COMPUTER PREDICTION, MOLECULAR DOCKING, AND BINDING MODEL ANALYSIS OF ANTIOXIDANT POTENTIAL IN BAIJIU DISTILLER’S GRAIN PROTEIN HYDROLYSATES
Keywords:
Baijiu distiller’s grain, Virtual screening, Molecular docking, AntioxidantAbstract
To efficiently utilize antioxidant peptides from Baijiu distiller’s grain protein hydrolysates, this study used Baijiu distiller’s grain protein hydrolysate as raw material and analyzed the molecular weight distribution via SEC-HPLC across ranges of ≥70 kDa, 10–70 kDa, 5–10 kDa, 1–5 kDa, 0. 2–1 kDa, and ≤0. 2 kDa. Results showed that the hydrolysates were dominated by small-molecule peptides below 1 kDa with uniform distribution. Subsequently, peptide sequences were identified by LC-MS/MS, and virtual screening combined with bioinformatics prediction yielded eight candidate peptides: PYPR, YPR, DPHG, YGPR, KWY, GRLPGYG, PRY, and YPVPR. All peptides exhibited favorable bioactivity scores, water solubility, and no toxicity or allergenicity. Antioxidant prediction revealed that PYPR had the highest free radical scavenging score (0. 551), and DPHG showed optimal metal chelating activity (0. 323). Molecular docking demonstrated that the binding energies of the eight peptides to Keap1 protein ranged from −8. 0 to −10. 3 kcal/mol. Among them, YGPR had the lowest binding energy (−10. 3 kcal/mol) and formed up to 10 hydrogen bonds, indicating the strongest binding capacity. This study rapidly screened eight high-potential antioxidant peptides from Baijiu distiller’s grain protein using a computer-assisted strategy, providing a theoretical basis and an efficient screening method for resource utilization of Baijiu distiller’s grain protein and development of food-derived antioxidant peptides.References
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