Refinement of the conformation of selected transmembrane helices in the cannabinoid receptor GPR55 using conformational memories (CM).

GPR55 is a newly de-orphanized cannabinoid receptor which belongs to the class A G-protein coupled receptors (GPCRs) family and binds constitutes of the plant, Cannabis sativa. It has been suggested that the manipulation of GPR55 may have a therapeutic potential in the treatment of inflammatory and neuropathic pain. The purpose of the present study was to refine the transmembrane helices (TMH) conformation in GPR55 that have significant sequence divergence from other class A GPCRs. The methods used were conformational memories (CM) to refine the transmembrane helices (TMH) of TMH2, TMH5, TMH6 and TMH7. The results of these calculations were used to modify the GPR55 computer model initially built in Reggio lab based on a rhodopsin template to generate refined inactive and active models of GPR55. The average proline kink angle and standard deviation for each set of conformational results generated by CM were measured using the Prokink program. A statistical analysis of the resultant face shift, wobble angle and bend angle of the helices containing proline was performed using the one sample t test and compared to the β-2 adrenergic receptor. The refined model of the inactive receptor of GPR55 obtained from the conformational memories is shown in figure 1. In conclusion the results of conformational memories are consistent with the proposal of Ballesteros, that even though the overall structure of rhodopsin and other class A GPCRs may be very similar, there are localized regions where the structures of these receptors diverge. A significant range of conformational diversity could be generated by the presence of Pro-kinks and Cys/Ser/Thr residues. The results obtained should help to define the mechanism of drug receptor interaction relevant to cannabinoid physiological and pathophysiological functions including drug abuse

Identification of agonist and antagonist binding sites at the G-Protein Coupled Receptor, GPR18

GPR18, a member of the Class A G-Protein Coupled Receptors (GPCRs), is recently a de-orphanized receptor, that upon activation has been found to boost the immune system. Although a GPR18 crystal structure has not been solved, a homology model of the inactive state (R) of GPR18 was built in the Reggio lab based upon the mu-opioid x-ray crystal structure. The present study continues this work by adding loop regions and N- and C-termini to the R state model and by developing a model of GPR18 R* (Active) state, complete with loop regions and N- and C-termini. The complete inactive and active state models were used for docking studies of five known GPR18 antagonists, 1,3-dimethoxy-5-methyl-2-[(1R,6R)-3-methyl-6-prop-1-en-2-ylcyclohex-2-en-1-yl]benzene; 1, (Z)-2-(3((4-chlorobenzyl)oxy)benzylidene)-3-methylene-2,3,6,7-tetrahydro-5H-imidazo[2,1-b][1,3]thiazine; 2, (1R,2R)-2',6'-dimethoxy-4',5-dimethyl-2-(prop-1-en-2-yl)-1,2,3,4-tetrahydro-1,1'-biphenyl; 3, (Z)-2-(3-(4-chlorobenzyloxy)benzylidene)-6,7-dihydro-2H-imidazo[2,1-b][1,3]thiazin-3(5H)-one; 4, and 2-[(1R,6R)-6-isopropenyl-3-methylcyclohex-2-en-1-yl]-5-pentylbenzene-1,3-diol; 5 and the GPR18 endogenous ligand, N-arachidonylglycine (NAGly). Conformational searches were performed on all antagonists using a systematic search using the Hartree-Fock method at the 6-31G* level of theory. Because NAGly is highly flexible, its low energy conformations were determined using the Conformational Memories method. All low energy conformations, less than 3.0 kcal/mol, of each ligand were docked using Glide into their respective bundles based on the state of the receptor each ligand stabilizes. The key interaction site for all antagonists, an ARG in TMH5, R5.42, anchors each antagonist in the TMH bundle such that rotameric changes in key toggle switch residues, F6.48/H6.52, are prevented, thus preventing the activation of the receptor. The extracellular loop 2 (EC2 loop) residue Y160 further stabilizes each antagonist in the binding site. Identified interactions result in Glide scores consistent with experimental EC50 data. The primary interaction site for the agonist, NAGly, was TMH2 residue R2.60. An additional NAGly interaction was identified with the EC2 loop residue K174. Mutation experiments of key residues identified here are underway in a collaborator’s lab. These studies will help confirm the importance of these key residues and further our understanding of the receptor

