Journal of Computer-Aided Molecular Design

, Volume 32, Issue 2, pp 385–400 | Cite as

“In silico” study of the binding of two novel antagonists to the nociceptin receptor

Article
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Abstract

Antagonists of the nociceptin receptor (NOP) are raising interest for their possible clinical use as antidepressant drugs. Recently, the structure of NOP in complex with some piperidine-based antagonists has been revealed by X-ray crystallography. In this study, a multi-flexible docking (MF-docking) procedure, i.e. docking to multiple receptor conformations extracted by preliminary molecular dynamics trajectories, together with hybrid quantum mechanics/molecular mechanics (QM/MM) simulations have been carried out to provide the binding mode of two novel NOP antagonists, one of them selective (BTRX-246040, formerly named LY-2940094) and one non selective (AT-076), i.e. able to inactivate NOP as well as the classical µ- k- and δ-opioid receptors (MOP KOP and DOP). According to our results, the pivotal role of residue D1303,32 (upper indexes are Ballesteros–Weinstein notations) is analogous to that enlighten by the already known X-ray structures of opioid receptors: binding of the molecules are predicted to require a slight readjustment of the hydrophobic pocket (residues Y1313,33, M1343,36, I2195,43, Q2806,52 and V2836,55) in the orthosteric site of NOP, accommodating either the pyridine–pyrazole (BTRX-246040) or the isoquinoline (AT-076) moiety of the ligand, in turn allowing the protonated piperidine nitrogen to maximize interaction (salt-bridge) with residue D1303,32 of the NOP, and the aromatic head to be sandwiched in optimal π-stacking between Y1313,33 and M1343,36. The QM/MM optimization after the MF-docking procedure has provided the more likely conformations for the binding to the NOP receptor of BTRX-246040 and AT-076, based on different pharmacophores and exhibiting different selectivity profiles. While the high selectivity for NOP of BTRX-246040 can be explained by interactions with NOP specific residues, the lack of selectivity of AT-076 could be associated to its ability to penetrate into the deep hydrophobic pocket of NOP, while retaining a conformation very similar to the one assumed by the antagonist JDTic into the K-opioid receptor. The proposed binding geometries fit better the binding pocket environment providing clues for experimental studies aimed to design selective or multifunctional opioid drugs.

Keywords

BTRX-246040 LY2940094 AT-076 Molecular dynamics Docking QM/MM GPCR Opioid receptor Antidepressant drugs NOPR antagonists OPRX N/OFQ 

Notes

Acknowledgements

This work was supported by Italian Ministry of University and Research (LINEA D1 Università Cattolica del Sacro Cuore) and by the CINECA supercomputing centers through the grants isC39 and isC48 (n. HP10CIU3D6 and HP10CXDJYH).

Author contributions

The manuscript was written through contributions of all the authors. All the authors have approved the final version of the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare no competing financial interest.

Supplementary material

10822_2017_95_MOESM1_ESM.pdf (2.5 mb)
Supplementary material 1 (PDF 2567 KB)

