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Updated: Jul 24, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Identification of potential Akt activators: a ligand and structure-based computational approach
Harish B Kumar1, Suman Manandhar1, Ekta Rathi2
1Department of Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Abstract:
The Akt pathway plays a significant role in various diseases like Alzheimer's, Parkinson's, and Diabetes. Akt is the central protein whose phosphorylation controls many downstream pathways. Binding of small molecules to the PH domain of Akt facilitates its phosphorylation in the cytoplasm and upregulates the Akt pathway. In the current study, to identify Akt activators, ligand-based approaches like 2D QSAR, shape, and pharmacophore-based screening were used, followed by structure-based approaches such as docking, MM-GBSA, ADME prediction, and MD simulation. The top twenty-five molecules from the Asinex gold platinum database found to be active in most 2D QSAR models were used for shape and pharmacophore-based screening. Later docking was performed using the PH domain of Akt1 (PDB: 1UNQ), and 197105, 261126, 253878, 256085, and 123435 were selected based on docking score and interaction with key residues, which were druggable and formed a stable protein-ligand complex. MD simulations of 261126 and 123435 showed better stability and interactions with key residues. To further investigate the SAR of 261126 and 123435, derivatives were downloaded from PubChem, and structure-based approaches were employed. MD simulation of derivatives 12289533, 12785801, 83824832, 102479045, and 6972939 was performed, in which 83824832 and 12289533 showed interaction with key residues for a longer duration of time, proving that they may act as Akt activators.
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