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a(CHEBI:sertraline)

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Entity

Name
sertraline
Namespace
chebi
Namespace Version
20180906
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/b46b65c3da259b6e86026514dfececab7c22a11b/external/chebi-names.belns

Appears in Networks 1

Nicotinic receptors: allosteric transitions and therapeutic targets in the nervous system v1.0.0

This document contains the curation of the review article Nicotinic receptors: allosteric transitions and therapeutic targets in the nervous system by Taly et al. 2009

In-Edges 0

Out-Edges 2

a(CHEBI:sertraline) decreases a(CHEBI:monoamine) View Subject | View Object

Meanwhile, a number of key antidepressants, such as fluoxetine (Prozac; lilly), sertraline (Zoloft; Pfizer), paroxetine (Paxil/Seroxat; Novo Nordisk/GlaxoSmithKline), nefazodone, nisoxetine, citalopram (Celexa/Cipramil/Cipram; H. lundbeck), nomifensine and vanoxerine211–216 were shown to inhibit neuronal nAChRs, in addition to inhibiting selective monoamine reuptake. PubMed:19721446

Appears in Networks:
Annotations
MeSH
Neurons
Text Location
Review

a(CHEBI:sertraline) decreases act(p(HGNCGENEFAMILY:"Cholinergic receptors nicotinic subunits")) View Subject | View Object

Meanwhile, a number of key antidepressants, such as fluoxetine (Prozac; lilly), sertraline (Zoloft; Pfizer), paroxetine (Paxil/Seroxat; Novo Nordisk/GlaxoSmithKline), nefazodone, nisoxetine, citalopram (Celexa/Cipramil/Cipram; H. lundbeck), nomifensine and vanoxerine211–216 were shown to inhibit neuronal nAChRs, in addition to inhibiting selective monoamine reuptake. PubMed:19721446

Appears in Networks:
Annotations
MeSH
Neurons
Text Location
Review

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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.