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Updated: May 10, 2026

Formation of Ordered Biomolecular Structures by the Self-assembly of Short Peptides
Published on: November 21, 2013
Design, Computational Assessment, and Experimental Characterization of a Self-Assembling Peptide Hydrogel
Ashish Malik1,2, Federico Fontana2, Valentina Corvaglia1,2
1Center for Nanomedicine and Tissue Engineering (CNTE), A.S.S.T. Grande Ospedale Metropolitano Niguarda, Piazza dell'Ospedale Maggiore 3, Milan 20162, Italy.
Abstract:
Self-assembling peptides (SAPs) are emerging as promising biomaterials for applications in drug delivery, regenerative medicine, and tissue engineering, where they form hydrogel scaffolds made of nanostructures such as fibrils, ribbons, and sheets through noncovalent interactions. However, the rational design of SAPs with predictable properties remains a significant challenge, necessitating a combination of computational and experimental methodologies. This study introduces peptide FDFK12 (FDFKFDFKFDFK), derived from peptide LDLK12 (LDLKLDLKLDLK) by substituting leucine with phenylalanine to introduce aromatic interactions, enhance π-π stacking-driven self-assembly, and promote favorable interactions with genipin via phenylalanine's aromatic rings, thereby facilitating cross-linking. The substitution of leucine with phenylalanine was strategically aimed at increasing the proximity of genipin, a natural derived cross-linker, to lysine residues, as phenylalanine facilitates π-π stacking interactions with genipin, thereby promoting more effective cross-linking. Molecular dynamics simulations were employed to compare peptide FDFK12 with other SAPs and evaluate its interaction with genipin, already demonstrated to boost mechanical properties and postprocessing capabilities of SAPs. Experimental assessments, including rheology, scanning electron microscopy, and FTIR spectroscopy, confirmed the enhanced aggregation and mechanical stability of peptide FDFK12. These findings highlight the potential of rational peptide design, coupled with comprehensive experimental validation, for the optimization of SAPs in advanced biomaterial applications.
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