Evolutionary Conservation and Hotspot Analysis of the p53 Tumor Suppressor Protein

This dataset presents a comprehensive analysis of the p53 tumor suppressor protein, focusing on its evolutionary conservation, functional hotspots, domain architecture, and structural features. The included PDF report contains detailed figures, tables, and explanations highlighting key conserved regions across species, phylogenetic relationships, and the identification of critical residues (hotspots) that are functionally significant.Analyses were performed using multiple computational approaches, including sequence alignments, phylogenetic tree construction, and domain mapping. Static 3D visualizations of p53 structures were generated using PyMOL to illustrate conserved domains and functional hotspots. All Python scripts and PyMOL scripts used for data processing and figure generation are provided in the associated GitHub repository: https://github.com/efe4r/p53_Evolution_Project.<b>Motivation and Impact:</b><br>Understanding the evolutionary conservation and functional hotspots of p53 enhances our knowledge of protein biology and its critical role in cancer suppression. This dataset is designed to facilitate further research in molecular evolution, structural biology, and computational analysis of tumor suppressor proteins. The project demonstrates a commitment to open science, reproducibility, and integrative computational approaches to study protein function and evolution.