Antioxidant peptides (AOPs) are highly valued in food and pharmaceutical industries due to their significant role in human function. This study introduces a novel approach to identifying robust AOPs using a deep generative model based on sequence representation. Through filtration with a deep-learning classification model and subsequent clustering via the Butina cluster algorithm, twelve peptides ( GP1–GP12 ) with potential antioxidant capacity were predicted. Density functional theory (DFT) calculations guided the selection of six peptides for synthesis and biological experiments. Molecular orbital representations revealed that the HOMO for these peptides is primarily localized on the indole segment, underscoring its pivotal role in antioxidant activity. All six synthesized peptides exhibited antioxidant activity in the DPPH assay, while the hydroxyl radical test showed suboptimal results. A hemolysis assay confirmed the non-hemolytic nature of the generated peptides. Additionally, an in silico investigation explored the potential inhibitory interaction between the peptides and the Keap1 protein. Analysis revealed that ligands GP3 , GP4 , and GP12 induced significant structural changes in proteins, affecting their stability and flexibility. These findings highlight the capability of machine learning approaches in generating novel antioxidant peptides.

This review article is an attempt to survey literature describing synthetic methods and reactivity of imidazole-1-sulfonate esters (imidazylates) in substitution, elimination, and metal-catalyzed cross-coupling reactions.

Biomass conversion to carbonaceous materials and their use in various applications, such as capacitors, catalyst supports, and adsorbents, have attracted considerable attention from the viewpoint of green chemistry. In this regard, chicken egg white is one of the most important biomass, which can act as an in situ nitrogen doping source. In this paper, nitrogen-rich porous carbon material was synthesized from egg white biomass via pyrolysis at 600 °C under nitrogen atmosphere, followed by chemical activation with KOH at 500 °C. The results showed that the as-synthesized porous carbon material has a high content of nitrogen and high surface area, on which nitrogen can tune the surface hydrophobicity–hydrophilicity through interaction with water molecules. Then, the copper nanoparticles were immobilized on the surface of nitrogen-rich activated carbon by a chemical reduction method. Nanocatalyst structure was characterized by elemental analysis, TEM, AFM, Raman, FT-IR, porosimetry and atomic adsorption techniques. Finally, catalytic activity was evaluated for the one-pot synthesis of triazole in aqueous medium. The nanocatalyst offers some advantages such as excellent activity, low loading of catalyst, good yields of products and short reaction times.