CE07 - Chimie moléculaire et procédés associés pour une chimie durable

Rational design of chemosensory compounds targeting smell, taste and emotion – chemosim

ChEmoSim

Rational design of chemosensory compounds targeting smells, tastes and emotions

Objectives

ChEmoSim is a fundamental and highly multidisciplinary project. It gathers academic experts in computational modeling, protein engineering, neuroscience, and a company expert in sensory analysis. The research hypothesis is that numerical models can crack the code of chemosensory sensations. To achieve this aim, ChEmoSim proposes to use ligand-based and receptor-based numerical models to tentatively decode i/ how our brain uses receptors to perceive its chemical environment, and ii/ how chemical senses are encoded within odorants and tastants (bitter and sweet) chemical properties. The properties to be optimized can either belong to the perceptive field (smell and taste) but also to the hedonic field (like or dislike), itself wired to our emotions. Here, in silico models (machine learning and molecular modeling) will process data coming from different readouts, ranging from cellular to sensory levels. Based on these modern computational methods, we will improve experimental efficiency, better understand how our brain processes its chemical environment, and enhance innovation in flavor and fragrance research.

In ChEmoSim, each predicted property by the numerical models is then assessed by a suited experimental technique:
- Smells cannot be directly observed at the receptor level, they will be assessed by quantitative sensory analysis on humans by sensory analysis experiments at Expression Parfumées (Grasse), the industrial partner, by experts in the evaluation of human senses (sight, smell, taste, touch and hearing) for the purposes of evaluating consumer products.
- Odorant receptor blockers might affect perception. Such chemicals, once discovered or synthesized at ICN (Nice) by experts in organic synthesis will be assessed in vitro at CSGA (Dijon) by experts in functionnal assays of chemosensory receptors, and tested in mixture with bad odors on human panels by the industrial partner.
- Bitter and sweet compounds cannot be directly tested on humans for obvious safety reasons. They will be functionally assessed. Once done, interesting (blocker or enhancer) compounds will be passed to colleagues outside of this project for toxicology and sensory tests.
- Emotions have naturally to be evaluated on humans. They will be measured at CRNL (Lyon), by experts in cognitive neuroscience.

Novel scaffold of natural compound eliciting sweet taste revealed by machine learning. C. Bouysset, C. Belloir, S. Antonczak, L. Briand, S. Fiorucci. Food Chem., 2020, 324, 126864.

Moranges, M., Rouby, C., Plantevit, M., & Bensafi, M. (2021). Explicit and implicit measures of emotions: Data-science might help to account for data complexity and heterogeneity. Food Quality and Preference, 92, 104181.

Dantec, M., Mantel, M., Lafraire, J., Rouby, C., & Bensafi, M. (2021). On the contribution of the senses to food emotional experience. Food Quality and Preference, 92, 104120.

Nicolas, S., & Bensafi, M. (2021). A historical review of olfactometry. L’Année psychologique, 121(3), 311-351.

Functional Molecular Switches of Mammalian G Protein-Coupled Bitter-Taste Receptors. J. Topin, C. Bouysset, J. Pacalon, Y. Kim, M. Rhyu, S. Fiorucci, J. Golebiowski. Cell. Mol. Life Sci., 2021, online (DOI : doi.org/10.1007/s00018-021-03968-7)

Besides the fundamental interest of understanding the mechanisms behind chemosensory perception which represents a breakthrough by itself, we will develop a tool capable of predicting the chemosensory property of novel molecules. Indeed, understanding how chemicals code for a certain type of odor/taste/emotion is a fundamental step for the development of reliable Structure-Property Relationships.

- Malodors blockers: The fight against malodors in safe areas will benefit from our research. Blockers of TAARs can be useful for scientists or medical doctors working in the field of forensic science and facing dead bodies for example. The same principles apply for thiols for examples. They are detected by odorant receptors and are generally wired to an aversive behavior. The discovery of blockers or modifiers would help increase well-being in olfactory polluted areas by cooking smells for example.

- Food biology and food science: Without being fully aware of it, we are daily confronted to odorant molecules. It is estimated that between 75% and 95% of what we commonly think of as taste is actually retronasal smell. Our project will identify new flavoring compounds and will be highly beneficial in food science. The identification of new candidates for sweeteners or blockers of bitter taste is central in the field of food industry. Non-caloric sweeteners are mandatory for the design of healthy food. Concerning the bitter compounds, we will mostly try to focus on bitter-taste receptors antagonists, which would for example be beneficial for the pharmacology industry as many oral drugs have a strong bitter taste.

Novel scaffold of natural compound eliciting sweet taste revealed by machine learning. C. Bouysset, C. Belloir, S. Antonczak, L. Briand, S. Fiorucci. Food Chem., 2020, 324, 126864.

Moranges, M., Rouby, C., Plantevit, M., & Bensafi, M. (2021). Explicit and implicit measures of emotions: Data-science might help to account for data complexity and heterogeneity. Food Quality and Preference, 92, 104181.

Dantec, M., Mantel, M., Lafraire, J., Rouby, C., & Bensafi, M. (2021). On the contribution of the senses to food emotional experience. Food Quality and Preference, 92, 104120.

Nicolas, S., & Bensafi, M. (2021). A historical review of olfactometry. L’Année psychologique, 121(3), 311-351.

Functional Molecular Switches of Mammalian G Protein-Coupled Bitter-Taste Receptors. J. Topin, C. Bouysset, J. Pacalon, Y. Kim, M. Rhyu, S. Fiorucci, J. Golebiowski. Cell. Mol. Life Sci., 2021, online (DOI : doi.org/10.1007/s00018-021-03968-7)

This project is fundamental and highly multidisciplinary. It gathers academic experts in computational modeling, protein engineering, behavioral neuroscience, and a company expert in sensory analysis. Their research hypothesis is that numerical models can crack the code of chemosensory sensations. The project aims at predicting or synthesizing chemicals targeting given smells, tastes, or modulating our mood or emotions. They will use ligand-based and receptor-based numerical models to tentatively decode i/ how our brain uses receptors to perceive its chemical environment, and ii/ how chemical senses are encoded within odorants and tastants chemical properties. These properties can either belong to the perceptive field (smell and taste) but also to the hedonic field (like or dislike), itself wired to our mood or emotions. Here, in silico models will process data coming from different level, ranging from cellular to sensory levels.

Project coordinator

Sebastien Fiorucci (Université Nice Sophia Antipolis - Institut de Chimie de Nice)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

UNS - ICN Université Nice Sophia Antipolis - Institut de Chimie de Nice
CSGA CENTRE DES SCIENCES DU GOUT ET DE L'ALIMENTATION - UMR 6265 - UMR A1324 - uB 80
CRNL Centre de Recherche en Neurosciences de Lyon
Expressions Parfumées / direction générale

Help of the ANR 443,920 euros
Beginning and duration of the scientific project: January 2020 - 48 Months

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