Pred-O3, a web server to predict molecules, olfactory receptors and odor relationships

Author:

Ollitrault Guillaume1,Achebouche Rayane1,Dreux Antoine1,Murail Samuel1,Audouze Karine2ORCID,Tromelin Anne3,Taboureau Olivier1ORCID

Affiliation:

1. Inserm U1133, CNRS UMR 8251, Université Paris Cité , Paris , France

2. Inserm UMR S-1124, Université Paris Cité , Paris , France

3. Centre des Sciences du Goût et de l’Alimentation, CNRS, INRAE, Institut Agro, Université de Bourgogne , F-21000  Dijon , France

Abstract

Abstract The sense of smell is a biological process involving volatile molecules that interact with proteins called olfactory receptors to transmit a nervous message that allows the recognition of a perceived odor. However, the relationships between odorant molecules, olfactory receptors and odors (O3) are far from being well understood due to the combinatorial olfactory codes and large family of olfactory receptors. This is the reason why, based on 5802 odorant molecules and their annotations to 863 olfactory receptors (human) and 7029 odors and flavors annotations, a web server called Pred-O3 has been designed to provide insights into olfaction. Predictive models based on Artificial Intelligence have been developed allowing to suggest olfactory receptors and odors associated with a new molecule. In addition, based on the encoding of the odorant molecule's structure, physicochemical features related to odors and/or olfactory receptors are proposed. Finally, based on the structural models of the 98 olfactory receptors a systematic docking protocol can be applied and suggest if a molecule can bind or not to an olfactory receptor. Therefore, Pred-O3 is well suited to aid in the design of new odorant molecules and assist in fragrance research and sensory neuroscience. Pred-O3 is accessible at ‘ https://odor.rpbs.univ-paris-diderot.fr/’.

Funder

Agence Nationale de la Recherche

Publisher

Oxford University Press (OUP)

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