IMPROVING PREDICTION OF G-PROTEIN COUPLED RECEPTOR LOOPS

Carnegie-Mellon University, Pittsburgh PA

Investigators

Linked publications & trials

Abstract

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. I am a postdoc working at Marta Filizola's Lab at the Department of Structural and Chemical Biology of Mount Sinai School of Medicine, New York. This request for a Development Allocation (DAC) of 30,000 SUs on TeraGrid platforms is based on a research project that has as a goal to improve structural prediction of intra- and extra-cellular loop regions of G-protein coupled receptors (GPCRs). Loop regions in GPCRs exhibit low sequence identity and variable length due to insertions and deletions. Thus homology modeling with the loops of rhodopsin or beta2 adrenergic receptor, the only GPCRs of known structure, is not feasible. Because of the importance of GPCR loops in signal transduction, de novo/ab initio strategies are being developed. Notably, Monte Carlo (MC) simulations in a temperature annealing protocol combined with a scaled collective variables (SCV) technique (Kortagere et al., 2006;Mehler et al., 2006) and coarse-grained backbone dihedral sampling (Nikiforovich and Marshall, 2005), were recently shown to accurately predict short loop regions of GPCRs. Like other ab initio loop prediction methods, however, the performance of these methods clearly deteriorates at increasing loop lengths (more than 10 residues). The reasons for this deterioration include: a) the difficulty in carrying out sufficiently complete searches of the very high dimensionality of the conformation spaces, b) the inherent flexibility of loop regions and, c) insufficiently accurate force fields. As a result, the lowest free energy ensemble represents the native ensemble less well as indicated by larger root mean square deviations from the native loop structure. To improve structural characterization of GPCR loops, we will compare predictions of the three intracellular and three extracellular loops of rhodopsin and beta2 adrenergic receptor crystal structures derived from application of fairly reliable and fast loop-prediction algorithms for globular proteins (e.g., PLOP (Jacobson et al., 2004), MODLOOP (Fiser and Sali, 2003), LOOPY (Xiang et al., 2002) etc.) with those obtained by the MC-SCV method (Kortagere et al., 2006;Mehler et al., 2006). This ab-initio approach consists of a two-step procedure that only requires knowledge of the structure (experimental or model) of the domains to be connected. Briefly, the method employs simulated annealing Monte Carlo (SA-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 (SCV-MC) especially designed to complete the closure of the segment. SA-MC simulations are carried out to find conformations that are representative of the segment structure in solution, as encoded in the primary sequence. The segment is then forced to fit the final protein conformation using an adjustable force constant scheme and MC simulations with a scaled collective variables technique. The scaled collective variables technique allows the MC simulation to improve the efficiency of the search. Finally, 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 also uses a continuum electrostatic model based on screened Coulomb potentials (see (Hassan et al., 2000a;Hassan et al., 2000b;Hassan and Mehler, 2002) for details). While computationally expensive so as to require large computational facilities to achieve results in a reasonable period of time, the SCV-MC technique has been tested and validated for several systems (Hassan et al., 2003). This request for resources will be used to combine application of different loop-prediction algorithms with the MC-SCV method in an attempt to reveal new more effective ways to identify conformations of long GPCR loops that belong to the native energy funnel. Specifically, the different loop prediction algorithms will provide initial conformations that will be fed into the MC-SCV method for comprehensive refinement. Preliminary studies combining the conformational prediction of LOOPY for intracellular loops 2 and 3 of rhodopsin with the MC-SCV method look very promising. Results of the proposed studies are expected to improve the efficiency of current algorithms in the prediction of long loops of GPCRs, as well as other proteins. REFERENCES 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. Hassan, S. A., Mehler, E. L., Zhang, D., and Weinstein, H.: Molecular dynamics simulations of peptides and proteins with a continuum electrostatic model based on screened Coulomb potentials. Proteins 51 (1): 109-25, 2003. 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. Nikiforovich, G. V., and Marshall, G. R.: Modeling flexible loops in the dark-adapted and activated states of rhodopsin, a prototypical G-protein-coupled receptor. Biophys J 89 (6): 3780-9, 2005. Xiang, Z., Soto, C. S., and Honig, B.: Evaluating conformational free energies: the colony energy and its application to the problem of loop prediction. Proc Natl Acad Sci U S A 99 (11): 7432-7, 2002.