An In Silico Framework to Mine Bioactive Peptides from Annotated Proteomes: A Case Study on Pancreatic Alpha Amylase Inhibitory Peptides from Algae and Cyanobacteria

Abstract

Bioactive peptides may exert beneficial activities in living organisms such as the regulation of glucose metabolism through the inhibition of alpha amylases. Algae and cyanobacteria are gaining a growing interest for their health-promoting properties, and possible effects on glucose metabolism have been described, although the underlying mechanisms need clarification. This study proposes a computer-driven workflow for a proteome-wide mining of alpha amylase inhibitory peptides from the proteome of Chlorella vulgaris, Auxenochlorella protothecoides and Aphanizomenon flos-aquae. Overall, this work presents an innovative and versatile approach to support the identification of bioactive peptides in annotated proteomes. The study: (i) highlighted the presence of alpha amylase inhibitory peptides within the proteomes under investigation (including ELS, which is among the most potent inhibitory tripeptides identified so far); (ii) mechanistically investigated the possible mechanisms of action; and (iii) prioritized further dedicated investigation on the proteome of C. vulgaris and A. flos-aquae, and on CSSL and PGG sequences.

Keywords

• bioactive peptides
• pancreatic alpha amylase inhibitors
• anti-nutrients
• bioinformatics
• molecular modeling
• in silico digestion