Top-Down Computational\nDesign of Molecule Recognition\nPeptides (MRPs) for Enzyme-Peptide Self-Assembly and Chemiluminescent\nBiosensing

The recognition of small molecules plays a crucial role\nin disease\ndiagnosis, environmental assessment, and food safety. Currently, their\nrecognition elements predominantly rely on antibodies and aptamers\nwhile suffering from a limitation of the complex screening process\ndue to the low immunogenicity of small molecules. Herein, we present\na top-down computational design strategy for molecule recognition\npeptides (MRPs) for enzyme-peptide self-assembly and chemiluminescence\nbiosensing. Taking ochratoxin A (OTA) as an illustrative example,\nhuman serum albumin (HSA) was selected as the parental protein due\nto its high affinity for OTA binding. Through iterative computational\nsimulations involving the binding domain of the HSA-OTA complex, our\nstrategy identified a specific 15-mer MRP (RLKCASLKFGERAFK), which\npossesses excellent binding affinity (38.02 ± 1.24 nM) against\nOTA. Molecular dynamics simulations revealed that the 15-mer MRP unfolds\ninto a flexible short chain with high affinity for OTA, but exhibits\nweak or no binding affinity with five structurally similar mycotoxins.\nFurthermore, we developed a novel enzyme-peptide self-assembly approach\nmediated by calcium(II) to obtain nanoflowers, which integrates both\nthe recognition element (MRP) and the signal translator (enzyme) for\nchemiluminescence biosensing. The assembled nanoflowers allow MRPs\nto be directly utilized as a tracer for OTA biosensing without labeling\nor secondary antibodies. This computational-to-application approach\noffers a new route for small-molecule recognition.