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 ...
Dopamine neurotransmitter and its receptors play a critical role in the cell signaling process responsible for information transfer in neurons functioning in the nervous system. Development of improved therapeutics for such disorders as Parkinson's disease and schizophrenia would be significantly enhanced with the availability of the 3D structure for the dopamine receptors and of the binding site for dopamine and other agonists and antagonists. We report here the 3D structure of the long isoform of the human D2 dopamine receptor, predicted from primary sequence using firstprinciples theoretical and computational techniques (i.e., we did not use bioinformatic or experimental 3D structural information in predicting structures). The predicted 3D structure is validated by comparison of the predicted binding site and the relative binding affinities of dopamine, three known dopamine agonists (antiparkinsonian), and seven known antagonists (antipsychotic) in the D2 receptor to experimentally determined values. These structures correctly predict the critical residues for binding dopamine and several antagonists, identified by mutation studies, and give relative binding affinities that correlate well with experiments. The predicted binding site for dopamine and agonists is located between transmembrane (TM) helices 3, 4, 5, and 6, whereas the best antagonists bind to a site involving TM helices 2, 3, 4, 6, and 7 with minimal contacts to TM helix 5. We identify characteristic differences between the binding sites of agonists and antagonists.W ith the implication of G protein-coupled receptor (GPCR) in many diseases (1, 2), the need to solve the highresolution 3D structure of this class of integral membrane proteins to enable structure-based drug design is an important problem in structural biology. Despite the importance of solving the structure of the GPCRs, the only experimental 3D structure available for a GPCR is bovine rhodopsin. This lack of structures is because the GPCRs are bound to the membrane, making it difficult to express in sufficient quantities for crystallization.To provide structural and ligand binding information on GPCRs, we have been developing first-principles computational techniques for predicting the 3D structure of GPCRs using only the amino acid sequence (MembStruk) and for predicting binding site and binding energy of various ligands to GPCRs (HierDock). Using these techniques, we have reported the structure of olfactory receptors (3, 4), bovine rhodopsin (4, 5), and other GPCRs (4). Dopamine neurotransmitter plays a critical role in cellular signaling processes responsible for information transfer in neurons functioning in the nervous system (6, 7). Dopamine receptors (DR) belong to the superfamily of GPCRs, and to date there are five reported sequences for the human DR with multiple isoforms for each. The DRs may be subdivided based on their pharmacological behavior into the D1-like and the D2-like subfamilies, and these are ideal targets for treating schizophrenia and Parkinson's disease; th...
A major challenge in the application of structure-based drug design methods to proteins belonging to the superfamily of G protein-coupled receptors (GPCRs) is the paucity of structural information (1). The 19 chemokine receptors, belonging to the Class A family of GPCRs, are important drug targets not only for autoimmune diseases like multiple sclerosis but also for the blockade of human immunodeficiency virus type 1 entry (2). Using the MembStruk computational method (3), we predicted the three-dimensional structure of the human CCR1 receptor. In addition, we predicted the binding site of the small molecule CCR1 antagonist BX 471, which is currently in Phase II clinical trials (4). Based on the predicted antagonist binding site we designed 17 point mutants of CCR1 to validate the predictions. Subsequent competitive ligand binding and chemotaxis experiments with these mutants gave an excellent correlation to these predictions. In particular, we find that Tyr-113 and Tyr-114 on transmembrane domain 3 and Ile-259 on transmembrane 6 contribute significantly to the binding of BX 471. Finally, we used the predicted and validated structure of CCR1 in a virtual screening validation of the Maybridge data base, seeded with selective CCR1 antagonists. The screen identified 63% of CCR1 antagonists in the top 5% of the hits. Our results indicate that rational drug design for GPCR targets is a feasible approach.Chemokines belong to a large family of small, chemotactic cytokines that regulate the trafficking of immune cells (5) by binding to cell surface receptors belonging to the GPCR 3 superfamily (5). CCR1, the first CC chemokine receptor to be identified, responds to a number of ligands, including MIP-1␣ (CCL3) and RANTES (regulated on activation normal T cell expressed and secreted) (CCL5) (6, 7). The strong association with a wide variety of autoimmune and pro-inflammatory diseases has made the CCR1 protein an attractive therapeutic target, and Berlex has developed a potent, specific, orally available antagonist, BX 471, currently in a Phase II clinical trial (8).The CCR1 antagonist program that yielded the clinical compound BX 471 followed a traditional drug discovery approach starting with high throughput screening of large compound libraries (9). Although high throughput screening is a main pillar of drug-finding programs in the pharmaceutical industry, it has recently been supplemented by in silico methods to maximize the probability of finding attractive novel leads. Structurebased in silico approaches have been challenging for GPCRs, because only one experimental GPCR structure, that of bovine rhodopsin, with only ϳ20% sequence identity to CCR1 (10), has been reported. Recent developments in GPCR structure prediction methods show great potential for structure-based drug design and identifying novel hits from virtual screens (11)(12)(13)(14)(15).In this communication we report a significant test of the computational method MembStruk by predicting the structure of CCR1. Further, we scanned the entire predicted struc...
The prevailing paradigm for G protein-coupled receptors is that each receptor is narrowly tuned to its ligand and closely related agonists. An outstanding problem is whether this paradigm applies to olfactory receptor (ORs), which is the largest gene family in the genome, in which each of 1,000 different G protein-coupled receptors is believed to interact with a range of different odor molecules from the many thousands that comprise ''odor space. ' O lfactory (odor) receptors (ORs) in the mammalian olfaction system exhibit a combinatorial response to odorant molecules (1). A single odor elicits response from multiple receptors and a single receptor also responds to multiple odorants, so every odorant has been thought to have a unique combination of responses from several receptors. This endows a discriminatory power to the mammalian olfactory system that could discriminate thousands of odors. The mechanisms by which the olfactory system accomplishes its multitude tasks are not clear. However, it is known that each olfactory neuron expresses only one receptor. Odor detection is mediated by Ϸ1,000 ORs that are G protein-coupled membrane-bound proteins. Malnic et al. (1) recently reported the differential responses of individual mouse OR neurons to 24 organic odor compounds (linear alcohols, acids, diacids, and bromoacids with four to nine carbons) by using Ca 2ϩ -imaging techniques, followed by single-cell reverse transcription-PCR to determine the sequence of the responsive OR. These clean single-cell experimental results (1) lead to the compelling question ''what is the molecular basis of odor recognition?'' Such questions can be answered only with the atomic level model of these ORs. No structural information is available for ORs. Also for any member of the membrane protein family, the insolubility of membrane proteins and the difficulty in crystallizing membrane proteins makes it harder to obtain structural information. In this work, we have derived an atomic level structural model for the mammalian OR S25 sequenced by Malnic et al. (1) and also identified the potential binding site for simple aliphatic alcohol and acid odorants to this receptor. The order of binding energies correlate well with the experimental recognition profiles and the binding site predictions also correlate well with the speculations. Modeling TechniquesPrediction of the Structure of ORs. ORs are seven helical transmembrane G protein-coupled receptors. We have derived the atomic model for OR S25 by using a combination of hydrophobicity profile prediction methods (2) and large-scale coarse grain molecular dynamics (MD) methods (3-8) with proper description of differential solvent environment. Prediction of helical regions by using hydrophobicity profiles andoptimization. The transmembrane helices were identified on the basis of hydrophobicity by the multisequence profile method of Donnelly (2), implemented in PERSCAN. A window size of 21 residues was used. For validation, the analysis was done on 21 rat ORs reported by Singer et al. (9)...
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