Investigation of Structural Mechanisms Underlying p53 Dysfunction Caused by 148 Missense Mutations Using AlphaFold3 and Molecular Dynamics Simulations
Abstract
Tumor protein p53 (TP53) is a crucial regulator of genomic integrity, frequently mutated in more than half of all human cancers. These mutations predominantly target the DNA-binding domain (DBD), impairing p53's interaction with DNA and its tumor-suppressive functions. To elucidate the structural and functional consequences of p53 mutations, we investigated 148 missense variants located within its DNA-binding interface using cutting-edge computational approaches. We employed AlphaFold3 (AF3) to predict p53-DNA complex structures, integrating these predictions with molecular dynamics (MD) and force-guided pulling simulations to assess mutation-induced changes in structural stability and DNA-binding properties. Moreover, we compared the results of our study with experimental in vitro enrichment scores (RFS) and Combined Annotation Dependent Depletion (CADD). We identified a moderate negative correlation between plDDT and the pathogenicity of mutant variants, suggesting that mutations causing more significant alterations in the protein tertiary structure have a greater negative impact on cellular function. Moreover, we identified two possible structural mechanisms through which mutations can impair the p53 functionality. Specifically, some mutations, such as R248P and N239S, reduce the binding affinity of the p53-DNA complex, whereas others, such as C238Y and P278R, enhance affinity but compromise the structural stability of the complex. Furthermore, we uncovered mutations with potential rescuing effects, such as E285A and M243T, which preserved structural stability and enhanced the DNA-binding ability. Our findings provide a comprehensive framework for understanding the molecular mechanisms underlying p53 mutations and their role in cancer pathogenesis. This study highlights the value of integrative computational approaches in investigating protein-nucleic acid interactions, providing critical insights that can guide the development of therapeutic strategies targeting p53 mutations.