Structure of the human histamine H1 receptor complex with doxepin

The biogenic amine histamine is an important pharmacological mediator involved in pathophysiological processes such as allergies and inflammations. Histamine H(1) receptor (H(1)R) antagonists are very effective drugs alleviating the symptoms of allergic reactions. Here we show the crystal structure of the H(1)R complex with doxepin, a first-generation H(1)R antagonist. Doxepin sits deep in the ligand-binding pocket and directly interacts with Trp?428(6.48), a highly conserved key residue in G-protein-coupled-receptor activation. This well-conserved pocket with mostly hydrophobic nature contributes to the low selectivity of the first-generation compounds. The pocket is associated with an anion-binding region occupied by a phosphate ion. Docking of various second-generation H(1)R antagonists reveals that the unique carboxyl group present in this class of compounds interacts with Lys?191(5.39) and/or Lys?179(ECL2), both of which form part of the anion-binding region. This region is not conserved in other aminergic receptors, demonstrating how minor differences in receptors lead to pronounced selectivity differences with small molecules. Our study sheds light on the molecular basis of H(1)R antagonist specificity against H(1)R.     

Structure of the human κ-opioid receptor in complex with JDTic

Opioid receptors mediate the actions of endogenous and exogenous opioids on many physiological processes, including the regulation of pain, respiratory drive, mood, and--in the case of κ-opioid receptor (κ-OR)--dysphoria and psychotomimesis. Here we report the crystal structure of the human κ-OR in complex with the selective antagonist JDTic, arranged in parallel dimers, at 2.9?? resolution. The structure reveals important features of the ligand-binding pocket that contribute to the high affinity and subtype selectivity of JDTic for the human κ-OR. Modelling of other important κ-OR-selective ligands, including the morphinan-derived antagonists norbinaltorphimine and 5'-guanidinonaltrindole, and the diterpene agonist salvinorin A analogue RB-64, reveals both common and distinct features for binding these diverse chemotypes. Analysis of site-directed mutagenesis and ligand structure-activity relationships confirms the interactions observed in the crystal structure, thereby providing a molecular explanation for κ-OR subtype selectivity, and essential insights for the design of compounds with new pharmacological properties targeting the human κ-OR.     

Structure of the nociceptin/orphanin FQ receptor in complex with a peptide mimetic

Members of the opioid receptor family of G-protein-coupled receptors (GPCRs) are found throughout the peripheral and central nervous system, where they have key roles in nociception and analgesia. Unlike the 'classical' opioid receptors, δ, κ and μ (δ-OR, κ-OR and μ-OR), which were delineated by pharmacological criteria in the 1970s and 1980s, the nociceptin/orphanin FQ (N/OFQ) peptide receptor (NOP, also known as ORL-1) was discovered relatively recently by molecular cloning and characterization of an orphan GPCR. Although it shares high sequence similarity with classical opioid GPCR subtypes (～60%), NOP has a markedly distinct pharmacology, featuring activation by the endogenous peptide N/OFQ, and unique selectivity for exogenous ligands. Here we report the crystal structure of human NOP, solved in complex with the peptide mimetic antagonist compound-24 (C-24) (ref. 4), revealing atomic details of ligand-receptor recognition and selectivity. Compound-24 mimics the first four amino-terminal residues of the NOP-selective peptide antagonist UFP-101, a close derivative of N/OFQ, and provides important clues to the binding of these peptides. The X-ray structure also shows substantial conformational differences in the pocket regions between NOP and the classical opioid receptors κ (ref. 5) and μ (ref. 6), and these are probably due to a small number of residues that vary between these receptors. The NOP-compound-24 structure explains the divergent selectivity profile of NOP and provides a new structural template for the design of NOP ligands.     

Revisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer

The study of animal foraging behaviour is of practical ecological importance, and exemplifies the wider scientific problem of optimizing search strategies. Lévy flights are random walks, the step lengths of which come from probability distributions with heavy power-law tails, such that clusters of short steps are connected by rare long steps. Lévy flights display fractal properties, have no typical scale, and occur in physical and chemical systems. An attempt to demonstrate their existence in a natural biological system presented evidence that wandering albatrosses perform Lévy flights when searching for prey on the ocean surface. This well known finding was followed by similar inferences about the search strategies of deer and bumblebees. These pioneering studies have triggered much theoretical work in physics (for example, refs 11, 12), as well as empirical ecological analyses regarding reindeer, microzooplankton, grey seals, spider monkeys and fishing boats. Here we analyse a new, high-resolution data set of wandering albatross flights, and find no evidence for Lévy flight behaviour. Instead we find that flight times are gamma distributed, with an exponential decay for the longest flights. We re-analyse the original albatross data using additional information, and conclude that the extremely long flights, essential for demonstrating Lévy flight behaviour, were spurious. Furthermore, we propose a widely applicable method to test for power-law distributions using likelihood and Akaike weights. We apply this to the four original deer and bumblebee data sets, finding that none exhibits evidence of Lévy flights, and that the original graphical approach is insufficient. Such a graphical approach has been adopted to conclude Lévy flight movement for other organisms, and to propose Lévy flight analysis as a potential real-time ecosystem monitoring tool. Our results question the strength of the empirical evidence for biological Lévy flights.