Abstract
The neuromodulator melatonin synchronizes circadian rhythms and related physiological functions through the actions of two G-protein-coupled receptors: MT1 and MT2. Circadian release of melatonin at night from the pineal gland activates melatonin receptors in the suprachiasmatic nucleus of the hypothalamus, synchronizing the physiology and behaviour of animals to the light–dark cycle1,2,3,4. The two receptors are established drug targets for aligning circadian phase to this cycle in disorders of sleep5,6 and depression1,2,3,4,7,8,9. Despite their importance, few in vivo active MT1-selective ligands have been reported2,8,10,11,12, hampering both the understanding of circadian biology and the development of targeted therapeutics. Here we docked more than 150 million virtual molecules to an MT1 crystal structure, prioritizing structural fit and chemical novelty. Of these compounds, 38 high-ranking molecules were synthesized and tested, revealing ligands with potencies ranging from 470 picomolar to 6 micromolar. Structure-based optimization led to two selective MT1 inverse agonists—which were topologically unrelated to previously explored chemotypes—that acted as inverse agonists in a mouse model of circadian re-entrainment. Notably, we found that these MT1-selective inverse agonists advanced the phase of the mouse circadian clock by 1.3–1.5 h when given at subjective dusk, an agonist-like effect that was eliminated in MT1- but not in MT2-knockout mice. This study illustrates the opportunities for modulating melatonin receptor biology through MT1-selective ligands and for the discovery of previously undescribed, in vivo active chemotypes from structure-based screens of diverse, ultralarge libraries.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Probe pairs (two similar ligands with and without activity) of inverse agonists selective for MT1 and agonists selective for hMT2 are available by arrangement with Sigma (Extended Data Fig. 3). The identities of the compounds docked in this study are freely available from the ZINC database (http://zinc15.docking.org) and active compounds may be purchased from Enamine. Raw data are available for Fig. 1, Extended Data Tables 1, 2 and Extended Data Figs. 1, 2 in Supplementary Tables 1 (MT1 and MT2 affinities, MT1 DOCK energies and ranks) and 2 (compound purity information). Bias information for Extended Data Fig. 3 is included in Supplementary Table 3. For Fig. 2, data from the GPCRome screens, concentration–response curves, and competition binding and LC–MS experiments are included in Supplementary Data 1–5 and synthesis routes and spectra of compounds in Supplementary Data 6, 7. Further data for Fig. 3 are included in Extended Data Figs. 4, 5, 7 and Supplementary Table 4. Raw data values and transformed data for in vitro cell-based assays as well as in vivo data for phase shift and re-entrainment are available for Figs. 2, 3 and Extended Data Figs. 4 (re-entrainment), 5 (phase shift), 6, 7a–c.
Code availability
DOCK3.7 is freely available for non-commercial research (http://dock.compbio.ucsf.edu/DOCK3.7/). A web-based version is freely available to all at http://blaster.docking.org/. The ultra-large library used here is freely available at http://zinc15.docking.org/.
References
Zisapel, N. New perspectives on the role of melatonin in human sleep, circadian rhythms and their regulation. Br. J. Pharmacol. 175, 3190–3199 (2018).
Dubocovich, M. L. et al. International Union of Basic and Clinical Pharmacology. LXXV. Nomenclature, classification, and pharmacology of G protein-coupled melatonin receptors. Pharmacol. Rev. 62, 343–380 (2010).
Liu, J. et al. MT1 and MT2 melatonin receptors: a therapeutic perspective. Annu. Rev. Pharmacol. Toxicol. 56, 361–383 (2016).
Dubocovich, M. L. Melatonin receptors: role on sleep and circadian rhythm regulation. Sleep Med. 8, 34–42 (2007).
Mundey, K., Benloucif, S., Harsanyi, K., Dubocovich, M. L. & Zee, P. C. Phase-dependent treatment of delayed sleep phase syndrome with melatonin. Sleep 28, 1271–1278 (2005).
Rajaratnam, S. M. et al. Melatonin agonist tasimelteon (VEC-162) for transient insomnia after sleep-time shift: two randomised controlled multicentre trials. Lancet 373, 482–491 (2009).
Lewy, A. J. et al. The phase shift hypothesis for the circadian component of winter depression. Dialogues Clin. Neurosci. 9, 291–300 (2007).
Jockers, R. et al. Update on melatonin receptors: IUPHAR Review 20. Br. J. Pharmacol. 173, 2702–2725 (2016).
de Bodinat, C. et al. Agomelatine, the first melatonergic antidepressant: discovery, characterization and development. Nat. Rev. Drug Discov. 9, 628–642 (2010).
Descamps-François, C. et al. Design and synthesis of naphthalenic dimers as selective MT1 melatoninergic ligands. J. Med. Chem. 46, 1127–1129 (2003).
Spadoni, G. et al. Bivalent ligand approach on N-2-[(3-methoxyphenyl)methylamino]ethylacetamide: synthesis, binding affinity and intrinsic activity for MT1 and MT2 melatonin receptors. Bioorg. Med. Chem. 19, 4910–4916 (2011).
Zlotos, D. P., Riad, N. M., Osman, M. B., Dodda, B. R. & Witt-Enderby, P. A. Novel difluoroacetamide analogues of agomelatine and melatonin: probing the melatonin receptors for MT1 selectivity. MedChemComm 6, 1340–1344 (2015).
Stauch, B. et al. Structural basis of ligand recognition at the human MT1 melatonin receptor. Nature 569, 284–288 (2019).
Johansson, L. C. et al. XFEL structures of the human MT2 melatonin receptor reveal the basis of subtype selectivity. Nature 569, 289–292 (2019).
Lyu, J. et al. Ultra-large library docking for discovering new chemotypes. Nature 566, 224–229 (2019).
Weiss, D. R. et al. Selectivity challenges in docking screens for GPCR targets and antitargets. J. Med. Chem. 61, 6830–6845 (2018).
Manglik, A. et al. Structure-based discovery of opioid analgesics with reduced side effects. Nature 537, 185–190 (2016).
Huang, X. P. et al. Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65. Nature 527, 477–483 (2015).
Lansu, K. et al. In silico design of novel probes for the atypical opioid receptor MRGPRX2. Nat. Chem. Biol. 13, 529–536 (2017).
Sterling, T. & Irwin, J. J. ZINC 15—ligand discovery for everyone. J. Chem. Inf. Model. 55, 2324–2337 (2015).
Coleman, R. G., Carchia, M., Sterling, T., Irwin, J. J. & Shoichet, B. K. Ligand pose and orientational sampling in molecular docking. PLoS ONE 8, e75992 (2013).
Bento, A. P. et al. The ChEMBL bioactivity database: an update. Nucleic Acids Res. 42, D1083–D1090 (2014).
Irwin, J. J. & Shoichet, B. K. Docking screens for novel ligands conferring new biology. J. Med. Chem. 59, 4103–4120 (2016).
Muchmore, S. W. et al. Application of belief theory to similarity data fusion for use in analog searching and lead hopping. J. Chem. Inf. Model. 48, 941–948 (2008).
Katritch, V. et al. Structure-based discovery of novel chemotypes for adenosine A2A receptor antagonists. J. Med. Chem. 53, 1799–1809 (2010).
de Graaf, C. et al. Crystal structure-based virtual screening for fragment-like ligands of the human histamine H1 receptor. J. Med. Chem. 54, 8195–8206 (2011).
Männel, B. et al. Structure-guided screening for functionally selective D2 dopamine receptor ligands from a virtual chemical library. ACS Chem. Biol. 12, 2652–2661 (2017).
Kiss, R. et al. Discovery of novel human histamine H4 receptor ligands by large-scale structure-based virtual screening. J. Med. Chem. 51, 3145–3153 (2008).
Congreve, M. et al. Discovery of 1,2,4-triazine derivatives as adenosine A2A antagonists using structure based drug design. J. Med. Chem. 55, 1898–1903 (2012).
Langmead, C. J. et al. Identification of novel adenosine A2A receptor antagonists by virtual screening. J. Med. Chem. 55, 1904–1909 (2012).
