Linked Life Data

19144451

Source:http://linkedlifedata.com/resource/pubmed/id/19144451

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2009-4-20
pubmed:abstractText
We developed a structure-property-activity relationship (SPAR)-model for psychopharmacological drugs acting as non-competitive 5-HT(3A) receptor antagonists by using a decision-tree learner provided by the RapidMiner machine learning tool. A single molecular descriptor, namely the molecular dipole moment per molecular weight (mu/MW), predicts whether or not a substance non-competitively antagonizes 5-HT-induced Na(+) currents. A low mu/MW is compatible with drug-cumulation in apolar lipid rafts. This study confirms that size-intensive descriptors allow the development of compact SPAR models.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1768-3254
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
44
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2667-72
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Molecular properties of psychopharmacological drugs determining non-competitive inhibition of 5-HT3A receptors.
pubmed:affiliation
Department of Psychiatry and Psychotherapy, University of Erlangen, Schwabachanlage 6, D-91054 Erlangen, Germany. johannes.kornhuber@uk-erlangen.de
pubmed:publicationType
Journal Article