Linked Life Data

18722033

Source:http://linkedlifedata.com/resource/pubmed/id/18722033

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2009-3-2
pubmed:abstractText
Docking simulations and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis were performed on a wide set of c-Src inhibitors. The study was conducted using a structure-based alignment and by applying the GRID/GOLPE approach. The present 3D-QSAR investigation proved to be of good statistical value, displaying r(2), q(2) and cross-validation SDEP values of 0.94, 0.84 and 0.42, respectively. Moreover, such a model also proved to be capable of predicting the activities of an external test set of compounds. The availability of the 3D structure of the target made possible the interpretation of steric and electrostatic maps within the binding site environment and provided useful insight into the structural requirements for inhibitory activity against c-Src. Two regions whose occupation by hydrophobic portions of ligands would favourably affect the activity were clearly identified. Moreover, hydrogen bond interactions involving residues Met343, Asp406 and Ser347 emerged as playing a key role in determining the affinity of the active inhibitors toward c-Src. Furthermore, the inhibitors bearing a basic nitrogen provided enhanced potency through protonation and salt bridge formation with Asp350. A preliminary pharmacokinetic profile of the molecules under analysis was also drawn on the basis of Volsurf predictions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1768-3254
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
44
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
990-1000
pubmed:dateRevised
2009-11-19
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Docking, 3D-QSAR studies and in silico ADME prediction on c-Src tyrosine kinase inhibitors.
pubmed:affiliation
Dipartimento Farmaco Chimico Tecnologico, Università degli Studi di Siena, Via Alcide de Gasperi, 2, I-53100 Siena, Italy.
pubmed:publicationType
Journal Article