Roles of residues 3 and 4 in cyclic tetrapeptide ligand recognition by the Κ -opioid receptor

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75723/1/j.1399-3011.2005.00220.x.pd

Design of high affinity cyclic pentapeptide ligands for Κ-opioid receptors

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73319/1/j.1399-3011.2005.00295.x.pd

Nociceptin receptor antagonist SB 612111 decreases high fat diet binge eating

Binge eating is a dysregulated form of feeding behavior that occurs in multiple eating disorders including binge-eating disorder, the most common eating disorder. Feeding is a complex behavioral program supported through the function of multiple brain regions and influenced by a diverse array of receptor signaling pathways. Previous studies have shown the overexpression of the opioid neuropeptide nociceptin (orphanin FQ, N/OFQ) can induce hyperphagia, but the role of endogenous nociceptin receptor (NOP) in naturally occurring palatability-induced hyperphagia is unknown. In this study we adapted a simple, replicable form of binge eating of high fat food (HFD). We found that male and female C57BL/6J mice provided with daily one-hour access sessions to HFD eat significantly more during this period than those provided with continuous 24 hour access. This form of feeding is rapid and entrained. Chronic intermittent HFD binge eating produced hyperactivity and increased light zone exploration in the open field and light-dark assays respectively. Treatment with the potent and selective NOP antagonist SB 612111 resulted in a significant dose-dependent reduction in binge intake in both male and female mice, and, unlike treatment with the serotonin selective reuptake inhibitor fluoxetine, produced no change in total 24-hour food intake. SB 612111 treatment also significantly decreased non-binge-like acute HFD consumption in male mice. These data are consistent with the hypothesis that high fat binge eating is modulated by NOP signaling and that the NOP system may represent a promising novel receptor to explore for the treatment of binge eating

Formalization, Annotation and Analysis of Diverse Drug and Probe Screening Assay Datasets Using the BioAssay Ontology (BAO)

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