Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
19
pubmed:dateCreated
2009-9-16
pubmed:abstractText
Computational modeling continues to play an important role in novel therapeutics discovery and development. In this study, we have investigated the use of in silico approaches to develop inhibitors of the pleckstrin homology (PH) domain of AKT (protein kinase B). Various docking/scoring schemes have been evaluated, and the best combination was selected to study the system. Using this strategy, two hits were identified and their binding behaviors were investigated. Robust and predictive QSAR models were built using the k nearest neighbor (kNN) method to study their cellular permeability. Based on our in silico results, long flexible aliphatic tails were proposed to improve the Caco-2 penetration without affecting the binding mode. The modifications enhanced the AKT inhibitory activity of the compounds in cell-based assays, and increased their activity as in vivo antitumor testing.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1464-3391
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
6983-92
pubmed:dateRevised
2010-12-3
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain.
pubmed:affiliation
Department of Experimental Therapeutics-Unit 36, The University of Texas, MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural