Apoptosis, or programmed cell death, plays a pivotal role in maintaining cellular homeostasis by eliminating damaged or surplus cells. Dysregulation of signaling pathways, such as JAK/STAT, is implicated in various diseases, rendering them attractive therapeutic targets for potential new anticancer drugs. Concurrently, it is imperative to preserve essential proteins like TNF-α and p53 to maintain normal cellular life/death balance. In light of these considerations, this study employs an innovative in silico hybrid and hierarchical virtual screening approach aimed at identifying JAK/STAT multi-target inhibitors as potential anticancer agents for several tumoral diseases. Initially, the Biotarget Predictor Tool is utilized in a combined ON/OFF-target/Multitarget mode using the extensive National Cancer Institute (NCI) database, previously filtered by ADME evaluation tools. Subsequently, Molecular Docking studies are conducted on JAK2, JAK3, and STAT3, facilitating the identification of the most promising compound, 755435. Finally, Molecular Dynamics Simulations validate the high stability of the potential multitarget inhibitor 755435 in complex with JAK2, JAK3, and STAT3.
Bono, A., La Monica, G., Alamia, F., Lauria, A., Martorana, A. (2024). A novel in silico approach for identifying multi-target JAK/STAT inhibitors as anticancer agents. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 135, 1 [10.1016/j.jmgm.2024.108913].
A novel in silico approach for identifying multi-target JAK/STAT inhibitors as anticancer agents
Bono, AlessiaPrimo
;La Monica, GabrieleSecondo
;Alamia, Federica;Lauria, Antonino
Penultimo
;Martorana, AnnamariaUltimo
2024-11-23
Abstract
Apoptosis, or programmed cell death, plays a pivotal role in maintaining cellular homeostasis by eliminating damaged or surplus cells. Dysregulation of signaling pathways, such as JAK/STAT, is implicated in various diseases, rendering them attractive therapeutic targets for potential new anticancer drugs. Concurrently, it is imperative to preserve essential proteins like TNF-α and p53 to maintain normal cellular life/death balance. In light of these considerations, this study employs an innovative in silico hybrid and hierarchical virtual screening approach aimed at identifying JAK/STAT multi-target inhibitors as potential anticancer agents for several tumoral diseases. Initially, the Biotarget Predictor Tool is utilized in a combined ON/OFF-target/Multitarget mode using the extensive National Cancer Institute (NCI) database, previously filtered by ADME evaluation tools. Subsequently, Molecular Docking studies are conducted on JAK2, JAK3, and STAT3, facilitating the identification of the most promising compound, 755435. Finally, Molecular Dynamics Simulations validate the high stability of the potential multitarget inhibitor 755435 in complex with JAK2, JAK3, and STAT3.File | Dimensione | Formato | |
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A novel in silico approach for identifying multi-target JAK_STAT inhibitors as anticancer agents.pdf
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