Structure based design of peptide-mimetic STAT3 inhibitors.

STAT3 belongs to the Signal Transducers and Activators of Transcription (STATs) family of proteins which functions as an intracellular effectors for cytokines and growth factors. A growing body of evidence has established a link between abnormal STAT3 signaling observed in many cancers and the dynamic genetic reprogramming that characterizes malignant transformation. Persistent STAT3 activity is documented in a wide variety of blood and solid tumors. While normal STAT3 signaling promotes growth and survival; persistent STAT3 signaling translates into a marked increase in its downstream gene products which alter the cell's apoptotic and proliferation programs. As a therapeutic strategy, inhibiting STAT3 can kill tumor cells by inducing apoptosis and sensitizing chemo-resistant cancer cells to cytotoxic agents. To inhibit persistent STAT3 signaling we designed, synthesized and evaluated peptide mimetics based on a peptide sequence from the STAT3 docking site on the gp130 receptor, pYLPQTV. Our inhibitors target STAT3's SH2 domain and in doing so our goal is to reduce STAT3's interactions with (1) cytokine receptors and/or JAKs; (2) other proteins; and (3) DNA. Our computational modeling of the gp130 peptide in complex with the STAT3 protein predicts that it adopts a beta-turn. As a tactic to constrain the peptide in its predicted binding conformation, we incorporated known monocyclic beta-turn mimetic scaffolds such as Freidinger lactams and 7- and 8-5 aza-bicyclic scaffolds in doing so we obtained a significant improvement in binding affinity (35 fold compared to our lead). Moreover, pull down analysis in various cell lines demonstrate our inhibitors containing the 8-5 aza-bicyclic scaffold are selective for STAT3 over other STAT family members and significantly reduced levels of c-Myc and phospho-STAT3 levels in DU 145 prostate cancer cells.Ph.D.Pharmacy sciencesPure SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/127107/2/3354158.pd