Linked Life Data

18312862

Source:http://linkedlifedata.com/resource/pubmed/id/18312862

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2008-6-16
pubmed:abstractText
Computational tools for the large-scale analysis and prediction of ligand-target interactions and the identification of small molecules having different selectivity profiles within target protein families complement research in chemical genetics and chemogenomics. For computational analysis and design, such tasks require a departure from the traditional focus on single targets, hit identification, and lead optimization. Recently, studies have been reported that profile compounds in silico against arrays of targets or systematically map ligand-target space. In order to identify small molecular probes that are suitable for chemical genetics applications, molecular diversity needs to be viewed in a way that partly differs from principles guiding conventional library design.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1367-5931
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
352-8
pubmed:dateRevised
2009-8-25
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Computational analysis of ligand relationships within target families.
pubmed:affiliation
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, Germany. bajorath@bit.uni-bonn.de
pubmed:publicationType
Journal Article, Review