Introduction: The tumor suppressor protein p53, known as the "guardian of the genome," plays a central role in maintaining genomic stability, cell cycle arrest, DNA repair, and apoptosis initiation in response to cellular stress. Dysfunction of p53 is a hallmark of human cancers, with mutations in the TP53 gene occurring in over 50% of all tumors. While many p53 mutations localize to its structured DNA-binding domain (DBD), directly disrupting its transcriptional activity, a significant number occur within its intrinsically disordered regions (IDRs), particularly the N-terminus. One such mutation is the proline-to-glycine substitution at position 4 (P4G).
The N-terminal region harbors the critical transcriptional activation domain 1 (TAD1), essential for interactions with key regulatory proteins such as MDM2 (p53’s primary negative regulator) and transcriptional coactivator complexes. Due to the lack of a stable three-dimensional structure in this region, the molecular mechanisms by which point mutations like P4G impair p53 function remain poorly understood. Conventional assumptions suggest that mutations in disordered regions have limited functional consequences. However, this study challenges that paradigm by proposing that such mutations may disrupt protein function not through structural alteration but by modulating conformational dynamics and thermodynamic properties.
Advances in artificial intelligence-based protein structure prediction, particularly AlphaFold2, now enable the generation of high-resolution atomic models and the analysis of dynamic features for both wild-type and mutant proteins. This study leverages this transformative technology to perform a comparative analysis of the wild-type and P4G mutant isoforms of p53, aiming to elucidate the molecular mechanism underlying this mutation and provide a new analytical framework for understanding how mutations in disordered regions contribute to disease pathogenesis.
Methods: This study utilized the advanced protein structure prediction system AlphaFold2 (version 2.3.1), developed by DeepMind, to generate high-resolution atomic three-dimensional models for both the wild-type and mutant (P4G) isoforms of the full-length human p53 protein. The protein sequences of both isoforms, corresponding to UniProt ID P04637, were used as input for the model.
Modeling was performed without applying any additional constraints, using AlphaFold's default database (including homologous sequences and experimental structures). For each isoform, five independent models (ranked_1 to ranked_5) and full confidence matrices (pLDDT and PAE) were generated. The ranked_1 model (with the highest confidence score) from each isoform was selected for subsequent analysis.
Qualitative and quantitative analysis of the results focused on the predicted local distance difference test (pLDDT) metric for each amino acid position, particularly in the N-Terminus region (residues 1–100) and the DNA-binding domain (residues 100–300). Direct comparison of the pLDDT profiles of the two isoforms was conducted to identify any differences in predicted structural accuracy. Furthermore, by considering the intrinsic physicochemical properties of proline and glycine (including side chain characteristics, bond angles, and conformational entropy), a robust inference was made regarding the impact of this substitution on the local dynamics and transient interaction potential of the mutated region. All structural visualizations and graphs were generated and processed using specialized structural biology software (PyMOL and ggplot2 in R).
A large language model was used for assistance in editing and drafting the manuscript.
Results: Using the advanced protein structure prediction system AlphaFold2, high-resolution atomic models were generated for both the wild-type and mutant (P4G) isoforms of the p53 protein. Comparative quantitative analysis revealed that the mutation has no discernible impact on the overall structural integrity of the protein, as the predicted confidence score (pLDDT) was identical across all positions, including the DNA-Binding Domain (DBD), between the two isoforms. However, a qualitative analysis of the physicochemical properties of the amino acid substitution revealed a fundamental local dynamic disruption in the N-Terminus region. The replacement of rigid Proline with flexible Glycine resulted in a significant increase in conformational freedom and a probable alteration in the potential for transient interactions within this region, which contains the Transcriptional Activation Domain (TAD) and the primary epitope for MDM2 binding.
Conclusion: The findings of this study demonstrate that the P4G mutation in p53 is a prime example of a "functionally disruptive yet dynamically originated mutation" rather than a structural one. While the protein's core domain remains structurally intact, the substitution fundamentally alters the dynamic and thermodynamic profile of the regulatory N-Terminal hub. This local dynamic perturbation has a high potential to disrupt two critical functions: allosteric binding patterns to key regulatory partners like MDM2, and the efficiency of assembling transcriptional activation complexes. Consequently, this seemingly minor mutation, by creating a disturbance in the protein's "dynamic language," can severely disrupt the tumor suppressor signaling pathway, potentially acting as an initial driver in oncogenesis. This research underscores the critical principle that "disorder does not equate to lack of function" and highlights the necessity of studying the dynamics of intrinsically disordered regions (IDRs) to fully understand disease pathogenesis, paving the way for novel therapeutic strategies focused on modulating protein dynamics.