Linked Life Data

18768239

Source:http://linkedlifedata.com/resource/pubmed/id/18768239

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2009-3-9
pubmed:abstractText
The first-principle, quantitative structure-hepatic clearance relationship for 50 drugs was constructed based on selected molecular descriptors calculated by TSAR software. The R(2) of the predicted and observed hepatic clearance for the training set (n=36) and test set (n=13) were 0.85 and 0.73, respectively. The average fold error (AFE) of the in silico model was 1.28 (n=50). The prediction accuracy of in silico model was superior to in vitro hepatocytes' model in literature (n=50, AFE=2.55). It is attractive to predict human hepatic clearance based on molecular descriptors merely. The structure-based model can be used as an efficient tool in the rapid identification of hepatic clearance of new drug candidates in drug discovery.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1768-3254
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
44
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1600-6
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
First-principle, structure-based prediction of hepatic metabolic clearance values in human.
pubmed:affiliation
Department of Biopharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, No. 59 Mailbox, No. 103 of Wenhua Road, Shenyang 110016, China.
pubmed:publicationType
Journal Article