Generation, Characterisation and Identification of Bioactive Peptides from Mesopelagic Fish Protein Hydrolysates Using In Silico and In Vitro Approaches

Abstract

This study generated bioactive hydrolysates using the enzyme Alcalase and autolysis from mesopelagic fish, including Maurolicus muelleri and Benthosema glaciale. Generated hydrolysates were investigated for their bioactivities using in vitro bioassays, and bioactive peptides were identified using mass spectrometry in active hydrolysates with cyclooxygenase, dipeptidyl peptidase IV and antioxidant activities. In silico analysis was employed to rank identified peptide sequences in terms of overall bioactivity using programmes including Peptide Ranker, PrepAIP, Umami-MRNN and AntiDMPpred. Seven peptides predicted to have anti-inflammatory, anti-type 2 diabetes or Umami potential using in silico strategies were chemically synthesised, and their anti-inflammatory activities were confirmed using in vitro bioassays with COX-1 and COX-2 enzymes. The peptide QCPLHRPWAL inhibited COX-1 and COX-2 by 82.90% (+/−0.54) and 53.84%, respectively, and had a selectivity index greater than 10. This peptide warrants further research as a novel anti-inflammatory/pain relief peptide. Other peptides with DPP-IV inhibitory and Umami flavours were identified. These offer potential for use as functional foods or topical agents to prevent pain and inflammation.

Keywords

• peptides
• anti-inflammatory
• heart health
• anti-diabetic
• type-2-diabetes
• in silico analysis