Top-Down Computational Design of Molecule Recognition Peptides (MRPs) for Enzyme-Peptide Self-Assembly and...

The recognition of small molecules plays a crucial role in disease diagnosis, environmental assessment, and food safety. Currently, their recognition elements predominantly rely on antibodies and aptamers while suffering from a limitation of the complex screening process due to the low immunogenicity of small molecules. Herein, we present a top-down computational design strategy for molecule recognition peptides (MRPs) for enzyme-peptide self-assembly and chemiluminescence biosensing. Taking ochratoxin A (OTA) as an illustrative example, human serum albumin (HSA) was selected as the parental protein due to its high affinity for OTA binding. Through iterative computational simulations involving the binding domain of the HSA-OTA complex, our strategy identified a specific 15-mer MRP (RLKCASLKFGERAFK), which possesses excellent binding affinity (38.02 ± 1.24 nM) against OTA. Molecular dynamics simulations revealed that the 15-mer MRP unfolds into a flexible short chain with high affinity for OTA, but exhibits weak or no binding affinity with five structurally similar mycotoxins. Furthermore, we developed a novel enzyme-peptide self-assembly approach mediated by calcium(II) to obtain nanoflowers, which integrates both the recognition element (MRP) and the signal translator (enzyme) for chemiluminescence biosensing. The assembled nanoflowers allow MRPs to be directly utilized as a tracer for OTA biosensing without labeling or secondary antibodies. This computational-to-application approach offers a new route for small-molecule recognition.