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Published May 2004 | public
Journal Article

Making Sense of Olfaction through Predictions of the 3-D Structure and Function of Olfactory Receptors

Abstract

We used the MembStruk first principles computational technique to predict the three-dimensional (3-D) structure of six mouse olfactory receptors (S6, S18, S19, S25, S46 and S50) for which experimental odorant recognition profiles are available for a set of 24 odorants (4–9 carbons aliphatic alcohols, acids, bromo-acids and diacids). We used the HierDock method to scan each predicted OR structure for potential odorant binding site(s) and to calculate binding energies of each odorant in these binding sites. The calculated binding affinity profiles are in good agreement with experimental activation profiles, validating the predicted 3-D structures and the predicted binding sites. For each of the six ORs, the binding site is located between trans-membrane domains (TMs) 3–6, with contributions from extracellular loops 2 and 3. In particular, we find six residue positions in TM3 and TM6 to be consistently involved in the binding modes of the odorants. Indeed, the differences in the experimental recognition profiles can be explained on the basis of these critical residues alone. These predictions are also consistent with mutation data on ligand binding for catecholamine receptors and sequence hypervariability studies for ORs. Based on this analysis, we defined amino acid patterns associated with the recognition of short aliphatic alcohols and mono-acids. Using these two sequence fingerprints to probe the alignment of 869 OR sequences from the mouse genome, we identified 34 OR sequences matching the fingerprint for aliphatic mono-acids and 36 corresponding to the recognition pattern for aliphatic alcohols. We suggest that these two sets of ORs might function as basic arrays for uniquely recognizing aliphatic alcohols and acids. We screened a library of 89 additional molecules against the six ORs and found that this set of ORs is likely to respond to aldehydes and esters with longer carbon chains than their currently known agonists. We also find that compounds associated with the flavor in foods are often among the best calculated binding affinities. This suggests that physiologic ligands for these ORs may be found among aldehydes and esters associated with flavor.

Additional Information

© 2004 Oxford University Press. Accepted February 10, 2004. We want to thank Professor Linda Buck and Dr Betina Malnic (Fred Hutchinson Cancer Research Center) for many helpful discussions about the experiments. We also want to thank Dr Michael Singer, Professor Gordon Shepherd (Yale Medical School) and Professor James Bower (University of Texas, San Antonio) for many insightful suggestions. In addition we thank Mr Spencer Hall for helpful discussions. This research was initiated with support by an ARO-MURI grant (Dr Robert Campbell) and completed with funding from NIHBRGRO1-GM625523, NIHR29AI40567 and NIH-HD36385. The computational facilities were provided by a SUR grant from IBM and a DURIP grant from ARO. The facilities of the Materials and Process Simulation Center are also supported by DURIP-ONR, DOE (ASCI ASAP), NSF, MURI-ONR, General Motors, ChevronTexaco, Seiko–Epson, Beckman Institute and Asahi Kasei.

Additional details

Created:
August 19, 2023
Modified:
October 24, 2023