Aromatic Amino Acid-based Property Analysis of Silk Nano Materials: a Molecular Dynamics Computational Analysis Method

In this study, we systematically investigated the structural and mechanical properties of silk β-sheet models through the targeted substitution of aromatic amino acids phenylalanine, tyrosine, and tryptophan. We performed molecular dynamics simulations on uniformly scaled β-sheet models containing 120 amino acids, allowing for consistent comparative analyses. Secondary structure and hydrogen bonding analyses revealed that the phenylalanine-substituted model exhibited the most stable β-sheet formation and the highest hydrogen-bond density. Although the tryptophan-substituted model revealed increased structural irregularity, strong hydrophobic interactions enhanced interchain attraction, resulting in improved hydrogen bonding and mechanical performance. In contrast, the tyrosine-substituted model displayed the lowest hydrogen-bond density and mechanical properties. Correspondingly, Young’s modulus followed the order of phenylalanine > tryptophan > tyrosine. These results demonstrate that amino acid sequence engineering serves as an effective strategy for tuning the mechanical performance of silk-based materials and expanding the functional design space of silk-derived nanomaterials.