References

  1. 1.
    Lambert DG (2008) The nociceptin/orphanin receptor: a target with broad therapeutic potential. Nature Rev Drug Discov 7:694–710CrossRefGoogle Scholar
  2. 2.
    Chiou LC, Liao YY, Fan PC, Kuo PH, Wang CH, Riemer C, Prinssen EP (2007) Nociceptin/orphanin FQ peptide receptors: pharmacology and clinical implications. Curr Drug Targets 8:117–135CrossRefGoogle Scholar
  3. 3.
    Mogil JS, Pasternak GW (2001) The molecular and behavioral pharmacology of the orphanin FQ/nociceptin peptide and receptor family. Pharmacol Rev 53:381–415Google Scholar
  4. 4.
    Meunier JC, Mollereau C, Toll L, Suaudeau C, Moisand C, Alvinerie P, Butour JL, Guillemot JC, Ferrara P, Monsarrat B et al (1995) Isolation and structure of the endogenous agonist of opioid receptor-like ORL1 receptor. Nature 377:532–535CrossRefGoogle Scholar
  5. 5.
    Reinscheid RK, Nothacker HP, Bourson A, Ardati A, Henningsen RA, Bunzow JR, Grandy DK, Langen H, Monsma FJ Jr, Civelli O (1995) Orphanin FQ: a neuropeptide that activates an opioidlike G protein-coupled receptor. Science 270:792–794CrossRefGoogle Scholar
  6. 6.
    Gavioli EC, Calo G (2013) Nociceptin/orphanin FQ receptor antagonists as innovative antidepressant drugs. Pharmacol Ther 140:10–25CrossRefGoogle Scholar
  7. 7.
    Thompson AA, Liu W, Chun E, Katritch V, Wu H, Vardy E, Huang XP, Trapella C, Guerrini R, Calo G, Roth BL, Cherezov V, Stevens RC (2012) Structure of the nociceptin/orphanin FQ receptor in complex with a peptide mimetic. Nature 485:395–399CrossRefGoogle Scholar
  8. 8.
    Miller RL, Thompson AA, Trapella C, Guerrini R, Malfacini D, Patel N, Han GW, Cherezov V, Calo G, Katritch V, Stevens RC (2015) The importance of ligand-receptor conformational pairs in stabilization: spotlight on the N/OFQ G protein-coupled receptor. Structure 23:2291–2299CrossRefGoogle Scholar
  9. 9.
    Ballesteros J, Weinstein H (1995) Integrated methods for the construction of three dimensional models and computational probing of structure function relations in G protein-coupled receptors. Academic Press, San DiegoCrossRefGoogle Scholar
  10. 10.
    Mustazza C, Bastanzio G (2011) Development of nociceptin receptor (NOP) agonists and antagonists. Med Res Rev 31:605–648CrossRefGoogle Scholar
  11. 11.
    Filizola M, Devi LA (2012) How opioid drugs bind to receptors. Nature 485:314–317CrossRefGoogle Scholar
  12. 12.
    Trapella C, Fischetti C, Pela M, Lazzari I, Guerrini R, Calo G, Rizzi A, Camarda V, Lambert DG, McDonald J, Regoli D, Salvadori S (2009) Structure-activity studies on the nociceptin/orphanin FQ receptor antagonist 1-benzyl-N-{3-[spiroisobenzofuran-1(3H),4′-piperidin-1-yl]propyl} pyrrolidine-2-carboxamide. Bioorg Med Chem 17:5080–5095CrossRefGoogle Scholar
  13. 13.
    Meng F, Ueda Y, Hoversten MT, Taylor LP, Reinscheid RK, Monsma FJ, Watson SJ, Civelli O, Akil H (1998) Creating a functional opioid alkaloid binding site in the orphanin FQ receptor through site-directed mutagenesis. Mol Pharmacol 53:772–777CrossRefGoogle Scholar
  14. 14.
    Totrov M, Abagyan R (2008) Flexible ligand docking to multiple receptor conformations: a practical alternative. Curr Opin Struct Biol 18:178–184CrossRefGoogle Scholar
  15. 15.
    Pagadala NS, Syed K, Tuszynski J (2017) Software for molecular docking: a review. Biophys Rev 9:91–102CrossRefGoogle Scholar
  16. 16.
    Toledo MA, Pedregal C, Lafuente C, Diaz N, Martinez-Grau MA, Jimenez A, Benito A, Torrado A, Mateos C, Joshi EM, Kahl SD, Rash KS, Mudra DR, Barth VN, Shaw DB, McKinzie D, Witkin JM, Statnick MA (2014) Discovery of a novel series of orally active nociceptin/orphanin FQ (NOP) receptor antagonists based on a dihydrospiro(piperidine-4,7′-thieno[2,3-c]pyran) scaffold. J Med Chem 57:3418–3429CrossRefGoogle Scholar
  17. 17.
    Statnick MA, Chen Y, Ansonoff M, Witkin JM, Rorick-Kehn L, Suter TM, Song M, Hu C, Lafuente C, Jimenez A, Benito A, Diaz N, Martinez-Grau MA, Toledo MA, Pintar JE (2016) A novel nociceptin receptor antagonist LY2940094 inhibits excessive feeding behavior in rodents: a possible mechanism for the treatment of binge eating disorder. J Pharmacol Exp Ther 356:493–502CrossRefGoogle Scholar
  18. 18.
    Witkin JM, Rorick-Kehn LM, Benvenga MJ, Adams BL, Gleason SD, Knitowski KM, Li X, Chaney S, Falcone JF, Smith JW, Foss J, Lloyd K, Catlow JT, McKinzie DL, Svensson KA, Barth VN, Toledo MA, Diaz N, Lafuente C, Jimenez A, Benito A, Pedregal C, Martinez-Grau MA, Post A, Ansonoff MA, Pintar JE, Statnick MA (2016) Preclinical findings predicting efficacy and side-effect profile of LY2940094, an antagonist of nociceptin receptors. Pharmacol Res Perspect 4:e00275CrossRefGoogle Scholar
  19. 19.
    Zaveri NT, Journigan VB, Polgar WE (2015) Discovery of the first small-molecule opioid pan antagonist with nanomolar affinity at mu, delta, kappa, and nociceptin opioid receptors. ACS Chem Neurosci 6:646–657CrossRefGoogle Scholar
  20. 20.
    Della Longa S, Arcovito A (2016) A dynamic picture of the early events in nociceptin binding to the NOP receptor by metadynamics. Biophys J 111:1203–1213CrossRefGoogle Scholar
