Linked Life Data

11033425

Source:http://linkedlifedata.com/resource/pubmed/id/11033425

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PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2000-12-5
pubmed:abstractText
A method for the modeling and prediction of pharmacokinetic properties based on computed molecular interaction fields and multivariate statistics has been investigated in different experimental datasets. The program VolSurf was used to correlate 3D molecular structures with physico-chemical and pharmacokinetic properties. In membrane partitioning, VolSurf produced a two-component model explaining 94% of the total variation with a predictive q(2) of 0.90. This result was achieved without conformational sampling and without any quantum-chemical calculation. For the prediction of blood-brain barrier penetration the VolSurf model was able to predict the BBB profile for most of the drugs in the external prediction set. In Caco-2 and MDCK permeation experiments, VolSurf was used with success to establish statistical models and to predict the behaviour of new compounds. The method thus appears as a valuable new property filter in virtual screening and as a novel tool in optimizing the pharmacokinetic profile of pharmaceutically relevant compounds.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0928-0987
pubmed:author
pubmed:issnType
Print
pubmed:volume
11 Suppl 2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S29-39
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
VolSurf: a new tool for the pharmacokinetic optimization of lead compounds.
pubmed:affiliation
Laboratory for Chemometrics, University of Perugia, Via Elce di Sotto 10, I-06123 Perugia, Italy. gabri@chemiome.chm.unipg.it
pubmed:publicationType
Journal Article