Multifaceted targeting strategies in cancer against the human notch 3 protein: a computational study

In Silico Pharmacol. 2021 Sep 29;9(1):53. doi: 10.1007/s40203-021-00112-y. eCollection 2021.

Abstract

Notch receptors play a significant role in the development and the regulation of cell-fate in several multicellular organisms. For normal differentiation, genomes are essential as their regular roles and play a role in cancer is dysregulated. Notch 3 has been shown to play a major role in lung cancer function and therefore, inhibition of notch 3 protein activation represents a clear plan for cancer treatment. This study accomplished a combined structure- and ligand-based pharmacophore hypothesis to explore novel notch 3 inhibitors. The analysis identified common lead molecule ZINC000013449462 that showed better XP GScore and binding energy score than the reference inhibitor DAPT. The identified lead compound that passed all the druggable characteristics exhibited stable binding. Furthermore, the lead molecule can also form hydrogen and salt bridge interactions with binding site residues Asp1621 and Arg1465 residues, respectively of the active pockets of notch 3 protein. In essence, the inhibitory activity of the hit was validated across 109 NSCLC cell lines by employing a deep neural network algorithm. Our study proposes that ZINC000013449462 would be a possible prototype molecule towards the notch 3 target and further examined by clinical studies to combat NSCLC.

Keywords: ADMET; Deep learning model; Drug repurposing; Lung cancer; Notch 3; Virtual screening.