Construction of a µ-opioid receptor model: identification of the opioid alkaloid binding pocket

Morphine and other analgesics bind to and activate the µ-opioid receptor (MOR). The opioid receptors belong to the Class A subfamily of G-Protein Coupled Receptors (GPCRs). These are transmembrane proteins with seven helices arranged to form a closed bundle with loops that extend both extracellularly and intracellularly. Activation of this family of GPCRs has been shown to involve the change of the ?1 dihedral of a tryptophan residue on TMH6, W6.48, from g+ to trans. The purpose of this project was to design a computational model of the MOR and to dock both morphine an agonist, and naloxone an antagonist, into the model such that their positions were consistent with their pharmacologies. A MOR model was created using the Beta-2-Adrenergic (ß 2-AR) crystal structure as a template with two major modifications. First, the Conformational Memories (CM) program was used to study the conformations of three transmembrane helices (TMH); TMH2, TMH4 and TMH6. Second, the TMH7/elbow/Hx8 region of the ß 2-AR was replaced with that of the adenosine A2A crystal structure because the adenosine A2A receptor has the same number of residues in the elbow region as is found in the MOR. Energy minimizations were performed on the MOR bundle in a three step process and the ligand binding pocket was identified. Docking studies suggested that naloxone binds in the TMH2-3-6-7 region of the MOR such that the N-allyl group sterically prohibits the movement of the ?1 of W6.48, thereby preventing activation of the receptor. Morphine was also found to bind in the TMH2-3-6-7 region of the MOR; however no portion of the morphine structure could block the movement of the ?1 of W6.48, thereby producing no impediment for activation. These results are consistent with the pharmacology of naloxone (MOR antagonist) and morphine (MOR agonist). Models created will be used for future mutation studies

Building and refinement of an in silico homology model of a novel G protein-coupled receptor: GPR35

Human GPR35 (hGPR35), a recently deorphanized Class A G-protein coupled receptor, has been shown to exhibit prominent expression in immune and gastrointestinal tissues, with additional expression in pancreatic islets, skeletal muscle, lung tissue, and the dorsal root ganglion. The rat GPR35 (rGPR35) analog, which has 72% sequence identity with human GPR35, has been shown to have expression in similar tissues as with human GPR35. GPR35 has been suggested to be involved in metabolism, heart failure, inflammation, asthma, a mental retardation syndrome associated with the deletion on 2q37.3, type II diabetes, as well as gastric cancer formation, making GPR35 a potential target for the treatment of multiple diseases. Both zaprinast, the well characterized cGMP-PDE inhibitor, and pamoic acid, a compound which the FDA has classified as an inactive compound, act as agonists at GPR35. However, interesting species differences have been found with these agonists and key mutations have also revealed differences between these two ligands. Pamoic acid is considerably lower in potency in rat GPR35, while zaprinast has increased efficacy in rat GPR35. Further, mutation studies suggest an increase in the potency of zaprinast in a human GPR35 R6.58A mutation. Pamoic acid, on the other hand shows similar potency to wild-type in this same mutant. To probe the molecular origins of these differences, three separate homology models, an active (R*) hGPR35, an R* hGPR35 R6.58A(240) mutant, and an R* rGPR35 model, were constructed and docking studies were performed with the aforementioned ligands. These studies revealed that the change in residue 5.43 (P5.43 in human; S5.43 in rat) alters the shape of the binding pocket for pamoic acid. In addition, arginines which contribute significantly to the interaction of pamoic acid in hGPR35 (R6.58 and R7.32) become uncharged residues (Q6.58 and S7.32) in rat GPR35. The increase of the potency of zaprinast in the hGPR35 R6.58A mutant receptor is due to the loss of bulk at position 6.58 (R6.58(240)¨ A6.58(240)), that allows for additional interactions with the ligand. The statistically equivalent potencies of pamoic acid for the wild-type and R6.58A(240) mutant hGPR35 receptors is due to the isoenergetic interchange of the direct interaction residue R6.58(240) with R7.32(255) in the R6.58(240)A mutant

