Implicated in pancreatic, ovarian as well as other cancer types, AKT (protein kinase B) is an important drug target.  However, due to the high degree of homology in the ATP-binding pocket on kinase domains of different serine/threonine kinases, selectivity remains a major problem. The aim of this study is to carry out in silico screening to identify novel potential allosteric inhibitors which are expected to bind the cavity between kinase and PH domains of AKT1. ZINC database is filtered using pharmacophore models based on the Akt allosteric site. The selected molecules are docked into the allosteric site using Glide software and the binding mode of ligands are predicted using the scoring function GlideScore (GScore). The hits are further analyzed considering predicted ADME properties and key ligand-protein interactions. The top scoring hits are then clustered based on similarity and a diverse set of chemical scaffolds are selected. This work combines structure based pharmacophore building and docking and allows the identification of a diverse set of chemical scaffolds. As future work, the proposed set of ligands will be experimentally tested for Akt1 inhibition.

Identification of allosteric Akt inhibitors by computational methods

246th National Meeting (2013)

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