Current Pharmaceutical Design - Volume 15, Issue 35, 2009

How do we communicate with the outside world? How are our senses of vision, smell, taste and pain controlled at the cellular and molecular levels? What causes medical conditions like allergies, hypertension, depression, obesity and various central nervous system disorders? G protein-coupled receptors (GPCRs) provide a major part of the answer to all of these questions. GPCRs constitute the largest family of cell-surface receptors and in humans are encoded by more than 900 genes. GPCRs convert extracellular messages into intracellular responses and are involved in essentially all physiological processes. GPCR dysfunction results in numerous human disorders, and over 50% of all prescription drugs on the market today directly or indirectly target GPCRs. While knowledge of a protein's structure furnishes important information for understanding its function and for drug design, progress in solving GPCR structures has been slow. Nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography are the two major techniques used to determine protein structures. NMR spectroscopy has the advantages that the protein does not need to be crystallized and dynamical information can be extracted. However, high concentrations of dissolved proteins are needed; and as yet no complete GPCR structure has been solved by the method. Crystal structures are spectacular central organizing models for just about everything you can determine about a protein. Mutants, homologs, interactors, ligands -- if you have a structure to hang them on, understanding them becomes much easier. For drug development a 3D structure can be powerful advice for chemistry efforts, suggesting directions to build out a molecule or to avoid changing. Because they are large, membrane-bound proteins with lots of floppy loops, GPCRs are particularly challenging structure targets, and they are extremely difficult to crystallize. In fact, only a few GPCRs, bovine rhodopsin, human β2- and β1- adrenergic receptors and, very recently, the human A2A adenosine receptor have been solved. Homology models of GPCRs, especially those supported by experimental data, and molecular docking experiments have been widely used in computational medicinal chemistry to guide site-directed mutagenesis and for drug discovery purposes, pursued also through virtual screenings and through the generation of docking-based quantitative structure-activity relationship (QSAR) models. Encouraging results led to a general acceptance of these models, which, however, although corroborated by indirect experimental evidence could not be ultimately validated. The recent publication of the crystal structure of the human A2A adenosine receptor conclusively that GPCRs indeed share a pretty structurally conserved 7TM core, strongly supporting the body of literature and the hypotheses that were built on the basis of homology modeling and molecular docking. Nowadays, GPCR computational medicinal chemistry brings together the most powerful concepts in modern chemistry, biology and pharmacology, linking medicinal chemistry with genomics and proteomics. Following our experience, both ligandbased and structure-based approaches to drug discovery in the absence, but probably also in the presence, of the real 3Dstructures require a multidisciplinary approach, where molecular models represent a structural context to efficiently integrate experimental data and inferences derived from molecular biological, biophysical, bioinformatic, pharmacological and organic chemical methods. Although not always achievable, the success of a synergistic effect among these disciplines is highly dependent on the experimental design. Synergy is best achieved when mutations are structurally interpretable, structural hypotheses are experimentally testable, ligands are well characterized pharmacologically, and the necessary chemical modifications of the ligands are feasible.

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the β1- and β2-adrenergic receptors and the A2A adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A2A adenosine receptor, the first ‘critical assessment of GPCR structural modeling and docking’ has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

G protein-coupled receptors (GPCRs) are a large superfamily of signaling proteins expressed on the plasma membrane. They are involved in a wide range of physiological processes and, therefore, are exploited as drug targets in a multitude of therapeutic areas. In this extent, knowledge of structural and functional properties of GPCRs may greatly facilitate rational design of modulator compounds. Solution and solid-state nuclear magnetic resonance (NMR) spectroscopy represents a powerful method to gather atomistic insights into protein structure and dynamics. In spite of the difficulties inherent the solution of the structure of membrane proteins through NMR, these methods have been successfully applied, sometimes in combination with molecular modeling, to the determination of the structure of GPCR fragments, the mapping of receptor-ligand interactions, and the study of the conformational changes associated with the activation of the receptors. In this review, we provide a summary of the NMR contributions to the study of the structure and function of GPCRs, also in light of the published crystal structures.

G Protein-Coupled Receptors (GPCRs) are the most targeted group of proteins for the development of therapeutic drugs. Until the last decade, structural information about this family of membrane proteins was relatively scarce, and their mechanisms of ligand binding and signal transduction were modeled on the assumption that GPCRs existed and functioned as monomeric entities. New crystal structures of native and engineered GPCRs, together with important biochemical and biophysical data that reveal structural details of the activation mechanism(s) of this receptor family, provide a valuable framework to improve dynamic molecular models of GPCRs with the ultimate goal of elucidating their allostery and functional selectivity. Since the dynamic movements of single GPCR protomers are likely to be affected by the presence of neighboring interacting subunits, oligomeric arrangements should be taken into account to improve the predictive ability of computer-assisted structural models of GPCRs for effective use in drug design.

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.

In silico (or virtual) screening has become a common practice in current computer-aided drug design efforts. However, application to hit discovery in the G Protein-Coupled Receptors (GPCRs) arena was until recently hampered by the paucity of crystal structures available for this important class of pharmaceutical targets, forcing practitioners in the field to rely on GPCR models derived either ab initio or through homology modeling approaches. In this work we describe the EPIX in silico screening workflow which consists of the following stages: (1) Target modeling; (2) Preparation of screening library; (3) Docking; (4) Binding mode selection; (5) Scoring; (6) Consensus scoring and (7) Selection of virtual hits. This workflow was applied to the virtual screening of 13 GPCRs (5 biogenic amine receptors, 5 peptide receptors, 1 lipid receptor, 1 purinergic receptor and 1 cannabinoid receptor). Hit rates vary between 4% and 21% with higher hit rates usually obtained for biogenic amines and lower hits rates for peptide receptors. These data are analyzed in the context of the available experimental information (i.e., mutational data), the model (i.e., binding site location, and type of interactions) and the screening library. Specific examples are discussed in more detail as well as the future directions and challenges of this approach to in silico screening.

The development of ligands for the A3 adenosine receptor (AR) has been directed mainly by traditional medicinal chemistry, but the influence of structure-based approaches is increasing. Rhodopsin-based homology modeling had been used for many years to obtain three-dimensional models of the A3AR, and different A3AR models have been published describing the hypothetical interactions with known A3AR ligands having different chemical scaffolds. The recently published structure of the human A2AAR provides a new template for GPCR modeling, however even use of the A2AAR as a template for modeling other AR subtypes is still imprecise. The models compared here are based on bovine rhodopsin, the human β2-adrenergic receptor, and the A2AAR as templates. The sequence of the human A3AR contains only one cysteine residue (Cys166) in the second extracellular loop (EL2), which putatively forms a conserved disulfide bridge with the respective cysteine residues of TM3 (Cys83). Homology models of the A3AR have been helpful in providing structural hypotheses for the design of new ligands. Site-directed mutagenesis of the A3AR shows an important role in ligand recognition for specific residues in TM3, TM6 and TM7.