Molecular modelling studies on the ORL1-receptor and ORL1-agonists
The ORL1 (opioid receptor like 1)- receptor is a member of the family of rhodopsin-like G protein-coupled receptors (GPCR) and represents an interesting new therapeutical target since it is involved in a variety of biomedical important processes, such as anxiety, nociception, feeding, and memory. In order to shed light on the molecular basis of the interactions of the GPCR with its ligands, the receptor protein and a dataset of specific agonists were examined using molecular modelling methods. For that purpose, the conformational space of a very potent non-peptide ORL1-receptor agonist (Ro 64-6198) with a small number of rotatable bonds was analysed in order to derive a pharmacophoric arrangement. The conformational analyses yielded a conformation that served as template for the superposition of a set of related analogues. Structural superposition was achieved by employing the program FlexS. Using the experimental binding data and the superposition of the ligands, a 3D-QSAR analysis applying the GRID/GOLPE method was carried out. After the ligand-based modelling approach, a 3D model of the ORL1-receptor has been constructed using homology modelling methods based on the crystal structure of bovine rhodopsin. A representative structure of the model taken from molecular dynamics simulations was used for a manual docking procedure. Asp-130 and Thr-305 within the ORL1-receptor model served as important hydrophilic interaction partners. Furthermore, a hydrophobic cavity was identified stabilizing the agonists within their binding site. The manual docking results were supported using FlexX, which identified the same protein-ligand interaction points.
Unable to display preview. Download preview PDF.
- 2.Ronzoni, S., Peretto, I. and Giardina, G., Exp. Opin. Ther. Patents, 11 (2001) 525.Google Scholar
- 4.Meunier, J.C., Exp. Opin. Ther. Patents, 10 (2000) 371.Google Scholar
- 9.Weiner, S. J., Kollman, P.A., Case, D.A., Singh, U.C., Ghio, C., Alagona, G., Profeta, S. and Weiner, P.J., J. Am. Chem. Soc., 106 (1984) 765.Google Scholar
- 12.GRID, Version 20, Molecular Discovery Ltd., Oxford, UK.Google Scholar
- 13.GOLPE 4.5. Multivariate Infometric Analysis Srl., Perugia, Italy, 1999.Google Scholar
- 16.Baroni, M., Constantino, G., Cruciani, G., Riganelli, D, Va-ligli, R. and Clementi, S., Quant. Struct.-Act. Relat., 12 (1993) 9.Google Scholar
- 19.Höltje, H.-D., Sippl, W., Rognan, D. and Folkers, G., Molecu-lar Modeling: Basic Principles and Applications, 2nd edition, Wiley-VCH Verlagsgesellschaft, Weinheim, Germany, 2003.Google Scholar
- 20.Palczewski, K., Kumasaka, T., Hori, T., Behnke, C.A., Mo-toshima, H., Fox, B.A., Le Trong, I., Teller, D.C., Okada, T., Stenkamp, R.E., Yamamoto, M. and Miyano, M., Science, 289 (2000) 739.Google Scholar
- 21.Insight II 2000, Accelrys Inc., San Diego, CA.Google Scholar
- 27.PROCHECK: Laskowski, R.A., MacArthur, M.W., Moss, D.S. and Thornton, J.M., J. Appl. Crystallogr., 26 (1993) 283.Google Scholar
- 33.Thomsen, C. and Hohlweg, R., Br. J. Pharmacol., 131 (2000)Google Scholar
- 34.Kolczewski, S., Adam, G., Cesura, A.M., Jenck, F., Hennig, M., Oberhauser, T., Poli, S.M., Rössler, F., Röver, S., Wich-mann, J. and Dautzenberg, F.M., J. Med. Chem., 46 (2003)Google Scholar