Intelligent decoding platform for peptide sequences: SERS detection via high affinity self-assembled silver nanoparticles and machine learning analysis.

BACKGROUND

Peptides are compounds formed by the dehydration-condensation reaction of two or more amino acids which play an important role in the life functions of the organism. Changes in the structure of amino acids and peptides are vital for elucidating the process of disease development. However, the existing methods make it difficult to accurately recognize slight variations in peptide sequences, which becomes a difficult detection task. Therefore, the necessity of novel, accurate, comprehensive and deep strategies for peptide sequence identification is imperative.

RESULTS

Here, an intelligent decoding system was developed, which synthesized a substrate (Ag/BDHA) with high affinity and self-assembly capabilities by double reduction method and utilized surface-enhanced Raman scattering (SERS) to achieve label-free, high-affinity and accurate capturing of peptide sequences. The platform can recognize peptide chains with the same molecular weight but different amino acid sequences, filling the loopholes of mass spectroscopy. Interestingly, it can also distinguish peptide chains with different amino acid lengths, different amino acid positions and different amino acid mutations. And further combined with machine learning methods to simplify the output of detection results, including thermogram, confusion matrix, principal component analysis and hierarchical cluster analysis, which was more suitable for practical applications. More importantly, to explore the potential for application, real influenza A viruses were selected and analyzed and successfully identifying mutations and subtypes of viruses.

SIGNIFICANCE: In sum, the original, versatile and intelligent detection system based on surface-enhanced Raman scattering we proposed provides a promising method and strategy for the precise and valid analysis of different variations of peptide sequences, which is of great significance for explaining life processes, exploring disease pathogenesis, and developing innovative drugs.