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Computational Modeling of TP63-TP53 Interaction and Rational Design of Inhibitors: Implications for Therapeutics.

E Sila OzdemirMichelle M GomesJared M Fischer
Published in: Molecular cancer therapeutics (2022)
Tumor protein p63 (TP63) is a member of the TP53 protein family that are important for development and in tumor suppression. Unlike TP53, TP63 is rarely mutated in cancer, but instead different TP63 isoforms regulate its activity. TA isoforms (TAp63) act as tumor suppressors, whereas ΔN isoforms are strong drivers of squamous or squamous-like cancers. Many of these tumors become addicted to ΔN isoforms and removal of ΔN isoforms result in cancer cell death. Furthermore, some TP53 conformational mutants (TP53CM) gain the ability to interact with TAp63 isoforms and inhibit their antitumorigenic function, while indirectly promoting tumorigenic function of ΔN isoforms, but the exact mechanism of TP63-TP53CM interaction is unclear. The changes in the balance of TP63 isoform activity are crucial to understanding the transition between normal and tumor cells. Here, we modeled TP63-TP53CM complex using computational approaches. We then used our models to design peptides to disrupt the TP63-TP53CM interaction and restore antitumorigenic TAp63 function. In addition, we studied ΔN isoform oligomerization and designed peptides to inhibit its oligomerization and reduce their tumorigenic activity. We show that some of our peptides promoted cell death in a TP63 highly expressed cancer cell line, but not in a TP63 lowly expressed cancer cell line. Furthermore, we performed kinetic-binding assays to validate binding of our peptides to their targets. Our computational and experimental analyses present a detailed model for the TP63-TP53CM interaction and provide a framework for potential therapeutic peptides for the elimination of TP53CM cancer cells.
Keyphrases
  • cell death
  • papillary thyroid
  • squamous cell carcinoma
  • signaling pathway
  • cell proliferation
  • young adults
  • squamous cell
  • transcription factor
  • molecular dynamics simulations
  • protein protein