  21. 21.
    Wu H, Wacker D, Mileni M, Katritch V, Han GW, Vardy E, Liu W, Thompson AA, Huang XP, Carroll FI, Mascarella SW, Westkaemper RB, Mosier PD, Roth BL, Cherezov V, Stevens RC (2012) Structure of the human kappa-opioid receptor in complex with JDTic. Nature 485:327–332CrossRefGoogle Scholar
  22. 22.
    Xu Z, Yang Z, Liu Y, Lu Y, Chen K, Zhu W (2014) Halogen bond: its role beyond drug-target binding affinity for drug discovery and development. J Chem Inf Model 54:69–78CrossRefGoogle Scholar
  23. 23.
    Biswas B, Mondal S, Singh PC (2017) Combined molecular dynamics, atoms in molecules, and IR studies of the bulk monofluoroethanol and bulk ethanol to understand the role of organic fluorine in the hydrogen bond network. J Phys Chem A 121:1250–1260CrossRefGoogle Scholar
  24. 24.
    Hernandes MZ, Cavalcanti SM, Moreira DR, de Azevedo Junior WF, Leite AC (2010) Halogen atoms in the modern medicinal chemistry: hints for the drug design. Curr Drug Targets 11:303–314CrossRefGoogle Scholar
  25. 25.
    Goto Y, Arai-Otsuki S, Tachibana Y, Ichikawa D, Ozaki S, Takahashi H, Iwasawa Y, Okamoto O, Okuda S, Ohta H, Sagara T (2006) Identification of a novel spiropiperidine opioid receptor-like 1 antagonist class by a focused library approach featuring 3D-pharmacophore similarity. J Med Chem 49:847–849CrossRefGoogle Scholar
  26. 26.
    Zimmerman DM, Leander JD, Cantrell BE, Reel JK, Snoddy J, Mendelsohn LG, Johnson BG, Mitch CH (1993) Structure-activity-relationships of trans-3,4-dimethyl-4-(3-hydroxyphenyl)piperidine antagonists for mu-opioid and kappa-opioid receptors. J Med Chem 36:2833–2841CrossRefGoogle Scholar
  27. 27.
    Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612CrossRefGoogle Scholar
  28. 28.
    Klamt A, Schuurmann G (1993) COSMO: a new approach to dielectric screening in solvents with explicit expression for the screening energy and its gradient. J Chem Soc Perkin Trans 2:799–805CrossRefGoogle Scholar
  29. 29.
    Breneman CM, Wiberg KB (1990) Determining atom-centered monopoles from molecular electrostatic potentials. The need for high sampling density in formamide conformational analysis. J Comput Chem 11:361–373CrossRefGoogle Scholar
  30. 30.
    Neese F (2009) ORCA: an ab-initio, DFT, and semiempirical electronic structure package. University of Bonn, BonnGoogle Scholar
  31. 31.
    Berendsen HJC, van der Spoel D, van Drunen R (1995) GROMACS: a message-passing parallel molecular dynamics implementation. Comput Phys Commun 91:43–56CrossRefGoogle Scholar
  32. 32.
    Hess B, Kutzner C, Lindhal E (2008) GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4:435–447CrossRefGoogle Scholar
  33. 33.
    Hornak V (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins 65:712–725CrossRefGoogle Scholar
  34. 34.
    Kothandan G, Gadhe CG, Balupuri A, Ganapathy J, Cho SJ (2014) The nociceptin receptor (NOPR) and its interaction with clinically important agonist molecules: a membrane molecular dynamics simulation study. Mol Biosyst 10:3188–3198CrossRefGoogle Scholar
  35. 35.
    Tribello GA, Bonomi M, Branduardi D, Camilloni C, Bussi G (2014) Plumed 2.0: new feathers for an old bird. Comput Phys Commun 185:604–613CrossRefGoogle Scholar
  36. 36.
    Nosé S (1984) A unified formulation of the constant temperature molecular-dynamics methods. J Chem Phys 81:511–519CrossRefGoogle Scholar
  37. 37.
    Hoover WG (1985) Canonical dynamics: equilibrium phase-space distributions. Phys Rev A 31:1695–1697CrossRefGoogle Scholar
  38. 38.
    Parrinello M, Rahman A (1981) Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys 52:7182–7190CrossRefGoogle Scholar
  39. 39.
    Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461Google Scholar
  40. 40.
    Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791CrossRefGoogle Scholar
  41. 41.
    Gasteiger J, Marsili M (1980) Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges. Tetrahedron 36:3219–3228CrossRefGoogle Scholar
  42. 42.
    Maseras F, Morokuma K (1995) IMOMM—a new integrated ab-initio plus molecular mechanics geometry optimization scheme of equilibrium structures and transition-states. J Comput Chem 16:1170–1179CrossRefGoogle Scholar
  43. 43.
    Svensson M, Humbel S, Froese RDJ, Matsubara T, Sieber S, Morokuma K (1996) ONIOM: a multilayered integrated MO + MM method for geometry optimizations and single point energy predictions. A test for Diels–Alder reactions and Pt(P(t-Bu)3)2 + H2 oxidative addition. J Phys Chem 100:19357–19363CrossRefGoogle Scholar
  44. 44.
    Nashev LG, Vuorinen A, Praxmarer L, Chantong B, Cereghetti D, Winiger R, Schuster D, Odermatt A (2012) Virtual screening as a strategy for the identification of xenobiotics disrupting corticosteroid action. PLoS ONE 7:e46958CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Life, Health and Environmental SciencesUniversity of L’AquilaL’AquilaItaly
  2. 2.Institute of Biochemistry and Clinical BiochemistryCatholic University of Sacred HeartRomeItaly

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