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Understanding olfaction process at a microscopic or molecular level needs more elucidation of the multiple stages involved in the olfaction mechanism. A worth full elucidation and a better understanding of this molecular mechanism, a necessary preamble should be achieved. The content of this work is a preamble for that. A study of the mouse and human olfactory receptors activation in response to two nitro musks stimuli, which are the musk xylol and the musk ketone, are considered here, first, for their wide expanded use in perfumery, but also to show some particular aspects of this process in the case of these two stimuli, which could help to deduce more details and more general aspects in the global olfactory mechanism. A statistical physics modeling using the monolayer model with two independent types of receptor binding sites of the response of the mouse olfactory receptor MOR215-1 and the human olfactory receptor OR5AN1, which are identified as specifically responding to musk compounds, is used to characterize the interaction between the two nitro musk molecules, the mouse and the human olfactory receptors and to determine the olfactory band of these two odorants through the determination of the molar adsorption energies and the adsorption energy distributions. The physico-chemical model parameters can be used for the steric characterization via the calculation of the receptor site size distributions. The docking computation between these two nitro musks and the human olfactory receptor OR5AN1 is performed demonstrating a large similarity in receptor-ligand detection process. Thus, docking finding results prove that the calculated binding affinities were belonging to the spectrum of adsorption energies. Copyright © 2021 Elsevier B.V. All rights reserved.

Citation

Ismahene Ben Khemis, Abir Sagaama, Noureddine Issaoui, Abdelmottaleb Ben Lamine. Steric and energetic characterizations of mouse and human musk receptors activated by nitro musk smelling compounds at molecular level: Statistical physics treatment and molecular docking analysis. International journal of biological macromolecules. 2021 Oct 01;188:333-342

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PMID: 34389381

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