PubMed 19126755

The receptor that exhibits the greatest upregulation when exposed to nicotine is the alpha4beta2 nAChR. Receptors assembled from this subunit combination form the highaffinity nicotine binding site (151, 215) and account for the vast majority of upregulated sites in the brain of smokers (55).

BEL
a(CHEBI:nicotine) increases p(HBP:"alpha-4 beta-2 nAChR")
Hash
1242ab1eba
TextLocation
Review
Networks

PubMed 19126755

transfection of cells with the beta4 and alpha2 nAChR subunits or expression of these in Xenopus oocytes leads to high-affinity nicotine-binding receptors that upregulate in response to prolonged exposure to nicotine (113, 184, 215).

BEL
a(CHEBI:nicotine) increases p(HBP:"alpha-4 beta-2 nAChR")
Hash
11690486fe
TextLocation
Review
Networks

PubMed 19126755

In particular, repeated self-administration produces the upregulation of high-affinity (alpha4beta2) nAChR expression, reduces receptor function due to desensitization and, in most cases, imparts developmental tolerance. Additional changes imposed by nicotine abuse range from reinforcement to physical discomfort associated with withdrawal including craving, anxiety, and a multitude of other less than desirable sensations of autonomic dysfunction when use is stopped.

BEL
a(CHEBI:nicotine) increases p(HBP:"alpha-4 beta-2 nAChR")
Hash
190b3098fa
TextLocation
Review
Networks
BEL
a(CHEBI:nicotine) decreases act(p(HBP:"alpha-4 beta-2 nAChR"))
Hash
442840984d
TextLocation
Review
Networks

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.