Discovery of new AKT1 inhibitors by combination of in silico structure based virtual screening approaches and biological evaluations

Abstract

AKT1 is emerging as a useful target for treating cancer. Herein, we discovered a new set of ligands that inhibit the AKT1, as shown by in vitro binding and cell line studies, using a newly designed virtual screening protocol that combines structurebased pharmacophore and docking screens. Taking together with the biological data, the combination of structure based pharamcophore and docking methods demonstrated reasonable success rate in identifying new inhibitors (60-70%) proving the success of aforementioned approach. A detail analysis of the ligand-protein interactions was performed explaining observed activities.

Atranorin is a novel potential candidate drug for treating myelodysplastic syndrome

“…Hence, inhibiting the AKT has been reported to adjuvant cancer therapy to increase patient survival. There have been extensive efforts to develop AKT inhibitors as therapeutics due to the involvement of oncogenic activating mutations in PI3K and AKT in cancer and overgrowth disorders [64][65][66] . Thus, the AKT protein was chosen as a potential target for atranorin binding.…”

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein

“…Unlike the previous ligand-based approach, in 2020 Fratev et al [29] proposed a structure-based pharmacophore model which was developed by combining the application of the e-Pharmacophore tool [66] from Schrödinger (https://www.schrodinger.com/), with fragment-based virtual screening. Specifically, the 3D model was generated based The predicted polar intermolecular interactions are illustrated as follows: magenta arrow, hydrogen bond; green dotted lines, π-π interaction.…”

“…Unlike the previous ligand-based approach, in 2020 Fratev et al [29] proposed a structure-based pharmacophore model which was developed by combining the application of the e-Pharmacophore tool [66] from Schrödinger (https://www.schrodinger.com/), with fragment-based virtual screening. Specifically, the 3D model was generated based on docking results obtained for several hundred fragments oriented into the ATP-binding site of AKT1 (PDB ID: 3QKK [67]).…”

Applications of machine learning in computer-aided drug discovery

“…Therefore, this approach can cut cost and accelerate the preliminary stage of drug development. CADD has been successfully applied to numerous disease-related target systems advancing research in treatments for congestive heart failure (Lindert et al, 2015 a ; Cai et al, 2016 ; Aprahamian et al, 2017 ; Coldren et al, 2020 ), several types of cancer (Lee et al, 2010 ; Ravindranathan et al, 2010 ; Chuang et al, 2015 ; Lee et al, 2019 ; Fratev et al, 2021 ; Hantz and Lindert, 2022 ), and various infectious diseases (Durrant et al, 2011 ; Zhu et al, 2013 ; Sinko et al, 2014 ; Lindert et al, 2015 b ; de Sousa et al, 2020 ).…”