Linked Life Data

21458999

Source:http://linkedlifedata.com/resource/pubmed/id/21458999

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2011-4-12
pubmed:abstractText
A QSAR model was developed for predicting intestinal drug permeability, one of the most important parameters when evaluating compounds in drug discovery projects. First, a set of relevant properties for establishing a drug-like chemical space was applied to a database of compounds with Caco-2 permeability values obtained from previous studies. Several QSAR regression models were then developed from this set of drug-like structures. The best model was selected based on the accuracy of correct classifications obtained for training and validation subsets previously defined, including 17 structures from the FDA Biopharmaceutics Classification System (BCS). Further validation of the QSAR model was performed by applying it to 21 drugs for which Caco-2 permeability values were experimentally determined by us. The good agreement between predictions and experimental values in all cases confirmed the reliability of the equation. Since the model was developed with very simple descriptors, easy to calculate, its applicability to large collections of in silico chemicals is guaranteed.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1464-3391
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 Elsevier Ltd. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
15
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2615-24
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
QSAR-based permeability model for drug-like compounds.
pubmed:affiliation
Department of Medicinal Chemistry, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain. rgozalbes@cipf.es
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't