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Predicting the Receptive Range of Olfactory Receptors

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  • Rafi Haddad
  • Liran Carmel
  • Noam Sobel
  • David Harel

Abstract

Although the family of genes encoding for olfactory receptors was identified more than 15 years ago, the difficulty of functionally expressing these receptors in an heterologous system has, with only some exceptions, rendered the receptive range of given olfactory receptors largely unknown. Furthermore, even when successfully expressed, the task of probing such a receptor with thousands of odors/ligands remains daunting. Here we provide proof of concept for a solution to this problem. Using computational methods, we tune an electronic nose to the receptive range of an olfactory receptor. We then use this electronic nose to predict the receptors' response to other odorants. Our method can be used to identify the receptive range of olfactory receptors, and can also be applied to other questions involving receptor–ligand interactions in non-olfactory settings.: A key goal in biology is to identify specific ligands for specific receptors. One example is where the ligand is a drug. In turn, in the olfactory system the ligand is the odorant that binds to olfactory receptors. There are many olfactory receptor types, and which odorants will activate which receptors remains largely unknown. One way to answer this is to systematically vary the molecular features of ligands and to measure the olfactory receptor response. However, the vast number of molecular features and their combinations renders such an effort potentially unsolvable. Here, rather than looking at the trees (each molecular feature), we looked at the forest (the smell they generate). We used a device called an electronic nose that generates a patterned response to odorants. We then obtained the response to a set of odorants that are known to activate a particular olfactory receptor, and we used this pattern to predict the response of that receptor to other odorants. We found that, on average in three out of four we could predict the response of olfactory receptors. This result provides a new method for probing the olfactory system, and also suggests a novel method for identifying potential drugs.

Suggested Citation

  • Rafi Haddad & Liran Carmel & Noam Sobel & David Harel, 2008. "Predicting the Receptive Range of Olfactory Receptors," PLOS Computational Biology, Public Library of Science, vol. 4(2), pages 1-8, February.
  • Handle: RePEc:plo:pcbi00:0040018
    DOI: 10.1371/journal.pcbi.0040018
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    Cited by:

    1. Rafi Haddad & Abebe Medhanie & Yehudah Roth & David Harel & Noam Sobel, 2010. "Predicting Odor Pleasantness with an Electronic Nose," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-11, April.

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