15 research outputs found

    Beyond Modeling: All-Atom Olfactory Receptor Model Simulations

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    Olfactory receptors (ORs) are a type of GTP-binding protein-coupled receptor (GPCR). These receptors are responsible for mediating the sense of smell through their interaction with odor ligands. OR-odorant interactions marks the first step in the process that leads to olfaction. Computational studies on model OR structures can generate focused and novel hypotheses for further bench investigation by providing a view of these interactions at the molecular level beyond inferences that are drawn merely from static docking. Here we have shown the specific advantages of simulating the dynamic environment associated with OR-odorant interactions. We present a rigorous protocol which ranges from the creation of a computationally derived model of an olfactory receptor to simulating the interactions between an OR and an odorant molecule. Given the ubiquitous occurrence of GPCRs in the membranes of cells, we anticipate that our OR-developed methodology will serve as a model for the computational structural biology of all GPCRs

    Integrated olfactory receptor and microarray gene expression databases

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    <p>Abstract</p> <p>Background</p> <p>Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD) to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB), which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction.</p> <p>Description</p> <p>ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data.</p> <p>Conclusion</p> <p>ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.</p

    A Framework for Exploring Functional Variability in Olfactory Receptor Genes

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    BACKGROUND: Olfactory receptors (ORs) are the largest gene family in mammalian genomes. Since nearly all OR genes are orphan receptors, inference of functional similarity or differences between odorant receptors typically relies on sequence comparisons. Based on the alignment of entire coding region sequence, OR genes are classified into families and subfamilies, a classification that is believed to be a proxy for OR gene functional variability. However, the assumption that overall protein sequence diversity is a good proxy for functional properties is untested. METHODOLOGY: Here, we propose an alternative sequence-based approach to infer the similarities and differences in OR binding capacity. Our approach is based on similarities and differences in the predicted binding pockets of OR genes, rather than on the entire OR coding region. CONCLUSIONS: Interestingly, our approach yields markedly different results compared to the analysis based on the entire OR coding-regions. While neither approach can be tested at this time, the discrepancy between the two calls into question the assumption that the current classification reliably reflects OR gene functional variability

    Integrated olfactory receptor and microarray gene expression databases-2

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    <p><b>Copyright information:</b></p><p>Taken from "Integrated olfactory receptor and microarray gene expression databases"</p><p>http://www.biomedcentral.com/1471-2105/8/231</p><p>BMC Bioinformatics 2007;8():231-231.</p><p>Published online 30 Jun 2007</p><p>PMCID:PMC1955752.</p><p></p>resent), and statistical P-value are provided. For each probe set, the target gene name is provided in the column "ORDB_name" (corresponding to the name used in SenseLab). The hyperlinks on the gene name lead to the detail page of chemosensory receptors in ORDB (see Figure 1). The PubMed_IDs are hyperlinks directing users to original publications related to the genes
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