Linked Life Data

18436460

Source:http://linkedlifedata.com/resource/pubmed/id/18436460

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2008-9-22
pubmed:abstractText
Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor beta (TRbeta), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q(2) (cross-validated) values 0.600 and 0.616 and non-cross-validated r(2) values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)(2)) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRbeta. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor beta but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1873-4243
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
27
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
95-104
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta.
pubmed:affiliation
Department of Chemistry, Lanzhou University, Lanzhou 730000, China.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Validation Studies