Targeted Discovery of a Novel Carrageenan-Binding Module with High Affinity through Computational Screening

Abstract

Carrageenan is a sulfated red algal polysaccharide widely used in food for its gelling and thickening properties. High-affinity recognition tools are needed for food quality control, and carbohydrate-binding modules (CBMs) are promising recognition elements. However, high-affinity carrageenan-specific CBMs remain scarce. Here, we developed a computationally driven screening strategy integrating structure prediction and molecular dynamics (MD) simulations for targeted high-affinity CBM discovery through binding free energy calculations prior to experimental validation. Using this strategy, a novel CBM designated AmCBM116 was identified from ι-carrageenases of the GH82 family. AmCBM116 specifically recognizes both κ- and ι-carrageenan with high affinity, with association constants (Ka) of 1.97 × 105 M–1 and 1.82 × 106 M–1, respectively. Key residues involved in ligand recognition were identified. AmCBM116 and its homologues reveal a novel CBM family, CBM116. This study expands the carrageenan-binding CBMs and provides a framework for the targeted discovery of high-affinity polysaccharide-binding modules.