Creation of a GPR18 homology model using conformational memories

G-protein coupled receptors (GPCRs) make up the largest family of eukaryotic membrane receptors, covering a broad range of cellular responses in the body. This wide range of activity makes them important pharmacological targets. In general, all Class A GPCRs share a common structure that consists of seven transmembrane alpha helices, connected by extracellular and intracellular loops, an extracellular N-terminus, and an intracellular C-terminus. These similarities can be used to construct a model of an unknown receptor, which can then be used to help guide further studies of this receptor and its pharmacology. The orphan GPCR GPR18 is a member of the Class A subfamily of GPCRs. GPR18 binds both lipid-like and small molecule ligands, such as NAGly and abnormal-cannabidiol (Abn-CBD), leading to belief that GPR18 may be the Abnormal Cannabinoid Receptor. The goal of this project was to construct a model of GPR18 in its inactive state and to explore the binding site of a key antagonist already identified for this receptor. A model of the GPR18 inactive (R) state was created using the μ-Opioid receptor (MOR) crystal structure as template (PDB: 4DKL). The Monte Carlo/simulated annealing method, Conformational Memories (CM) was used to study the accessible conformations of three GPR18 transmembrane helices (TMHs) with important sequence divergences from the MOR template: TMH3, TMH4, and TMH7. CM was also used to calculate the accessible conformations for TMH6, which allowed the choice of TMH6 conformers appropriate for the GPR18 R and R* models. Docking studies were guided by the hypothesis that a positively charged residue (either R2.60 or R5.42) may be the primary ligand interaction site in the GPR18 binding pocket. The binding pocket of the antagonist, cannabidiol (CBD) was explored in the inactive state GPR18 model using Glide, an automatic docking program in the Schrödinger modeling suite. These studies identified that both of these argenines are the primary interaction site for CBD. With the pocket determined, extracellular and intracellular loops were calculated using another Monte Carlo technique, Modeler. Once loops were attached, the N and C termini were modeled and added as well. Much like the S1PR1 receptor, and continuing the hypothesis that GPR18 used a lipid level access to the binding pocket, the N terminus displayed a small helical portion that lay atop the bundle, effectively blocking the extracellular side along with EC2. With the identification of key residues and a complete bundle, further mutation studies and dynamic simulations can be used to further refine and test these modeling results

Molecular mechanisms of mutant mu-opioid receptors where naloxone acts as an agonist

