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Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain.

ABSTRACT: 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.

SUBMITTER: Du-Cuny L

PROVIDER: S-EPMC2808703 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain.

Du-Cuny Lei L Song Zuohe Z Moses Sylvestor S Powis Garth G Mash Eugene A EA Meuillet Emmanuelle J EJ Zhang Shuxing S

Bioorganic & medicinal chemistry 20090819 19

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 mode ...[more]

PMID: 19734051

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Project description:Phospholipases C (PLCs) reversibly associate with membranes to hydrolyze phosphatidylinositol-4, 5-bisphosphate (PI[4,5]P(2)) and comprise four main classes: beta, gamma, delta, and epsilon. Most eukaryotic PLCs contain a single, N-terminal pleckstrin homology (PH) domain, which is thought to play an important role in membrane targeting. The structure of a single PLC PH domain, that from PLCdelta1, has been determined; this PH domain binds PI(4,5)P(2) with high affinity and stereospecificity and has served as a paradigm for PH domain functionality. However, experimental studies demonstrate that PH domains from different PLC classes exhibit diverse modes of membrane interaction, reflecting the dissimilarity in their amino acid sequences. To elucidate the structural basis for their differential membrane-binding specificities, we modeled the three-dimensional structures of all mammalian PLC PH domains by using bioinformatic tools and calculated their biophysical properties by using continuum electrostatic approaches. Our computational analysis accounts for a large body of experimental data, provides predictions for those PH domains with unknown functions, and indicates functional roles for regions other than the canonical lipid-binding site identified in the PLCdelta1-PH structure. In particular, our calculations predict that (1). members from each of the four PLC classes exhibit strikingly different electrostatic profiles than those ordinarily observed for PH domains in general, (2). nonspecific electrostatic interactions contribute to the membrane localization of PLCdelta-, PLCgamma-, and PLCbeta-PH domains, and (3). phosphorylation regulates the interaction of PLCbeta-PH with its effectors through electrostatic repulsion. Our molecular models for PH domains from all of the PLC classes clearly demonstrate how a common structural fold can serve as a scaffold for a wide range of surface features and biophysical properties that support distinctive functional roles.

Dataset Information

Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain.

Publications

Computational modeling of novel inhibitors targeting the Akt pleckstrin homology domain.

Similar Datasets

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