Peptide Technologies for the Detection and Remediation of Micro and Nanoplastics from Molecular Mechanisms to Artificial Intelligence Guided Design

The escalating environmental and health impacts of microplastic and nanoplastic pollution have created an urgent need for sensitive and selective detection and remediation technologies. Among emerging receptor-based detection approaches, peptides have attracted significant attention due to their binding affinity, low production cost, and compatibility with diverse analytical platforms. Rather than surveying detection and remediation platforms one by one, this review takes a peptide-centric approach, moving from molecular recognition mechanisms, through peptide discovery and design, to practical applications. It summarizes the physicochemical basis of peptide–microplastic interactions, including hydrophobic effects, π–π stacking, electrostatic attraction, and hydrogen bonding, with special emphasis on how environmental aging of microplastics alters binding behavior. Additionally, the evolution of peptide discovery and design strategies is discussed, ranging from traditional phage display–based biopanning and physics-based molecular dynamics simulations to emerging artificial intelligence–driven approaches, including generative adversarial networks and deep learning models. Key applications of peptide-based technologies for microplastic detection and remediation, including colorimetric biosensors, plasmonic nanosensors, machine-learning–assisted fluorescence sensor arrays, microneedle-based sensing platforms, and magnetic nanoplastic enrichment systems, are also reviewed. Finally, current challenges, such as selectivity limitations, solubility and aggregation issues, and the lack of specialized computational tools for predicting peptide–polymer interfaces, are critically evaluated alongside proposed directions for integrated detection and remediation strategies.