Priority Research Papers:
Cancer therapeutic approach based on conformational stabilization of mutant p53 protein by small peptides
Metrics: PDF 3107 views | HTML 3690 views | ?
Perry Tal1, Shay Eizenberger1, Elad Cohen1, Naomi Goldfinger1, Shmuel Pietrokovski2, Moshe Oren1 and Varda Rotter1
1 Department of Molecular Cell Biology, The Weizmann Institute of Science, Rehovot, Israel
2 Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot, Israel
Perry Tal, email:
Moshe Oren, email:
Varda Rotter, email:
Keywords: p53, reactivation, peptides, conformation, pre-clinical
Received: November 29, 2015 Accepted: February 11, 2016 Published: March 02, 2016
The p53 tumor suppressor serves as a major barrier against malignant transformation. Over 50% of tumors inactivate p53 by point mutations in its DNA binding domain. Most mutations destabilize p53 protein folding, causing its partial denaturation at physiological temperature. Thus a high proportion of human tumors overexpress a potential potent tumor suppressor in a non-functional, misfolded form. The equilibrium between the properly folded and misfolded states of p53 may be affected by molecules that interact with p53, stabilizing its native folding and restoring wild type p53 activity to cancer cells. To select for mutant p53 (mutp53) reactivating peptides, we adopted the phage display technology, allowing interactions between mutp53 and random peptide libraries presented on phages and enriching for phage that favor the correctly folded p53 conformation. We obtained a large database of potential reactivating peptides. Lead peptides were synthesized and analyzed for their ability to restore proper p53 folding and activity. Remarkably, many enriched peptides corresponded to known p53-binding proteins, including RAD9. Importantly, lead peptides elicited dramatic regression of aggressive tumors in mouse xenograft models. Such peptides might serve as novel agents for human cancer therapy.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.