Abstract
The perception of aroma mixtures is based on interactions beginning at the peripheral olfactory system, but the process remains poorly understood. The perception of a mixture of ethyl isobutyrate (Et-iB, strawberry-like odor) and ethyl maltol (Et-M, caramel-like odor) was investigated previously in both human and animal studies. In those studies, the binary mixture of Et-iB and Et-M was found to be configurally processed. In humans, the mixture was judged as more typical of a pineapple odor, similar to allyl hexanoate (Al-H, pineapple-like odor), than the odors of the individual components. To explore the key features of this aroma blend, we developed an in silico approach based on molecules having at least one of the odors—strawberry, caramel or pineapple. A dataset of 293 molecules and their related odors was built. We applied the notion of a “social network” to describe the network of the odors. Additionally, we explored the structural properties of the molecules in this dataset. The network of the odors revealed peculiar links between odors, while the structural study emphasized key characteristics of the molecules. The association between “strawberry” and “caramel” notes, as well as the structural diversity of the “strawberry” molecules, were notable. Such elements would be key to identifying potential odors/odorants to form aroma blends.
Highlights
The first step of odor detection is the interaction between the odorants and the olfactory receptors (ORs) in the nose [1]
We developed a statistical analysis method based on several molecular descriptors; we applied a pharmacophore approach to explore the structural similarities between the STR/caramel-like odor (CAR)/pineapple-like odor (PNA) molecules
The selection of the molecules was based on the occurrence of the simple odor notes “strawberry” (STR), “caramellic” (CAR) and “pineapple” (PNA) in their odor description
Summary
The first step of odor detection is the interaction between the odorants and the olfactory receptors (ORs) in the nose [1]. The perception of an odor’s quality is a result of combinatorial coding [2], whereby an odorant can interact with several ORs, while ORs can be activated by several structurally diverse odorants. Odors perceived in our environment are mainly the result of mixtures of odorants [5]. It has been theorized and experimentally confirmed that the olfactory processing of a mixture of odorants can produce two types of percepts: (i) heterogeneous percepts in which the specific odor qualities of several individual odorants can be identified within the mixture; or (ii) homogeneous percepts in which a single odor is perceived from the mixture [5,6]. Odor blending occurs if a mixture of molecules A and B carrying
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