Computational Predictions and In Silico Structural Characterization of Putative Progerin-Interacting Peptides

Progeria is one of the rarest diseases in the world, affecting about one in every 20 million people. Progeria is caused by a single mutation in the LMNA gene, which creates an abnormal splicing site that leads to the removal of 50 amino acids from the final protein. The resulting protein, called Progerin, behaves like Lamin A, the wild-type version of the protein, and integrates into the nuclear lamina, causing the nucleus to lose its correct shape. This leads to all the typical symptoms of Progeria. Our proposed solution is a therapeutic strategy based on the RING-bait system which recognizes Progerin and marks it for degradation by ubiquitination. To achieve this, we aim to develop a new protein that can bind Progerin and is linked to the RING domain. In this work, we propose a method to design such an interactor using several bioinformatic tools. The pipeline developed in this project includes an initial structural prediction and refinement analysis of Progerin, the use of deep learning and diffusion models to design candidate interacting peptide sequences, the prediction and analysis of these interactors and docking studies to evaluate the affinity and specificity of the binding process.