Pain management is often one of the most difficult aspects of treatment for patients suffering from acute or chronic pain. The mu-opioid receptor (MOR) agonist, morphine, and its derivatives are highly used in pain management strategies. However, these medications have many side effects including respiratory depression, gastrointestinal problems, as well as dependence and addiction liabilities. For these reasons, innovative new modalities for pain management continue to be needed. One new approach to the design of opioid therapies for chronic pain with reduced liabilities is a targeted-gene therapy strategy developed by the lab of Dr. Ping-Yee Law at the University of Minnesota. This strategy makes novel use of a MOR S4.54A mutant at which the classical opioid antagonist, naloxone, acts as a partial agonist. Targeted gene therapy studies using this mutant have shown that naloxone becomes an antinociceptive agent at the S4.54A mutant both in vitro and in vivo. Because expression of the mutant MOR is targeted to the spinal cord injection site region, systemic administration of naloxone results in antagonism of all other (native) MOR's. The reduced number of receptors activated in this paradigm results in no measurable dependence/addiction as seen with traditional mu agonists like morphine. Despite the clear success of basing this strategy on the S4.54A MOR mutant, the origins of this unusual phenotype are not yet understood. It was therefore the overall goal of this dissertation to identify the molecular basis for the agonism of naloxone at this novel S4.54A mutant. To this end, a model of the wild-type and S4.54A mu opioid receptor was developed and ligand docking studies were used to probe this model. The opioid receptors, delta, kappa and mu, belong to the Class A subfamily of G-Protein Coupled Receptors (GPCRs). These are integral membrane proteins that possess seven transmembrane helices (TMHs) arranged to form a closed bundle with loops that extend both extracellularly and intracellularly. The N-terminus is extracellular and the C-terminus is intracellular. In recent years, X-ray crystallography studies have yielded structures of numerous GPCRs. In 2012, the nociception/orphanin FQ receptor and the mu, delta and kappa opioid receptor crystal structures were published. Prior to the release of the MOR crystal structure, we developed a homology model of WT MOR using the β2-AR crystal structure2,3 as a template with substitutions for TMH 1, 2, 4 and 7 based on sequence divergences, as described in methods. This model was then used for studies of the MOR including analyzing the receptor for cholesterol and palmitoylaiton interactions as well as modeling a homodimer interface for the MOR based on experimental data. In 2012, new models of WT MOR and the S4.54A/L mutants were developed using the MOR crystal structure. The conformational change in TMH4 that would be created upon the S4.54A mutation was examined using the simulated annealing/Monte Carlo method, Conformational Memories, and the result was incorporated into the model. The S4.54A mutant model was then used for naloxone docking studies using Glide. These studies revealed that in the crystal structure, Y3.34 forms a hydrogen bond with the sidechain of S4.54; however, in the S4.54A MT MOR, this interaction is broken as there is no polar partner for Y3.34. The breaking of this interaction allows the extracellular end of TMH4 to kink away from TMH3 and towards TMH5, which leads to changes in the packing of the receptor binding pocket. In the wild type MOR, naloxone interacts with D3.32 and sits in close proximity to the binding pocket "toggle switch" residue, W6.48, restricting its movement. However, in the S4.54A MT MOR, naloxone sits higher in the binding pocket, away from W6.48 and interacts with D3.32 and E5.35. In this higher location, naloxone exerts no effect on W6.48, permitting W6.48 to assume an active state conformation. This shift in binding pocket location for naloxone may be the origin of naloxone's partial agonism in the S4.54A MOR mutant. We also explored additional experimental data generated in Dr. Ping Law's lab for other mutations at the 4.54 locus. Mutating S4.54 to Phe or Gly results in the same phenotype as the S4.54A mutation. On the other hand, for Ile or Val mutants, naloxone behaves as in WT MOR. We propose that in the case of the S4.54 I / V, an increase in hydrophobic interactions between W4.50 and I/V4.54 allow TMH4 to maintain its wild type conformation. However, while the S4.54F is also able to increase hydrophobic interactions, its size prevents the helix from maintaining the wild type shape. In the S4.54L mutant, there is no increase in hydrophobic interactions and the orientation of the leucine gives rise to a straighter TMH4, as seen in the S4.54A MT MOR. The S4.54G mutant offers additional flexibility and a higher turn ratio, with 5 residues per turn in that region such that the extracellular end of TMH4 moves away from TMH3 and towards TMH5. Additionally, Law and coworkers have published studies using a S4.54L/T7.44A/C7.47S triple mutant MOR that gives rise to naloxone acting as a full agonist.4 While this gene therapy has been shown in cells and in spinal cord, the underlying mechanism is unknown. A triple mutant MOR model was developed and analyzed to determine the molecular mechanism for which naloxone acts as an agonist. The binding pocket for mu opioid ligands is formed by TMHs 3, 5 and 6 in the wild type receptor, as seen in the crystal structure with β-FNA5 and in our glide dock of naloxone (see Chapter 3). As studied in the single mutant MOR, S4.54 is a lipid facing residue. Interestingly, both of the mutated residues on TMH7 (T7.44 and C7.47) in the triple mutant MOR also face lipid. We report here that the combination of the S4.54L mutation on TMH4 along with TMH7 face shift changes occur upon mutation of T7.44 and C7.47 produce overall packing changes that give rise to a different binding pocket than seen in the wild type or single mutant MORs. These changes result in naloxone's ability to fully activate the S4.54L/T7.44A/C7.47S MOR

Do theoretical physicists care about the protein-folding problem?

