Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain

Lei Du-Cuny, Zuohe Song, Sylvestor Moses, Garth Powis, Eugene A. Mash, Emmanuelle J. Meuillet, Shuxing Zhang

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)6983-6992
Number of pages10
JournalBioorganic and Medicinal Chemistry
Issue number19
StatePublished - Oct 1 2009


  • Akt inhibitors
  • Anticancer drugs
  • Cell permeability
  • In silico drug design
  • Metabolism
  • Molecular docking/scoring
  • Pleckstrin homology domain
  • QSAR

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Medicine
  • Molecular Biology
  • Pharmaceutical Science
  • Drug Discovery
  • Clinical Biochemistry
  • Organic Chemistry


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