Adamah-Biassi, E. B., Stepien, I., Hudson, R. L. & Dubocovich, M. L. Effects of the melatonin receptor antagonist (MT2)/inverse agonist (MT1) luzindole on re-entrainment of wheel running activity and spontaneous homecage behaviors in C3H/HeN Mice. FASEB J. 26, 1042.5 (2012).
Dubocovich, M. L. Luzindole (N-0774): a novel melatonin receptor antagonist. J. Pharmacol. Exp. Ther. 246, 902–910 (1988).
Browning, C., Beresford, I., Fraser, N. & Giles, H. Pharmacological characterization of human recombinant melatonin mt1 and MT2 receptors. Br. J. Pharmacol. 129, 877–886 (2000).
Dubocovich, M. L., Yun, K., Al-Ghoul, W. M., Benloucif, S. & Masana, M. I. Selective MT2 melatonin receptor antagonists block melatonin-mediated phase advances of circadian rhythms. FASEB J. 12, 1211–1220 (1998).
Benloucif, S. & Dubocovich, M. L. Melatonin and light induce phase shifts of circadian activity rhythms in the C3H/HeN mouse. J. Biol. Rhythms 11, 113–125 (1996).
Burgess, H. J., Revell, V. L., Molina, T. A. & Eastman, C. I. Human phase response curves to three days of daily melatonin: 0.5 mg versus 3.0 mg. J. Clin. Endocrinol. Metab. 95, 3325–3331 (2010).
Rawashdeh, O., Hudson, R. L., Stepien, I. & Dubocovich, M. L. Circadian periods of sensitivity for ramelteon on the onset of running-wheel activity and the peak of suprachiasmatic nucleus neuronal firing rhythms in C3H/HeN mice. Chronobiol. Int. 28, 31–38 (2011).
Van Reeth, O. et al. Comparative effects of a melatonin agonist on the circadian system in mice and Syrian hamsters. Brain Res. 762, 185–194 (1997).
Erşahin, C., Masana, M. I. & Dubocovich, M. L. Constitutively active melatonin MT1 receptors in male rat caudal arteries. Eur. J. Pharmacol. 439, 171–172 (2002).
Soares, J. M. Jr, Masana, M. I., Erşahin, C. & Dubocovich, M. L. Functional melatonin receptors in rat ovaries at various stages of the estrous cycle. J. Pharmacol. Exp. Ther. 306, 694–702 (2003).
Lewy, A. J. et al. The human phase response curve (PRC) to melatonin is about 12 hours out of phase with the PRC to light. Chronobiol. Int. 15, 71–83 (1998).
Gillette, M. U. & Mitchell, J. W. Signaling in the suprachiasmatic nucleus: selectively responsive and integrative. Cell Tissue Res. 309, 99–107 (2002)
Reid, K. J. et al. Familial advanced sleep phase syndrome. Arch. Neurol. 58, 1089–1094 (2001).
Kufareva, I., Gustavsson, M., Zheng, Y., Stephens, B. S. & Handel, T. M. What do structures tell us about chemokine receptor function and antagonism? Annu. Rev. Biophys. 46, 175–198 (2017).
Cooke, R. M., Brown, A. J., Marshall, F. H. & Mason, J. S. Structures of G protein-coupled receptors reveal new opportunities for drug discovery. Drug Discov. Today 20, 1355–1364 (2015).
Lefkowitz, R. J., Mullikin, D. & Caron, M. G. Regulation of β-adrenergic receptors by guanyl-5′-yl imidodiphosphate and other purine nucleotides. J. Biol. Chem. 251, 4686–4692 (1976).
Word, J. M., Lovell, S. C., Richardson, J. S. & Richardson, D. C. Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. J. Mol. Biol. 285, 1735–1747 (1999).
Weiner, S. J. et al. A new force field for molecular mechanical simulation of nucleic acids and proteins. J. Am. Chem. Soc. 106, 765–784 (1984).
Carlsson, J. et al. Structure-based discovery of A2A adenosine receptor ligands. J. Med. Chem. 53, 3748–3755 (2010).
Gallagher, K. & Sharp, K. Electrostatic contributions to heat capacity changes of DNA-ligand binding. Biophys. J. 75, 769–776 (1998).
Mysinger, M. M. & Shoichet, B. K. Rapid context-dependent ligand desolvation in molecular docking. J. Chem. Inf. Model. 50, 1561–1573 (2010).
Southan, C. et al. The IUPHAR/BPS guide to pharmacology in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. Nucleic Acids Res. 44, D1054–D1068 (2016).
Tolmachev, A. et al. Expanding synthesizable space of disubstituted 1,2,4-oxadiazoles. ACS Comb. Sci. 18, 616–624 (2016).
Kroeze, W. K. et al. PRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome. Nat. Struct. Mol. Biol. 22, 362–369 (2015).
Kenakin, T., Watson, C., Muniz-Medina, V., Christopoulos, A. & Novick, S. A simple method for quantifying functional selectivity and agonist bias. ACS Chem. Neurosci. 3, 193–203 (2012).
Kenakin, T. Biased receptor signaling in drug discovery. Pharmacol. Rev. 71, 267–315 (2019).
Longo, P. A., Kavran, J. M., Kim, M. S. & Leahy, D. J. Transient mammalian cell transfection with polyethylenimine (PEI). Methods Enzymol. 529, 227–240 (2013).
Besnard, J. et al. Automated design of ligands to polypharmacological profiles. Nature 492, 215–220 (2012).
Popovska-Gorevski, M., Dubocovich, M. L. & Rajnarayanan, R. V. Carbamate insecticides target human melatonin receptors. Chem. Res. Toxicol. 30, 574–582 (2017).
Cheng, Y.-C. & Prusoff, W. H. Relationship between the inhibition constant (K I) and the concentration of inhibitor which causes 50 per cent inhibition (I 50) of an enzymatic reaction. Biochem. Pharmacol. 22, 3099–3108 (1973).
Sumaya, I. C., Masana, M. I. & Dubocovich, M. L. The antidepressant-like effect of the melatonin receptor ligand luzindole in mice during forced swimming requires expression of MT2 but not MT1 melatonin receptors. J. Pineal Res. 39, 170–177 (2005).
Dubocovich, M. L., Hudson, R. L., Sumaya, I. C., Masana, M. I. & Manna, E. Effect of MT1 melatonin receptor deletion on melatonin-mediated phase shift of circadian rhythms in the C57BL/6 mouse. J. Pineal Res. 39, 113–120 (2005).
Acknowledgements
This study was supported by US NIH awards U24DK1169195 (to B.L.R. and B.K.S.), R35GM122481 (to B.K.S.), the NIMH Psychoactive Drug Screening Contract (to B.L.R.), GM133836 (to J.J.I.), ES023684 (to M.L.D.), UL1TR001412 and KL2TR001413 (to the University at Buffalo), a PhRMA Foundation Fellowship (73309 to A.J.J.), Jacobs School of Medicine and Biomedical Sciences unrestricted funds (to M.L.D.), R35GM127086 (to V.C.), EMBO ALTF 677-2014 (to B.S.), HFSP long-term fellowship LT000046/2014-L (to L.C.J.), a postdoctoral fellowship from the Swedish Research Council (to L.C.J.) and the National Science Foundation (NSF) BioXFEL Science and Technology Center 1231306 (to B.S. and V.C.). We thank G. Wilding from the Biostatistics, Epidemiology and Research Design (BERD) Core of the Clinical and Translational Science Institute at the University at Buffalo for statistical advice regarding analyses of in vivo data.
