used at very high concentrations? It seems to be something observed in the arrestin assays in particular.

10) A bias factor for MP1202 at the mutant Y312W is stated as 34 and this is shown in figure S7L. The authors should provide the data/calculations in a supplementary table from which these values were derived, similar to those tables S10/11 that they have already provided for ligands at WT ORs.

11) Abstract: arrestin instead of arestin.

https://doi.org/10.7554/eLife.56519.sa1

Author response

[…] This work could have significant utility in guiding future efforts to develop safer analgesics. Overall, all reviewers were enthusiastic about the work. Several significant weaknesses were identified and would need to be addressed. Below is a summary of the major points followed by the comments from individual reviewers.

1) All reviewers have agreed that the in vivo work has significant weaknesses. However, it is essential for the paper. Mostly, the reviewers were concerned that you are overly focused on the G protein bias while ignoring efficacy. It remains unclear whether G protein bias might confer benefits as opposed to other mechanisms such as partial agonism. A key issue is that comparisons are made between different opioid drugs that are administered differently and used at different relative doses. This makes it more challenging to make conclusions about each agonist's relative propensity to cause a particular effect. Three possible solutions to this:1) you provide further explanations/existing data as to why this experimental approach was taken and why you can draw the conclusions you make; 2) you repeat experiments using more consistent doses/administration routes; 3) you revise the discussion of these data so that any statement regarding the relative effect of agonists is qualified by the limitations we have highlighted.

We thank the reviewers and the editor for pointing out partial agonism at MOR as an alternative pharmacological mechanism that may explain in vivo results for our ligands, which specifically demonstrated effective analgesia with reduced side effects, including lack of respiratory depression in mice. We are acutely aware of the ongoing debate about whether β-arrestin2 is indeed responsible for MOR-mediated respiratory depression. As the reviewers noted, our lead ligands, designed as dual MOR/KOR agonists with reduced (KOR) or abolished (MOR) arrestin recruitment, also behave as partial agonists in MOR cAMP and BRET assays. This comprises a complex multidimensional pharmacological profile for our ligands, and we demonstrate in vivo that it is beneficial. But we agree that it would be a great oversimplification to ascribe these reduced side effects results to any specific property of our new ligands, whether its dual, biased, or partial agonism, or a combination of these properties. Moreover, it is unlikely that any specific in vivo experiment would be sufficient to unambiguously commit to any conclusion here. Therefore, we revised the discussion of the in vivo data to include partial agonism at MOR and KOR as a possible factor in MP1207’s as well as 1208’s (now fully characterized in vivo) favorable attenuated opioid side-effect profile. Also, to address some inconsistencies noted by reviewers, we added new icv morphine/U50,488h analgesia, respiration, and CPP/CPA data as described in the answers below.

2) The physiological experiments use the partial agonist morphine as a standard for comparison, while the cell-based and in-vitro assays all use the full agonists DAMGO or U50,488 as references. Morphine and/or buprenorphine should be included in the cell-based assays or the GTPγS assay to get an idea of the relative efficacy and affinity compared to these compounds. The comparison would allow for a less ambiguous interpretation of the data. Additionally, the GTPγS activity table (Appendix 1—table 2) is important and should be in the main manuscript- with morphine included.

Morphine and buprenorphine data has been added for GTPgS (Table S2) and cAMP assays as well as BRET assays (Appendix 1—table 7). We prefer to keep the GTPgS data in the supplementary section to maintain the flow of the manuscript. Two in vivo figures are now part of the main manuscript (Figures 5-6). MP1208 has also been fully characterized pharmacologically and similar to MP1207 shows no CPP/CPA and attenuated respiratory depression.

3) There are some questions about the potential rewarding effects of MP-120. Locomotor effects of MP-120 appear to be highest at the lower dose and at a later time point. Locomotor stimulation often corresponds with increased mesolimbic dopamine release, which can also underlie the rewarding properties of a ligand. It would be important to reconcile this dose and timing with the conditioning experiment to more clearly determine if MP-120 has rewarding properties.

The editor raises a good point here. We find that hyperlocomotion and the rewarding effect of drugs as reflected by CPP seem to be separable. New data with MP1207 CPP/CPA at 30 nmol and MP1208 CPA/CPP at 100 nmol icv have been added, showing that no place preference and/or place aversion is seen at either dose. Furthermore, at equianalgesic doses, both MP1207 and 1208 show far less hyperlocomotion (See Appendix 1—figure 11) compared to icv morphine, and morphine shows CPP whereas neither 1207 nor 1208 does so.

4) Data analysis in the in vitro experiments is not satisfactory. The finding that by targeting a sub-pocket in the receptors can allow the “rational” design of biased ligands is potentially important. However, unless you provide details about how these biased values are derived and provide errors and statistical analysis it is impossible to say if these findings are robust.

As requested by the editor to accurately estimate bias we have added a new Appendix 1—figure 4 showing a graphical representation of bias with errors associated with the bias of ligands. Bias calculations are shown in newly added Appendix 1—table 10 and 11.

Reviewer 1:

1) For the tail flick experiment could you please include the time course in the supplementary data? It would be good to see the peak time for anti-nociceptive effects relative to respiratory depression and locomotor stimulation.

