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Updated: Jan 12, 2026

A Generalized Method for Determining Free Soluble Phenolic Acid Composition and Antioxidant Capacity of Cereals and Legumes
Published on: June 10, 2022
A novel antioxidant peptide from black soybean [Glycine max (L.) Merr.] with verified MPO interaction and multi-scale
Dan Zhu1, Hai Zheng2, Xiaolin Xie3
1Department of Endocrinology and Clinical Nutrition, Gezhouba Central Hospital of Sinopharm, Third Clinical Medical College of China Three Gorges University, Yichang, China.
Abstract:
Oxidative stress-related diseases drive the demand for natural antioxidants, with plant-derived peptides emerging as promising candidates. This study focused on identifying and characterizing a novel antioxidant peptide from black soybean (Glycine max) aqueous extracts, targeting myeloperoxidase (MPO), a key enzyme in oxidative damage. Peptide components were profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The candidate peptide VPNHFNAP was selected via molecular docking and dynamics simulations against MPO, followed by binding affinity validation using surface plasmon resonance (SPR). Antioxidant capacity was assessed through DPPH/ABTS radical scavenging assays (IC50: 12.3 ± 0.8 μM and 9.7 ± 0.5 μM, respectively). Cytoprotective effects were evaluated in HaCaT cells under H2O2-induced oxidative stress (viability by MTT assay, ROS by DCFH-DA fluorescence). VPNHFNAP exhibited strong MPO binding (KD = 1.2 × 10-7 M, SPR) and radical scavenging activity (DPPH: 82.4 ± 3.1%; ABTS: 88.6 ± 2.7% at 100 μM). Molecular docking revealed hydrogen bonds with MPO's His95 and Arg239. In cellular models, 50 μM VPNHFNAP increased viability by 2.1-fold (p < 0.001 vs. H2O2 group) and reduced ROS levels by 58 ± 4%. This study establishes VPNHFNAP as a potent MPO-targeted antioxidant peptide through an integrated computational-experimental strategy. Its dual function (direct radical scavenging + cellular protection) highlights potential applications in functional foods or cosmeceuticals. The screening framework also advances plant peptide discovery by combining bioinformatics with multi-level validation.
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