Understanding the self-ordering of amino acids into supramolecular architectures: co-assembly-based modulation of phenylalanine nanofibrils

Amino acids have emerged as promising molecular frameworks for the generation of functional materials owing to the bio-compatibility and thermodynamic stability of their self-assembled architectures. The homogeneous and heterogeneous self-assembly of all naturally occurring amino acids may demonstrate vast functional diversity owing to their common zwitterionic motif, which can serve as a library for the generation of nano/microscale supramolecular biomaterials. Furthermore, amino acids-based self-assembled amyloid structures exhibit pathological relevance, which shifts the paradigm from the self-assembly of polymeric entities to the self-assembly of simple organic molecules or metabolites. Thus, in order to understand the in-built self-ordering behaviour of amino acids, we investigated all naturally occurring amino acids (except aromatic amino acids) for their well-defined morphology and solution-phase beta-sheet-like amyloid characteristics. Furthermore, this comprehensive analysis of self-assembly data led to the discovery of aliphatic chain amino acids (ACAAs; Ala, Leu, Ile and Val) as potential candidates for the modulation of phenylalanine fibril toxicity. Thus, this inclusive amino acid self-assembly analysis may pave the way for the design and development of simple organic molecules with inherited self-assembling properties for the generation of functional nanomaterials.

Automated summary

Amino acids are promising for the generation of functional materials due to their bio-compatibility and thermodynamic stability. The self-assembly of all naturally occurring amino acids, with their common zwitterionic motif, demonstrates vast functional diversity. Aliphatic chain amino acids have been discovered as potential candidates for modulating phenylalanine fibril toxicity, paving the way for the design and development of simple organic molecules with inherited self-assembling properties for functional nanomaterials.