Menthol Stereoisomers Exhibit Different Effects on α4β2 nAChR Upregulation and Dopamine Neuron Spontaneous Firing.
Brandon J HendersonStephen GrantBetty W ChuRezvan ShahoeiStephanie M HuardShyam S M SaladiEmad TajkhorshidDennis A DoughertyHenry A LesterPublished in: eNeuro (2019)
Menthol contributes to poor cessation rates among smokers, in part because menthol enhances nicotine reward and reinforcement. Mentholated tobacco products contain (-)-menthol and (+)-menthol, in varying proportions. We examined these two menthol stereoisomers for their ability to upregulate α4β2 nAChRs and to alter dopamine neuron firing frequency using long-term, low-dose (≤500 nm) exposure that is pharmacologically relevant to smoking. We found that (-)-menthol upregulates α4β2 nAChRs while (+)-menthol does not. We also found that (-)-menthol decreases dopamine neuron baseline firing and dopamine neuron excitability, while (+)-menthol exhibits no effect. We then examined both stereoisomers for their ability to inhibit α4β2 nAChR function at higher concentrations (>10 µm) using the Xenopus oocyte expression system. To probe for the potential binding site of menthol, we conducted flooding simulations and site-directed mutagenesis. We found that menthol likely binds to the 9´ position on the TM2 (transmembrane M2) helix. We found that menthol inhibition is dependent on the end-to-end distance of the side chain at the 9´ residue. Additionally, we have found that (-)-menthol is only modestly (∼25%) more potent than (+)-menthol at inhibiting wild-type α4β2 nAChRs and a series of L9´ mutant nAChRs. These data reveal that menthol exhibits a stereoselective effect on nAChRs and that the stereochemical effect is much greater for long-term, submicromolar exposure in mice than for acute, higher-level exposure. We hypothesize that of the two menthol stereoisomers, only (-)-menthol plays a role in enhancing nicotine reward through nAChRs on dopamine neurons.
Keyphrases
- low dose
- smoking cessation
- wild type
- signaling pathway
- gene expression
- metabolic syndrome
- dna methylation
- type diabetes
- poor prognosis
- insulin resistance
- photodynamic therapy
- climate change
- risk assessment
- single cell
- molecular dynamics
- machine learning
- cell proliferation
- artificial intelligence
- binding protein
- big data
- extracorporeal membrane oxygenation
- respiratory failure
- dna binding
- high fat diet induced