Chris de Graaf

Structure of the human glucagon class B G-protein-coupled receptor

Binding of the glucagon peptide to the glucagon receptor (GCGR) triggers the release of glucose from the liver during fasting; thus GCGR plays an important role in glucose homeostasis. Here we report the crystal structure of the seven transmembrane helical domain of human GCGR at 3.4 Å resolution, complemented by extensive site-specific mutagenesis, and a hybrid model of glucagon bound to GCGR to understand the molecular recognition of the receptor for its native ligand. Beyond the shared seven transmembrane fold, the GCGR transmembrane domain deviates from class A G-protein-coupled receptors with a large ligand-binding pocket and the first transmembrane helix having a ‘stalk’ region that extends three alpha-helical turns above the plane of the membrane. The stalk positions the extracellular domain (∼12 kilodaltons) relative to the membrane to form the glucagon-binding site that captures the peptide and facilitates the insertion of glucagon’s amino terminus into the seven transmembrane domain.

Conformational states of the full-length glucagon receptor.

Class B G protein-coupled receptors are composed of an extracellular domain (ECD) and a seven-transmembrane (7TM) domain, and their signalling is regulated by peptide hormones. Using a hybrid structural biology approach together with the ECD and 7TM domain crystal structures of the glucagon receptor (GCGR), we examine the relationship between full-length receptor conformation and peptide ligand binding. Molecular dynamics (MD) and disulfide crosslinking studies suggest that apo-GCGR can adopt both an open and closed conformation associated with extensive contacts between the ECD and 7TM domain. The electron microscopy (EM) map of the full-length GCGR shows how a monoclonal antibody stabilizes the ECD and 7TM domain in an elongated conformation. Hydrogen/deuterium exchange (HDX) studies and MD simulations indicate that an open conformation is also stabilized by peptide ligand binding. The combined studies reveal the open/closed states of GCGR and suggest that glucagon binds to GCGR by a conformational selection mechanism.

Crystal structure-based virtual screening for novel fragment-like ligands of the human histamine H1 receptor

The recent crystal structure determinations of druggable class A G protein-coupled receptors (GPCRs) have opened up excellent opportunities in structure-based ligand discovery for this pharmaceutically important protein family. We have developed and validated a customized structure-based virtual fragment screening protocol against the recently determined human histamine H(1) receptor (H(1)R) crystal structure. The method combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. The optimized in silico screening approach was successfully applied to identify a chemically diverse set of novel fragment-like (≤22 heavy atoms) H(1)R ligands with an exceptionally high hit rate of 73%. Of the 26 tested fragments, 19 compounds had affinities ranging from 10 μM to 6 nM. The current study shows the potential of in silico screening against GPCR crystal structures to explore novel, fragment-like GPCR ligand space.

Insights into the structure of class B GPCRs

The secretin-like (class B) family of G protein-coupled receptors (GPCRs) are key players in hormonal homeostasis and are interesting drug targets for the treatment of several metabolic disorders (such as type 2 diabetes, osteoporosis, and obesity) and nervous system diseases (such as migraine, anxiety, and depression). The recently solved crystal structures of the transmembrane domains of the human glucagon receptor and human corticotropin-releasing factor receptor 1 have opened up new opportunities to study the structure and function of class B GPCRs. The current review shows how these structures offer more detailed explanations to previous biochemical and pharmacological studies of class B GPCRs, and provides new insights into their interactions with ligands.

Diazepam-bound GABAA receptor models identify new benzodiazepine binding-site ligands

Benzodiazepines exert their anxiolytic, anticonvulsant, muscle-relaxant and sedative-hypnotic properties by allosterically enhancing the action of GABA at GABA(A) receptors via their benzodiazepine-binding site. Although these drugs have been used clinically since 1960, the molecular basis of this interaction is still not known. By using multiple homology models and an unbiased docking protocol, we identified a binding hypothesis for the diazepam-bound structure of the benzodiazepine site, which was confirmed by experimental evidence. Moreover, two independent virtual screening approaches based on this structure identified known benzodiazepine-site ligands from different structural classes and predicted potential new ligands for this site. Receptor-binding assays and electrophysiological studies on recombinant receptors confirmed these predictions and thus identified new chemotypes for the benzodiazepine-binding site. Our results support the validity of the diazepam-bound structure of the benzodiazepine-binding pocket, demonstrate its suitability for drug discovery and pave the way for structure-based drug design.

