Novel and efficient techniques in the discovery of antioxidant peptides

AbstractAs a research hotspot in food science and nutrition, antioxidant peptides can function by scavenging free radicals, inhibiting peroxides, and chelating metal ions. Therefore, how to efficiently discover and screen antioxidant peptides has become a key issue in research and production. Traditional discovery methods are time-consuming and costly, but also challenging to resolve the quantitative structure-activity relationship of antioxidant peptides. Several novel techniques, including artificial intelligence, molecular docking, bioinformatics, quantum chemistry, phage display, switchSENSE, surface plasmon resonance, and fluorescence polarization, are emerging rapidly as solutions. These techniques possess efficient capability for the discovery of antioxidant peptides, even with the potential for high-throughput screening. In addition, the quantitative structure-activity relationship can be resolved. Notably, combining these novel techniques can overcome the drawbacks of a single one, thus improving efficiency and expanding the discovery horizon. This review has summarized eight novel and efficient techniques for discovering antioxidant peptides and the combination of techniques. This review aims to provide scientific evidence and perspectives for antioxidant peptide research.Keywords: Antioxidant peptidesartificial intelligencebioinformaticsquantum chemistryswitchSENSEsurface plasmon resonance Disclosure statementThe authors report there are no competing interests to declare.Additional informationFundingThis work was supported by the Jiangsu Provincial TCM Science and Technology Development Program Project [MS2021004]; National Natural Science Foundation of China [81703642]; Key Project of Jiangsu Collaborative Innovation Center of Chinese Medicinal Re-sources Industrialization [ZDXM-2022-06]; Nanjing University of Chinese Medicine Natural Science Foundation Youth Project [NZY81703642]; National Administration of Traditional Chinese Medicine Chinese Medicine innovation team and talent support program project [ZYYCXTD-D-202005]; Shandong Province Key R&D Program [2021SFGC1203] and 2021 Student Innovation Training Program Project [202110315031].