The perception of odors remains in many ways a mystery. Our research team has perfected a new protocol for predicting the activation of an olfactory receptor by an odor molecule. A step towards the development of a biomimetic nose.
Combining machine learning with molecular modeling and in vitro assays, we show how artificial intelligence can infer ligands activity based on physical and chemical properties.
Our project “From a molecule to an odor: decoding odor perception through a computational microscope” has been granted 5.5 million core hours on the CINES Occigen supercomputer for the period of May 2018 – April 2019, through the 2018-2019 DARI-A4 call for proposals by GENCI (Grand Equipement National de Calcul Intensif, http://www.genci.fr).
Molecular modeling predicts the activation of a G protein-coupled olfactory receptor in which a polymorphism influences food preference.
We here show for the first time that the pattern of piglet castration in Europe can be tracked down to 2 interacting amino acids within the OR7D4 receptor.
Ang. Chem. Int. Ed. (2018) : https://doi.org/10.1002/anie.201713065
“Draw me an odor” in UCANews : https://t.co/xabS0tHRyt
Our research project Prediscent has been awarded by Maison de la Modélisation, de la Simulation et des interactions and by Centre de Créativité et d’Innovation en Sciences des odorants (UCA Idex). It aims to predict the odor and/or the physiological response induced by a molecule using its chemical structure as input.
UCA News : The Pierre Laffitte prize rewards excellence and innovation in academic research areas in partnership with the industry.
Caroline was awarded for her talk ‘Smelling in silico‘ about her promising research!
The project named ” Cracking the code of olfactory receptor activation using computational tools ” submitted during the third call for proposals of the Academy 2 – Complex Systems has been selected by the Scientific Council.
The webserver associated to the article published in J. Comput. Chem. is now online
“Update of the ATTRACT force field for the prediction of protein-protein binding affinity.” J.B. Chéron, M. Zacharias, S. Antonczak, S. Fiorucci. J. Comput. Chem. 2017, 38(21), 1887-1890. Abstract / PDF
Un reportage sur les activités de l’équipe publié dans le journal du CNRS de Mai 2017: