Proteın dinamikleri ile evrimsel bağlantıların deşifre edilmesi

Proteins are inherently dynamic, and their functional mechanisms often rely on collective internal motions. While the relationship between structure and dynamics has been widely studied, the connection between intrinsic dynamics and evolutionarily conserved sequence motifs remains poorly understood. This thesis addresses this gap by investigating the dynamic roles of themes—short conserved sequence segments shared across diverse proteins—through elastic network modeling and information-theoretic analysis. Using the Gaussian Network Model (GNM), dynamic elements (DEs) were defined as contiguous, co-fluctuating segments derived from low-frequency collective modes. To assess their correspondence with themes, mutual information (MI) was calculated between DEs and theme-based partitions across a curated dataset of 150 ECOD domains, with statistical validation performed against randomized controls. The results indicate that many themes align significantly with DEs, suggesting that reused segments are embedded in functional dynamic units. In a focused case study, previously identified adenine-binding themes were analyzed using a GNM-based Transfer Entropy (GNM-TE) method. The analysis revealed that these motifs frequently act as dynamic communication hubs, implicating them in long-range allosteric signaling. Building on this, the thesis classifies themes according to their information transfer roles and applies statistical analysis to evaluate enrichment patterns among binding themes. Together, these studies offer the first systematic framework for linking evolutionarily reused sequence segments with intrinsic dynamic architectures and communication properties. By introducing the concept of dynamic elements and integrating them with directional information flow, this work advances our understanding of protein evolution and function from a structure–dynamics perspective.