Generic GPCR residue numbers – aligning topology maps while minding the gaps

Generic residue numbers facilitate comparisons of, for example, mutational effects, ligand interactions, and structural motifs. The numbering scheme by Ballesteros and Weinstein for residues within the class A GPCRs (G protein-coupled receptors) has more than 1100 citations, and the recent crystal structures for classes B, C, and F now call for a community consensus in residue numbering within and across these classes. Furthermore, the structural era has uncovered helix bulges and constrictions that offset the generic residue numbers. The use of generic residue numbers depends on convenient access by pharmacologists, chemists, and structural biologists. We review the generic residue numbering schemes for each GPCR class, as well as a complementary structure-based scheme, and provide illustrative examples and GPCR database (GPCRDB) web tools to number any receptor sequence or structure.

Molecular modeling of the second extracellular loop of G-protein coupled receptors and its implication on structure-based virtual screening.

The current study describes the validation of high‐throughput modeling procedures for the construction of the second extracellular loop (ecl2) of all nonolfactory human G Protein‐coupled receptors. Our modeling flowchart is based on the alignment of essential residues determining the particular ecl2 fold observed in the bovine rhodopsin (bRho) crystal structure. For a set of GPCR targets, the dopamine D2 receptor (DRD2), adenosine A3 receptor (AA3R), and the thromboxane A2 receptor (TA2R), the implications of including ecl2 atomic coordinates is evaluated in terms of structure‐based virtual screening accuracy: the suitability of the 3D models to distinguish between known antagonists and randomly chosen decoys using automated docking approaches. The virtual screening results of different models describing increasingly exhaustive receptor representations (seven helices only, seven helices and ecl2 loop, full model) have been compared. Explicit modeling of the ecl2 loop was found to be important in only one of three test cases whereas a loopless model was shown to be accurate enough in the two other receptors. An exhaustive comparison of ecl2 loops of 365 receptors to that of bRho suggests that explicit ecl2 loop modeling should be reserved to receptors where loop building can be guided by experimental restraints. Proteins 2008; 71:599–620.

KLIFS: A Knowledge-Based Structural Database To Navigate Kinase–Ligand Interaction Space

Protein kinases regulate the majority of signal transduction pathways in cells and have become important targets for the development of designer drugs. We present a systematic analysis of kinase-ligand interactions in all regions of the catalytic cleft of all 1252 human kinase-ligand cocrystal structures present in the Protein Data Bank (PDB). The kinase-ligand interaction fingerprints and structure database (KLIFS) contains a consistent alignment of 85 kinase ligand binding site residues that enables the identification of family specific interaction features and classification of ligands according to their binding modes. We illustrate how systematic mining of kinase-ligand interaction space gives new insights into how conserved and selective kinase interaction hot spots can accommodate the large diversity of chemical scaffolds in kinase ligands. These analyses lead to an improved understanding of the structural requirements of kinase binding that will be useful in ligand discovery and design studies.

Customizing G Protein-Coupled Receptor Models for Structure-Based Virtual Screening

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Structure-Based Discovery of Allosteric Modulators of Two Related Class B G-Protein-Coupled Receptors

Despite the availability of X‐ray crystal structure data for several members of the G‐protein‐coupled receptor (GPCR) superfamily, structure‐based discovery of GPCR ligands has been exclusively restricted to class A (rhodopsin‐like) receptors. Herein we report the identification, by a docking‐based virtual screening approach, of noncompetitive ligands for two related class B (secretin‐like) GPCRs: the glucagon receptor (GLR) and the glucagon‐like peptide 1 receptor (GLP‐1R). Starting from a knowledge‐based three‐dimensional model of the GLR, a database of 1.9 million commercially available drug‐like compounds was screened for chemical similarity to existing GLR noncompetitive antagonists and docked to the transmembrane cavity of the GLR; 23 compounds were then selected based on protein–ligand interaction fingerprints, and were then purchased and evaluated for in vitro binding to GLR and modulation of glucagon‐induced cAMP release. Two of the 23 compounds inhibited the effect of glucagon in a dose‐dependent manner, with one inhibitor exhibiting the same potency as L‐168 049, a reference noncompetitive GLR antagonist, in a whole‐cell‐based functional assay. Interestingly, one virtual hit that was inactive at the GLR was shown to bind to GLP‐1R and potentiate the response to the endogenous GLP‐1 ligand.