The prediction of the biologically active native conformation of a protein is one of the fundamental challenges of structural biology. This problem remains yet unsolved mainly due to three factors: the partial knowledge of the effective free energy function that governs the folding process, the enormous size of the conformational space of a protein and, finally, the relatively small differences of energy between conformations, in particular, between the native one and the ones that make up the unfolded state. Herein, we recall the importance of taking into account, in a detailed manner, the many interactions involved in the protein folding problem (such as steric volume exclusion, Ramachandran forces, hydrogen bonds, weakly polar interactions, coulombic energy or hydrophobic attraction) and we propose a strategy to effectively construct a free energy function that, including the effects of the solvent, could be numerically tractable. It must be pointed out that, since the internal free energy function that is mainly described does not include the constraints of the native conformation, it could only help to reach the 'molten globule' state. We also discuss about the limits and the lacks from which suffer the simple models that we, physicists, love so much.Comment: 27 pages, 4 figures, LaTeX file, aipproc package. To be published in the book: "Meeting on Fundamental Physics 'Alberto Galindo'", Alvarez-Estrada R. F. et al. (Ed.), Madrid: Aula Documental, 200

Construction and validation of GPR55 active and inactive state in silico models through the use of biological assays, mutation data, and structure activity relationships

G-protein coupled receptors (GPCRs) function as both gatekeepers and molecular messengers of the cell. They relay signals that span the cell membrane mediating nearly every significant physiological process and currently represent the target of about 30% of all drugs. The signals they transmit can arise from a remarkable variety of stimuli which includes, but is not limited to, photons, neurotransmitters and hormones. GPR55, a rhodopsin-like (Class A) GPCR, has received a great deal of attention due to its emerging involvement in a multitude of physiological processes and its putative identity as a third type of cannabinoid receptor. Characterizations of GPR55 knock-out mice reveal a role for the receptor in controlling inflammatory pain, neuropathic pain, and bone resorption.1 Myriad other studies indicate that GPR55 activation may play a part in oncogenesis and metathesis. GPR55 can be found in numerous tissue types throughout the body and is also highly expressed throughout the cerebellum and surrounding central nervous system lending credence to the idea that this receptor may play a more crucial physiological role than originally thought.2 GPR55 has an extensive physiological profile and has been shown to respond uniquely to a great number of diverse compounds. Specifically, it has been shown to recognize many cannabinoid compounds, including CB1 and CB2 endogenous ligands, phytocannabinoids and synthetic cannabinoids. Similar to the ligands of the CB1 and CB2 receptors, the endogenous ligand of GPR55, lysophosphatidylinositol (LPI), is a lipid-derived molecule.3 LPI activates ERK1/2 and increases [Ca2+] and, to date, there has been no evidence that LPI interacts with the other cannabinoid receptors. Despite innumerable prospective clinical uses hinted at by the aforementioned research no low nanomolar potency ligands of GPR55 have been identified. Nor has there been a radio-ligand developed to characterize the binding site of this receptor. Lack of such tools is a great impediment to any forward progress towards developing the GPR55 receptor as a therapeutic target for drug design. The following research details the creation of both a GPR55 active- and a GPR55 inactive- state homology model. Towards this goal, Chapter I details the background of the discovery, pharmacological relevance and ligand scope of GPR55. Its purpose is to establish a framework for the research that follows and highlight the medical importance of this elusive receptor. Chapter II describes the synthetic preparation of antagonists of GPR55 for use in preliminary SAR studies. The original high throughput screen that lead to the identification of novel GPR55 scaffold chemotypes from the screening of over 300,000 compounds gave rise to the piperidinyloxadiazolone compound CID23612552 and the synthetic diversification of what was then dubbed Scaffold 1. A detailed description of the methods used in the construction of the updated R and R* state of GPR55 models is handled in Chapter III. A combination of Conformational Memories4,5 (using the CHARMM forcefield), Ligand Conformational Analysis (performed using Spartan (Wavefunction, Inc., Irvine, CA)) and Macromodel/Maestro/Glide (from the Schrödinger suite) was used to build and refine both GPR55 model states. Chapter IV then covers model validation and refinement. Using the phenylpiperazine (ML184 CID2440433) and mutations performed in the lab of Dr. Mary Abood (Temple University) it was shown that the current iteration of the GPR55 R* model was indeed a valid representation of the activated state of this receptor. This chapter also provides information that gives rise to the “Future Directions” chapter, Chapter V. This final chapter is a look forward to the research that still remains to be done to ensure that these models will function as the accurate tools that they have the potential to be. We used the GPR55 R bundle to suggest antagonist structures that will maximize ligand/receptor interactions and hopefully give rise to nanomolar potency molecules. These ligands will need to be synthesized and tested. We also identified key residues in the active bundle (GPR55 R*) that could be mutated to enhance or verify ligand binding. Mutations that destroy receptor function, while interesting, would not have the same utility as the aforementioned kinds of mutations