Time course of analgesia for both icv administered MP1207 (Figure 5C) and MP1208 (Figure 5D) has now been added. Note the peak effect for analgesia and respiratory effects do not match for both drugs compared to morphine. This is not unexpected; there are many suggestions in the literature that the analgesic effects of opioids may be dissociated from those doses inducing other effects, such as reward (De Vry et al., Eur J Pharmacol, 1989; Wilson et al., Peptides, 2000) or respiration (Brice-Tutt et al., 2020 from our lab). It is further possible that receptor occupancy required to produce analgesia is different from that producing respiratory effects when polypharmacology involving two receptors is involved, a topic outside the current scope.

2) For the CPP experiments I think you should test 30 nmol of MP1207 since this lower dose had a greater effect on locomotor stimulation which is associated with mesolimbic dopamine release. Also the timing for conditioning should be discussed. Locomotor stimulation peaks around 120 min, while conditioning for CPP was done 0-40 min following infusion.

We appreciate this critique from the reviewer. CPP of MP1207 at 30 nmol and MP1208 at 100 nmol (Figure 5B) has been added. Both drugs show no CPP and/or CPA. We have added more animals to the morphine group for both respiration (Figure 6B) and locomotor experiments (Figure 6E). Morphine at 30 and 100 nmol showed hyperlocomotor activity. Furthermore, morphine shows respiratory depression as well as CPP while MP1207 doesn’t at the highest dose tested. There is a discrepancy in peak effects for MP1207 and MP1208 analgesia vs respiration and locomotor effects which we are unable to explain at this point (although see response to 1; above). However, while comparisons of this sort are common (for instance, see Varadi et al., 2016), and a 40 min conditioning session still matches our analgesic time course to demonstrate pharmacological activity, we now offer the caveat of conditioning duration in the Discussion.

3) The authors hypothesize that the respiratory stimulation induced by MP1207 is due to KOR activation. What does a "standard" KOR agonist like U50,488 do in this assay? Also, could you please discuss what respiratory stimulation might mean clinically.

We have added U50,488h groups. icv U50,488h 30 nmol and 100 nmol (Figure 6B), showing it has no effect on respiration when administered icv. Dr. McLaughlin’s group has previously shown that U50,488h administered i.p. shows no respiratory stimulation up to 10 mg/kg, IP (PMID: 31258480). There is evidence from another paper published from the McLaughlin group that suggests KOR agonism can negate MOR mediated respiratory depression (PMID: 32562259), a finding reported previously with individual treatments of U50,488h and MOR agonists; Dosaka-Akita et al., 1993. It stands to reason that this respiratory stimulation would serve clinically to offset the respiratory effects of morphine and other MOR agonists used for pain management, potentially rendering safer analgesia.

4) The data with the MOR and KOR knockouts add a level of rigor to the study. However, I'm not sure that it necessarily adds clarity. I think expressing the data in Figure 6F and G, as area under the curves as well would help with the analysis. Also, in the KOR KO, MP1207 doesn't show respiratory depression as a traditional MOR agonist would. Could you please discuss this further? Is there are reason to not do these types of experiments with MOR and KOR antagonists?

We have removed the KO results on respiration and locomotor effects from this manuscript. Notably, reviewer 2 wanted us to evaluate MP1207 respiration at multiple doses in KOR KO mice, and we agree that would be ideal to evaluate the role of MOR/KOR towards respiration/locomotor effects to add further rigor to our work. KO mice are cleaner for testing as compared to using antagonists, which have defined durations of activity and compete with the compounds for receptor sites, making the KO mice more attractive for our work. Unfortunately, our KO colonies at UF were ordered to be much reduced during the Covid crisis and have not yet recovered, precluding additional experiments with KO animals.

Reviewer 2:

1) The physiological experiments use the partial agonist morphine as a standard for comparison while the cell-based and in-vitro assays all use the full agonists DAMGO or U50,488 as references. Morphine should be included in the cell-based assays, or the GTPγS assay at a minimum, to get an idea of the relative efficacy and affinity compared to morphine. This would allow for a more complete interpretation of the data. Additionally, the GTPγS activity table (Appendix 1—table 2), is important and should be in the main manuscript- with morphine included.

As requested by the reviewer morphine and buprenorphine has been added to the GTPgS table (Appendix 1—table 2) as well as cAMP assays and BRET (Appendix 1—table 7). The buprenorphine published data (PMID: 27223691) is from the laboratory of the late Dr. Pasternak. Both drugs appear as full agonists in the GTPgS assays, suggesting the presence of substantial receptor reserve. Numerous other papers from Pasternak’s lab (PMID: 15939800 in mMOR, PMID: 15893644 in hMOR, PMID: 14579421 in mMOR) have shown morphine to act as a full agonist. In addition, morphine has been found to be a full agonist by others (PMID: 32234959 using BRET-Gαi2, PMID: 20647394 and PMID: 31501422 using cAMP and Gαi2 activation). In cAMP assay morphine is a full agonist while buprenorphine is a partial agonist (EMax=77% of DAMGO). In Gi-1-BRET assay at hMOR, morphine behaves as a full agonist while buprenorphine is a partial agonist (Author response image 1).

Author response image 1

Similarly at mMOR in BRET assays morphine was a full agonist (Emax=109%) while buprenorphine was a partial (EMax=59%). See Appendix 1—table 7. We also note that both drugs have been shown in the literature to be partial agonists (PMID: 16436499 in C6 glioma transfected with MOR and buprenorphine in mMOR-CHO; PMID: 9580589 ) suggestive partial vs full agonism is cell line and assay dependent.Taken together, it is clear out our in vitro assays are showing substantial receptor reserve, making it difficult to capture the partiality of some compounds such as morphine.