Author information
Authors and Affiliations
Contributions
B.K.S., B.L.R. and M.L.D. conceived the study. R.M.S. performed the docking and structure-based optimization. J.D.M. and H.J.K. performed the initial binding and functional assays and analyses, assisted by T.C. A.J.J. performed the 2-[I125]iodomelatonin and GTP-perturbation assays. S.S. performed the profiling studies. G.C.G. performed the in vivo mouse pharmacology experiments and all animal husbandry. Y.S.M. and O.S. directed the compound synthesis, purification and characterization experiments. B.S., L.C.J., V.C., B.L.R., X.-P.H. and J.D.M. determined and validated the structures of the MT1 and MT2 receptor types, and made them available before publication. T.K. performed signalling bias calculations. J.J.I. created the ultra-large libraries. B.L.R. supervised the pharmacology studies; B.K.S. supervised the docking and compound optimization; M.L.D. supervised the binding studies and the in vivo circadian rhythm experiments in mice. M.L.D. G.C.G. designed all in vivo experiments. R.M.S., B.K.S., M.L.D., G.C.G., J.D.M., H.J.K. and B.L.R. wrote the paper with contributions from other authors.
Corresponding authors
Ethics declarations
Competing interests
B.K.S. and J.J.I. are founders of a company, BlueDolphin LLC, that works in the area of molecular docking. All other authors declare no competing interests.
Additional information
Peer review information Nature thanks Derk-Jan Dijk, Irina Kufareva and Ieva Sutkeviciute for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Concentration–response curves of the initial 15 compounds in cAMP assays.
a–f, Inhibition of isoproterenol-stimulated cAMP mediated by hMT1 (a, c, e) or hMT2 (b, d, f) in HEK293T cells by melatonin and the 15 initial compounds. Data are normalized to the melatonin response. The 15 initial compounds were split into three graphs for clarity, melatonin response curves are the same across graphs in a, c, e and b, d, f. Data are mean ± s.e.m. of four biologically independent experiments (n = 4) run in triplicate, unless otherwise indicated, in which case the number of biologically independent experiments is indicated in parentheses next to the compound name.
Extended Data Fig. 2 Concentration–response curves of notable analogues based on initial hits in cAMP assays.
a–f, Inhibition of isoproterenol-stimulated cAMP mediated by hMT1 (a, c, e) or hMT2 (b, d, f) in HEK293T cells by melatonin and select analogues. Data are normalized to the melatonin response. The compounds were split into three graphs for clarity, melatonin response curves are the same across graphs in a, c, e and b, d, f. Data are mean ± s.e.m. of four biologically independent experiments (n = 4) run in triplicate, unless otherwise indicated, in which case the number of biologically independent experiments is indicated in parentheses next to the compound name.
Extended Data Fig. 3 Small changes in the ligand structure have large effects on the activity and selectivity of the melatonin receptor.
a, Docked pose of ZINC151209032, an MT1-selective direct-docking hit. b, Docked pose of ZINC497291360, a close analogue of ZINC151209032 that has twofold selectivity for MT2 over MT1. c, Docked pose of ZINC151192780, an analogue for which the MT2 selectivity increases to 89-fold over MT1. d, Docked pose of ZINC485552623, which adds a bulkier 2-chloro-3-methylthiophene into a proposed MT2-selective hydrophobic cleft, resulting in a fully MT2-selective agonist without detectable MT1 activity. All docked poses are overlaid onto the crystallographic pose of 2-phenylmelatonin in transparent blue. e, Concentration–response curves of the four analogues binding to MT1 and MT2. Data are normalized to the melatonin response and are mean ± s.e.m. of four biologically independent experiments (n = 4) run in triplicate. f, Bias plots of ZINC482850041 and ZINC608506688 relative to melatonin signalling. Mean values (Supplementary Table 3) are presented as solid lines and the shading indicates the 95% confidence interval. Data in f are normalized to the melatonin response and represent mean ± s.e.m. of three biologically independent experiments (n = 3) run in triplicate, except for ZINC608506688 for Gi activation (n = 4).
Extended Data Fig. 4 MT1-selective inverse agonists decelerate the re-entrainment rate in vivo via MT1 receptors.
