Allosterism in Targeting p53 Tumor Suppressor for Improved Cancer Therapy – Can AI Solve the Puzzle?

Intrinsically disordered p53 is a promising yet difficult target for precision oncology. p53 undergoes conformational changes in response to binding to the protein partners, amino acid substitution, or posttranslational modifications. These shifts often provoke the long-chain fluctuations which underlie allosteric transformations associated with the regulation of p53 function. Allosteric shifts regulate p53 translation, protein stability, and transcription activity. The 2024 Nobel Prize in Chemistry recognises advancements in computational protein design and structure prediction through AI innovations. Yet, current AI-based tools still fall short in unravelling the complexity of allosteric regulation in p53, a knowledge which is scarce yet essential for turning p53 into a feasible therapeutic target. Here, we highlight the challenges and the avenues to decipher the structure of locally misfolded p53, a multipotent transcription factor and the most abundantly inhibited tumour suppressor in human cancers.