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

Advances in structure and small molecule docking predictions for crystallized G-Protein coupled receptors

This dissertation discusses two main aspects of protein-ligand interaction for G-Protein coupled receptors: structure predictions of the flexible loop domains and docking into these receptors. The prediction of loop structure has been long worked on in the context of native, globular proteins. In this work it is extended to transmembrane proteins, which requires an explicit integration of the lipid bilayer into the loop prediction calculation. In the initial work, this new approach to loop prediction yields highly accurate 3-dimensional structures of the intra and intercellular loops of four G-protein coupled receptors--the A2A adenosine, bovine rhodopsin, β1 and β2 adronergic receptors. For these cases, the loops were predicted in the context of a completely native crystal structure. In subsequent work the approach was extended to work on perturbed cases, where all loops and tails were removed, and side chains near the loop being predicted were in nonnative conformations. Lastly, a full homology model of the β2 adronergic receptor was successfully built from the β1 adronegric receptor as its template. Work on docking into these receptors focuses on the kappa opioid receptor. Known antagonist binders are discriminated from a set of decoy nonbinders via docking calculations. Two new terms were added to the scoring function, WScore to achieve this, based on a detailed molecular understanding of how the receptor works

Novel Strategies for Model-Building of G Protein-Coupled Receptors

The G protein-coupled receptors constitute still the most densely populated proteinfamily encompassing numerous disease-relevant drug targets. Consequently, medicinal chemistry is expected to pursue targets from that protein family in that hits need to be generated and subsequently optimized towards viable clinical candidates for a variety of therapeutic areas. For the purpose of rationalizing structure-activity relationships within such optimization programs, structural information derived from the ligand's as well as the macromolecule's perspective is essential. While it is relatively straightforward to define pharmacophore hypotheses based on comparative modelling of structurally and biologically characterized low-molecular weight ligands, a deeper understanding of the molecular recognition event underlying, remains challenging, since the principally available amount of experimentally derived structural data on GPCRs is extremely scarse when compared to, e.g., soluble enzymes. In this context, the protein modelling methodologies introduced, developed, optimized, and applied in this thesis provide structural models that are capable of assisting in the development of structural hypotheses on ligand-receptor complexes. As such they provide a valuable structural framework not only for a more detailed insight into ligand-GPCR interaction, but also for guiding the design process towards next-generation compounds which should display enhanced affinity. The model building procedure developed in this thesis systematically follows a hierarchical approach, sequentially generating a 1D topology, followed by a 2D topology that is finally converted into a 3D topology. The determination of a 1D topology is based on a compartmentalization of the linear amino acid sequence of a GPCR of interest into the extracellular, intracellular, and transmembrane sequence stretches. The entire chapter 3 of this study elaborates on the strengths and weaknesses of applying automated prediction tools for the purpose of identifying the transmembrane sequence domains. Based on an once derived 1D topology, a type of in-plane projection structure for the seven transmembrane helices can be derived with the aide of calculated vectorial property moments, yielding the 2D topology. Thorough bioinformatics studies revealed that only a consensus approach based on a conceptual combination of different methods employing a carefully made selection of parameter sets gave reliable results, emphasizing the danger to fully automate a GPCR modelling procedure. Chapter 4 describes a procedure to further expand the 2D topological findings into 3D space, exemplified on the human CCK-B receptor protein. This particular GPCR was chosen as the receptor of interest, since an enormous experimentally derived and structurally relevant data-set was available. Within the computational refinement procedure of constructed GPCR models, major emphasis was laid on the explicit treatment of a non-isotropic solvent environment during molecular mechanics (i.e. energy minimization and molecular dynamics simulations) calculations. The majority of simulations was therefore carried out in a tri-phasic solvent box accounting for a central lipid environment, flanked by two aqueous compartments, mimicking the extracellular and cytoplasmic space. Chapter 5 introduces the reference compound set, comprising low-molecular weight compounds modulating CCK receptors, that was used for validation purposes of the generated models of the receptor protein. Chapter 6 describes how the generated model of the CCK-B receptor was subjected to intensive docking studies employing compound series introduced in chapter 5. It turned out that by applying the DRAGHOME methodology viable structural hypotheses on putative receptor-ligand complexes could be generated. Based on the methodology pursued in this thesis a detailed model of the receptor binding site could be devised that accounts for known structure-activity relationships as well as for results obtained by site-directed mutagenesis studies in a qualitative manner. The overall study presented in this thesis is primarily aimed to deliver a feasibility study on generating model structures of GPCRs by a conceptual combination of tailor-made bioinformatics techniques with the toolbox of protein modelling, exemplified on the human CCK-B receptor. The generated structures should be envisioned as models only, not necessarily providing a detailed image of reality. However, consistent models, when verified and refined against experimental data, deliver an extremely useful structural contextual platform on which different scientific disciplines such as medicinal chemistry, molecular biology, and biophysics can effectively communicate

