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Neuroreceptor Activation by Vibration-Assisted Tunneling

2015/03/24 by Ross D. Hoehn, David Nichols, Hartmut Neven +1
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #5-HT receptor #Agonist #G protein-coupled receptor #In silico #Molecular Junctions and Nanostructures #Molecular Pharmacology #Nervous system #Nicotinic Acetylcholine Receptors Study #Receptor #Receptor Mechanisms and Signaling #Signal transduction #physics.bio-ph #physics.chem-ph #q-bio.BM #quant-ph

paper · pdf · doi:10.1038/srep09990

published as Scientific Reports 5, Article number: 9990 Published 2015 · Accepted to Scientific Reports; Main text 15 pgs with 4 figs; Sup Materials 10 pgs 7 figs

arxiv created 2015/03/24 · openalex publication_date 2015/04/24 · arxiv updated 2015/05/12 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06

Abstract

G protein-coupled receptors (GPCRs) constitute a large family of receptor proteins that sense molecular signals on the exterior of a cell and activate signal transduction pathways within the cell. Modeling how an agonist activates such a receptor is fundamental for an understanding of a wide variety of physiological processes and it is of tremendous value for pharmacology and drug design. Inelastic electron tunneling spectroscopy (IETS) has been proposed as a model for the mechanism by which olfactory GPCRs are activated by a bound agonist. We apply this hyothesis to GPCRs within the mammalian nervous system using quantum chemical modeling. We found that non-endogenous agonists of the serotonin receptor share a particular IET spectral aspect both amongst each other and with the serotonin molecule: a peak whose intensity scales with the known agonist potencies. We propose an experiential validation of this model by utilizing lysergic acid dimethylamide (DAM-57), an ergot derivative, and its deuterated isotopologues; we also provide theoretical predictions for comparison to experiment. If validated our theory may provide new avenues for guided drug design and elevate methods of in silico potency/activity prediction.

Citations