1. Catalog
  2. Nodes
  3. a(MESH:VU0357017)

a(MESH:VU0357017)

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

Entity

Name
VU0357017
Namespace
mesh
Namespace Version
20181007
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/8ccfed235e418e4c8aa576f9a5ef0f838e794c7f/external/mesh-names.belns

Appears in Networks 2

Activation of M1 and M4 muscarinic receptors as potential treatments for Alzheimer's disease and schizophrenia. v1.0.0

This file encodes the article Activation of M1 and M4 muscarinic receptors as potential treatments for Alzheimer’s disease and schizophrenia by Choi et al, 2014

M1 muscarinic acetylcholine receptor in Alzheimer’s disease v1.0.0

This file encodes the article M1 muscarinic acetylcholine receptor in Alzheimer’s disease by Jiang et al, 2014

In-Edges 1

complex(a(MESH:VU0357017), p(HGNC:CHRM1)) hasComponent a(MESH:VU0357017) View Subject | View Object

Appears in Networks:

Out-Edges 6

a(MESH:VU0357017) increases complex(a(MESH:VU0357017), p(HGNC:CHRM1)) View Subject | View Object

More recently, the M1-selective allosteric agonist VU0357017 was discovered, which displayed improved potency via binding to a novel allosteric site on the M1 mAChR. VU0357017 significantly blocked scopolamine-impaired contextual fear conditioning and enhanced spatial and contextual fear learning PubMed:24511233

Appears in Networks:

a(MESH:VU0357017) decreases act(a(CHEBI:scopolamine)) View Subject | View Object

More recently, the M1-selective allosteric agonist VU0357017 was discovered, which displayed improved potency via binding to a novel allosteric site on the M1 mAChR. VU0357017 significantly blocked scopolamine-impaired contextual fear conditioning and enhanced spatial and contextual fear learning PubMed:24511233

Appears in Networks:

a(MESH:VU0357017) increases bp(GO:"behavioral fear response") View Subject | View Object

More recently, the M1-selective allosteric agonist VU0357017 was discovered, which displayed improved potency via binding to a novel allosteric site on the M1 mAChR. VU0357017 significantly blocked scopolamine-impaired contextual fear conditioning and enhanced spatial and contextual fear learning PubMed:24511233

Appears in Networks:

a(MESH:VU0357017) increases act(p(HGNC:CHRM1)) View Subject | View Object

During the past few years, the M1 mAChR allosteric agonists VU0184670 and VU0357017 have been screened out, and have more exciting properties. Both compounds have high solubility in aqueous solutions as well as good CNS penetration, without any agonist or antagonist activity for the M2 and M5 subtypes PubMed:24590577

Appears in Networks:

a(MESH:VU0357017) decreases path(MESH:"Cognitive Dysfunction") View Subject | View Object

Moreover, VU0184670 potentiates neuronal NMDAR-mediated currents in hippocampal brain slices and VU0357017 reverses the cognitive deficits induced by an mAChR antagonist in a contextual fear conditioning paradigm, exhibiting improvement of hippocampus-dependent learning[110, 123]. PubMed:24590577

Appears in Networks:
Annotations
MeSH
Hippocampus

a(MESH:VU0357017) increases bp(GO:learning) View Subject | View Object

Moreover, VU0184670 potentiates neuronal NMDAR-mediated currents in hippocampal brain slices and VU0357017 reverses the cognitive deficits induced by an mAChR antagonist in a contextual fear conditioning paradigm, exhibiting improvement of hippocampus-dependent learning[110, 123]. PubMed:24590577

Appears in Networks:
Annotations
MeSH
Hippocampus

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.