However, the use of the operational model mitigates against this by considering shifts in both potency and efficacy. Furthermore, the literature clearly suggests that receptor reserve is present in vivo as well. Note that buprenorphine is a fully effective analgesic in rodents (PMID: 27223691) and humans, despite a “true” efficacy of ~25% in unamplified systems ( PMID: 32234959). We have decided to keep the GTPΥS data in the supplementary section so that we don’t interrupt the flow of the manuscript. Accordingly, we think it best to keep the GTPgS data in the supplementary section for those readers wishing to review it.

2) The respiratory depression data is confounded by the increased locomotion rate (measured at the same time) induced by the new compounds, perhaps due to KOR agonist actions. Increased movement will increase the respiratory rate and introduce artifacts into the respiration measurements. This is clear with 100 nmol morphine in Figure 6D. It is not clear how these complications were addressed.

We share the reviewer’s concern. We have added more animals to the icv morphine group for both respiration (Figure 6B) as well as locomotor (Figure 6D). Data on MP1208 at 35 nmol (Figure 6C) is now also included and a similar increase in breath rates is seen, consistent with the pharmacology of MP1207, a mixed KOR/MOR agonist. However, please note that KOR agonism is well documented to impair locomotor activity (including our own demonstration in Brice-Tutt et al., 2020). Moreover, in spite of inducing hyperlocomotion in rodents (as shown in Figure 6F), morphine still shows respiratory depression well documented to be mediated by MOR agonism. Collectively, our current data suggest that activity at KOR plays a role in the enhancement of breath rate with both MP1207/08. Also note, morphine produces far more hyperlocomotion compared to MP1207 and MP1208 at equianalgesic doses (See Appendix 1—figure 11). The data is also consistent with PMID: 32562259.

3) It's not clear that the doses chosen for respiratory depression and CPP are equianalgesic with morphine with respect to MOR activity. A full dose response in the KOR knockout (Figure 6B) would help with interpretation of the respiratory depression data.

4) Comparing IP morphine with icv MP1207 in the CPP assay is also questionable.

We have added icv morphine (30 nmol) and icv U50488h (100 nmol) CPP/CPA data at equianalgesic doses (Figure 5B). icv analgesia of morphine was determined instead of relying on the literature values. The analgesic ED50 is 4.77 nmol for morphine (Figure 5A). At approximately 5x analgesic ED50 doses morphine (30 nmol) shows CPP and MP1207 (30 nmol, ED50=6.1 nmol) does not. Similarly, icv U50,488h (ED50=8.8 nmol) at approximately 15x analgesic ED50, U50,488h (100 nmol) shows CPA while MP1207 (analgesic ED50=6.1 nmol) and MP1208 (analgesic ED50=7.2 nmol) do not show CPA or CPP.

We are however unable to add a KOR KO dose response curve. We do agree this would add rigor as well as allow us to evaluate the role KOR plays in negating MOR induced respiratory depression. Unfortunately, as noted in response to reviewer 1 above, our KO colonies at UF were effectively eliminated during the Covid crisis and have not yet recovered, precluding additional experiments with KO animals. Respecting the wishes of the reviewer, we have accordingly decided to remove the KO experiments evaluating respiration of MP1207 at 30 nmol from the manuscript.

5) Recent work with a "G protein biased" MOR mouse (Kliewer et al., 2019) is an elegant study that raises serious questions about the G protein bias and on-target opioid effects. Is there any evidence that arrestin signaling can actually cause respiratory depression or place preference? This should be addressed.

This is indeed an elegant paper. The role of arrestin in opioid induced respiratory depression has also been questioned by investigators from the same group (PMID: 32052419) and bioRxiv 2020, 2020.08.28.272575. Both these papers and the preprint are now cited in our Discussion where we have included a role for partial agonism as a rationale for MP1207/08 decreased adverse effects compared to classical opioid agonists. A manuscript on low intrinsic efficacy playing a role towards low respiratory depression is also cited (PMID: 32234959). A preprint challenging this hypothesis is also now included in our citations (https://www.biorxiv.org/content/10.1101/2020.11.19.390518v1).

We also note that our compounds are biased and partial at KOR as well as MOR so different receptor mechanisms with poly pharmacology are also at play. Evidence for a role of arrestin signaling for CPP is low; we agree with the reviewer on this. However, compounds with mixed MOR/KOR profile haven’t been thoroughly evaluated for Gi vs arrestin signaling as well as partial agonism at MOR/KOR and their in vivo outcomesrespiration vs addiction potential is thereby less well characterized for compounds with activity at KOR

Reviewer 3:

1) The final sentence of the Abstract that suggests that dual G protein biased MOR/KOR signalling provides better therapeutic profiles does not entirely fit with the data set or indeed, the discussion of these data by the authors. I suggest the authors rewrite this such that while dual Mu/Kappa engagement appears to be beneficial there is no definitive causal link with bias (or indeed evidence that it is not important).

