Abstract
Due to their beneficial effects on human health, antioxidant peptides have attracted much attention from researchers. However, the structure-activity relationships of antioxidant peptides have not been fully understood. In this paper, quantitative structure-activity relationships (QSAR) models were built on two datasets, i.e., the ferric thiocyanate (FTC) dataset and ferric-reducing antioxidant power (FRAP) dataset, containing 214 and 172 unique antioxidant tripeptides, respectively. Sixteen amino acid descriptors were used and model population analysis (MPA) was then applied to improve the QSAR models for better prediction performance. The results showed that, by applying MPA, the cross-validated coefficient of determination (Q2) was increased from 0.6170 to 0.7471 for the FTC dataset and from 0.4878 to 0.6088 for the FRAP dataset, respectively. These findings indicate that the integration of different amino acid descriptors provide additional information for model building and MPA can efficiently extract the information for better prediction performance.
Highlights
Bioactive peptides, usually containing 2–20 amino acid residues, are typically derived from the enzymatic hydrolysis of proteins [1]
The methods to assess the antioxidant capacities of peptides include the Trolox equivalent antioxidant capacity (TEAC), the ferric ion reducing antioxidant power (FRAP), the 2,2-diphenyl-1-picrylhydrazyl radical-scavenging capacity (DPPH), the oxygen radical absorbance capacity (ORAC), the total radical trapping antioxidant parameter (TRAP), etc
It is impossible to test all of the peptides to find valid antioxidants, when considering the large number of theoretical possible peptides, i.e., 400 dipeptides, 8000 tripeptides, 160,000 tetrapeptides, etc
Summary
Usually containing 2–20 amino acid residues, are typically derived from the enzymatic hydrolysis of proteins [1]. They are inactive within the sequence of proteins, but they can exert various physiological functions after release. Antioxidant peptides are one of the most important groups of bioactive peptides, which can prevent oxidative stress and they have notable contributions to human health [2]. It is impossible to test all of the peptides to find valid antioxidants, when considering the large number of theoretical possible peptides, i.e., 400 dipeptides, 8000 tripeptides, 160,000 tetrapeptides, etc
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