Investigation of ligand selectivity and activation dynamics of G protein-coupled receptors using enhanced sampling simulations

G protein-coupled receptors (GPCRs) are a large superfamily of transmembrane proteins found in eukaryotes. They play a crucial role in the transduction of signals across the plasma membrane of cells, and are involved in the regulation of a plethora of processes. Due to their function in countless biological pathways they have a primary role in many pathological conditions, and are thus therapeutic targets of great importance. Notwithstanding the growing availability of X-ray and cryo-EM structures and the intense involvement of the scientific community, many gaps are still present in our understanding of the mechanisms of ligand binding, receptor activation and allostery. Computational methods open the possibility for the study of the dynamics of such processes at atomistic resolution, complementing experimental findings. In this work key processes of a number of different GPCRs are explored with the use of computational approaches. Molecular dynamics and enhanced sampling methods are leveraged for sampling rare events of great interest and for the calculation of the associated free energy landscapes. In the first place our study of ligand binding and the selectivity mechanism in adenosine A2a and A1 receptors is reported, elucidating how selectivity arises from an interplay of structural factors. The activation mechanism of glucagon receptor and the coupling with a G protein is then investigated, highlighting the cooperative action of glucagon and G protein in the process. A detailed overview of allosteric antagonism in chemokine receptors is built by mining databases of experimental data and complementing this picture with insights on the dynamics of these receptors. Finally, the performance of TS-PPTIS (Transition State-Partial Path Transition State Sampling), a method for the calculation of kinetic rate constants, is studied for the prediction of ligand binding kinetic rates. The findings of this study add to the understanding of the mechanism of signal transduction through GPCRs, and detail this process from its origin outside the cell to the intracellular medium

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

Enhancing the fight against malaria : from genome to structure and activity of a G-protein coupled receptor from the mosquito, Anopheles Gambiae

Includes abstract.Includes bibliographical references (leaves 183-184).G-proton coupled receptors (GPCRs) are excellent drug targets that occupy a central position in the physiology of insects and are involved in transmission of signal from the extracellular to the intracellular side of the cell. Adipokinetic hormone receptors (AKHRs) are GPCRs that mediate physiological functions of the neurohormones, adipokinetic hormones (AKHs) that regulate mobilisation of energy reserves during mosquito flight. Ligand binding to GPCRs depends on the three dimensional (3D) structures of the receptors but to date no crystal structures of insect GPCRs are available. This work focused on building molecular models of AKHR from the genome of the malaria mosquito, identifying its binding site and studying the conformational and structural changes during molecular dynamics of the active and inactive receptor

Novel Strategies for Model-Building of G Protein-Coupled Receptors

The G protein-coupled receptors constitute still the most densely populated proteinfamily encompassing numerous disease-relevant drug targets. Consequently, medicinal chemistry is expected to pursue targets from that protein family in that hits need to be generated and subsequently optimized towards viable clinical candidates for a variety of therapeutic areas. For the purpose of rationalizing structure-activity relationships within such optimization programs, structural information derived from the ligand's as well as the macromolecule's perspective is essential. While it is relatively straightforward to define pharmacophore hypotheses based on comparative modelling of structurally and biologically characterized low-molecular weight ligands, a deeper understanding of the molecular recognition event underlying, remains challenging, since the principally available amount of experimentally derived structural data on GPCRs is extremely scarse when compared to, e.g., soluble enzymes. In this context, the protein modelling methodologies introduced, developed, optimized, and applied in this thesis provide structural models that are capable of assisting in the development of structural hypotheses on ligand-receptor complexes. As such they provide a valuable structural framework not only for a more detailed insight into ligand-GPCR interaction, but also for guiding the design process towards next-generation compounds which should display enhanced affinity. The model building procedure developed in this thesis systematically follows a hierarchical approach, sequentially generating a 1D topology, followed by a 2D topology that is finally converted into a 3D topology. The determination of a 1D topology is based on a compartmentalization of the linear amino acid sequence of a GPCR of interest into the extracellular, intracellular, and transmembrane sequence stretches. The entire chapter 3 of this study elaborates on the strengths and weaknesses of applying automated prediction tools for the purpose of identifying the transmembrane sequence domains. Based on an once derived 1D topology, a type of in-plane projection structure for the seven transmembrane helices can be derived with the aide of calculated vectorial property moments, yielding the 2D topology. Thorough bioinformatics studies revealed that only a consensus approach based on a conceptual combination of different methods employing a carefully made selection of parameter sets gave reliable results, emphasizing the danger to fully automate a GPCR modelling procedure. Chapter 4 describes a procedure to further expand the 2D topological findings into 3D space, exemplified on the human CCK-B receptor protein. This particular GPCR was chosen as the receptor of interest, since an enormous experimentally derived and structurally relevant data-set was available. Within the computational refinement procedure of constructed GPCR models, major emphasis was laid on the explicit treatment of a non-isotropic solvent environment during molecular mechanics (i.e. energy minimization and molecular dynamics simulations) calculations. The majority of simulations was therefore carried out in a tri-phasic solvent box accounting for a central lipid environment, flanked by two aqueous compartments, mimicking the extracellular and cytoplasmic space. Chapter 5 introduces the reference compound set, comprising low-molecular weight compounds modulating CCK receptors, that was used for validation purposes of the generated models of the receptor protein. Chapter 6 describes how the generated model of the CCK-B receptor was subjected to intensive docking studies employing compound series introduced in chapter 5. It turned out that by applying the DRAGHOME methodology viable structural hypotheses on putative receptor-ligand complexes could be generated. Based on the methodology pursued in this thesis a detailed model of the receptor binding site could be devised that accounts for known structure-activity relationships as well as for results obtained by site-directed mutagenesis studies in a qualitative manner. The overall study presented in this thesis is primarily aimed to deliver a feasibility study on generating model structures of GPCRs by a conceptual combination of tailor-made bioinformatics techniques with the toolbox of protein modelling, exemplified on the human CCK-B receptor. The generated structures should be envisioned as models only, not necessarily providing a detailed image of reality. However, consistent models, when verified and refined against experimental data, deliver an extremely useful structural contextual platform on which different scientific disciplines such as medicinal chemistry, molecular biology, and biophysics can effectively communicate