In silico refinement of a computer model of GPR55, a cannabinoid receptor

Cannabinoid receptors have great therapeutic potential and are important targets in drug discovery. As part of a broader project whose long-term goal is the determination of the basis for the actions of cannabinoids at the molecular level, this research project focuses on increasing the knowledge of the newly discovered third cannabinoid receptor, GPR55, through computer simulations by refining the model of the inactive (R) state of GPR55. In order to explore the conformational space available to specific transmembrane helices (TMHs) of GPR55, the Conformational Memories (CM), a computational method was used. CM is a Monte Carlo/Simulated Annealing (MC/SA) algorithm that can employ different molecular force fields. In the first part of this work the force field employed and the starting structure used were varied in order to optimize the method. This was done by exploring the conformational space of the second transmembrane helix (TMH2) of CB2, for which experimental data was available for validation. The GPR55 sequence exhibits many of the key sequence motifs of the Class A GPCRs and can therefore be easily aligned with other Class A GPCR sequences. From this alignment possible flexible regions of amino acids on each helix were identified for exploration. The regions were: VLSLP in TMH2, KVFFP, GFLLP, MGIMG in TMH5, VSFLP in TMH6, and CCLDV in TMH7. The calculated conformational space available to these helices is of special importance when building the computer model of GPR55 so that the resultant model reflects the sequence dictated conformation of the receptor bundle. At the beginning of this project, rhodopsin (Rho), the prototype receptor of Class A GPCRs, was the only transmembrane protein for which the crystal structure has been solved. For this reason and because GPR55 has sufficiently sequence similarity with Rho, this receptor was used as a template to build an initial model presented in a poster at the 2006 International Cannabinoid Research Society meeting. The results revealed differences between the conformational tendencies of GPR55 TMHs compared to the template. In the case of the TMH2 population, most helices reached over towards TMH3 more than rhodopsin, while TMH5 bends away from the template regardless of which flexible region was varied. The results of TMH6 conformational memories showed that this population leaned toward the TMH5 at the extracellular end. The present work deepens our understanding of the structure of GPR55 and the conformational differences between it and Rho that are dictated by divergences in amino acid sequence

Palmitoylation and membrane cholesterol stabilize μ-opioid receptor homodimerization and G protein coupling

<p>Abstract</p> <p>Background</p> <p>A cholesterol-palmitoyl interaction has been reported to occur in the dimeric interface of the β₂-adrenergic receptor crystal structure. We sought to investigate whether a similar phenomenon could be observed with μ-opioid receptor (OPRM1), and if so, to assess the role of cholesterol in this class of G protein-coupled receptor (GPCR) signaling.</p> <p>Results</p> <p>C3.55(170) was determined to be the palmitoylation site of OPRM1. Mutation of this Cys to Ala did not affect the binding of agonists, but attenuated receptor signaling and decreased cholesterol associated with the receptor signaling complex. In addition, both attenuation of receptor palmitoylation (by mutation of C3.55[170] to Ala) and inhibition of cholesterol synthesis (by treating the cells with simvastatin, a HMG-CoA reductase inhibitor) impaired receptor signaling, possibly by decreasing receptor homodimerization and Gαi2 coupling; this was demonstrated by co-immunoprecipitation, immunofluorescence colocalization and fluorescence resonance energy transfer (FRET) analyses. A computational model of the OPRM1 homodimer structure indicated that a specific cholesterol-palmitoyl interaction can facilitate OPRM1 homodimerization at the TMH4-TMH4 interface.</p> <p>Conclusions</p> <p>We demonstrate that C3.55(170) is the palmitoylation site of OPRM1 and identify a cholesterol-palmitoyl interaction in the OPRM1 complex. Our findings suggest that this interaction contributes to OPRM1 signaling by facilitating receptor homodimerization and G protein coupling. This conclusion is supported by computational modeling of the OPRM1 homodimer.</p