Prediction of structure and function of G protein-coupled receptors

Abstract

G protein-coupled receptors (GPCRs) mediate our sense of vision, smell, taste, and pain. They are also involved in cell recognition and communication processes, and hence have emerged as a prominent superfamily for drug targets. Unfortunately, the atomic-level structure is available for only one GPCR (bovine rhodopsin), making it difficult to use structure-based methods to design drugs and mutation experiments. We have recently developed first principles methods (MembStruk and HierDock) for predicting structure of GPCRs, and for predicting the ligand binding sites and relative binding affinities. Comparing to the one case with structural data, bovine rhodopsin, we find good accuracy in both the structure of the protein and of the bound ligand. We report here the application of MembStruk and HierDock to ␤1-adrenergic receptor, endothelial differential gene 6, mouse and rat I7 olfactory receptors, and human sweet receptor. We find that the predicted structure of ␤1-adrenergic receptor leads to a binding site for epinephrine that agrees well with the mutation experiments. Similarly the predicted binding sites and affinities for endothelial differential gene 6, mouse and rat I7 olfactory receptors, and human sweet receptor are consistent with the available experimental data. These predicted structures and binding sites allow the design of mutation experiments to validate and improve the structure and function prediction methods. As these structures are validated they can be used as targets for the design of new receptor-selective antagonists or agonists for GPCRs.GPCR ͉ olfactory receptor ͉ ␤-adrenergic receptor ͉ endothelial differentiation gene ͉ taste receptor G protein-coupled receptors (GPCRs) mediate senses such as odor, taste, vision, and pain (1) in mammals. In addition, important cell recognition and communication processes often involve GPCRs. Indeed, many diseases involve malfunction of these receptors (2), making them important targets for drug development. Unfortunately, despite their importance there is insufficient structural information on GPCRs for structure-based drug design. This is because these membrane-bound proteins are difficult to crystallize, and the atomic-level structure has been solved only for bovine rhodopsin (3, 4). Consequently, it is important to develop theoretical methods to predict the structure and function of GPCRs (5, 6).Experimental data relevant to the function of GPCRs is available for ligand activation of GPCRs (7-15) and site-directed mutagenesis (16)(17)(18). This data has led to information about structural features in the ligand-binding regions of GPCRs (refs. 5 and 19, and references therein). Protein sequence analyses on GPCRs reveals a common protein topology consisting of a membrane-spanning seven-helix bundle, which likely accommodates the binding site for low-molecular-weight ligands. Structurally, GPCRs can be classified as (i) GPCRs with short N terminus (5-80 residues) and (ii) GPCRs with a long N-terminal ectodomain (Ϸ80-600 residues). The long N terminus of ...

An Automated System for the Analysis of G Protein-Coupled Receptor Transmembrane Binding Pockets: Alignment, Receptor-Based Pharmacophores, and Their Application

“…In an explicit homology model, individual rotamer positions are assigned to all amino acids, and the model is then typically refined by molecular dynamics or stepwise relaxation steps folding the side chains around a number of known ligands. While there are various techniques described in the literature to arrive at state-of-the-art homology models, 23,24 they all stress the need of additional information from highly potent ligands 7,[23][24][25][26][27][28][29][30][31][32]34,35 and of several refinement cycles. There is no reference point by which the accuracy of such models can be judged, except for consistency with known rules about protein folding.…”

“…23,24 To obtain high-quality homology models suitable for docking experiments, additional, work-intensive refinement cycles are needed that explicitly take into account binding studies with highly potent ligands. 7,21,23,[25][26][27][28][29][30][31][32][33][34][35] This kind of approach is very valuable for optimizations of medicinal chemistry series in advanced projects on wellcharacterized targets, where mutational data and structureactivity relationships for the ligands are available and can be incorporated into validation cycles of the models. In earlystage GPCR projects, however, where often only the natural ligands are known and data from site-directed mutagenesis are missing, a traditional GPCR homology model with its focus on atomic details may turn out to be of only limited use.…”

Prediction of the 3-D structure of rat MrgA G protein-coupled receptor and identification of its binding site

“…This work builds upon our recent studies in which we first predicted the 3-D structures of mouse MrgC11 (mMrgC11) and MrgA1 (mMrgA1) receptors using the MembStruk computational method [9,10]. These structures were validated by predicting the binding sites and energies for several tetrapeptides, identifying key residues, and then experimentally confirming the expected changes in binding resulting from mutations of these residues.…”

“…This protocol has been used for several GPCRs [9,10,13,14,16,27,28], outer membrane protein A [29], and globular proteins [15,[30][31][32][33][34]. In this paper we used the modified HierDock protocol (MSCdock) described in Cho et al 2005 [35].…”

An Olfactory Receptor Pseudogene whose Function emerged in Humans

“…Our standard model building protocols differ slightly from those previously established 36,53,54 , by independently predicting the TM regions followed by removing of rhodopsin structure specific biases. In the case of hOR17-210, we are breaking new ground because we have identified and attempt to model a novel TM (TM 7') that has not been sequence-structurally observed.…”