Data are an extension of Fig. 3a–c. a–e, Representative actograms of running wheel activity in wild-type (WT) C3H/HeN mice treated with vehicle (VEH) (a), 30 μg melatonin (MLT) per mouse (b), UCSF7447 (‘7447) (c), UCSF3384 (‘3384) (d) or 300 μg luzindole (LUZ) per mouse (e) immediately before the new dark onset (black dots) after an abrupt advance in the dark onset of 6 h in a 12:12 light:dark cycle (grey, dark phase; white, light phase). Compounds were administered once a day for 3 days (see Methods for additional details). f–k, Representative actograms of running wheel activity for C3H/HeN mice treated with vehicle (wild-type (f), MT1KO (h), MT2KO (j)) or inverse agonist UCSF7447 (wild-type (g), MT1KO (i), MT2KO (k)) after a 6-h advance in dark onset. Mice were kept on a 12:12 light:dark cycle. UCSF7447 (30 μg per mouse) was administered for three consecutive days immediately before the new dark onset (black dots). l, The inverse agonist UCSF3384 decelerates the rate of re-entrainment of the rhythm of running wheel activity onset in C3H/HeN wild-type mice. Data are expressed in hours advanced each day for wild-type mice treated with vehicle or UCSF3384 (two-way repeated-measures ANOVA; treatment × time interaction: F16,647 = 1.99, P = 0.0122). m, The inverse agonist UCSF7447 does not modulate the rate of re-entrainment of the onset of a running wheel activity rhythm in C3H/HeN MT1KO mice. Data are expressed in hours advanced each day for MT1KO mice treated with vehicle or UCSF7447 (mixed-effect two-way repeated-measures ANOVA; treatment × time interaction: F16,474 = 1.44, P = 0.117). n, The inverse agonist UCSF7447 decelerates the rate of re-entrainment of the onset of a running wheel activity rhythm in C3H/HeN MT2KO mice. Data are expressed in hours advanced each day for MT2KO mice treated with vehicle or UCSF7447 (mixed-effect two-way repeated-measures ANOVA; treatment × time interaction: F16,683 = 2.57, P = 0.000686). Data are mean + s.e.m. *P < 0.05, **P < 0.01; multiple comparisons were corrected using Tukey’s post-test (P < 0.05). The dotted line in l–n indicates the new dark onset. Additional details of all statistical analyses as well as n numbers for each condition can be found in the Methods, ‘Statistics and reproducibility’. All treatments were given as a subcutaneous injection.
Extended Data Fig. 5 MT1-selective inverse agonists induce a phase advance in circadian activity at CT 10 that is mediated by MT1 in vivo.
Data are an extension of Fig. 3d–f. a–e, Representative actograms of running wheel activity from individual C3H/HeN wild-type mice kept in constant dark (grey bars) treated with vehicle (a), melatonin (b), UCSF7447 (c), UCSF3384 (d) or luzindole (e). All treatments were 30 μg per mouse except for luzindole, which was 300 μg per mouse as described in the Methods. Mice were treated at dusk (CT 10; 2 h before the onset of running wheel activity) for three consecutive days (black dots). Red lines indicate the best-fit line of pre-treatment onsets and blue lines indicate the best-fit line of post-treatment onsets, which were both used for phase shift determinations (see Methods for more details). The corresponding quantification can be found in Fig. 3d. f–h, Representative actograms of running wheel activity from individual C3H/HeN wild-type mice kept in the constant dark treated with vehicle (f), melatonin (g) or UCSF7447 (h; all treatments were 0.9 μg per mouse) at CT 10. The corresponding quantification can be found in Fig. 3d. i–k, Representative actograms of running wheel activity from individual C3H/HeN wild-type mice kept in the constant dark treated with melatonin (i) at CT 2 (10 h before the onset of running wheel activity) or vehicle (j) compared with UCSF7447 (k; all treatments were 30 μg per mouse) at CT 6 (6 h before the onset of running wheel activity). The corresponding quantification can be found in Extended Data Fig. 7. l–q, Representative actograms of running wheel activity from individual C3H/HeN wild-type (l, m), MT1KO (n, o) and MT2KO (p, q) mice kept in constant dark treated with vehicle (white; l, n, p) or UCSF7447(blue; m, o, q; 30 μg per mouse) at CT 10. The corresponding quantification can be found in Fig. 3e. r–w, Representative actograms of running wheel activity from individual C3H/HeN wild-type (r, s), MT1KO (t, u) and MT2KO (v, w) mice kept in constant dark treated with vehicle (white; r, t, v) or UCSF7447(blue; s, u, w; 30 μg per mouse) at CT 2. The corresponding quantification can be found in Fig. 3f. All treatments were given by subcutaneous injection.
