This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This request for a Development Allocation (DAC) of 30,000 SUs on TeraGrid platforms is based on a NIH supported research project (R01 DA020032;PI: Dr. Marta Filizola). The goal of this project is to identify the molecular determinants responsible for the oligomerization of delta- and mu-opioid receptors (both homo- and heteromers) in a structural context of receptor models, using an iterative combined computational and experimental approach. This request for resources will specifically be used to obtain new refined molecular models of inactive delta- and mu-opioid receptor monomers, which will serve as a basis for the construction of dimers or higher-order oligomers of these receptors. The recent publication of the crystal structure of beta2-adrenergic receptor(Cherezov et al., 2007), and its higher sequence homology with opioid receptors compared to rhodopsin, prompted us to re-build three-dimensional models of the transmembrane (TM) regions of delta- and mu-opioid receptors using beta2-adrenergic as a structural template. We will now use these new TM models to add optimal extra- and intra-cellular loop regions using an ab-initio approach that was originally developed in the lab of Dr. Ernest Mehler at Weill Medical College of Cornell University, and is currently being optimized in a collaborative effort by the Mehler and Filizola labs. Briefly, this method employs simulated annealing Monte Carlo (MC) simulations carried out on the loop segment starting from a completely extended structure, combined with a biased scaled collective variables (SCV) Monte Carlo technique especially designed to complete the closure of the segment. Since an accurate force field for the study of peptide and protein conformational preferences must account for the hydrophobic and electrostatic effects of the solvent, the method uses a validated continuum electrostatic model based on screened Coulomb potentials, which has extensively been validated for small molecules as well as proteins (Hassan et al., 2000a;Hassan et al., 2000b;Hassan and Mehler, 2002). Alhough the MC-SCV-MC approach has been shown to predict reliably the conformations of loop regions of GPCRs (Kortagere et al., 2006;Mehler et al., 2006), like other ab initio loop prediction methods, its performance deteriorates with increasing loop lengths (more than 10 residues). Thus, to improve structural characterization of long loops of GPCRs, we have recently been studying modeling approaches that combine two or more of the currently available ab initio loop prediction methods with the MC-SCV-MC protocol (Bandhyopadhyay et al., 2008). Our results show that the integrated use of a side-chain prediction strategy based on rotamer libraries (SCAP (Xiang and Honig, 2001)) into the standard MC-SCV-MC protocol considerably improves loop structure predictions obtained by MC-SCV-MC alone or other fairly reliable and fast loop prediction algorithms for globular proteins (e.g., LOOPY (Jacobson et al., 2004), MODLOOP (Fiser and Sali, 2003), etc.). Thus, we will apply our modified MC-SCV-MC protocol to predict loops of the delta- and mu-opioid receptors. The resulting conformations will then be used to: 1) build agonist-bound models of the opioid receptors through the application of a state-of-the-art knowledge-based distance constraint approach that we recently tested on rhodopsin (Niv et al., 2006);and 2) run long-scale molecular dynamics simulations of inactive and agonist-bound opioid receptors in an explicit lipid-water environment. Simulations will be performed with GROMACS (Van Der Spoel et al., 2005) using the protocol we recently tested on a rhodopsin monomer and dimer (Filizola et al., 2006). These studies will help us achieve a more complete representation of the opioid receptor function by identifying quantitatively the intermolecular mode of receptor activation, and adding it to current models of ligand-binding and signal transduction. REFERENCES Bandhyopadhyay, D., Bortolato, A., Filizola, M., and Mehler, E. L.: Improving Prediction of G-Protein Coupled Receptor Loops. 52nd Annual Meeting of the Biophysical Society and 16th IUPAB International Biophysics Congress (Long Beach, CA), 2008. Cherezov, V., Rosenbaum, D. M., Hanson, M. A., Rasmussen, S. G., Thian, F. S., Kobilka, T. S., Choi, H. J., Kuhn, P., Weis, W. I., Kobilka, B. K., and Stevens, R. C.: High-resolution crystal structure of an engineered human beta2-adrenergic G protein-coupled receptor. Science 318 (5854): 1258-65, 2007. Filizola, M., Wang, S. X., and Weinstein, H.: Dynamic models of G-protein coupled receptor dimers: indications of asymmetry in the rhodopsin dimer from molecular dynamics simulations in a POPC bilayer. J Comput Aided Mol Des 20 (7-8): 405-16, 2006. Fiser, A., and Sali, A.: ModLoop: automated modeling of loops in protein structures. Bioinformatics 19 (18): 2500-1, 2003. Hassan, S., Guarnieri, F., and Mehler, E.: Characterization of Hydrogen Bonding in a Continuum Solvent Model. . J. Phys. Chem. 104: 6490, 2000a. Hassan, S., Guarnieri, F., and Mehler, E.: A General Treatment for Solvent Effects Based on Screened Coulomb Potentials. . J. Phys. Chem. 104: 6478, 2000b. Hassan, S. A., and Mehler, E. L.: A critical analysis of continuum electrostatics: the screened Coulomb potential--implicit solvent model and the study of the alanine dipeptide and discrimination of misfolded structures of proteins. Proteins 47 (1): 45-61, 2002. Jacobson, M. P., Pincus, D. L., Rapp, C. S., Day, T. J., Honig, B., Shaw, D. E., and Friesner, R. A.: A hierarchical approach to all-atom protein loop prediction. Proteins 55 (2): 351-67, 2004. Kortagere, S., Roy, A., and Mehler, E. L.: Ab initio computational modeling of long loops in G-protein coupled receptors. J Comput Aided Mol Des 20 (7-8): 427-36, 2006. Mehler, E. L., Hassan, S. A., Kortagere, S., and Weinstein, H.: Ab initio computational modeling of loops in G-protein-coupled receptors: lessons from the crystal structure of rhodopsin. Proteins 64 (3): 673-90, 2006. Niv, M. Y., Skrabanek, L., Filizola, M., and Weinstein, H.: Modeling activated states of GPCRs: the rhodopsin template. J Comput Aided Mol Des 20 (7-8): 437-48, 2006. Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., and Berendsen, H. J.: GROMACS: fast, flexible, and free. J Comput Chem 26 (16): 1701-18, 2005. Xiang, Z., and Honig, B.: Extending the accuracy limits of prediction for side-chain conformations. J Mol Biol 311 (2): 421-30, 2001.
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