We share the reviewer’s concerns, which is generally discussed in response to the Editors’s request at the beginning of this letter. We have toned down our focus on biased signaling as a rationale for the improved therapeutic benefit of MP1207/08 and added that dual engagement of mu as well as kappa receptor in addition to partial agonism may also be necessary. The focus of our manuscript is structure based design leading to biased agonists at KOR, using the crystal structure of MP1104. We computationally designed and synthesized 12 compounds each requiring multi-step synthesis, evaluated signaling independently in two labs and used MD simulations to validate receptor subpocket activity. However, we certainly cannot rule out a role for partial agonism as a mechanism of action., To address the reviewer’s comments, we have in addition to our lead compound MP1207 added MP1208 pharmacology (analgesia, respiration, locomotor effects and CPP/CPA) too in vivo and both drugs attenuated side-effects at highest doses tested possibly because of mixed actions at MOR and KOR.

2) The Introduction quotes bias factors from different studies. No explanation is given in the Introduction text as to what these values are or what they might mean. Values based on methodologies using the Black and Leff operational model developed by Kenakin, Christopoulos and Ehlert to generate log[Tau/KA] are relative values subject to the experimental system used. Different studies will have used different cell backgrounds, different receptor expression levels, different assays/approaches to measure signalling events and even different reference agonists. The comparison of bias factors across different studies is likely not meaningful and such quantitative comparisons should be removed from the Introduction.

As suggested, the literature-based bias factors for all ligands in the Introduction section have been removed.

3) Bias factors are quoted throughout the manuscript but the work up to these values is not provided nor an explanation as to what they mean. Presumably, a bias factor >1 means bias toward cAMP inhibition and < 1 means bias towards arrestin recruitment. I notice that often ligands with a bias factor of < 1 are described as balanced rather than arrestin biased? The authors are using a methodology based on the operational model of agonism. We need to see the various steps that have been used to calculate these values including the Log[tau/KA], deltaLog[tau/KA] (which should be compared with appropriate statistical methods and deltadeltaLog[tau/KA] values). The bias factors are presented without error associated with them so it is impossible to evaluate the significance of such values, and ultimately this means that we cannot assess the robustness of these findings. This information is needed for publication. I would also like to see a more detailed description of the use of this analysis in the Materials and methods rather than the citation of the Kenakin and Christopoulos methodology paper.

Requested changes have been made. The steps involved in calculating bias factors and errors related to bias factors have now been included. Please see Appendix 1—figure 4. Appendix 1—table 10-11 show Log[tau/KA], deltaLog[tau/KA] and deltadeltaLog[tau/KA] values. Only compounds with a measurable arrestin efficacy/potency and those with bias factors>1 are called G protein biased and ones with bias factor<1 are designated as not G-biased or in most cases referred to as compounds showing arrestin recruitment. The word balanced agonist is not used or used only for DAMGO and U50,488h. Note our computational, structural design complemented by ligand synthesis cannot distinguish between arrestin biased ligands and balanced agonists. We admit this is a limitation at our end. The focus of the manuscript is to develop predictive models that give a bias factor>1 or towards preferably G-biased signaling.

Please note there are differences between bias calculated between assays. For instance, MP1601 and IBNtxA are balanced agonists at rKOR (in BRET assay) while being arrestin biased at hKOR(in the cAMP/Tango determinations). In spite of these differences (which could be because of rat vs human receptor or assay used (BRET vs cAMP/Tango) or receptor reserve), the results are predictive towards a model which states that the alignment of the amidophenyl arm towards TM2-TM3 will lead to preference away from G protein signaling.

4) Some of the curve fitting in some of the figure panels needs to be addressed. For example, in Figure 1C the lower asymptote of MP1104 is not defined at all and the concentration-response curve appears to start below zero. How was the lower asymptote of this curve defined? The same issue is true for the IBtxA curve at the hKOR G protein assay (S3C) and MP1202 in Figure 2I. In Appendix 1—figure 1 the maximal response of IBNtxA and MP1202 in the arrestin assay are not defined so it is not clear how this not has been fitted or how EC50 and Emax have been estimated. The same is true for IBNtxA in S3G. Fitting data in this way will likely impact bias calculations too. In some cases (eg. IBtxA) there are some compelling reversals of the order of potency with DAMGO as qualitative indicators of bias but in some cases I am not sure if reliable quantitative estimates of bias can be derived from these data.

Changes have made and lower asymptote and maximal response defined in the legend. New cAMP data for IBNtxA, MP1202 and MP1104 at hKOR have been added and concentration-response curve now start at zero. The arrestin potency of IBNtxA and MP1202 at mMOR is now not reported as maximal response and potency could not be determined and bias factors for these are now not reported. Bias factors are now only reported for compounds with a measurable arrestin potency. As discussed above, compounds with bias factors >1 relative to either DAMGO for MOR or U50488H for KOR are designated as biased while ones with bias factor<1 are designated as not biased.

5) DAMGO is less potent in the arrestin recruitment assay as compared to the cAMP assay indicating the former is more weakly coupled to the MOR and/or less amplified. The same is true for the reference agonist U50,488 at the KOR. In such systems, a partial agonist may give a robust response in the highly coupled endpoint but a weak response or no response in the weakly coupled endpoint. From these data, I would say that the authors cannot definitively call such examples “G protein biased”. This includes MP1207 and MP1208 at the MOR (Figure 3 and Appendix 1—figure 1), MP1209 and 1210 “G protein biased” at the MOR (Figure 4), MP1306 and MP1601 at the mMOR (Appendix 1—figure 1). Indeed, the [35S]GTPgS data for some of these ligands does indicate that these ligands are partial agonists for G protein activation too. The possibility that partial agonism might account for these observations is acknowledged in the Discussion. I recommend that the descriptions of these ligands as G protein biased in the results text is toned down to be consistent with this ambiguity. MP1207 and MP1208 have been assigned bias values (8 and 23) in S2D but, given that no response is observed in the arrestin assay, it is not clear how these bias factors have been derived. The boxes in various figures that define such ligands as “G protein-biased” is at odds with the above ambiguity and should be removed.

