The "guardian of the genome", p53, functions as a tumor suppressor that responds to cell stressors such as DNA damage, hypoxia, and tumor formation by inducing cell-cycle arrest, senescence, or apoptosis. Mutation of p53 disrupts its tumor suppressor function, leading to various types of human cancers. One particular mutant, R175H, is a structural mutant that inactivates the DNA damage response pathway and acquires oncogenic functions that promotes both cancer and drug resistance. Our current work aims to understand how p53 wild-type function is disrupted due to the R175H mutation. We use a series of atomistic integrative models built previously from crystal structures of the full-length p53 tetramer bound to DNA and model the R175H mutant using in silico site-directed mutagenesis. Explicitly solvated all-atom molecular dynamics (MD) simulations on wild-type and the R175H mutant p53 reveal insights into how wild-type p53 searches and recognizes DNA, and how this mechanism is disrupted as a result of the R175H mutation. Specifically, our work reveals the optimal quaternary DNA binding mode of the DNA binding domain and shows how this binding mode is altered via symmetry loss as a result of the R175H mutation, indicating a recognition mechanism that is reminiscent of the asymmetry seen in wild type p53 binding to nonspecific genomic elements. Altogether our work sheds new light into the hitherto unseen molecular mechanisms governing transcription factor, DNA recognition.

The tumor suppressor p53 plays a vital role in responding to cell stressors such as DNA damage, hypoxia, and tumor formation by inducing cell-cycle arrest, senescence, or apoptosis. Expression level alterations and mutational frequency implicates p53 in most human cancers. In this review, we show how both computational and experimental methods have been used to provide an integrated view of p53 dynamics, function, and reactivation potential. We argue that p53 serves as an exceptional case study for developing methods in modeling intrinsically disordered proteins. We describe how these methods can be leveraged to improve p53 reactivation molecule design and other novel therapeutic modalities, such as PROteolysis TARgeting Chimeras (PROTACs).