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2000
Volume 28, Issue 18
  • ISSN: 1386-2073
  • E-ISSN: 1875-5402

Abstract

Background

Extracts from have been detected to have antioxidant activity and tyrosinase (TYR) inhibitory activity. However, bioactive peptides (BPs) released from proteins (PPs) have not been comprehensively reported.

Objective

The aim of this study is to rapidly identify bifunctional peptides with antioxidant and TYR inhibitory activities from a large number of digested peptides from PPs.

Methods

In this study, a total of 3,288 proteins from six main species of were collected, and the antioxidant potential (AP) was evaluated. Hydrolyzed peptides with 2–8 amino acid lengths were collected and known antioxidants were removed. Next, these peptides were further screened using ADMET analysis. Finally, the DPPH· scavenging potential (IC) and TYR inhibition potential (TIP) of these peptides were further predicted by QSAR models and molecular docking based pharmacophore models, respectively.

Results

The most released antioxidant peptides after digestion of all types of PPs were dipeptides with sequences EL, IR and AY. In addition, 44,689 short non-repeatable peptides were swirled in these hydrolysates, which have not yet been reported to have antioxidant activity. Next, 337 of these digested peptides were predicted to be absorbed without hepato-renal toxicity and had virtual metabolic scores > 0.01%. Finally, 138 peptides were predicted to have AP and TIP.

Conclusion

is a kind of promising source rich in bifunctional peptides. Present study adopted an innovative method with some free scripts to rapid discovery of bifunctional peptides from a large number of unknown PPs.

© 2025 Bentham Science Publishers
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2025-04-29
2025-12-25

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Exploring Potential Bifunctional Peptides with Anti-tyrosinase and Antioxidant Activities from Porphyra Protolysate Using in Silico Analysis
Comb Chem High Throughput Screen 28, 3238 (2025); https://doi.org/10.2174/0113862073341023250113053959
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  • Article Type:     Research Article
Keyword(s): AMDET; bioactive peptides; bioinformatics; in silico; pharmacophore; Porphyra proteins; QSAR

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