Identification of allosteric AKT inhibitors by computational methods

Abstract

AKT kinases are known to be major contributors to the development of many human cancers according to preclinical data and studies of tumor specimens. Design and development of small molecule inhibitors targeting AKT and its signaling pathway is therefore an area of intense research in the field of cancer therapeutics. To date, most of the small molecule inhibitors target the kinase domain of AKT. However, due to the high degree of homology in the ATP-binding pocket among different serine/threonine kinases, achieving selectivity for these inhibitors remains a major problem. The evolutionarily less conserved PH domain and the interface it makes with the kinase domain is an attractive alternative to develop more selective inhibitors. The aim of this thesis study is to carry out in silico screening to identify potential allosteric inhibitors expected to bind the cavity between kinase and PH domains of Akt1. To this end, both structure-based and ligand-based pharmacophore models were developed. Structure-based pharmacophore models were constructed using important structural features of Akt1. The 3D structural information of previously identified allosteric Akt inhibitors was used to develop a ligand-based pharmacophore model. Database screening was performed based on 3D similarity to the selected pharmacophore hypotheses. Glide was used to predict binding modes of the ligands. Top scoring hits were further analyzed considering 2D similarity between the compounds, interactions with Akt1, fitness to pharmacophore models, ADME and druglikeness criteria. Derivatives of 3-methyl-xanthine, quinoline-4-carboxamide and 2-[4-(cyclohexa-1,3-dien-1-yl)-1H-pyrazol-3-yl]phenol were proposed as potential leads for allosteric inhibiton of Akt1.