Requested changes have been made. Only compounds where measurable arrestin efficacy was observed are characterized as G-biased while others are noted as agonists without measurable β-arrestin2 recruitment. This includes MP1207/08/09/10 at MOR (mouse and human) and MP1305, MP1601 at mMOR. Bias factors for MP1207 and MP1208 at rKOR have been removed and boxes with G-biased/not biased have been removed from all figures throughout the manuscript, We have toned down the discussion of bias and included a discussion on partial agonism for ligands that do not recruit arrestin.

6) The authors should provide further characterization/description of the double mutant is needed in order to interpret their data. Is it efficiently expressed at the cell surface and how does this expression compare to WT? How does the affinity and potency of the reference agonist change at this mutant? Indeed, given that bias is always expressed relative to the action of the reference agonist can the authors be sure that these mutations have altered the bias of MP1207/8 but not U50,488? How does U50,488 bind the receptor in terms of interaction with TM2/ECL2?

This is an excellent question. Although all points raised by the reviewer are fair, the loss of Dr. Pasternak’s lab leaves us unable to carry out any additional experiments to resolve this. In light of the reviewer’s concerns, we have taken out this figure and added an MD simulation, which computationally determines that the polar amine group binds between TM5 and ECL2 region. MD results in combination with MP1209 and MP12010 synthesis and kappa bias results together suggest that MP1207 requires acidic residues in TM5-ECL2 region to mediate its G-biased agonism. We are not able to answer the reviewer’s question of whether the mutation changes cell surface expression and if it affects potency and efficacy of the reference ligand vs MP1207/08. We add that U50,488H does not bind in the TM2/ECL2 region based on our computational studies. Furthermore, we have carried out BRET assays to evaluate whether the efficacy of MP1207 and 1208 is altered by TM5-ECl2 region mutations. We find that the efficacy of MP1207/08 is not altered by E209AD223A. We have retained the Y312W hKOR mutation results because mutant was extensively characterized in our previous publication (PMID: 29307491).

7) The figures legends are excessively long due to the inclusion of potency data for each agonist in each panel. These data should be presented in a table as the authors have done for their DOR data. In the figures more detail is needed regarding the data shown. Is this grouped data or is this an individual experiment? The authors should clarify if the numbers in parentheses are pEC50 plus minus SEM. The authors should provide the number of individual experiments and the number of replicates within each experiment for each data set. This information is available for some but not all data sets.

In order to reduce the length of the figure legend as requested by the reviewer, we have now included all in vitro potency and efficacy data in a table. See Appendix 1—table 7-9. Data shown is grouped in cohorts to increase rigor. We now clarify in the figure legend that the data represented is EC50 ± SEM. Legends of each figure now further include the number of individual replicates for each figure.

8) All in vivo data is shown as % decreases or as %MPE. Baseline values for each group should be given to show that they were not different in both analgesia and respiratory depressant assays. I would strongly encourage including raw data from these experiments as a supplementary table.

We agree this increases rigor. All analgesia and respiration raw data has been added as source data with the manuscript as requested by the reviewer. We did not however add the baseline values to the figures as they become too crowded and busy.

9) Drug administration route: In the in vivo experiments there are instances in which drugs are compared in the same assay but are administered differently. The reason for this needs further explanation. The basis for chosen doses needs further clarification. In the CPA/CPP experiments it is not clear why IP morphine/U50,488h is compared to ICV MP1207 drug administration. Unless there is evidence that this route results in appreciable concentrations of MP1207 in the circulating plasma you are not comparing like with like. It is a significant confound in this experiment when trying to demonstrate improvement over morphine in particular. Routes of administration and factors such as ability to cross the blood-brain barrier will, naturally, determine the measured effects of an opioid. This may be problematic when comparing the effects of opioid administered via different routes. Indeed, given the importance of peripheral opioid receptors for analgesia, tolerance and constipation it is difficult to predict the relative therapeutic benefits of a drug based on ICV data alone. This should be discussed.

Being charged at physiological pH, both MP1207/08 were not expected to be active peripherally and hence were evaluated after icv administration. This is also a well-established route of administration for initial testing of novel compounds, for which the supply is understandably limited. Still, to address the direct comparison requested by the reviewer, icv morphine and U50,488h controls for analgesia, respiration, CPP/CPA are now added wherever appropriate to facilitate direct comparison of the compounds by the same route of administration. See Figures 5 and 6. Notably, our conclusions were not changed by this revision.

We appreciate the reviewer’s concern about tolerance and constipation being dependent on peripheral opioid receptors. However, analgesia (at least in part), respiratory depression, locomotor effects and addiction/aversion potential are well established to be supraspinally mediated. Accordingly, only those side-effects were evaluated here. Indeed, with improved design and possibly structures of these biased drugs, the next generation of MP1207 analogs will be aimed at developing systemically active analogs where other side-effects can be evaluated in great detail and mechanisms of MOR/KOR G/arrestin signaling and partial agonism in vivo will be probed.

