Wanzhou Yang,Zhiyuan Tai,Yuexin Pan,Wenhao Zhang,Jia Ran,Zeyuan Yu,Xiaodong Yu,Qiyi He
Oxidative stress, arising from a dysregulation between the generation of reactive oxygen species (ROS) and antioxidant defense mechanisms, is closely linked to the pathogenesis of numerous chronic diseases. To identify natural peptide-based antioxidants, rabbit meat proteins were enzymatically hydrolyzed using seven proteases. Among them, Hydrolysates produced by papain demonstrated the greatest radical scavenging activity, with DPPH and ABTS inhibition rates of 51.50 % and 61.50 %, respectively. Ultrafiltration and Sephadex G-15 fractionation revealed that the <3 kDa fraction (PH3) and its subfraction F5 possessed the strongest antioxidant activity. LC-MS/MS analysis of F5 identified 163 peptides, of which 56 were predicted to exhibit antioxidant potential using PeptideRanker and AnOxPePred algorithms. Notably, seven novel peptides showed strong binding affinities to Keap1 (binding energy < −8.0 kcal/mol) in molecular docking, suggesting possible modulation of the Keap1–Nrf2 antioxidant pathway. Quantum chemical analysis (HOMO–LUMO orbitals and electrostatic potential mapping) combined with radical scavenging assays demonstrated that electron-donating aromatic residues (Trp, Tyr) played key roles in antioxidant activity via hydrogen atom and electron transfer mechanisms, establishing a molecular-level structure–activity relationship. In vivo validation using an AAPH-induced zebrafish model confirmed the peptides' safety and efficacy, including reduced ROS levels and restored endogenous antioxidant enzyme activities (SOD and CAT). Collectively, these findings provide mechanistic insight into the antioxidant action of rabbit-derived peptides and support their potential application as natural antioxidants for functional food development and oxidative stress-related disease prevention.
Yan Hai,Qiyao Cong,Yingnan Pang,Yunxing Zhao,Weilun Yan,Jianfeng Zhang,Jing Liang
Hexavalent chromium and phenol coexist in wastewater and exhibit synergistic toxicity, enhancing biological harmful effects. The integration of Density Functional Theory (DFT) and Machine Learning (ML) offers a promising approach to addressing complex environmental challenges, through bridging macroscopic and microscopic regular analysis. DFT simulations revealed that the tertiary amine (-N(CH 3 ) 2 ) and quaternary ammonium (-N + (CH 3 ) 3 ) groups on D301, carrying positive charges, can assemble phenol-degrading microorganisms through electrostatic interactions. HOMO/LUMO energy and the Fukui function revealed a low energy gap of 0.128 Ha between D301 and Cr(VI), suggesting the potential for spontaneous Cr(VI) reduction by D301. experiments demonstrated that the resin–microorganism composite material could degrade 1500 mg/L of phenol and reduce 20 mg/L of Cr(VI), which is higher than most of the currently reported co-removal levels. Using Bayesian regression, a synergistic metabolic model is established to predict the removal performance. The resin-microbe system can remove 34–36 % of 1800 mg/L phenol under 20 mg/L Cr(VI), with a prediction error of less than 5 %. This study, through DFT and integrated ML, revealed the active sites of the resin and constructed a co-metabolism model of phenol and Cr(VI), providing a new strategy for material design and microbial assembly in the removal of co-contaminants.
危险品化学品经营许可证（带存储）