Linked Life Data

20637670

Source:http://linkedlifedata.com/resource/pubmed/id/20637670

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-9-6
pubmed:abstractText
The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1873-4243
pubmed:author
pubmed:copyrightInfo
(c) 2010. Published by Elsevier Inc.
pubmed:issnType
Electronic
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
214-20
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.
pubmed:affiliation
College of Bioengineering, Chongqing University, Chongqing 400030, People's Republic of China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't