The neurotransmitter serotonin (5-hydroxytryptamine) is a well-established modulator of energy balance. Both pharmacological and genetic evidence implicate the serotonin 2C receptor (5-HT(2C)R) as a critical receptor mediator of serotonin's effects on ingestive behavior. Here we characterized the effect of the novel and selective 5-HT(2C)R agonist BVT.X on energy balance in obese and lean mice and report that BVT.X significantly reduces acute food intake without altering locomotor activity or oxygen consumption. In an effort to elucidate the mechanism of this effect, we examined the chemical phenotype of 5-HT(2C)R-expressing neurons in a critical brain region affecting feeding behavior, the arcuate nucleus of the hypothalamus. We show that 5-HT(2C)Rs are coexpressed with neurons containing proopiomelanocortin, known to potently affect appetite, in the arcuate nucleus of the hypothalamus of the mouse. We then demonstrate that prolonged infusion with BVT.X in obese mice significantly increases Pomc mRNA and reduces body weight, percent body fat, and initial food intake. To evaluate the functional importance of melanocortin circuitry in the effect of BVT.X on ingestive behavior, we assessed mice with disrupted melanocortin pathways. We report that mice lacking the melanocortin 4 receptor are not responsive to BVT.X-induced hypophagia, demonstrating that melanocortins acting on melanocortin 4 receptor are a requisite downstream pathway for 5-HT(2C)R agonists to exert effects on food intake. The data presented here not only indicate that the novel 5-HT(2C)R agonist BVT.X warrants further investigation as a treatment for obesity but also elucidate specific neuronal pathways potently affecting energy balance through which 5-HT(2C)R agonists regulate ingestive behavior.

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A BSTRACTOpioid receptors interact with a variety of ligands, including endogenous peptides, opiates, and thousands of synthetic compounds with different structural scaffolds. In the absence of experimental structures of opioid receptors, theoretical modeling remains an important tool for structurefunction analysis. The combination of experimental studies and modeling approaches allows development of realistic models of ligand-receptor complexes helpful for elucidation of the molecular determinants of ligand affi nity and selectivity and for understanding mechanisms of functional agonism or antagonism. In this review we provide a brief critical assessment of the status of such theoretical modeling and describe some common problems and their possible solutions. Currently, there are no reliable theoretical methods to generate the models in a completely automatic fashion. Models of higher accuracy can be produced if homology modeling, based on the rhodopsin X-ray template, is supplemented by experimental structural constraints appropriate for the active or inactive receptor conformations, together with receptor-specifi c and ligand-specifi c interactions. The experimental constraints can be derived from mutagenesis and cross-linking studies, correlative replacements of ligand and receptor groups, and incorporation of metal binding sites between residues of receptors or receptors and ligands. This review focuses on the analysis of similarity and differences of the refi ned homology models of m , d , and k -opioid receptors in active and inactive states, emphasizing the molecular details of interaction of the receptors with some representative peptide and nonpeptide ligands, underlying the multiple modes of binding of small opiates, and the differences in binding modes of agonists and antagonists, and of peptides and alkaloids.K EYWORDS: ligand docking , modeling , opioid receptors , opioid ligands , pharmacophore model INTRODUCTIONClinical interest in opioid receptors (ORs) is related to the development of strong analgesics without potential for abuse or adverse side effects. This task, however, cannot be accomplished without understanding the differences in the OR subtypes as well as the modes of interactions of drugs/ ligands with these receptors.Research on ORs was signifi cantly advanced by the cloning of d -opioid (DOR), m -opioid (MOR), and k -opioid (KOR) receptors in the early 1990s. 1 , 2 Sequence comparison confi rmed that ORs belong to the rhodopsin-like family of G-protein-coupled receptors (GPCRs). 1 ORs are composed of a core domain of 7 transmembrane (TM) a -helices and an adjacent, peripheral helix 8 (IL4), are connected by 3 extracellular (EL1, EL2, EL3) and 3 intracellular (IL1, IL2, IL3) loops, and contain glycosylated N-terminal and palmitoylated C-terminal domains of different sizes. ORs demonstrate high sequence identity in their TM domain (73%-76%) and in ILs (63%-66%) and large divergence in N-and C-terminal domains and ELs (34%-40% identity). ORs are activated by either endogenous peptides o...

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology.org/ontologies/1533. BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens.