RNA molecules are pivotal in cellular processes with their functions intricately tied to their sequence and structural properties. Palindromic sequences-regions of self complementarity-are hypothesized to play a significant role in RNA self-interactions and secondary structure formation. These interactions are critical in regulating RNA stability, folding, binding, and resultant function, and are important for study of regulation of gene expression, and development of therapeutic RNAs. This study introduces a computational framework to investigate the prevalence, structural classification, and functional implications of palindromic sequences across various RNA types. We first detect palindromes across the human transcriptome, and apply a classification scheme based on known and predicted secondary structure. Finally, we use coarse-grained molecular dynamics simulations to quantify the interplay between folding-unfolding transitions and binding affinity and specificity.
