Screening and Identification of Antifreeze Peptides from Fish-derived Waste Using Molecular Modeling Technology

Objective: This study aimed to screen antifreeze peptides (AFP) from fish-derived waste and elucidate their mechanisms of interaction with ice crystals by integrating molecular simulation with experimental validation. Methods: Cod skin collagen was used as the substrate. Simulated enzymatic hydrolysis was employed to identify proteases with optimal bioactive peptide yield. The hydrolysates were analyzed using Peptide Ranker, CryoProtect, ToxinPred and ExPASy databases to evaluate antifreeze potential and physicochemical properties. Molecular docking and dynamics simulations were employed to characterize AFP-ice binding mechanisms. Finally, the screened antifreeze peptides were synthesized using solid-phase synthesis, and differential scanning calorimetry (DSC) was applied to identify the thermal hysteresis activity (THA) of antifreeze peptide AFP2 (AGSSGPGGER). Results: Trypsin demonstrated the highest efficiency among 39 proteases screened via the Peptide Cutter database. Eleven non-toxic, non-allergenic, and good water solubility AFPs were identified from 103 peptides. The binding energy between antifreeze peptide AFP2 and ice crystals was −130.45 kcal/mol. AFP2 bound to ice crystals and dynamically adjusted its conformation during the binding process to enhance the interaction stability via hydrogen bonding and hydrophobic interactions. Antifreeze peptide AFP2 exhibited high antifreeze activity, with thermal hysteresis activity of 0.9 ℃ and only 12.29% ice crystal formation during freeze-thaw cycles. Conclusion: This study efficiently screened and identified a highly active antifreeze peptide from fish-derived collagen using molecular simulation technology, providing a feasible approach for developing antifreeze peptides from fish waste and a theoretical foundation for the resource utilization of fish-derived byproducts.