Linked Life Data

11410068

Source:http://linkedlifedata.com/resource/pubmed/id/11410068

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2001-6-18
pubmed:abstractText
Using a simple model of ligand-receptor interactions, the interactions between ligands and receptors of varying complexities are studied and the probabilities of binding calculated. It is observed that as the systems become more complex the chance of observing a useful interaction for a randomly chosen ligand falls dramatically. The implications of this for the design of combinatorial libraries is explored. A large set of drug leads and optimized compounds is profiled using several different properties relevant to molecular recognition. The changes observed for these properties during the drug optimization phase support the hypothesis that less complex molecules are more common starting points for the discovery of drugs. An extreme example of the use of simple molecules for directed screening against thrombin is provided.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0095-2338
pubmed:author
pubmed:issnType
Print
pubmed:volume
41
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
856-64
pubmed:dateRevised
2005-11-16
pubmed:meshHeading
pubmed:articleTitle
Molecular complexity and its impact on the probability of finding leads for drug discovery.
pubmed:affiliation
Computational Chemistry and Informatics Unit, GlaxoSmithKline Medicines Research Centre, Gunnels Wood Road, Stevenage, SG1 2NY, England. mmh1203@gsk.com
pubmed:publicationType
Journal Article, Review