10) In measurements of respiratory depression, a dose of 10 mg/kg morphine IP is used. Without a correlate in the other assays it is not clear why this is a useful comparator for the action of ICV MP1207. Similarly, U50,488h is also administered IP in this assay but ICV in the antinociception assay. The 30 nmol and 100 nmol ICV dose of morphine used in respiration are in excess of the maximal concentration of morphine used in the tail-flick assay. 10 nM ICV morphine would seem a more logical concentration to use for comparison with 30 nmol MP1207. This is also true for measurements of locomotor activity.

We had added animals and determined that morphine icv ED50 is 4.77 nmol (Figure 5A) which is similar to icv MP1207 ED50 6.1 nmol. Hence determining respiration at 30 and 100 nmol for morphine is appropriate (Figure 6B). We have added icv morphine/U50,488h data for CPP and respiration also (Figure 5B).

11) Data was taken at the point of peak antinociception for each drug, but it is not clear if these drugs peak at the same timepoint. The duration of an analgesic effect is also important information to know. The authors should supply supplementary data showing the time course of analgesia.

Data has been added showing the time course of analgesia. See Figures 5C for MP1207 and Figure 5D for MP1208. We note the peak analgesic effects and peak increase in respiration and locomotor activity vary as discussed above.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Revisions:

All reviewers agree that the manuscript has been significantly improved. Only minor additional concerns listed below were raised:

1) Since these agonists appear to be slightly more partial than buprenorphine (adding this reference agonist was helpful), it would be useful to discuss what is known about buprenorphine in respiratory depression, CPP and hyperlocomotion assays- with the caveat that the buprenorphine metabolite norbuprenorphine may be biologically relevant. This may help strengthen the case that partial KOR agonism is beneficial relative to the weak MOR agonism KOR antagonism of bup.

As requested by the reviewer we have added references for hyperlocomotion, CPP (PMID: 17367825), respiration (PMID: 15833777) and role of norbuprenorphine (PMID: 11303059 and PMID: 22739506) in mediating some of buprenorphine’s effects. We have added a line distinguishing our probes MP1207/08 from buprenorphine. Briefly, buprenorphine causes hyperlocomotion, shows CPP and is known to have lower respiratory depression compared to classical mu opioiod agonists. Buprenorphine also metabolizes to norbuprenorphine further complicating its pharmacology. Norbuprenorphine has lower potency but higher efficacy over buprenorphine and norbuprenorphine shows respiratory depression. MP1207/08 in contrast shows attenuated CPP as well as respiratory depression at least in part because of dual low intrinsic efficacy at both KOR and MOR. This conjunction of KOR partial agonism with MOR partial agonism may have therapeutic benefits over the more broadly active buprenorphine, for example as shown presently with our probes by blunting MOR mediated respiratory depression.

2) It appears there is some weak DOR agonism/ antagonism and that both MP1207/1208 can bind to DOR with only slightly lower affinity than MOR and KOR. DOR antagonism is known to modulate some MOR-mediated behaviors, so there is the potential for DOR agonism to play a role in some of the behaviors reported, which should be acknowledged.

MP1207/08 certainly can label DOR at high doses and it is possible that DOR partial agonism and/or antagonism may impact the overall pharmacology of MP1207/08 in mice. We have added references for mixed MOR-DOR ligands, ligands with MOR agonists-DOR antagonists are known to have less tolerance as well as physical dependence (PMID: 27556704) while ligands with mixed MOR agonism-DOR agonism (PMID: 31201990) are known to be more active in chronic pain models.

3) "Together, these results support that dual MOR and KOR agonism may offset the liabilities characteristic of receptor-selective agonists".

Requested change has been made.

4) The results are consistent with the dual MOR/KOR agonism hypothesis. Still, they might not differentiate weak MOR agonism from MOR/KOR agonism unless they are also done in the KOR knockout mice as was done for analgesia. Therefore, the language should be toned down.

As requested a line stating the above noted limitation has been added in the Discussion section. Briefly, given the uncertainty over a mechanism by which KOR activity blunts MOR-mediated respiratory depression, future respiratory testing of mixed action ligands with MOR KO and KOR KO mice will be needed. Such testing may also better resolve whether weak MOR agonism alone or a combination MOR-KOR dual partial agonism, rather than the functional selectivity of MP1207 and MP1208 would be sufficient to account for the reduced liabilities presently observed.

5) Throughout the manuscript, the authors refer to bias factors. For example, MP1104 is said to have bias factors of 0.58 and 0.15 at MOR and KOR. Bias factors are not absolute values and are relative to the reference agonist used. Readers unfamiliar with bias factors will have no idea what these values mean unless they go to the Materials and methods section and then read a couple of papers cited there. The first time these bias factors are used, the authors need to explain more clearly how they were derived and what exactly they mean. Specifically: A) That at the MOR this is relative to the action of the agonist DAMGO and at the KOR, this is relative to the action of the agonist U50,488h – this is in the Materials and methods but needs to be stated in the text. B) That in all cases in the manuscript, you are comparing G protein signaling with arrestin recruitment so that bias factors greater than 1 means bias towards G protein and less than 1 means bias towards arrestin. C ) Where your values of Log bias are not significantly different from zero (so your bias factors are around 1) you need to state that the ligand is not biased.