Extended Data Fig. 6 Concentration–response curves and Schild plots of the inverse agonists UCSF7447 and UCSF3384 in cAMP assays.
a, b, d, e, Modulation of hMT1-mediated (a, d) or hMT2-mediated (b, e) inhibition of isoproterenol-stimulated cAMP in HEK293T cells by melatonin in the presence of UCSF7447 (a, b) or UCSF3384 (d, e) for a range of concentrations. Data are normalized to the effect of isoproterenol alone and are mean ± s.e.m. of three biologically independent experiments (n = 3) run in triplicate. c, f, Schild plots depicting the competitive antagonism of melatonin by UCSF7447 (c) and UCSF3384 (f). Schild analysis of hMT1 (purple) and hMT2 (teal) show the competitive antagonism of UCSF7447 (hMT1, pKB = 7.4 ± 0.1, slope = 0.98 ± 0.03; hMT2, pKB = 6.2 ± 0.1, slope = 1.3 ± 0.4) (c) and UCSF3384 (hMT1, pA2 = 7.9 ± 0.1, slope = 0.80 ± 0.04; hMT2 pKB = 6.7 ± 0.1, slope = 1.0 ± 0.1) (f). Data are mean ± s.e.m. of three biologically independent experiments (n = 3) run in triplicate.
Extended Data Fig. 7 Differential phase shift profile for the inverse agonist UCSF7447 compared to the agonist melatonin and a prototype antagonist (luzindole) across the circadian cycle.
a–c, C3H/HeN mice were kept in constant dark and treated with vehicle, melatonin, luzindole or UCSF7447 (all treatments were 30 μg per mouse except for luzindole, which was 300 μg per mouse, subcutaneously). Mice were treated at CT 2, 6 or 10 (10, 6 or 2 h before the onset of running wheel activity) for three consecutive days (Methods). a, CT 2 phase shift data were compared using one-way ANOVA (F3,11 = 28.16, P = 1.85 × 10−5). b, CT 6 phase shift data were compared using one-way ANOVA (F3,26 = 0.61, P = 0.61). c, CT 10 phase shift data were compared using one-way ANOVA (F3,17 = 35.13, P = 1.66 × 10−7). All multiple comparisons were made compared with vehicle using a Dunnet’s post hoc test (P < 0.05). Values for melatonin and UCSF7447 at CT 10 were pooled from previous data for comparison to luzindole. Data are mean ± s.e.m. ****P < 0.0001 for comparisons with vehicle. All treatments were given by subcutaneous injection.
Supplementary information
Supplementary Information
This file contains Supplementary Tables 2-5 and Supplementary Data 2-7.
Supplementary Table 1
All Molecules tested against MT1/MT2 | Excel file containing all molecules that were tested against the melatonin receptors organized by cluster with DOCK scores, closest known melatonin receptor ligands by ECFP4 Tanimoto coefficient, affinities at both receptors, and any close patented molecules.
Source Data
This file contains source Data for Supplementary Data 3.
Source Data
This file contains source Data for Supplementary Data 4.
Rights and permissions
About this article
Cite this article
Stein, R.M., Kang, H.J., McCorvy, J.D. et al. Virtual discovery of melatonin receptor ligands to modulate circadian rhythms. Nature 579, 609–614 (2020). https://doi.org/10.1038/s41586-020-2027-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-020-2027-0
This article is cited by
-
Molecular mechanism of antihistamines recognition and regulation of the histamine H1 receptor
Nature Communications (2024)
-
Computational drug development for membrane protein targets
Nature Biotechnology (2024)
-
Cardiac-targeted delivery of nuclear receptor RORα via ultrasound targeted microbubble destruction optimizes the benefits of regular dose of melatonin on sepsis-induced cardiomyopathy
Biomaterials Research (2023)
-
Modeling the expansion of virtual screening libraries
Nature Chemical Biology (2023)
-
Computational approaches streamlining drug discovery
Nature (2023)
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.