Last Month's Most Accessed Feature: Bioactive peptides from cyanobacteria: In silico prediction

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  • Published: Mar 1, 2018
  • Categories: Proteomics & Genomics / Proteomics
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Bioactive peptide sources

A proteomics approach employing in silico digestion has been proposed as an alternative way to identify bioactive peptides in aquatic species, exemplified with the edible cyanobacterium Arthrospira platensis.

The popularity of functional foods that provide more than simple nourishment continues to rise dramatically as new products with human health-promoting effects are designed. Tracking this increase is a surge in efforts to identify novel bioactive components for food supplementation, with peptides to the fore. Many bioactive peptides have been derived from natural sources such as milk, fungi and microbes by breaking down the proteins in ways that mimic their degradation in the human body.

Novel bioactive peptides are discovered increasingly by bioinformatic methods, theoretically breaking down the proteins in silico and comparing the peptide sequences to those in databases such as PepBank and BIOPEP. The latter source “contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments”. This approach has been applied successfully to foods such as meat and plants.

Other bountiful sources of bioactive peptides are aquatic organisms, particularly microalgae and cyanobacteria, also known as blue-green algae. However, a group of scientists has noted that efforts to mine cyanobacteria for functional peptides are not supported currently by a successful in silico approach. So, they have set out to design a systematic method exemplified by the cyanobacterium Arthrospira platensis. Chaofan Ji and coresearchers affiliated to Dalian Polytechnic University, National Engineering Research Center of Seafood in Dalian and Iowa State University, USA, set out their ideas in Journal of the Science of Food and Agriculture.

Cyanobacterial peptides

The proteins in Arthrospira platensis were extracted and broken up into their constituent peptides by enzymatic digestion with trypsin for analysis by mass spectrometry. A total of 593 proteins were detected and quantified, the most abundant being those related to the photosystem of the organism.

The proteins were then subjected individually to simulated proteolysis by the enzymes trypsin, pepsin and chymotrypsin which cleave at known sites in proteins determined by the amino acid sequences. The resulting sets of peptides were compared with those in the BIOPEP database of 3271 peptides to see if any bioactive peptides had been formed as a result of the theoretical digestion.

In fact, trypsin, pepsin and chymotrypsin produced 78, 99 and 96 bioactive peptides, respectively. Their occurrence frequencies (OF) from the proteome were comparable to those recorded for other food sources such as bovine meat and the common green bean. Tryptic digestion produced higher OF values due to the more aggressive nature of the enzyme to produce more peptides than pepsin and chymotrypsin.

Aquatic organism screening

For each enzyme, the majority of the bioactive peptides were angiotensin-converting enzyme (ACE) inhibitors, dipeptidyl peptidase IV inhibitors and antioxidants. Other less abundant peptides were associated with ion flow regulation, neuropeptide inhibition and renin inhibition. Some were also opioids and antibacterial peptides. The enzyme producing the most diverse set of activities was chymotrypsin.

The results suggest that this combined practical and in silico approach could be useful as an initial screen for aquatic organisms, as long as the relevant genome and proteome are known. However, there is a key disadvantage in that only those bioactive peptides that are already included in the BIOPEP database can be identified. This limitation will be improved as newly found active peptides are discovered in different food sources and used to supplement the database.

The abundance and frequency data will help to direct scientists towards the best proteins to target and the most abundant bioactive peptides to collect. Identification of the key target proteins in a particular organism will also lead to improved procedures for their cultivation and extraction and for peptide separation.

This process will be amended to achieve better performance as extra criteria are introduced. "In the future, the predictive models will be further improved by taking into account chemical, thermodynamic and chromatographic properties of produced peptides, to yield better planning and optimization tools for the bioactive peptide industry," the researchers concluded.

Related Links

Journal of the Science of Food and Agriculture 2018, 98, 984-990: "Omics-prediction of bioactive peptides from the edible cyanobacterium Arthrospira platensis proteome"

BIOPEP Database

Article by Steve Down

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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