6) In some cases, the analysis shows that some of the ligands show bias towards arrestin, but this is not highlighted in the text. Instead, it seems to be stated that the ligand shows robust at recruiting arrestin (e.g., MP1104, IBNtxa @ the KOR). This is not the case for G protein biased ligands. Why the difference? It is less confusing if bias is described the same way in both directions.

Thank you for this thoughtful suggestion. Requested changes under items 5 and 6 has been made. All ligands with bias factor >1 are named as G protein biased; ones with bias factor less <1 are arrestin biased while compounds with bias factor lacking statistically significant deviation from 1 are deemed unbiased throughout the manuscript wherever applicable. Definition of how bias factor is calculated in relative terms is now illustrated clearly.

7) The statement that IBNtxa induces minimal arrestin recruitment at the MOR is at odds with the Appendix 1—figure 3, which shows that this ligand can induce a robust level of recruitment to 70% of that of DAMGO – the interesting thing is that the ligand is more potent than DAMGO in the G protein assay but less potent than DAMGO in the arrestin assay.

8) Similarly, the statement that MP1202 shows diminished arrestin recruitment is at odds with Appendix 1—figure 1C as the maximum effect of the ligand at arrestin recruitment is not reached at the highest concentration used – indeed, it would appear that MP1202 is less potent in the arrestin assay, but relative to DAMGO, may be more efficacious in this assay as compared to the cAMP assay.

We thank the reviewers for pointing this out. The efficacy for both ligands is lower than DAMGO in arrestin as well as G protein assay. The potency in the G protein assay is greater than DAMGO for both ligands and as pointed out by the reviewers, ligands trend towards lower potency in the arrestin assay relative to DAMGO. While the exact reason for this is not known, we have made changes and used the phrase “trending towards lower arrestin potency” versus G protein potency compared to DAMGO in this case.

Note, we did not calculate the bias factors in this case because we cannot accurately determine the EC50 for ligands at βarrestin2 because the curves don’t show a plateau. Therefore we are not claiming these to be biased in this assay. We do however see a clear preference for G protein pathway with same ligands using cAMP/Tango assays. The bias analysis of all ligands is covered by Appendix 1—figure 4 and calculations of bias which cover efficacy and potency at both signaling pathways is shown in Appendix 1—tables 10-11.

9) Some of the concentration-response curves appear to be biphasic and not well fitted to the concentration-response curve shown in the relevant figure: Figure 3B, 1208; Figure 4D, 1209 and 1210, Figure S7C, 1202; Figure S7F, 1208; maybe Figure S7G, 1208; Figure S9D, 1305. Can the authors provide an explanation for this? Can they rule out some sort of non-specific effect occurring when these ligands are used at very high concentrations? It seems to be something observed in the arrestin assays in particular.

We thank the reviewers for pointing this out. We do not believe this effect is non-specific, because it was not seen for the same compounds in otherwise identical conditions in MOR Tango assays. Furthermore, it is not a general property of the KOR Tango assays as it was also not seen when testing U50,488h. The most plausible explanation for the observed biphasic response could be compounds at high concentrations hitting intracellular receptors, either with a basal pool of internal receptors or with receptors that have been internalized in response to agonist addition. Consistent with this interpretation, we and other groups have shown that a high density of receptors do exist intracellularly (Stoeber et al., 2018; Che et al., 2020). We have now included this discussion in the main text.

10) A bias factor for MP1202 at the mutant Y312W is stated as 34 and this is shown in Figure S7L. The authors should provide the data/calculations in a supplementary table from which these values were derived, similar to those tables S10/11 that they have already provided for ligands at WT ORs.

The requested calculations are shown Appendix 1—table 10. It is possible reviewers had missed seeing it.

https://doi.org/10.7554/eLife.56519.sa2

Article and author information

Author details

  1. Rajendra Uprety

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing
    Contributed equally with
    Tao Che and Saheem A Zaidi
    Competing interests
    RU have filed a provisional patent on MP1207 and related molecules.
  2. Tao Che

    1. Department of Pharmacology, University of North Carolina, Chapel Hill, United States
    2. Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, St. Louis, United States
    3. Department of Anesthesiology, Washington University in St. Louis School of Medicine, St. Louis, United States
    Contribution
    Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing
    Contributed equally with
    Rajendra Uprety and Saheem A Zaidi
    Competing interests
    No competing interests declared
  3. Saheem A Zaidi

    Department of Quantitative and Computational Biology, Department of Chemistry, Bridge Institute, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Rajendra Uprety and Tao Che
    Competing interests
    SZ has filed a provisional patent on MP1207 and related molecules.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7531-3587
  4. Steven G Grinnell

    Division of Molecular Therapeutics, New York State Psychiatric Institute and Departments of Psychiatry, Pharmacology, Columbia University Vagelos College of Physicians & Surgeons, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Balázs R Varga

    1. Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, St. Louis, United States
    2. Department of Anesthesiology, Washington University in St. Louis School of Medicine, St. Louis, United States
    Contribution
    Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0986-9477
  6. Abdelfattah Faouzi

    1. Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, St. Louis, United States
    2. Department of Anesthesiology, Washington University in St. Louis School of Medicine, St. Louis, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9059-4791
  7. Samuel T Slocum

    Department of Pharmacology, University of North Carolina, Chapel Hill, United States
    Contribution
    Resources, Data curation, Formal analysis, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  8. Abdullah Allaoa

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Resources, Data curation, Writing - review and editing
    Competing interests
    No competing interests declared
  9. András Varadi

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Resources, Data curation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5591-377X
  10. Melissa Nelson

