Study of feline olfactory receptors using a computational reverse chemical ecology approach
Fri-P2-097
Presented by: Rajesh Durairaj
Semiochemicals can induce physiological and behavioural responses using chemical communication in mammals. These molecules can be detected by the olfactory receptor (OR) in the main olfactory epithelium (MOE) and trigger signals to the olfactory bulb and to the brain regions. Several computational studies have been reported about the structural modelling of mouse and human ORs and the receptor deorphanization from the ligands. However, the experimental structures of ORs are unavailable. Therefore, in silico studies are necessary to build the OR models. In this study, we aimed to deorphanize ORs of cats using semiochemicals and related odorants. We used a computational “reverse chemical ecology strategy” on cat ORs to analyze the conservation, phylogeny, and topology and to build models to identify their ligands. We have selected 54 deorphanized human ORs and found the feline orthologs using 10 human ORs which are known to bind at least 5 semiochemicals and odorants. The present results showed that cat ORs sequences share an average of 80% to 90% identity with other mammals. Phylogenetic studies showed the evolution between cat ORs and other mammalian orthologs of the 10 selected ORs. Further, the cat ORs were screened based on the 7-transmembrane (TM) OUT topology analysis. Then, the 6 selected OR sequences were modelled using multi-template modeling and 3 of them (OR1A1, OR2W1, OR52D1) were validated by dynamics simulations with a lipid membrane (DPPC). The virtual screening and docking study showed that the cat ORs depicted potential interactions with the ligands of the human ORs and the ligands of IRSEA patents CAP, FFP, and FIS. The androstadienone, linoleic acid, and oleic acid were evaluated as best-fit ligands by the binding-free energy, H-bonds, and 2D residual interactions. The results revealed that the best-fit ligands would be suitable for deorphanizing the receptor models, which will improve the understanding of chemical communication in cats.