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a(MESH:"Amyloid Precursor Protein Secretases")

Equivalencies: 0 | Classes: 0 | Children: 0 | Explore

Entity

Name
Amyloid Precursor Protein Secretases
Namespace
mesh
Namespace Version
20180828
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/1b20f0637c395f8aa89c2e2e342d7b704062c242/external/mesh-names.belns

Appears in Networks 3

APP processing in Alzheimer's disease v1.0.1

APP processing in Alzheimer's disease

Alzheimer's Disease: Targeting the Cholinergic System v1.0.0

The Ubiquitin Proteasome System in Neurodegenerative Diseases: Sometimes the Chicken, Sometimes the Egg v1.0.0

In-Edges 1

a(PUBCHEM:10013505) increases a(MESH:"Amyloid Precursor Protein Secretases") View Subject | View Object

Moreover, AF267B treatment leads to an increase in alpha secretase, which is an enzyme that can prevent the production of Aβ peptide PubMed:26813123

Appears in Networks:
Annotations
MeSH
Alzheimer Disease

Out-Edges 3

a(MESH:"Amyloid Precursor Protein Secretases") increases rxn(reactants(p(HGNC:APP)), products(a(CHEBI:"amyloid-beta"))) View Subject | View Object

Abeta is generated from b-amyloid precursor protein (APP) through sequential cleavages first by beta-secretase and then by gamma-secretase complex PubMed:21214928

Appears in Networks:
Annotations
Confidence
Medium

a(MESH:"Amyloid Precursor Protein Secretases") decreases a(MESH:"Amyloid beta-Peptides") View Subject | View Object

Moreover, AF267B treatment leads to an increase in alpha secretase, which is an enzyme that can prevent the production of Aβ peptide PubMed:26813123

Appears in Networks:
Annotations
MeSH
Alzheimer Disease

a(MESH:"Amyloid Precursor Protein Secretases") increases rxn(reactants(p(HGNC:APP)), products(a(MESH:"Amyloid beta-Peptides"))) View Subject | View Object

Three different proteases, called alpha, beta, and gamma secretases, can cleave APP at specific sites and generate products that are well characterized. PubMed:14556719

Appears in 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.