Linked Life Data

19207462

Source:http://linkedlifedata.com/resource/pubmed/id/19207462

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-2-11
pubmed:abstractText
For the computational exploration of structure-selectivity relationships, a compound selectivity system consisting of 243 antagonists of ionotropic glutamate ligand-gated ion channels was designed. Selected antagonists were organized in nine different selectivity sets. In systematic selectivity search calculations utilizing these data sets, structural fingerprints produced a significant enrichment of selective compounds over non-selective molecules and database decoys. The molecular basis of these findings was explored in detail. Fingerprint bit settings characteristic of antagonists with different selectivity profiles were identified and the corresponding structural features were correlated with sets of molecular fragments derived from selective and non-selective antagonists following a hierarchical fragmentation strategy separating aromatic and aliphatic core structure elements and substituents. This analysis rationalized the selectivity search performance of structural fingerprints and revealed structural motifs that are selectivity markers for different types of ion channel antagonists.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1747-0285
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
73
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
273-82
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Methods for computer-aided chemical biology. Part 4: selectivity searching for ion channel ligands and mapping of molecular fragments as selectivity markers.
pubmed:affiliation
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Dahlmannstr. 2, D-53113 Bonn, Germany. bajorath@bit.uni-bonn.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't