    Division of Molecular Therapeutics, New York State Psychiatric Institute and Departments of Psychiatry, Pharmacology, Columbia University Vagelos College of Physicians & Surgeons, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  11. Sarah M Bernhard

    Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Data curation, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8549-0413
  12. Elizaveta Kulko

    Division of Molecular Therapeutics, New York State Psychiatric Institute and Departments of Psychiatry, Pharmacology, Columbia University Vagelos College of Physicians & Surgeons, New York, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
  13. Valerie Le Rouzic

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
  14. Shainnel O Eans

    Department of Pharmacodynamics, University of Florida, Gainesville, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
  15. Chloe A Simons

    Department of Pharmacodynamics, University of Florida, Gainesville, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
  16. Amanda Hunkele

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
  17. Joan Subrath

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared
  18. Ying Xian Pan

    1. Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    2. Department of Anesthesiology, Rutgers New Jersey Medical School, New Jersey, Newark, United States
    Present address
    Department of Anesthesiology,, Rutgers New Jersey Medical School, New Jersey, Newark, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing
    Competing interests
    YXP is a co-founder of Sparian biosciences.
  19. Jonathan A Javitch

    Division of Molecular Therapeutics, New York State Psychiatric Institute and Departments of Psychiatry, Pharmacology, Columbia University Vagelos College of Physicians & Surgeons, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7395-2967
  20. Jay P McLaughlin

    Department of Pharmacodynamics, University of Florida, Gainesville, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    JM has filed a provisional patent on MP1207 and related molecules.
  21. Bryan L Roth

    Department of Pharmacology, University of North Carolina, Chapel Hill, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    bryan_roth@med.unc.edu
    Competing interests
    BLR has filed a provisional patent on MP1207 and related molecules.
  22. Gavril W Pasternak (deceased)

    Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    GWP is a co-founder of Sparian biosciences. GWP have filed a provisional patent on MP1207 and related molecules.
  23. Vsevolod Katritch

    Department of Quantitative and Computational Biology, Department of Chemistry, Bridge Institute, Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    katritch@usc.edu
    Competing interests
    VK has filed a provisional patent on MP1207 and related molecules.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3883-4505
  24. Susruta Majumdar

    1. Department of Neurology and Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, United States
    2. Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University School of Medicine, St. Louis, United States
    3. Department of Anesthesiology, Washington University in St. Louis School of Medicine, St. Louis, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    susrutam@email.wustl.edu
    Competing interests
    SM
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2931-3823

Funding

National Institute on Drug Abuse (DA045884)

  • Susruta Majumdar

National Institute on Drug Abuse (DA046487)

  • Susruta Majumdar

National Institute on Alcohol Abuse and Alcoholism (AA026949)

  • Susruta Majumdar

National Institute on Drug Abuse (DA038858)

  • Vsevolod Katritch

National Institute on Drug Abuse (DA035764)

  • Bryan L Roth
  • Vsevolod Katritch

National Institute on Drug Abuse (DA007242)

  • Ying Xian Pan
  • Gavril W Pasternak

National Institute on Drug Abuse (DA042888)

  • Ying Xian Pan

National Institute of Mental Health (MH018870)

  • Steven G Grinnell

National Institute of Mental Health (MH112205)

  • Jonathan A Javitch

National Institute on Drug Abuse (DA045657)

  • Jonathan A Javitch

National Institute on Drug Abuse (DA006241)

  • Ying Xian Pan
  • Gavril W Pasternak

National Institute on Drug Abuse (DA046714)

  • Ying Xian Pan

National Institutes of Health (W81XWH-17-1-0256)

  • Susruta Majumdar

St. Louis College of Pharmacy and Washington University

  • Susruta Majumdar

National Institute on Drug Abuse (MH54137)

  • Jonathan A Javitch

Hope for Depression Research Foundation

  • Jonathan A Javitch

National Institute of Mental Health

  • Bryan L Roth

University of Florida Foundation

  • Jay P McLaughlin

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

SM is supported by funds from NIH grants DA045884, DA046487, AA026949 and W81XWH-17-1-0256 (Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program) and start-up funds from Center for Clinical Pharmacology, St. Louis College of Pharmacy and Washington University to SM. This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748 to MSKCC. Studies were also supported by NIDA grants R33DA038858 (VK) and P01DA035764 (VK and BLR), DA042888 and DA046714 (YXP) and DA007242 and DA006241 (GWP/YXP). T32 MH018870 (SGG), MH54137 and the Hope for Depression Research Foundation (JAJ). This work was also supported by NIH grants (R37DA045657 and RO1MH112205), the NIMH Psychoactive Drug Screening Program Contract, and the Michael Hooker Distinguished Chair of Pharmacology (to B.L.R.) and funds from the University of Florida (J.P.M.).

Ethics

Animal experimentation: All animal studies were preapproved by the Institutional Animal Care and Use Committees of University of Florida in accordance with the 2002 National Institutes of Health Guide for the Care and Use of Laboratory Animals. protocols 201808990 and 202011105.

Senior and Reviewing Editor

  1. Olga Boudker, Weill Cornell Medicine, United States

Publication history

  1. Received: March 1, 2020
  2. Accepted: February 7, 2021
  3. Accepted Manuscript published: February 8, 2021 (version 1)
  4. Version of Record published: February 26, 2021 (version 2)

Copyright

© 2021, Uprety et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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