Editorial [Hot topic: In Silico Approaches in G Protein-Coupled Receptors (GPCRs) Drug Discovery: Quo Vadis? (Executive Editor: Stefano Moro)]

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.