Current Signal Transduction Therapy - Online First

AKT inhibition presents a promising avenue for cancer treatment strategies. By exploring natural analogues using in-silico docking and ADMET profiles, this work aims to design effective anti-cancer therapies shown by binding affinities and pharmacokinetic assessments.

The aim of this research paper is to utilize in-silico ADMET profiling and molecular docking studies to investigate the potential of natural analogues as inhibitors of the AKT enzyme. By leveraging computational techniques, including Molegro Virtual Docker (MVD) 6.0 and computational techniques like pkCSM, we aim to identify promising compounds with strong binding affinities to the target protein (PDB ID: 3OCB) and favorable pharmacokinetic properties. Our objectives include identifying key molecular interactions, evaluating optimal molecular weight ranges, and prioritizing compounds based on their MolDock scores for cancer treatment. Through this approach, our goal is to contribute to the design and development of effective anti-cancer therapies targeting the AKT signaling pathway.

The Protein Data Bank provided the target protein (PDB ID: 3OCB) for the molecular docking study, which was conducted using Molegro Virtual Docker (MVD) 6.0. The selection of ligands from PubChem was focused on natural analogues. ADMET profiling benefited from the use of computational techniques such as pkCSM.

A molecular docking study of selected natural compounds was performed, and the top three compounds with higher MolDock scores were considered to be the best among all sixteen natural analogues. The compounds [00]UNX_16, [01]UNX_13, and [00]UNX_11 showed the highest MolDock score of -111.09, -98.31, and -96.37, respectively, and can show great potential in treating cancer.

The analysis primarily focuses on a docking study investigating the potential inhibition of the AKT enzyme by natural analogs. The study explores molecular interactions and ADMET properties, offering insights into their role in drug discovery. Key findings include strong binding affinities of selected analogs against the target 3OCB, with specific amino acid residues and steric/hydrogen bond interactions influencing binding success. Compounds within the 400-500 Da molecular weight range show favorable interactions, suggesting implications for future drug design. Additionally, ADMET analysis identifies compounds like [00]UNX_16, [01]UNX_13, and [00]UNX_11 with high MolDock scores, indicating potential as AKT inhibitors for cancer treatment.