Sequence-Defined Oligourea–Peptide Hybrids as Self-Assembling Platforms for Early Diagnosis of Neurodegenerative Diseases

Neurodegenerative diseases, including Alzheimer's and Parkinson's diseases, are characterized by the accumulation and aggregation of misfolded proteins. Early detection of these pathological events remains a major challenge, necessitating the development of robust molecular platforms capable of recognizing disease-associated biomarkers with high sensitivity and selectivity.

 In this study, we report the design and synthesis of sequence-defined oligourea–peptide hybrids as potential diagnostic platforms for the early detection of neurodegenerative diseases. Oligoureas are attractive peptidomimetic scaffolds owing to their exceptional conformational stability, resistance to proteolytic degradation, and ability to adopt well-defined helical structures. By conjugating bioactive peptide sequences to oligourea backbones, we aim to combine the structural robustness of oligoureas with the molecular recognition properties of peptides.

 Sequence-defined oligourea trimers were synthesized through a stepwise solution-phase approach and subsequently coupled with seqeucne defined peptide fragments using amide bond formation. The resulting oligourea–peptide hybrids were purified and characterized by NMR spectroscopy, CD spectrometry, and TEM. Furthermore, their self-assembly behavior and secondary structural features are being investigated to evaluate their potential as biomolecular recognition platforms.

 This work establishes a versatile strategy for constructing sequence-defined oligourea–peptide architectures and provides a foundation for the development of next-generation diagnostic materials targeting early-stage neurodegenerative disease biomarkers.