| Description: |
Cancer represents a leading cause of mortality globally, with its complex biological nature posing significant challenges for treatment. Central to cancer progression are molecular pathways that govern cellular function, among which protein phosphatase 2A (PP2A) plays a vital role. As a serine/threonine phosphatase, PP2A maintains cellular homeostasis by dephosphorylating a broad range of protein substrates and has emerged as a key tumor suppressor. However, PP2A activity can be physiologically inhibited by endogenous regulators such as the SE Translocation (SET) protein. Overexpression of SET has been associated with the loss of PP2A function, promoting hallmark features of cancer. Interestingly, targeting the PP2A/SET interaction has shown therapeutic potential. Indeed, inhibiting SET to reactivate PP2A may restore cellular regulation, induce apoptosis in tumor cells, and attenuate cancer progression. Research efforts have explored compounds such as the endogenous D-erythro-C18-ceramide and the drug fingolimod (FTY720), both known for their ability to reactivate PP2A. In this work, PP2A/SET complex models were generated through a computational approach and, using molecular docking, the interaction of potential SET inhibitors from a library of 26 alkoxy phenyl 1-propan-one derivatives (APPDs) was characterized. Additionally, absorption, distribution, metabolism, and excretion (ADME) predictions were performed to assess pharmacokinetic properties and therapeutic potential. Eventually, the predicted binding affinities were then correlated with biological data to assess the reliability of the models. These findings provide valuable insights into molecule–receptor interactions and lay the groundwork for developing inhibitors with encouraging therapeutic implications. |