Defatted oilseeds, such as flaxseed, rapeseed, sunflower and sesame seed, are by-products from the food industry and currently used as animal feeds or waste. In the last two decades, these under-utilised food materials have gained growing interest due to their high protein content, which could be an abundant and low-cost source of bioactive peptides. Experimental approaches have been widely applied for exploring the biological activities of peptides. However, drawbacks of this approach are time-consuming, expensive and low yields of targeted peptides. Therefore, this study aimed to use a bioinformatic approach to assess the potential of different oilseed storage proteins as precursors of ACE and DPP-IV inhibitory peptides.

Four predominant oilseed storage proteins were selected to undergo in silico simulated pepsin (pH > 2) (EC 3·4·23·1) hydrolysis using ‘Enzyme(s) action tool’ available through BIOPEP⁽Reference Minkiewicz, Dziuba and Iwaniak¹⁾. The frequency of occurrence and the potency index of ACE and DPP-IV inhibitors released from precursor proteins were calculated based on peptide profiles. The peptide sequences obtained through in silico hydrolysis were aligned with scores using PeptideRanker based on the likelihood of bioactive peptide generation⁽Reference Mooney, Haslam and Pollastri²⁾. Finally, the peptides with a score > 0·80 (score ranges from 0-poorest to 1-most promising) were selected to predict binding sites in ACE and DPP-IV using Pepsite2, a molecular docking program⁽Reference Trabuco, Lise and Petsalaki³⁾. Bovine beta-lactoglobulin was used as a comparison.

Frequency of occurrence and potency index of ACE and DPP-IV inhibitors were variable among the five proteins. In general, the peptides generated from these proteins had relatively more potent ACE inhibiting activities, despite the higher frequency of DPP-IV inhibitors (Table 1). 51 out of 1060 peptide sequences, aligned the score > 0·8, underwent the binding-site simulation using Pepsite2. These selected peptides were predicted to bind with several subsites in ACE (such as Q281, H353, H513 and Y523) and DPP-IV (such as Y547, Y666, W627 and S630) to lower the catalytic activities of both enzymes.

Table 1. Frequency and Potency Index of ACE and DPP-IV inhibitors obtained using pepsin hydrolysis.

This study concludes that, based on the amino acid sequences, oilseed proteins can be considered as good precursors of ACE and DPP-IV inhibitors as compared to animal proteins, such as beta-lactoglobulin. A number of peptides have demonstrated to bind both active and none-active sites in ACE and DPP-IV, which indicates competitive and non-competitive inhibition, respectively. Further studies are required to detail the inhibition mechanisms involved and verify the predicted findings through in vitro and in vivo models.