NMR Investigation of Structures of G-Protein Coupled Receptor Folding Intermediates

Folding of G-protein coupled receptors (GPCRs) according to the two-stage model (Popot et al., Biochemistry 29(1990), 4031) is postulated to proceed in 2 steps: Partitioning of the polypeptide into the membrane followed by diffusion until native contacts are formed. Herein we investigate conformational preferences of fragments of the yeast Ste2p receptor using NMR. Constructs comprising the first, the first two and the first three transmembrane (TM) segments, as well as a construct comprising TM1-TM2 covalently linked to TM7 were examined. We observed that the isolated TM1 does not form a stable helix nor does it integrate well into the micelle. TM1 is significantly stabilized upon interaction with TM2, forming a helical hairpin reported previously (Neumoin et al., Biophys. J. 96(2009), 3187), and in this case the protein integrates into the hydrophobic interior of the micelle. TM123 displays a strong tendency to oligomerize, but hydrogen exchange data reveal that the center of TM3 is solvent exposed. In all GPCRs so-far structurally characterized TM7 forms many contacts with TM1 and TM2. In our study TM127 integrates well into the hydrophobic environment, but TM7 does not stably pack against the remaining helices. Topology mapping in microsomal membranes also indicates that TM1 does not integrate in a membrane-spanning fashion, but that TM12, TM123 and TM127 adopt predominantly native-like topologies. The data from our study would be consistent with the retention of individual helices of incompletely synthesized GPCRs in the vicinity of the translocon until the complete receptor is released into the membrane interior

A single AKH neuropeptide activating three different fly AKH-receptors: an insecticide study via computational methods

Flies are a widely distributed pest insect that poses a significant threat to food security. Flight is essential for the dispersal of the adult flies to find new food sources and ideal breeding spots. The supply of metabolic fuel to power the flight muscles of insects is regulated by adipokinetic hormones (AKHs). The fruit fly, Drosophila melanogaster, the flesh fly, Sarcophaga crassipalpis, and the oriental fruit fly, Bactrocera dorsalis all have the same AKH that is present in the blowfly, Phormia terraenovae; this AKH has the code-name Phote-HrTH. Binding of the AKH to the extracellular binding site of a G protein-coupled receptor causes its activation. In this thesis, the structure of Phote-HrTH in SDS micelle solution was determined using NMR restrained molecular dynamics. The peptide was found to bind to the micelle and be reasonably rigid, with an S 2 order parameter of 0.96. The translated protein sequence of the AKH receptor from the fruit fly, Drosophila melanogaster, the flesh fly, Sarcophaga crassipalpis, and the oriental fruit fly, Bactrocera dorsalis were used to construct two models for each receptor: Drome-AKHR, Sarcr-AKHR, and Bacdo-AKHR. It is proposed that these two models represent the active and inactive state of the receptor. The models based on the crystal structure of the β-2 adrenergic receptor were found to bind Phote-HrTH with a predicted binding free energy of –107 kJ mol–1 for Drome-AKHR, –102 kJ mol–1 for Sarcr-AKHR and –102 kJ mol–1 for Bacdo-AKHR. Under molecular dynamics simulation, in a POPC membrane, the β-2AR receptor-like complexes transformed to rhodopsin-like. The identification and characterisation of the ligand-binding site of each receptor provide novel information on ligand-receptor interactions, which could lead to the development of species-specific control substances to use discriminately against these pest flies